{"id":100101,"date":"2026-07-09T09:27:09","date_gmt":"2026-07-09T09:27:09","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/100101\/"},"modified":"2026-07-09T09:27:09","modified_gmt":"2026-07-09T09:27:09","slug":"non-idealities-in-artificial-synapses-nature-reviews-physics","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/100101\/","title":{"rendered":"Non-idealities in artificial synapses | Nature Reviews Physics"},"content":{"rendered":"<p class=\"c-article-references__text\" id=\"ref-CR1\">Lecun, Y., Bengio, Y. &amp; Hinton, G. Deep learning. Nature 521, 436\u2013444 (2015).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2015Natur.521..436L\" aria-label=\"ADS reference 1\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 1\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Deep%20learning&amp;journal=Nature&amp;volume=521&amp;pages=436-444&amp;publication_year=2015&amp;author=Lecun%2CY&amp;author=Bengio%2CY&amp;author=Hinton%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR2\">Krizhevsky, A., Sutskever, I. &amp; Hinton, G. E. ImageNet classification with deep convolutional neural networks. Adv. Neural Inf. Process. Syst. 25, 1097\u20131105 (2012).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 2\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=ImageNet%20classification%20with%20deep%20convolutional%20neural%20networks&amp;journal=Adv.%20Neural%20Inf.%20Process.%20Syst&amp;volume=25&amp;pages=1097-1105&amp;publication_year=2012&amp;author=Krizhevsky%2CA&amp;author=Sutskever%2CI&amp;author=Hinton%2CGE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR3\">Vaswani, A. et al. Attention is all you need. In Proc. 31st Conference on Neural Information Processing Systems (NeurIPS, 2017).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR4\">Zou, X., Xu, S., Chen, X., Yan, L. &amp; Han, Y. Breaking the von Neumann bottleneck: architecture-level processing-in-memory technology. Sci. China Inf. Sci. 64, 1\u201310 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021ScChD..64....1X\" aria-label=\"ADS reference 4\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 4\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Breaking%20the%20von%20Neumann%20bottleneck%3A%20architecture-level%20processing-in-memory%20technology&amp;journal=Sci.%20China%20Inf.%20Sci.&amp;volume=64&amp;pages=1-10&amp;publication_year=2021&amp;author=Zou%2CX&amp;author=Xu%2CS&amp;author=Chen%2CX&amp;author=Yan%2CL&amp;author=Han%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR5\">Gholami, A. et al. AI and memory wall. IEEE Micro 44, 33\u201339 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 5\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=AI%20and%20memory%20wall&amp;journal=IEEE%20Micro&amp;volume=44&amp;pages=33-39&amp;publication_year=2024&amp;author=Gholami%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR6\">Seok, H. et al. Beyond von Neumann architecture: brain-inspired artificial neuromorphic devices and integrated computing. Adv. Electron. Mater. 10, 2300839 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 6\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Beyond%20von%20Neumann%20architecture%3A%20brain-inspired%20artificial%20neuromorphic%20devices%20and%20integrated%20computing&amp;journal=Adv.%20Electron.%20Mater.&amp;volume=10&amp;publication_year=2024&amp;author=Seok%2CH\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR7\">Ganguly, A., Muralidhar, R. &amp; Singh, V. Towards energy efficient non-von Neumann architectures for deep learning. In Proc. International Symposium on Quality Electronic Design 335\u2013342 (IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR8\">Upadhyay, N. K. et al. Emerging memory devices for neuromorphic computing. Adv. Mater. Technol. 4, 1800589 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 8\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Emerging%20memory%20devices%20for%20neuromorphic%20computing&amp;journal=Adv.%20Mater.%20Technol.&amp;volume=4&amp;publication_year=2019&amp;author=Upadhyay%2CNK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR9\">Rajendran, B. &amp; Alibart, F. Neuromorphic computing based on emerging memory technologies. IEEE J. Emerg. Sel. Top. Circuits Syst. 6, 198\u2013211 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2016IJEST...6..198R\" aria-label=\"ADS reference 9\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 9\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Neuromorphic%20computing%20based%20on%20emerging%20memory%20technologies&amp;journal=IEEE%20J.%20Emerg.%20Sel.%20Top.%20Circuits%20Syst.&amp;volume=6&amp;pages=198-211&amp;publication_year=2016&amp;author=Rajendran%2CB&amp;author=Alibart%2CF\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR10\">Mannocci, P. et al. In-memory computing with emerging memory devices: status and outlook. APL Mach. Learn. 1, 010902 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 10\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=In-memory%20computing%20with%20emerging%20memory%20devices%3A%20status%20and%20outlook&amp;journal=APL%20Mach.%20Learn.&amp;volume=1&amp;publication_year=2023&amp;author=Mannocci%2CP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR11\">Sun, X. &amp; Yu, S. Impact of non-ideal characteristics of resistive synaptic devices on implementing convolutional neural networks. IEEE J. Emerg. Sel. Top. Circuits Syst. 9, 570\u2013579 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019IJEST...9..570S\" aria-label=\"ADS reference 11\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 11\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Impact%20of%20non-ideal%20characteristics%20of%20resistive%20synaptic%20devices%20on%20implementing%20convolutional%20neural%20networks&amp;journal=IEEE%20J.%20Emerg.%20Sel.%20Top.%20Circuits%20Syst.&amp;volume=9&amp;pages=570-579&amp;publication_year=2019&amp;author=Sun%2CX&amp;author=Yu%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR12\">Chen, P.-Y. et al. Mitigating effects of non-ideal synaptic device characteristics for on-chip learning. In Proc. 2015 IEEE\/ACM International Conference on Computer-Aided Design 194\u2013199 (IEEE, 2016).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR13\">Burr, G. W. et al. Recent progress in phase-change memory technology. IEEE J. Emerg. Sel. Top. Circuits Syst. 6, 146\u2013162 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2016IJEST...6..146B\" aria-label=\"ADS reference 13\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 13\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Recent%20progress%20in%20phase-change%20memory%20technology&amp;journal=IEEE%20J.%20Emerg.%20Sel.%20Top.%20Circuits%20Syst.&amp;volume=6&amp;pages=146-162&amp;publication_year=2016&amp;author=Burr%2CGW\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR14\">Ielmini, D. &amp; Pedretti, G. Resistive switching random-access memory (RRAM): applications and requirements for memory and computing. Chem. Rev. 125, 5584\u20135625 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 14\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Resistive%20switching%20random-access%20memory%20%28RRAM%29%3A%20applications%20and%20requirements%20for%20memory%20and%20computing&amp;journal=Chem.%20Rev.&amp;volume=125&amp;pages=5584-5625&amp;publication_year=2025&amp;author=Ielmini%2CD&amp;author=Pedretti%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR15\">Sengupta, A. &amp; Roy, K. Encoding neural and synaptic functionalities in electron spin: a pathway to efficient neuromorphic computing. Appl. Phys. Rev. 4, 41105 (2017).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 15\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Encoding%20neural%20and%20synaptic%20functionalities%20in%20electron%20spin%3A%20a%20pathway%20to%20efficient%20neuromorphic%20computing&amp;journal=Appl.%20Phys.%20Rev.&amp;volume=4&amp;publication_year=2017&amp;author=Sengupta%2CA&amp;author=Roy%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR16\">Kim, K., Song, M. S., Hwang, H., Hwang, S. &amp; Kim, H. A comprehensive review of advanced trends: from artificial synapses to neuromorphic systems with consideration of non-ideal effects. Front. Neurosci. 18, 1279708 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 16\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20comprehensive%20review%20of%20advanced%20trends%3A%20from%20artificial%20synapses%20to%20neuromorphic%20systems%20with%20consideration%20of%20non-ideal%20effects&amp;journal=Front.%20Neurosci.&amp;volume=18&amp;publication_year=2024&amp;author=Kim%2CK&amp;author=Song%2CMS&amp;author=Hwang%2CH&amp;author=Hwang%2CS&amp;author=Kim%2CH\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR17\">Islam, R. et al. Device and materials requirements for neuromorphic computing. J. Phys. D Appl. Phys. 52, 113001 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019JPhD...52k3001I\" aria-label=\"ADS reference 17\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 17\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Device%20and%20materials%20requirements%20for%20neuromorphic%20computing&amp;journal=J.%20Phys.%20D%20Appl.%20Phys.&amp;volume=52&amp;publication_year=2019&amp;author=Islam%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR18\">Chen, B. et al. Efficient in-memory computing architecture based on crossbar arrays. In Proc. 2015 IEEE International Electron Devices Meeting 17.5.1\u201317.5.4 (IEEE, 2015).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR19\">Hur, J. et al. Nonvolatile capacitive crossbar array for in-memory computing. Adv. Intell. Syst. 4, 2100258 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 19\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Nonvolatile%20capacitive%20crossbar%20array%20for%20in-memory%20computing&amp;journal=Adv.%20Intell.%20Syst.&amp;volume=4&amp;publication_year=2022&amp;author=Hur%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR20\">Luo, Y. C. et al. Experimental demonstration of non-volatile capacitive crossbar array for in-memory computing. In Proc. 2021 IEEE International Electron Devices Meeting 1\u20134 (IEEE, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR21\">Wang, C. et al. Scalable massively parallel computing using continuous-time data representation in nanoscale crossbar array. Nat. Nanotechnol. 16, 1079\u20131085 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021NatNa..16.1079W\" aria-label=\"ADS reference 21\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 21\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Scalable%20massively%20parallel%20computing%20using%20continuous-time%20data%20representation%20in%20nanoscale%20crossbar%20array&amp;journal=Nat.%20Nanotechnol.&amp;volume=16&amp;pages=1079-1085&amp;publication_year=2021&amp;author=Wang%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR22\">Huang, Y., Ravichandran, V., Zhao, W. &amp; Xia, Q. Towards energy-efficient computing hardware based on memristive nanodevices. IEEE Nanotechnol. Mag. 17, 30\u201338 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 22\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Towards%20energy-efficient%20computing%20hardware%20based%20on%20memristive%20nanodevices&amp;journal=IEEE%20Nanotechnol.%20Mag.&amp;volume=17&amp;pages=30-38&amp;publication_year=2023&amp;author=Huang%2CY&amp;author=Ravichandran%2CV&amp;author=Zhao%2CW&amp;author=Xia%2CQ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR23\">Rumelhart, D. E., Hinton, G. E. &amp; Williams, R. J. Learning representations by back-propagating errors. Nature 323, 533\u2013536 (1986).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=1986Natur.323..533R\" aria-label=\"ADS reference 23\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 23\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Learning%20representations%20by%20back-propagating%20errors&amp;journal=Nature&amp;volume=323&amp;pages=533-536&amp;publication_year=1986&amp;author=Rumelhart%2CDE&amp;author=Hinton%2CGE&amp;author=Williams%2CRJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR24\">Ruder, S. An overview of gradient descent optimization algorithms. ruder.io <a href=\"https:\/\/www.ruder.io\/optimizing-gradient-descent\/\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/www.ruder.io\/optimizing-gradient-descent\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.ruder.io\/optimizing-gradient-descent\/<\/a> (2016).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR25\">Hu, R. et al. Investigation of resistive switching mechanisms in Ti\/TiOx\/Pd-based RRAM devices. Adv. Electron. Mater. 8, 2100827 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 25\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Investigation%20of%20resistive%20switching%20mechanisms%20in%20Ti%2FTiOx%2FPd-based%20RRAM%20devices&amp;journal=Adv.%20Electron.%20Mater.&amp;volume=8&amp;publication_year=2022&amp;author=Hu%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR26\">Duan, Y. et al. In-depth understanding of physical mechanism of the gradual switching in AlOxNy-based RRAM as memory and synapse device. Appl. Phys. Lett. 120, 263504 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022ApPhL.120z3504D\" aria-label=\"ADS reference 26\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 26\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=In-depth%20understanding%20of%20physical%20mechanism%20of%20the%20gradual%20switching%20in%20AlOxNy-based%20RRAM%20as%20memory%20and%20synapse%20device&amp;journal=Appl.%20Phys.%20Lett.&amp;volume=120&amp;publication_year=2022&amp;author=Duan%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR27\">Spiga, S., Sebastian, A., Querlioz, D. &amp; Rajendran, B. in Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications \u2014 Computational Memory, Deep Learning, and Spiking Neural Networks 3\u201316 (Elsevier, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR28\">Agarwal, S. et al. Resistive memory device requirements for a neural algorithm accelerator. In Proc. International Joint Conference on Neural Networks 929\u2013938 (IEEE, 2016).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR29\">Jang, J. W., Park, S., Burr, G. W., Hwang, H. &amp; Jeong, Y. H. Optimization of conductance change in Pr1\u2212xCaxMnO3-based synaptic devices for neuromorphic systems. IEEE Electron. Device Lett. 36, 457\u2013459 (2015).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2015IEDL...36..457J\" aria-label=\"ADS reference 29\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 29\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Optimization%20of%20conductance%20change%20in%20Pr1%E2%88%92xCaxMnO3-based%20synaptic%20devices%20for%20neuromorphic%20systems&amp;journal=IEEE%20Electron.%20Device%20Lett.&amp;volume=36&amp;pages=457-459&amp;publication_year=2015&amp;author=Jang%2CJW&amp;author=Park%2CS&amp;author=Burr%2CGW&amp;author=Hwang%2CH&amp;author=Jeong%2CYH\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR30\">Ge, R. et al. Atomristor: nonvolatile resistance switching in atomic sheets of transition metal dichalcogenides. Nano Lett. 18, 434\u2013441 (2017).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018NanoL..18..434G\" aria-label=\"ADS reference 30\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 30\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Atomristor%3A%20nonvolatile%20resistance%20switching%20in%20atomic%20sheets%20of%20transition%20metal%20dichalcogenides&amp;journal=Nano%20Lett.&amp;volume=18&amp;pages=434-441&amp;publication_year=2017&amp;author=Ge%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR31\">Yang, S. J. et al. Giant memory window performance and low power consumption of hexagonal boron nitride monolayer atomristor. npj 2D Mater. Appl. 9, 9 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 31\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Giant%20memory%20window%20performance%20and%20low%20power%20consumption%20of%20hexagonal%20boron%20nitride%20monolayer%20atomristor&amp;journal=npj%202D%20Mater.%20Appl.&amp;volume=9&amp;publication_year=2025&amp;author=Yang%2CSJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR32\">Khan, A. I. et al. Ultralow-switching current density multilevel phase-change memory on a flexible substrate. Science 373, 1243\u20131247 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021Sci...373.1243K\" aria-label=\"ADS reference 32\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 32\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Ultralow-switching%20current%20density%20multilevel%20phase-change%20memory%20on%20a%20flexible%20substrate&amp;journal=Science&amp;volume=373&amp;pages=1243-1247&amp;publication_year=2021&amp;author=Khan%2CAI\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR33\">Liu, B. et al. Multi-level phase-change memory with ultralow power consumption and resistance drift. Sci. Bull. 66, 2217\u20132224 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 33\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Multi-level%20phase-change%20memory%20with%20ultralow%20power%20consumption%20and%20resistance%20drift&amp;journal=Sci.%20Bull.&amp;volume=66&amp;pages=2217-2224&amp;publication_year=2021&amp;author=Liu%2CB\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR34\">Zhou, Y., Zhang, W., Ma, E. &amp; Deringer, V. L. Device-scale atomistic modelling of phase-change memory materials. Nat. Electron. 6, 746\u2013754 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 34\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Device-scale%20atomistic%20modelling%20of%20phase-change%20memory%20materials&amp;journal=Nat.%20Electron.&amp;volume=6&amp;pages=746-754&amp;publication_year=2023&amp;author=Zhou%2CY&amp;author=Zhang%2CW&amp;author=Ma%2CE&amp;author=Deringer%2CVL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR35\">Wang, K. L., Alzate, J. G. &amp; Khalili Amiri, P. Low-power non-volatile spintronic memory: STT-RAM and beyond. J. Phys. D\u00a046, 074003 (2013).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2013JPhD...46g4003W\" aria-label=\"ADS reference 35\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 35\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Low-power%20non-volatile%20spintronic%20memory%3A%20STT-RAM%20and%20beyond&amp;journal=J.%20Phys.%20D&amp;volume=46&amp;publication_year=2013&amp;author=Wang%2CKL&amp;author=Alzate%2CJG&amp;author=Khalili%20Amiri%2CP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR36\">Ramaswamy, R., Lee, J. M., Cai, K. &amp; Yang, H. Recent advances in spin\u2013orbit torques: moving towards device applications. Appl. Phys. Rev. 5, 031107 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018ApPRv...5c1107R\" aria-label=\"ADS reference 36\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 36\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Recent%20advances%20in%20spin%E2%80%93orbit%20torques%3A%20moving%20towards%20device%20applications&amp;journal=Appl.%20Phys.%20Rev.&amp;volume=5&amp;publication_year=2018&amp;author=Ramaswamy%2CR&amp;author=Lee%2CJM&amp;author=Cai%2CK&amp;author=Yang%2CH\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR37\">Siddiqui, S. A. et al. Magnetic domain wall based synaptic and activation function generator for neuromorphic accelerators. Nano Lett. 20, 1033\u20131040 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020NanoL..20.1033S\" aria-label=\"ADS reference 37\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 37\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Magnetic%20domain%20wall%20based%20synaptic%20and%20activation%20function%20generator%20for%20neuromorphic%20accelerators&amp;journal=Nano%20Lett.&amp;volume=20&amp;pages=1033-1040&amp;publication_year=2019&amp;author=Siddiqui%2CSA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR38\">Raymenants, E. et al. Chain of magnetic tunnel junctions as a spintronic memristor. J. Appl. Phys. 124, 152116 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018JAP...124o2116R\" aria-label=\"ADS reference 38\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 38\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Chain%20of%20magnetic%20tunnel%20junctions%20as%20a%20spintronic%20memristor&amp;journal=J.%20Appl.%20Phys.&amp;volume=124&amp;publication_year=2018&amp;author=Raymenants%2CE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR39\">Ross, A. et al. Multilayer spintronic neural networks with radiofrequency connections. Nat. Nanotechnol. 18, 1273\u20131280 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2023NatNa..18.1273R\" aria-label=\"ADS reference 39\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 39\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Multilayer%20spintronic%20neural%20networks%20with%20radiofrequency%20connections&amp;journal=Nat.%20Nanotechnol.&amp;volume=18&amp;pages=1273-1280&amp;publication_year=2023&amp;author=Ross%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR40\">Liu, L. et al. Domain wall magnetic tunnel junction-based artificial synapses and neurons for all-spin neuromorphic hardware. Nat. Commun. 15, 4534 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024NatCo..15.4534L\" aria-label=\"ADS reference 40\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 40\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Domain%20wall%20magnetic%20tunnel%20junction-based%20artificial%20synapses%20and%20neurons%20for%20all-spin%20neuromorphic%20hardware&amp;journal=Nat.%20Commun.&amp;volume=15&amp;publication_year=2024&amp;author=Liu%2CL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR41\">Hassan, N. et al. Magnetic domain wall neuron with lateral inhibition. J. Appl. Phys. 124, 152127 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018JAP...124o2127H\" aria-label=\"ADS reference 41\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 41\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Magnetic%20domain%20wall%20neuron%20with%20lateral%20inhibition&amp;journal=J.%20Appl.%20Phys.&amp;volume=124&amp;publication_year=2018&amp;author=Hassan%2CN\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR42\">Durner, C. A., Migliorini, A., Jeon, J. C. &amp; Parkin, S. S. P. Reconfigurable magnetic inhibitor for domain wall logic and neuronal devices. ACS Nano 19, 5316\u20135325 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 42\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Reconfigurable%20magnetic%20inhibitor%20for%20domain%20wall%20logic%20and%20neuronal%20devices&amp;journal=ACS%20Nano&amp;volume=19&amp;pages=5316-5325&amp;publication_year=2025&amp;author=Durner%2CCA&amp;author=Migliorini%2CA&amp;author=Jeon%2CJC&amp;author=Parkin%2CSSP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR43\">Vakili, H. et al. Skyrmionics \u2014 computing and memory technologies based on topological excitations in magnets. J. Appl. Phys. 130, 70908 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 43\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Skyrmionics%20%E2%80%94%20computing%20and%20memory%20technologies%20based%20on%20topological%20excitations%20in%20magnets&amp;journal=J.%20Appl.%20Phys.&amp;volume=130&amp;publication_year=2021&amp;author=Vakili%2CH\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR44\">da C\u00e2mara Santa Clara Gomes, T. et al. Neuromorphic weighted sums with magnetic skyrmions. Nat. Electron. 8, 204\u2013214 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 44\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Neuromorphic%20weighted%20sums%20with%20magnetic%20skyrmions&amp;journal=Nat.%20Electron.&amp;volume=8&amp;pages=204-214&amp;publication_year=2025&amp;author=da%20C%C3%A2mara%20Santa%20Clara%20Gomes%2CT\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR45\">Chai, X. et al. Nonvolatile ferroelectric field-effect transistors. Nat. Commun. 11, 2811 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020NatCo..11.2811C\" aria-label=\"ADS reference 45\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 45\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Nonvolatile%20ferroelectric%20field-effect%20transistors&amp;journal=Nat.%20Commun.&amp;volume=11&amp;publication_year=2020&amp;author=Chai%2CX\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR46\">Mulaosmanovic, H. et al. Ferroelectric field-effect transistors based on HfO2: a review. Nanotechnology 32, 502002 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 46\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Ferroelectric%20field-effect%20transistors%20based%20on%20HfO2%3A%20a%20review&amp;journal=Nanotechnology&amp;volume=32&amp;publication_year=2021&amp;author=Mulaosmanovic%2CH\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR47\">Yu, E., Gaurav Kumar, K., Saxena, U. &amp; Roy, K. Ferroelectric capacitors and field-effect transistors as in-memory computing elements for machine learning workloads. Sci. Rep. 14, 9426 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024NatSR..14.9426Y\" aria-label=\"ADS reference 47\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 47\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Ferroelectric%20capacitors%20and%20field-effect%20transistors%20as%20in-memory%20computing%20elements%20for%20machine%20learning%20workloads&amp;journal=Sci.%20Rep.&amp;volume=14&amp;publication_year=2024&amp;author=Yu%2CE&amp;author=Gaurav%20Kumar%2CK&amp;author=Saxena%2CU&amp;author=Roy%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR48\">Luo, J. D. et al. Ferroelectric undoped HfOx capacitor with symmetric synaptic for neural network accelerator. IEEE Trans. Electron Devices 68, 1374\u20131377 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021ITED...68.1374L\" aria-label=\"ADS reference 48\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 48\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Ferroelectric%20undoped%20HfOx%20capacitor%20with%20symmetric%20synaptic%20for%20neural%20network%20accelerator&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=68&amp;pages=1374-1377&amp;publication_year=2021&amp;author=Luo%2CJD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR49\">Cao, R. et al. Improvement of endurance in HZO-based ferroelectric capacitor using Ru electrode. IEEE Electron. Device Lett. 40, 1744\u20131747 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019IEDL...40.1744C\" aria-label=\"ADS reference 49\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 49\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Improvement%20of%20endurance%20in%20HZO-based%20ferroelectric%20capacitor%20using%20Ru%20electrode&amp;journal=IEEE%20Electron.%20Device%20Lett.&amp;volume=40&amp;pages=1744-1747&amp;publication_year=2019&amp;author=Cao%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR50\">Fouda, M. E., Neftci, E., Eltawil, A. &amp; Kurdahi, F. Effect of asymmetric nonlinearity dynamics in RRAMs on spiking neural network performance. In Proc. Asilomar Conference on Signals, Systems, and Computers 495\u2013499 (IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR51\">Onen, M. et al. Neural network training with asymmetric crosspoint elements. Front. Artif. Intell. 5, 891624 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 51\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Neural%20network%20training%20with%20asymmetric%20crosspoint%20elements&amp;journal=Front.%20Artif.%20Intell.&amp;volume=5&amp;publication_year=2022&amp;author=Onen%2CM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR52\">Balatti, S. et al. Understanding pulsed-cycling variability and endurance in HfOx RRAM. In Proc. 2015 IEEE International Reliability Physics Symposium 5B31\u20135B36 (IEEE, 2015).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR53\">Garg, C. et al. Impact of random spatial fluctuation in non-uniform crystalline phases on the device variation of ferroelectric FET. IEEE Electron. Device Lett. 42, 1160\u20131163 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021IEDL...42.1160G\" aria-label=\"ADS reference 53\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 53\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Impact%20of%20random%20spatial%20fluctuation%20in%20non-uniform%20crystalline%20phases%20on%20the%20device%20variation%20of%20ferroelectric%20FET&amp;journal=IEEE%20Electron.%20Device%20Lett.&amp;volume=42&amp;pages=1160-1163&amp;publication_year=2021&amp;author=Garg%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR54\">Bin Hamid, S. &amp; Zunaid Baten, M. Impact of process variation in spin\u2013orbit torque-based magnetic tunnel junctions on the performance of spiking neural networks. IEEE Trans. Electron Devices 71, 6672\u20136679 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024ITED...71.6672B\" aria-label=\"ADS reference 54\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 54\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Impact%20of%20process%20variation%20in%20spin%E2%80%93orbit%20torque-based%20magnetic%20tunnel%20junctions%20on%20the%20performance%20of%20spiking%20neural%20networks&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=71&amp;pages=6672-6679&amp;publication_year=2024&amp;author=Bin%20Hamid%2CS&amp;author=Zunaid%20Baten%2CM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR55\">Ni, K. et al. Impact of extrinsic variation sources on the device-to-device variation in ferroelectric FET. In Proc. 2020 IEEE International Reliability Physics Symposium 1\u20135 (IEEE, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR56\">Resch, S. et al. On endurance of processing in (nonvolatile) memory. In Proc. 50th Annual International Symposium on Computer Architecture 1\u201313 (Association for Computing Machinery, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR57\">Gong, N. &amp; Ma, T. P. A study of endurance issues in HfO2-based ferroelectric field effect transistors: charge trapping and trap generation. IEEE Electron. Device Lett. 39, 15\u201318 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018IEDL...39...15G\" aria-label=\"ADS reference 57\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 57\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20study%20of%20endurance%20issues%20in%20HfO2-based%20ferroelectric%20field%20effect%20transistors%3A%20charge%20trapping%20and%20trap%20generation&amp;journal=IEEE%20Electron.%20Device%20Lett.&amp;volume=39&amp;pages=15-18&amp;publication_year=2018&amp;author=Gong%2CN&amp;author=Ma%2CTP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR58\">Li, J., Luan, B. &amp; Lam, C. Resistance drift in phase change memory. In Proc.\u00a02012 IEEE International Reliability Physics Symposium\u00a06C.1.1\u20136C.1.6 (IEEE, 2012).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR59\">Baroni, A. et al. Low conductance state drift characterization and mitigation in resistive switching memories (RRAM) for artificial neural networks. IEEE Trans. Device Mater. Reliab. 22, 340\u2013347 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 59\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Low%20conductance%20state%20drift%20characterization%20and%20mitigation%20in%20resistive%20switching%20memories%20%28RRAM%29%20for%20artificial%20neural%20networks&amp;journal=IEEE%20Trans.%20Device%20Mater.%20Reliab.&amp;volume=22&amp;pages=340-347&amp;publication_year=2022&amp;author=Baroni%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR60\">Sun, D. et al. Uniformity, linearity, and symmetry enhancement in TiOx\/MoS2\u2212xOx based analog RRAM via S-vacancy confined nanofilament. Nano Lett. 24, 16283\u201316292\u00a0(2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024NanoL..2416283S\" aria-label=\"ADS reference 60\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 60\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Uniformity%2C%20linearity%2C%20and%20symmetry%20enhancement%20in%20TiOx%2FMoS2%E2%88%92xOx%20based%20analog%20RRAM%20via%20S-vacancy%20confined%20nanofilament&amp;journal=Nano%20Lett.&amp;volume=24&amp;pages=16283-16292&amp;publication_year=2024&amp;author=Sun%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR61\">Liao, Y. et al. A compact model of analog RRAM with device and array nonideal effects for neuromorphic systems. IEEE Trans. Electron Devices 67, 1593\u20131599 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020ITED...67.1593L\" aria-label=\"ADS reference 61\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 61\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20compact%20model%20of%20analog%20RRAM%20with%20device%20and%20array%20nonideal%20effects%20for%20neuromorphic%20systems&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=67&amp;pages=1593-1599&amp;publication_year=2020&amp;author=Liao%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR62\">Pedretti, G., Ambrosi, E. &amp; Ielmini, D. Conductance variations and their impact on the precision of in-memory computing with resistive switching memory (RRAM). In Proc. 2021 IEEE International Reliability Physics Symposium 1\u20138 (IEEE, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR63\">Degraeve, R. et al. Causes and consequences of the stochastic aspect of filamentary RRAM. Microelectron. Eng. 147, 171\u2013175 (2015).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 63\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Causes%20and%20consequences%20of%20the%20stochastic%20aspect%20of%20filamentary%20RRAM&amp;journal=Microelectron.%20Eng.&amp;volume=147&amp;pages=171-175&amp;publication_year=2015&amp;author=Degraeve%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR64\">Zhao, M. et al. Investigation of statistical retention of filamentary analog RRAM for neuromorphic computing. In Proc. 2017 IEEE International Electron Devices Meeting 39.4.1\u201339.4.4 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR65\">Zhao, M. et al. Endurance and retention degradation of intermediate levels in filamentary analog RRAM. IEEE J. Electron Devices Soc. 7, 1239\u20131247 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 65\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Endurance%20and%20retention%20degradation%20of%20intermediate%20levels%20in%20filamentary%20analog%20RRAM&amp;journal=IEEE%20J.%20Electron%20Devices%20Soc.&amp;volume=7&amp;pages=1239-1247&amp;publication_year=2019&amp;author=Zhao%2CM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR66\">Moon, K. et al. Bidirectional non-filamentary RRAM as an analog neuromorphic synapse, Part I: Al\/Mo\/Pr0.7Ca0.3MnO3 material improvements and device measurements. IEEE J. Electron Devices Soc. 6, 146\u2013155 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 66\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Bidirectional%20non-filamentary%20RRAM%20as%20an%20analog%20neuromorphic%20synapse%2C%20Part%20I%3A%20Al%2FMo%2FPr0.7Ca0.3MnO3%20material%20improvements%20and%20device%20measurements&amp;journal=IEEE%20J.%20Electron%20Devices%20Soc.&amp;volume=6&amp;pages=146-155&amp;publication_year=2018&amp;author=Moon%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR67\">Fatheema, J., Liang, L., Lee, B. H., Wang, W. &amp; Akinwande, D. First-principles investigation of the resistive switching energetics in monolayer MoS2: insights into metal diffusion and adsorption. npj 2D Mater. Appl. 9, 74 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 67\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=First-principles%20investigation%20of%20the%20resistive%20switching%20energetics%20in%20monolayer%20MoS2%3A%20insights%20into%20metal%20diffusion%20and%20adsorption&amp;journal=npj%202D%20Mater.%20Appl.&amp;volume=9&amp;publication_year=2025&amp;author=Fatheema%2CJ&amp;author=Liang%2CL&amp;author=Lee%2CBH&amp;author=Wang%2CW&amp;author=Akinwande%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR68\">Yang, S. J., Gu, Y. &amp; Akinwande, D. Multifunctional resistance switching in monolayer hexagonal boron nitride atomristor. In Proc. 2023 Device Research Conference 1\u20132 (IEEE, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR69\">Nandakumar, S. R. et al. A phase-change memory model for neuromorphic computing. J. Appl. Phys. 124, 152135 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018JAP...124o2135N\" aria-label=\"ADS reference 69\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 69\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20phase-change%20memory%20model%20for%20neuromorphic%20computing&amp;journal=J.%20Appl.%20Phys.&amp;volume=124&amp;publication_year=2018&amp;author=Nandakumar%2CSR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR70\">Boybat, I. et al. Neuromorphic computing with multi-memristive synapses. Nat. Commun. 9, 2514 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018NatCo...9.2514B\" aria-label=\"ADS reference 70\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 70\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Neuromorphic%20computing%20with%20multi-memristive%20synapses&amp;journal=Nat.%20Commun.&amp;volume=9&amp;publication_year=2018&amp;author=Boybat%2CI\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR71\">Syed, G. S., Le Gallo, M. &amp; Sebastian, A. Phase-change memory for in-memory computing. Chem. Rev. 125, 5163\u20135194 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 71\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Phase-change%20memory%20for%20in-memory%20computing&amp;journal=Chem.%20Rev.&amp;volume=125&amp;pages=5163-5194&amp;publication_year=2025&amp;author=Syed%2CGS&amp;author=Gallo%2CM&amp;author=Sebastian%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR72\">Kumari, S., Durai, S. &amp; Manivannan, A. Impact of process-induced variability on multi-bit phase change memory devices. Microelectron. J. 130, 105638 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 72\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Impact%20of%20process-induced%20variability%20on%20multi-bit%20phase%20change%20memory%20devices&amp;journal=Microelectron.%20J.&amp;volume=130&amp;publication_year=2022&amp;author=Kumari%2CS&amp;author=Durai%2CS&amp;author=Manivannan%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR73\">Zhang, W. &amp; Li, T. Characterizing and mitigating the impact of process variations on phase change based memory systems. In Proc. 42nd Annual IEEE\/ACM International Symposium on Microarchitecture 2\u201313 (Association for Computing Machinery, 2009).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR74\">Wu, B. et al. Electronic mechanism for resistance drift in phase-change memory materials: link to persistent photoconductivity. J. Phys. D Appl. Phys. 53, 214002 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 74\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Electronic%20mechanism%20for%20resistance%20drift%20in%20phase-change%20memory%20materials%3A%20link%20to%20persistent%20photoconductivity&amp;journal=J.%20Phys.%20D%20Appl.%20Phys.&amp;volume=53&amp;publication_year=2020&amp;author=Wu%2CB\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR75\">Wu, X. et al. Understanding interface-controlled resistance drift in superlattice phase change memory. IEEE Electron Device Lett. 43, 1669\u20131672 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022IEDL...43.1669W\" aria-label=\"ADS reference 75\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 75\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Understanding%20interface-controlled%20resistance%20drift%20in%20superlattice%20phase%20change%20memory&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=43&amp;pages=1669-1672&amp;publication_year=2022&amp;author=Wu%2CX\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR76\">Balatti, S. et al. Pulsed cycling operation and endurance failure of metal\u2013oxide resistive (RRAM). In Proc. 2014 IEEE International Electron Devices Meeting 14.3.1\u201314.3.4 (IEEE, 2015).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR77\">Swaidan, Z., Kanj, R., El Hajj, J., Saad, E. &amp; Kurdahi, F. RRAM endurance and retention: challenges, opportunities and implications on reliable design. In Proc. 2019 26th IEEE International Conference on Electronics, Circuits and Systems 402\u2013405 (IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR78\">Kim, S. B., Burr, G. W., Kim, W. &amp; Nam, S. W. Phase-change memory cycling endurance. MRS Bull. 44, 710\u2013714 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019MRSBu..44..710K\" aria-label=\"ADS reference 78\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 78\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Phase-change%20memory%20cycling%20endurance&amp;journal=MRS%20Bull.&amp;volume=44&amp;pages=710-714&amp;publication_year=2019&amp;author=Kim%2CSB&amp;author=Burr%2CGW&amp;author=Kim%2CW&amp;author=Nam%2CSW\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR79\">Safranski, C. et al. Demonstration of nanosecond operation in stochastic magnetic tunnel junctions. Nano Lett. 21, 2040\u20132045 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021NanoL..21.2040S\" aria-label=\"ADS reference 79\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 79\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Demonstration%20of%20nanosecond%20operation%20in%20stochastic%20magnetic%20tunnel%20junctions&amp;journal=Nano%20Lett.&amp;volume=21&amp;pages=2040-2045&amp;publication_year=2021&amp;author=Safranski%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR80\">Finocchio, G. et al. The promise of spintronics for unconventional computing. J. Magn. Magn. Mater. 521, 167506 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 80\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20promise%20of%20spintronics%20for%20unconventional%20computing&amp;journal=J.%20Magn.%20Magn.%20Mater.&amp;volume=521&amp;publication_year=2021&amp;author=Finocchio%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR81\">Kl\u00e4ui, M. et al. Domain wall pinning and controlled magnetic switching in narrow ferromagnetic ring structures with notches (invited). J. Appl. Phys. 93, 7885\u20137890 (2003).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2003JAP....93.7885K\" aria-label=\"ADS reference 81\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 81\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Domain%20wall%20pinning%20and%20controlled%20magnetic%20switching%20in%20narrow%20ferromagnetic%20ring%20structures%20with%20notches%20%28invited%29&amp;journal=J.%20Appl.%20Phys.&amp;volume=93&amp;pages=7885-7890&amp;publication_year=2003&amp;author=Kl%C3%A4ui%2CM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR82\">De Araujo, C. I. L. et al. Investigation of domain wall pinning by square anti-notches and its application in three terminals MRAM. Appl. Phys. Lett. 114, 212403 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019ApPhL.114u2403D\" aria-label=\"ADS reference 82\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 82\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Investigation%20of%20domain%20wall%20pinning%20by%20square%20anti-notches%20and%20its%20application%20in%20three%20terminals%20MRAM&amp;journal=Appl.%20Phys.%20Lett.&amp;volume=114&amp;publication_year=2019&amp;author=Araujo%2CCIL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR83\">Jenkins, S. et al. Magnetic stray fields in nanoscale magnetic tunnel junctions. J. Phys. D Appl. Phys. 53, 044001 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020JPhD...53d4001J\" aria-label=\"ADS reference 83\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 83\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Magnetic%20stray%20fields%20in%20nanoscale%20magnetic%20tunnel%20junctions&amp;journal=J.%20Phys.%20D%20Appl.%20Phys.&amp;volume=53&amp;publication_year=2019&amp;author=Jenkins%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR84\">Dutta, R. et al. Experimental and theoretical investigation of intracell magnetic coupling-induced variability of spin-transfer torque magnetic RAMs. IEEE Trans. Electron. Devices 70, 5428\u20135434 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2023ITED...70.5428D\" aria-label=\"ADS reference 84\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 84\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Experimental%20and%20theoretical%20investigation%20of%20intracell%20magnetic%20coupling-induced%20variability%20of%20spin-transfer%20torque%20magnetic%20RAMs&amp;journal=IEEE%20Trans.%20Electron.%20Devices&amp;volume=70&amp;pages=5428-5434&amp;publication_year=2023&amp;author=Dutta%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR85\">Carboni, R. et al. Modeling of breakdown-limited endurance in spin-transfer torque magnetic memory under pulsed cycling regime. IEEE Trans. Electron Devices 65, 2470\u20132478 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018ITED...65.2470C\" aria-label=\"ADS reference 85\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 85\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Modeling%20of%20breakdown-limited%20endurance%20in%20spin-transfer%20torque%20magnetic%20memory%20under%20pulsed%20cycling%20regime&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=65&amp;pages=2470-2478&amp;publication_year=2018&amp;author=Carboni%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR86\">Carboni, R. et al. Understanding cycling endurance in perpendicular spin-transfer torque (p-STT) magnetic memory. In Proc. 2016 IEEE International Electron Devices Meeting 21.6.1\u201321.6.4 (IEEE, 2017).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR87\">Katti, R. R. Magnetoresistive random access memories for space and radiation-hardened applications. In Proc. 2021 IEEE 32nd Magnetic Recording Conference 1\u20133\u00a0(IEEE, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR88\">Jerry, M. et al. Ferroelectric FET analog synapse for acceleration of deep neural network training. In Proc. 2017 IEEE International Electron Devices Meeting 6.2.1\u20136.2.4 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR89\">Clima, S. et al. Ferroelectric switching in FEFET: physics of the atomic mechanism and switching dynamics in HfZrOx, HfO2 with oxygen vacancies and Si dopants. In Proc. 2020 IEEE International Electron Devices Meeting 4.2.1\u20134.2.4 (IEEE, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR90\">Yurchuk, E. et al. Charge-trapping phenomena in HfO2-based FeFET-type nonvolatile memories. IEEE Trans. Electron Devices 63, 3501\u20133507 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2016ITED...63.3501Y\" aria-label=\"ADS reference 90\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 90\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Charge-trapping%20phenomena%20in%20HfO2-based%20FeFET-type%20nonvolatile%20memories&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=63&amp;pages=3501-3507&amp;publication_year=2016&amp;author=Yurchuk%2CE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR91\">Deng, S. et al. Examination of the interplay between polarization switching and charge trapping in ferroelectric FET. In Proc. 2020 IEEE International Electron Devices Meeting 4.4.1\u20134.4.4 (IEEE, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR92\">Higashi, Y. et al. Impact of charge trapping and depolarization on data retention using simultaneous P\u2013V and I\u2013V in HfO-based ferroelectric FET. IEEE Trans. Electron Devices 68, 4391\u20134396 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021ITED...68.4391H\" aria-label=\"ADS reference 92\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 92\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Impact%20of%20charge%20trapping%20and%20depolarization%20on%20data%20retention%20using%20simultaneous%20P%E2%80%93V%20and%20I%E2%80%93V%20in%20HfO-based%20ferroelectric%20FET&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=68&amp;pages=4391-4396&amp;publication_year=2021&amp;author=Higashi%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR93\">Ma, T. P. &amp; Gong, N. Retention and endurance of FeFET memory cells. In Proc.\u00a02019 IEEE 11th International Memory Workshop 1\u20134 (IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR94\">Song, Y. et al. Fatigue of ferroelectric field effect transistor: mechanisms and optimization strategies. J. Semicond. 46, 061302 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2025JSemi..46f1302S\" aria-label=\"ADS reference 94\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 94\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Fatigue%20of%20ferroelectric%20field%20effect%20transistor%3A%20mechanisms%20and%20optimization%20strategies&amp;journal=J.%20Semicond.&amp;volume=46&amp;publication_year=2025&amp;author=Song%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR95\">Higashi, Y. et al. Impact of charge trapping on imprint and its recovery in HfO2 based FeFET. In Proc. 2019 IEEE International Electron Devices Meeting 15.6.1\u201315.6.4 (IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR96\">Crafton, B., Talley, C., Spetalnick, S., Yoon, J. H. &amp; Raychowdhury, A. Characterization and mitigation of IR-drop in RRAM-based compute in-memory. In Proc. 2022 IEEE International Symposium on Circuits and Systems 70\u201374 (IEEE, 2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR97\">Lupo, N., P\u00e9rez, E., Wenger, C., Maloberti, F. &amp; Bonizzoni, E. Analysis of parasitic effects in filamentary-switching memristive memories using an approximated Verilog \u2014 a memristor model. IEEE Trans. Circuits Syst. I Regul. Pap. 66, 1935\u20131947 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 97\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Analysis%20of%20parasitic%20effects%20in%20filamentary-switching%20memristive%20memories%20using%20an%20approximated%20Verilog%20%E2%80%94%20a%20memristor%20model&amp;journal=IEEE%20Trans.%20Circuits%20Syst.%20I%20Regul.%20Pap.&amp;volume=66&amp;pages=1935-1947&amp;publication_year=2019&amp;author=Lupo%2CN&amp;author=P%C3%A9rez%2CE&amp;author=Wenger%2CC&amp;author=Maloberti%2CF&amp;author=Bonizzoni%2CE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR98\">Lee, Y. et al. Recent progress in memristor array structures and solutions for sneak path current reduction. Adv. Mater. Technol. 10, 2400585 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 98\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Recent%20progress%20in%20memristor%20array%20structures%20and%20solutions%20for%20sneak%20path%20current%20reduction&amp;journal=Adv.%20Mater.%20Technol.&amp;volume=10&amp;publication_year=2025&amp;author=Lee%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR99\">Murmann, B. Mixed-signal computing for deep neural network inference. IEEE Trans. Very Large Scale Integr. VLSI Syst. 29, 3\u201313 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 99\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Mixed-signal%20computing%20for%20deep%20neural%20network%20inference&amp;journal=IEEE%20Trans.%20Very%20Large%20Scale%20Integr.%20VLSI%20Syst.&amp;volume=29&amp;pages=3-13&amp;publication_year=2021&amp;author=Murmann%2CB\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR100\">Zeng, T. et al. Approaching the ideal linearity in epitaxial crystalline-type memristor by controlling filament growth. Adv. Mater. 36, 2401021 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 100\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Approaching%20the%20ideal%20linearity%20in%20epitaxial%20crystalline-type%20memristor%20by%20controlling%20filament%20growth&amp;journal=Adv.%20Mater.&amp;volume=36&amp;publication_year=2024&amp;author=Zeng%2CT\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR101\">Islam, R. et al. Improved gradual resistive switching range and 1000\u2009\u00d7\u2009on\/off ratio in HfOx RRAM achieved with a Ge2Sb2Te5 thermal barrier. Appl. Phys. Lett. 121, 082103 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022ApPhL.121h2103I\" aria-label=\"ADS reference 101\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 101\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Improved%20gradual%20resistive%20switching%20range%20and%201000%E2%80%89%C3%97%E2%80%89on%2Foff%20ratio%20in%20HfOx%20RRAM%20achieved%20with%20a%20Ge2Sb2Te5%20thermal%20barrier&amp;journal=Appl.%20Phys.%20Lett.&amp;volume=121&amp;publication_year=2022&amp;author=Islam%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR102\">Wu, W. et al. A methodology to improve linearity of analog RRAM for neuromorphic computing. In Proc. 2018 IEEE Symposium on VLSI Technology 103\u2013104 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR103\">Vishwakarma, K., Datta, A. &amp; Kishore, R. Symmetric linear rise and fall of conductance in a trilayer stack engineered RERAM-based synapse. ACS Appl. Electron. Mater. 2, 3263\u20133269 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 103\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Symmetric%20linear%20rise%20and%20fall%20of%20conductance%20in%20a%20trilayer%20stack%20engineered%20RERAM-based%20synapse&amp;journal=ACS%20Appl.%20Electron.%20Mater.&amp;volume=2&amp;pages=3263-3269&amp;publication_year=2020&amp;author=Vishwakarma%2CK&amp;author=Datta%2CA&amp;author=Kishore%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR104\">Kang, J. et al. Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing. Nat. Commun. 13, 4040 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022NatCo..13.4040K\" aria-label=\"ADS reference 104\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 104\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Cluster-type%20analogue%20memristor%20by%20engineering%20redox%20dynamics%20for%20high-performance%20neuromorphic%20computing&amp;journal=Nat.%20Commun.&amp;volume=13&amp;publication_year=2022&amp;author=Kang%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR105\">Kempen, T., Waser, R. &amp; Rana, V. 50x endurance improvement in TaOx RRAM by extrinsic doping. In Proc. 2021 IEEE International Memory Workshop 1\u20134\u00a0(IEEE, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR106\">Lee, M. J. et al. A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O(5-x)\/TaO(2-x) bilayer structures. Nat. Mater. 10, 625\u2013630 (2011).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2011AIPC.1399..625L\" aria-label=\"ADS reference 106\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 106\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20fast%2C%20high-endurance%20and%20scalable%20non-volatile%20memory%20device%20made%20from%20asymmetric%20Ta2O%285-x%29%2FTaO%282-x%29%20bilayer%20structures&amp;journal=Nat.%20Mater.&amp;volume=10&amp;pages=625-630&amp;publication_year=2011&amp;author=Lee%2CMJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR107\">Lee, H. Y. et al. Low power and high speed bipolar switching with a thin reactive Ti buffer layer in robust HfO2 based RRAM. In Proc.\u00a02008 IEEE International Electron Devices Meeting 1\u20134 (IEEE, 2008).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR108\">Lee, Y. et al. Programmable retention characteristics in MoS2-based atomristors for neuromorphic and reservoir computing systems. ACS Nano 18, 14327\u201314338 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 108\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Programmable%20retention%20characteristics%20in%20MoS2-based%20atomristors%20for%20neuromorphic%20and%20reservoir%20computing%20systems&amp;journal=ACS%20Nano&amp;volume=18&amp;pages=14327-14338&amp;publication_year=2024&amp;author=Lee%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR109\">Yuan, Y. et al. On-chip atomristors. Mater. Sci. Eng. R Rep. 165, 101006 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 109\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=On-chip%20atomristors&amp;journal=Mater.%20Sci.%20Eng.%20R%20Rep.&amp;volume=165&amp;publication_year=2025&amp;author=Yuan%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR110\">Chang, H.-P., Akinwande, D. &amp; Incorvia, J. A. C. Monolayer hBN RRAM with high DC endurance and low operation voltages using an oxidized top electrode. In Proc. 2024 Device Research Conference 1\u20132\u00a0(IEEE, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR111\">Choi, S. et al. SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations. Nat. Mater. 17, 335\u2013340 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 111\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=SiGe%20epitaxial%20memory%20for%20neuromorphic%20computing%20with%20reproducible%20high%20performance%20based%20on%20engineered%20dislocations&amp;journal=Nat.%20Mater.&amp;volume=17&amp;pages=335-340&amp;publication_year=2018&amp;author=Choi%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR112\">Park, J. et al. Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge. Nat. Commun. 15, 3492 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024NatCo..15.3492P\" aria-label=\"ADS reference 112\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 112\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Multi-level%2C%20forming%20and%20filament%20free%2C%20bulk%20switching%20trilayer%20RRAM%20for%20neuromorphic%20computing%20at%20the%20edge&amp;journal=Nat.%20Commun.&amp;volume=15&amp;publication_year=2024&amp;author=Park%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR113\">Kim, S. et al. 4-bit multilevel operation in overshoot suppressed Al2O3\/TiOx resistive random-access memory crossbar array. Adv. Intell. Syst. 4, 2100273 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 113\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=4-bit%20multilevel%20operation%20in%20overshoot%20suppressed%20Al2O3%2FTiOx%20resistive%20random-access%20memory%20crossbar%20array&amp;journal=Adv.%20Intell.%20Syst.&amp;volume=4&amp;publication_year=2022&amp;author=Kim%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR114\">Ren, K. et al. Controllable SET process in O\u2013Ti\u2013Sb\u2013Te based phase change memory for synaptic application. Appl. Phys. Lett. 112, 073106 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018ApPhL.112g3106R\" aria-label=\"ADS reference 114\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 114\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Controllable%20SET%20process%20in%20O%E2%80%93Ti%E2%80%93Sb%E2%80%93Te%20based%20phase%20change%20memory%20for%20synaptic%20application&amp;journal=Appl.%20Phys.%20Lett.&amp;volume=112&amp;publication_year=2018&amp;author=Ren%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR115\">Zhou, X. et al. Understanding phase-change behaviors of carbon-doped Ge2Sb2Te5 for phase-change memory application. ACS Appl. Mater. Interfaces 6, 14207\u201314214 (2014).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 115\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Understanding%20phase-change%20behaviors%20of%20carbon-doped%20Ge2Sb2Te5%20for%20phase-change%20memory%20application&amp;journal=ACS%20Appl.%20Mater.%20Interfaces&amp;volume=6&amp;pages=14207-14214&amp;publication_year=2014&amp;author=Zhou%2CX\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR116\">Khan, A. I. et al. Energy efficient neuro-inspired phase\u2013change memory based on Ge4Sb6Te7 as a novel epitaxial nanocomposite. Adv. Mater. 35, 2300107 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 116\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Energy%20efficient%20neuro-inspired%20phase%E2%80%93change%20memory%20based%20on%20Ge4Sb6Te7%20as%20a%20novel%20epitaxial%20nanocomposite&amp;journal=Adv.%20Mater.&amp;volume=35&amp;publication_year=2023&amp;author=Khan%2CAI\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR117\">Bin Hamid, S., Intisar Khan, A., Zhang, H., Davydov, A. V. &amp; Pop, E. Low-energy spiking neural network using Ge4Sb6Te7 phase change memory synapses. IEEE Electron Device Lett. 45, 1819\u20131822 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024IEDL...45.1819B\" aria-label=\"ADS reference 117\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 117\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Low-energy%20spiking%20neural%20network%20using%20Ge4Sb6Te7%20phase%20change%20memory%20synapses&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=45&amp;pages=1819-1822&amp;publication_year=2024&amp;author=Hamid%2CS&amp;author=Intisar%20Khan%2CA&amp;author=Zhang%2CH&amp;author=Davydov%2CAV&amp;author=Pop%2CE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR118\">Suri, M. et al. Addition of HfO2 interface layer for improved synaptic performance of phase change memory (PCM) devices. Solid State Electron. 79, 227\u2013232 (2013).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2013SSEle..79..227S\" aria-label=\"ADS reference 118\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 118\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Addition%20of%20HfO2%20interface%20layer%20for%20improved%20synaptic%20performance%20of%20phase%20change%20memory%20%28PCM%29%20devices&amp;journal=Solid%20State%20Electron.&amp;volume=79&amp;pages=227-232&amp;publication_year=2013&amp;author=Suri%2CM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR119\">Lin, J. et al. Design of all-phase-change-memory spiking neural network enabled by Ge\u2013Ga\u2013Sb compound. Sci. China Mater. 66, 1551\u20131558 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2023usnb.book.....L\" aria-label=\"ADS reference 119\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 119\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Design%20of%20all-phase-change-memory%20spiking%20neural%20network%20enabled%20by%20Ge%E2%80%93Ga%E2%80%93Sb%20compound&amp;journal=Sci.%20China%20Mater.&amp;volume=66&amp;pages=1551-1558&amp;publication_year=2023&amp;author=Lin%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR120\">Kim, W. et al. Confined PCM-based analog synaptic devices offering low resistance-drift and 1000 programmable states for deep learning. In Proc. 2019 Symposium on VLSI Technology T66\u2013T67 (IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR121\">Wu, X. et al. Novel nanocomposite-superlattices for low energy and high stability nanoscale phase-change memory. Nat. Commun. 15, 13 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024NatCo..15...13W\" aria-label=\"ADS reference 121\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 121\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Novel%20nanocomposite-superlattices%20for%20low%20energy%20and%20high%20stability%20nanoscale%20phase-change%20memory&amp;journal=Nat.%20Commun&amp;volume=15&amp;publication_year=2024&amp;author=Wu%2CX\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR122\">Intisar Khan, A. et al. First demonstration of Ge2Sb2Te5-based superlattice phase change memory with low reset current density (\u22123 MA\/cm2) and low resistance drift (\u22120.002 at 105\u2009\u00b0C). In Proc. 2022 IEEE Symposium on VLSI Technology and Circuits 310\u2013311 (IEEE, 2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR123\">Liu, S. et al. A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks. Appl. Phys. Lett. 118, 202405 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021ApPhL.118t2405L\" aria-label=\"ADS reference 123\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 123\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20domain%20wall-magnetic%20tunnel%20junction%20artificial%20synapse%20with%20notched%20geometry%20for%20accurate%20and%20efficient%20training%20of%20deep%20neural%20networks&amp;journal=Appl.%20Phys.%20Lett.&amp;volume=118&amp;publication_year=2021&amp;author=Liu%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR124\">Hissariya, R. &amp; Bhowmik, D. Improving linearity and symmetry of synaptic update characteristics and retentivity of synaptic states of the domain-wall device through addition of edge notches. IEEE Open J. Nanotechnol. 6, 1\u20139 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 124\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Improving%20linearity%20and%20symmetry%20of%20synaptic%20update%20characteristics%20and%20retentivity%20of%20synaptic%20states%20of%20the%20domain-wall%20device%20through%20addition%20of%20edge%20notches&amp;journal=IEEE%20Open%20J.%20Nanotechnol.&amp;volume=6&amp;pages=1-9&amp;publication_year=2025&amp;author=Hissariya%2CR&amp;author=Bhowmik%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR125\">Leonard, T. et al. Shape-dependent multi-weight magnetic artificial synapses for neuromorphic computing. Adv. Electron. Mater. 8, 2200563 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 125\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Shape-dependent%20multi-weight%20magnetic%20artificial%20synapses%20for%20neuromorphic%20computing&amp;journal=Adv.%20Electron.%20Mater.&amp;volume=8&amp;publication_year=2022&amp;author=Leonard%2CT\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR126\">Ostwal, V., Zand, R., Demara, R. &amp; Appenzeller, J. A novel compound synapse using probabilistic spin-orbit-torque switching for MTJ-based deep neural networks. IEEE J. Explor. Solid State Comput. Devices Circuits 5, 182\u2013187 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019IJESS...5..182O\" aria-label=\"ADS reference 126\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 126\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20novel%20compound%20synapse%20using%20probabilistic%20spin-orbit-torque%20switching%20for%20MTJ-based%20deep%20neural%20networks&amp;journal=IEEE%20J.%20Explor.%20Solid%20State%20Comput.%20Devices%20Circuits&amp;volume=5&amp;pages=182-187&amp;publication_year=2019&amp;author=Ostwal%2CV&amp;author=Zand%2CR&amp;author=Demara%2CR&amp;author=Appenzeller%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR127\">Jeong, J. et al. Spintronic artificial synapses using voltage-controlled multilevel magnetic states. Adv. Electron. Mater. 10, 2300889 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 127\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Spintronic%20artificial%20synapses%20using%20voltage-controlled%20multilevel%20magnetic%20states&amp;journal=Adv.%20Electron.%20Mater.&amp;volume=10&amp;publication_year=2024&amp;author=Jeong%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR128\">Raymenants, E. et al. Nanoscale domain wall devices with magnetic tunnel junction read and write. Nat. Electron. 4, 392\u2013398 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 128\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Nanoscale%20domain%20wall%20devices%20with%20magnetic%20tunnel%20junction%20read%20and%20write&amp;journal=Nat.%20Electron.&amp;volume=4&amp;pages=392-398&amp;publication_year=2021&amp;author=Raymenants%2CE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR129\">Jeon, J. C., Migliorini, A., Fischer, L., Yoon, J. &amp; Parkin, S. S. P. Dynamic manipulation of chiral domain wall spacing for advanced spintronic memory and logic devices. ACS Nano 18, 14507\u201314513 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 129\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Dynamic%20manipulation%20of%20chiral%20domain%20wall%20spacing%20for%20advanced%20spintronic%20memory%20and%20logic%20devices&amp;journal=ACS%20Nano&amp;volume=18&amp;pages=14507-14513&amp;publication_year=2024&amp;author=Jeon%2CJC&amp;author=Migliorini%2CA&amp;author=Fischer%2CL&amp;author=Yoon%2CJ&amp;author=Parkin%2CSSP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR130\">Zhou, Y. et al. Hybrid-FE-layer FeFET with high linearity and endurance toward on-chip CIM by array demonstration. IEEE Electron Device Lett. 45, 276\u2013279 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024IEDL...45..276Z\" aria-label=\"ADS reference 130\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 130\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Hybrid-FE-layer%20FeFET%20with%20high%20linearity%20and%20endurance%20toward%20on-chip%20CIM%20by%20array%20demonstration&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=45&amp;pages=276-279&amp;publication_year=2024&amp;author=Zhou%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR131\">Aabrar, K. A. et al. BEOL-compatible superlattice FeFET analog synapse with improved linearity and symmetry of weight update. IEEE Trans. Electron Devices 69, 2094\u20132100 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022ITED...69.2094A\" aria-label=\"ADS reference 131\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 131\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=BEOL-compatible%20superlattice%20FeFET%20analog%20synapse%20with%20improved%20linearity%20and%20symmetry%20of%20weight%20update&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=69&amp;pages=2094-2100&amp;publication_year=2022&amp;author=Aabrar%2CKA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR132\">Yoon, S. J. et al. Improvement in long-term and high-temperature retention stability of ferroelectric field-effect memory transistors with metal-ferroelectric-metal\u2013insulator\u2013semiconductor gate-stacks using Al-doped HfO2 thin films. IEEE Trans. Electron Devices 67, 499\u2013504 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020ITED...67..499Y\" aria-label=\"ADS reference 132\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 132\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Improvement%20in%20long-term%20and%20high-temperature%20retention%20stability%20of%20ferroelectric%20field-effect%20memory%20transistors%20with%20metal-ferroelectric-metal%E2%80%93insulator%E2%80%93semiconductor%20gate-stacks%20using%20Al-doped%20HfO2%20thin%20films&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=67&amp;pages=499-504&amp;publication_year=2020&amp;author=Yoon%2CSJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR133\">Ali, T. et al. High Endurance ferroelectric hafnium oxide-based FeFET memory without retention penalty. IEEE Trans. Electron Devices 65, 3769\u20133774 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018ITED...65.3769A\" aria-label=\"ADS reference 133\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 133\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=High%20Endurance%20ferroelectric%20hafnium%20oxide-based%20FeFET%20memory%20without%20retention%20penalty&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=65&amp;pages=3769-3774&amp;publication_year=2018&amp;author=Ali%2CT\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR134\">Tan, A. J. et al. Ferroelectric HfO2 memory transistors with high-\u03ba interfacial layer and write endurance exceeding 1010 cycles. IEEE Electron Device Lett. 42, 994\u2013997 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021IEDL...42..994T\" aria-label=\"ADS reference 134\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 134\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Ferroelectric%20HfO2%20memory%20transistors%20with%20high-%CE%BA%20interfacial%20layer%20and%20write%20endurance%20exceeding%201010%20cycles&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=42&amp;pages=994-997&amp;publication_year=2021&amp;author=Tan%2CAJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR135\">Zhang, Y. et al. Optimized programming scheme enabling symmetric conductance modulation in HfO resistive random-access memory (RRAM) for neuromorphic systems. IEEE Electron Device Lett. 43, 1203\u20131206 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022IEDL...43.1203Z\" aria-label=\"ADS reference 135\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 135\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Optimized%20programming%20scheme%20enabling%20symmetric%20conductance%20modulation%20in%20HfO%20resistive%20random-access%20memory%20%28RRAM%29%20for%20neuromorphic%20systems&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=43&amp;pages=1203-1206&amp;publication_year=2022&amp;author=Zhang%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR136\">Park, J. et al. TiOx-based RRAM synapse with 64-levels of conductance and symmetric conductance change by adopting a hybrid pulse scheme for neuromorphic computing. IEEE Electron Device Lett. 37, 1559\u20131562 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2016IEDL...37.1559P\" aria-label=\"ADS reference 136\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 136\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=TiOx-based%20RRAM%20synapse%20with%2064-levels%20of%20conductance%20and%20symmetric%20conductance%20change%20by%20adopting%20a%20hybrid%20pulse%20scheme%20for%20neuromorphic%20computing&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=37&amp;pages=1559-1562&amp;publication_year=2016&amp;author=Park%2CJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR137\">Moon, K., Kwak, M., Park, J., Lee, D. &amp; Hwang, H. Improved conductance linearity and conductance ratio of 1T2R synapse device for neuromorphic systems. IEEE Electron Device Lett. 38, 1023\u20131026 (2017).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2017IEDL...38.1023M\" aria-label=\"ADS reference 137\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 137\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Improved%20conductance%20linearity%20and%20conductance%20ratio%20of%201T2R%20synapse%20device%20for%20neuromorphic%20systems&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=38&amp;pages=1023-1026&amp;publication_year=2017&amp;author=Moon%2CK&amp;author=Kwak%2CM&amp;author=Park%2CJ&amp;author=Lee%2CD&amp;author=Hwang%2CH\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR138\">Sakhuja, J., Patil, S., Mondal, S., Lashkare, S. &amp; Ganguly, U. Enhancement in bipolar conductance linearity by one transistor\u2013one resistor (1T1R) cell with non-filamentary PCMO-RRAM as synapse for neural networks. In Proc. 2023 7th IEEE Electron Devices Technology &amp; Manufacturing Conference 1\u20133 (IEEE, 2023).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR139\">Zhou, Z. et al. A new hardware implementation approach of BNNs based on nonlinear 2T2R synaptic cell. In Proc. 2018 IEEE International Electron Devices Meeting 20.7.1\u201320.7.4 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR140\">Li, C. et al. Efficient and self-adaptive in-situ learning in multilayer memristor neural networks. Nat. Commun. 9, 2385 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018NatCo...9.2385L\" aria-label=\"ADS reference 140\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 140\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Efficient%20and%20self-adaptive%20in-situ%20learning%20in%20multilayer%20memristor%20neural%20networks&amp;journal=Nat.%20Commun.&amp;volume=9&amp;publication_year=2018&amp;author=Li%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR141\">Ninomiya, T. et al. Improvement of data retention during long-term use by suppressing conductive filament expansion in TaOx bipolar-ReRAM. IEEE Electron Device Lett. 34, 762\u2013764 (2013).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2013IEDL...34..762N\" aria-label=\"ADS reference 141\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 141\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Improvement%20of%20data%20retention%20during%20long-term%20use%20by%20suppressing%20conductive%20filament%20expansion%20in%20TaOx%20bipolar-ReRAM&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=34&amp;pages=762-764&amp;publication_year=2013&amp;author=Ninomiya%2CT\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR142\">Zhang, Y. et al. An improved RRAM-based binarized neural network with high variation-tolerated forward\/backward propagation module. IEEE Trans. Electron Devices 67, 469\u2013473 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020ITED...67..469Z\" aria-label=\"ADS reference 142\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 142\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=An%20improved%20RRAM-based%20binarized%20neural%20network%20with%20high%20variation-tolerated%20forward%2Fbackward%20propagation%20module&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=67&amp;pages=469-473&amp;publication_year=2020&amp;author=Zhang%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR143\">Bichler, O. et al. Visual pattern extraction using energy-efficient \u20182-PCM synapse\u2019 neuromorphic architecture. IEEE Trans. Electron Devices 59, 2206\u20132214 (2012).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2012ITED...59.2206B\" aria-label=\"ADS reference 143\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 143\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Visual%20pattern%20extraction%20using%20energy-efficient%20%E2%80%982-PCM%20synapse%E2%80%99%20neuromorphic%20architecture&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=59&amp;pages=2206-2214&amp;publication_year=2012&amp;author=Bichler%2CO\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR144\">Kuzum, D., Jeyasingh, R. G. D., Lee, B. &amp; Wong, H. S. P. Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing. Nano Lett. 12, 2179\u20132186 (2012).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2012NanoL..12.2179K\" aria-label=\"ADS reference 144\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 144\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Nanoelectronic%20programmable%20synapses%20based%20on%20phase%20change%20materials%20for%20brain-inspired%20computing&amp;journal=Nano%20Lett.&amp;volume=12&amp;pages=2179-2186&amp;publication_year=2012&amp;author=Kuzum%2CD&amp;author=Jeyasingh%2CRGD&amp;author=Lee%2CB&amp;author=Wong%2CHSP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR145\">Stern, K. et al. Sub-nanosecond pulses enable partial reset for analog phase change memory. IEEE Electron Device Lett. 42, 1291\u20131294 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021IEDL...42.1291S\" aria-label=\"ADS reference 145\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 145\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Sub-nanosecond%20pulses%20enable%20partial%20reset%20for%20analog%20phase%20change%20memory&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=42&amp;pages=1291-1294&amp;publication_year=2021&amp;author=Stern%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR146\">Shi, Y. et al. Adaptive quantization as a device-algorithm co-design approach to improve the performance of in-memory unsupervised learning with SNNs. IEEE Trans. Electron Devices 66, 1722\u20131728 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019ITED...66.1722S\" aria-label=\"ADS reference 146\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 146\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Adaptive%20quantization%20as%20a%20device-algorithm%20co-design%20approach%20to%20improve%20the%20performance%20of%20in-memory%20unsupervised%20learning%20with%20SNNs&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=66&amp;pages=1722-1728&amp;publication_year=2019&amp;author=Shi%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR147\">Joshi, V. et al. Accurate deep neural network inference using computational phase-change memory. Nat. Commun. 11, 2473 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020NatCo..11.2473J\" aria-label=\"ADS reference 147\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 147\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Accurate%20deep%20neural%20network%20inference%20using%20computational%20phase-change%20memory&amp;journal=Nat.%20Commun.&amp;volume=11&amp;publication_year=2020&amp;author=Joshi%2CV\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR148\">Taylor, L. &amp; Nitschke, G. Improving deep learning with generic data augmentation. In Proc. 2018 IEEE Symposium Series on Computational Intelligence 1542\u20131547 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR149\">Zhang, W. &amp; Li, T. Helmet: a resistance drift resilient architecture for multi-level cell phase change memory system. In Proc. 2011 IEEE\/IFIP 41st International Conference on Dependable Systems &amp; Networks 197\u2013208 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR150\">Nandakumar, S. R. et al. Experimental demonstration of supervised learning in spiking neural networks with phase-change memory synapses. Sci. Rep. 10, 8080 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020NatSR..10.8080N\" aria-label=\"ADS reference 150\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 150\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Experimental%20demonstration%20of%20supervised%20learning%20in%20spiking%20neural%20networks%20with%20phase-change%20memory%20synapses&amp;journal=Sci.%20Rep.&amp;volume=10&amp;publication_year=2020&amp;author=Nandakumar%2CSR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR151\">Chen, C. et al. Nonideality suppression and 16-state multilevel cell storage optimization in phase change memory with linear-like circuit. IEEE Trans. Electron Devices 70, 493\u2013498 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2023ITED...70..493C\" aria-label=\"ADS reference 151\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 151\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Nonideality%20suppression%20and%2016-state%20multilevel%20cell%20storage%20optimization%20in%20phase%20change%20memory%20with%20linear-like%20circuit&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=70&amp;pages=493-498&amp;publication_year=2023&amp;author=Chen%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR152\">Oh, S. et al. HfZrOx-based ferroelectric synapse device with 32 levels of conductance states for neuromorphic applications. IEEE Electron Device Lett. 38, 732\u2013735 (2017).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2017IEDL...38..732O\" aria-label=\"ADS reference 152\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 152\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=HfZrOx-based%20ferroelectric%20synapse%20device%20with%2032%20levels%20of%20conductance%20states%20for%20neuromorphic%20applications&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=38&amp;pages=732-735&amp;publication_year=2017&amp;author=Oh%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR153\">Sun, X., Wang, P., Ni, K., Datta, S. &amp; Yu, S. Exploiting hybrid precision for training and inference: a 2T-1FeFET based analog synaptic weight cell. In Proc. 2018 IEEE International Electron Devices Meeting 3.1.1\u20133.1.4 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR154\">Gong, N. et al. Deep learning acceleration in 14\u2009nm CMOS compatible ReRAM array: device, material and algorithm co-optimization. In Proc. 2022 International Electron Devices Meeting 33.7.1\u201333.7.4 (IEEE, 2022).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR155\">Zhao, G. et al. Design-technology co-optimizations for symmetric linear synapse behaviors in ferroelectric FET based neuromorphic computing. IEEE Trans. Nanotechnol. 21, 747\u2013751 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022ITNan..21..747Z\" aria-label=\"ADS reference 155\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 155\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Design-technology%20co-optimizations%20for%20symmetric%20linear%20synapse%20behaviors%20in%20ferroelectric%20FET%20based%20neuromorphic%20computing&amp;journal=IEEE%20Trans.%20Nanotechnol.&amp;volume=21&amp;pages=747-751&amp;publication_year=2022&amp;author=Zhao%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR156\">Lederer, M. et al. Ferroelectric field effect transistors as a synapse for neuromorphic application. IEEE Trans. Electron Devices 68, 2295\u20132300 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021ITED...68.2295L\" aria-label=\"ADS reference 156\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 156\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Ferroelectric%20field%20effect%20transistors%20as%20a%20synapse%20for%20neuromorphic%20application&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=68&amp;pages=2295-2300&amp;publication_year=2021&amp;author=Lederer%2CM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR157\">Agarwal, S. et al. Achieving ideal accuracies in analog neuromorphic computing using periodic carry. In Proc. 2017 Symposium on VLSI Technology T174\u2013T175 (IEEE, 2017).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR158\">Hu, M. et al. Memristor-based analog computation and neural network classification with a dot product engine. Adv. Mater. 30, 1705914 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018hwwc.book.....H\" aria-label=\"ADS reference 158\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 158\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Memristor-based%20analog%20computation%20and%20neural%20network%20classification%20with%20a%20dot%20product%20engine&amp;journal=Adv.%20Mater.&amp;volume=30&amp;publication_year=2018&amp;author=Hu%2CM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR159\">Yao, P. et al. Fully hardware-implemented memristor convolutional neural network. Nature 577, 641\u2013646 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2020Natur.577..641Y\" aria-label=\"ADS reference 159\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 159\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Fully%20hardware-implemented%20memristor%20convolutional%20neural%20network&amp;journal=Nature&amp;volume=577&amp;pages=641-646&amp;publication_year=2020&amp;author=Yao%2CP\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR160\">Nandakumar, S. R. et al. Mixed-precision deep learning based on computational memory. Front. Neurosci. 14, 519263 (2020).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 160\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Mixed-precision%20deep%20learning%20based%20on%20computational%20memory&amp;journal=Front.%20Neurosci.&amp;volume=14&amp;publication_year=2020&amp;author=Nandakumar%2CSR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR161\">Bayat, F. M. et al. Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits. Nat. Commun. 9, 2331 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018NatCo...9.2331B\" aria-label=\"ADS reference 161\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 161\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Implementation%20of%20multilayer%20perceptron%20network%20with%20highly%20uniform%20passive%20memristive%20crossbar%20circuits&amp;journal=Nat.%20Commun.&amp;volume=9&amp;publication_year=2018&amp;author=Bayat%2CFM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR162\">Yu, S., Kuzum, D. &amp; Wong, H. S. P. Design considerations of synaptic device for neuromorphic computing. In Proc. 2014 IEEE International Symposium on Circuits and Systems 1062\u20131065 (IEEE, 2014).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR163\">Eryilmaz, S. B., Kuzum, D., Yu, S. &amp; Wong, H.-S. P. Device and system level design considerations for analog-non-volatile-memory based neuromorphic architectures. In Proc. 2015 IEEE International Electron Devices Meeting 4.1.1\u20134.1.4 (IEEE, 2015).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR164\">Bi, G. Q. &amp; Poo, M. M. Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J. Neurosci. 18, 10464\u201310472 (1998).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 164\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Synaptic%20modifications%20in%20cultured%20hippocampal%20neurons%3A%20dependence%20on%20spike%20timing%2C%20synaptic%20strength%2C%20and%20postsynaptic%20cell%20type&amp;journal=J.%20Neurosci.&amp;volume=18&amp;pages=10464-10472&amp;publication_year=1998&amp;author=Bi%2CGQ&amp;author=Poo%2CMM\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR165\">Fusi, S., Drew, P. J. &amp; Abbott, L. F. Cascade models of synaptically stored memories. Neuron 45, 599\u2013611 (2005).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 165\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Cascade%20models%20of%20synaptically%20stored%20memories&amp;journal=Neuron&amp;volume=45&amp;pages=599-611&amp;publication_year=2005&amp;author=Fusi%2CS&amp;author=Drew%2CPJ&amp;author=Abbott%2CLF\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR166\">Branco, T. &amp; Staras, K. The probability of neurotransmitter release: variability and feedback control at single synapses. Nat. Rev. Neurosci. 10, 373\u2013383 (2009).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 166\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20probability%20of%20neurotransmitter%20release%3A%20variability%20and%20feedback%20control%20at%20single%20synapses&amp;journal=Nat.%20Rev.%20Neurosci.&amp;volume=10&amp;pages=373-383&amp;publication_year=2009&amp;author=Branco%2CT&amp;author=Staras%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR167\">Laborieux, A., Ernoult, M., Hirtzlin, T. &amp; Querlioz, D. Synaptic metaplasticity in binarized neural networks. Nat. Commun. 12, 2549 (2021).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2021NatCo..12.2549L\" aria-label=\"ADS reference 167\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 167\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Synaptic%20metaplasticity%20in%20binarized%20neural%20networks&amp;journal=Nat.%20Commun.&amp;volume=12&amp;publication_year=2021&amp;author=Laborieux%2CA&amp;author=Ernoult%2CM&amp;author=Hirtzlin%2CT&amp;author=Querlioz%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR168\">Zanardi, G., Bettotti, P., Morand, J., Pavesi, L. &amp; Tubiana, L. Metaplasticity and memory in multilevel recurrent feed-forward networks. Phys. Rev. E 110, 054304 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024PhRvE.110e4304Z\" aria-label=\"ADS reference 168\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"mathscinet reference\" data-track-action=\"mathscinet reference\" href=\"http:\/\/www.ams.org\/mathscinet-getitem?mr=4843432\" aria-label=\"MathSciNet reference 168\" target=\"_blank\">MathSciNet<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 168\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Metaplasticity%20and%20memory%20in%20multilevel%20recurrent%20feed-forward%20networks&amp;journal=Phys.%20Rev.%20E&amp;volume=110&amp;publication_year=2024&amp;author=Zanardi%2CG&amp;author=Bettotti%2CP&amp;author=Morand%2CJ&amp;author=Pavesi%2CL&amp;author=Tubiana%2CL\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR169\">Kireev, D. et al. Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing. Nat. Commun. 13, 4386 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2022NatCo..13.4386K\" aria-label=\"ADS reference 169\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 169\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Metaplastic%20and%20energy-efficient%20biocompatible%20graphene%20artificial%20synaptic%20transistors%20for%20enhanced%20accuracy%20neuromorphic%20computing&amp;journal=Nat.%20Commun.&amp;volume=13&amp;publication_year=2022&amp;author=Kireev%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR170\">Bernard, G. et al. Dynamic control of weight-update linearity in magneto-ionic synapses. Nano Lett. 25, 1443\u20131450 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2025NanoL..25.1443B\" aria-label=\"ADS reference 170\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 170\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Dynamic%20control%20of%20weight-update%20linearity%20in%20magneto-ionic%20synapses&amp;journal=Nano%20Lett.&amp;volume=25&amp;pages=1443-1450&amp;publication_year=2025&amp;author=Bernard%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR171\">Neal, R. M. Bayesian Learning for Neural Networks (Springer, 1996).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR172\">Liu, S. et al. Bayesian neural networks using magnetic tunnel junction-based probabilistic in-memory computing. Front. Nanotechnol. 4, 1021943 (2022).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 172\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Bayesian%20neural%20networks%20using%20magnetic%20tunnel%20junction-based%20probabilistic%20in-memory%20computing&amp;journal=Front.%20Nanotechnol.&amp;volume=4&amp;publication_year=2022&amp;author=Liu%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR173\">Shim, Y., Chen, S., Sengupta, A. &amp; Roy, K. Stochastic spin\u2013orbit torque devices as elements for Bayesian inference. Sci. Rep. 7, 14101 (2017).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2017NatSR...714101S\" aria-label=\"ADS reference 173\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 173\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Stochastic%20spin%E2%80%93orbit%20torque%20devices%20as%20elements%20for%20Bayesian%20inference&amp;journal=Sci.%20Rep.&amp;volume=7&amp;publication_year=2017&amp;author=Shim%2CY&amp;author=Chen%2CS&amp;author=Sengupta%2CA&amp;author=Roy%2CK\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR174\">Harabi, K. E. et al. A memristor-based Bayesian machine. Nat. Electron. 6, 52\u201363 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 174\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20memristor-based%20Bayesian%20machine&amp;journal=Nat.%20Electron.&amp;volume=6&amp;pages=52-63&amp;publication_year=2023&amp;author=Harabi%2CKE\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR175\">Turck, C. et al. The logarithmic memristor-based Bayesian machine. Commun. Eng. 4, 35 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 175\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20logarithmic%20memristor-based%20Bayesian%20machine&amp;journal=Commun.%20Eng.&amp;volume=4&amp;publication_year=2025&amp;author=Turck%2CC\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR176\">Neftci, E. O., Pedroni, B. U., Joshi, S., Al-Shedivat, M. &amp; Cauwenberghs, G. Stochastic synapses enable efficient brain-inspired learning machines. Front. Neurosci. 10, 185771 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 176\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Stochastic%20synapses%20enable%20efficient%20brain-inspired%20learning%20machines&amp;journal=Front.%20Neurosci.&amp;volume=10&amp;publication_year=2016&amp;author=Neftci%2CEO&amp;author=Pedroni%2CBU&amp;author=Joshi%2CS&amp;author=Al-Shedivat%2CM&amp;author=Cauwenberghs%2CG\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR177\">Das, H., Patel, K. P., Febbo, R. D., Schuman, C. D. &amp; Rose, G. S. Leveraging stochasticity in memristive synapses for efficient and reliable neuromorphic systems. npj Unconv. Comput. 2, 3 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 177\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Leveraging%20stochasticity%20in%20memristive%20synapses%20for%20efficient%20and%20reliable%20neuromorphic%20systems&amp;journal=npj%20Unconv.%20Comput.&amp;volume=2&amp;publication_year=2025&amp;author=Das%2CH&amp;author=Patel%2CKP&amp;author=Febbo%2CRD&amp;author=Schuman%2CCD&amp;author=Rose%2CGS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR178\">Wang, Z. et al. In situ training of feed-forward and recurrent convolutional memristor networks. Nat. Mach. Intell. 1, 434\u2013442 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 178\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=In%20situ%20training%20of%20feed-forward%20and%20recurrent%20convolutional%20memristor%20networks&amp;journal=Nat.%20Mach.%20Intell.&amp;volume=1&amp;pages=434-442&amp;publication_year=2019&amp;author=Wang%2CZ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR179\">Bhattacharjee, A. &amp; Panda, P. Rethinking non-idealities in memristive crossbars for adversarial robustness in neural networks. Preprint at <a href=\"https:\/\/arxiv.org\/pdf\/2008.11298\" data-track=\"click_references\" data-track-action=\"external reference\" data-track-value=\"external reference\" data-track-label=\"https:\/\/arxiv.org\/pdf\/2008.11298\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/arxiv.org\/pdf\/2008.11298<\/a> (2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR180\">Liu, Y., Mao, S., Mei, X., Yang, T. &amp; Zhao, X. Sensitivity of adversarial perturbation in fast gradient sign method. In Proc. 2019 IEEE Symposium Series on Computational Intelligence 433\u2013436 (IEEE, 2019).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR181\">Deng, Y. &amp; Karam, L. J. Universal adversarial attack via enhanced projected gradient descent. In Proc. 2020 IEEE International Conference on Image Processing 1241\u20131245 (IEEE, 2020).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR182\">Barve, S., Shukla, S., Dinakarrao, S. M. P. &amp; Jha, R. Adversarial attack mitigation approaches using RRAM-neuromorphic architectures. In Proc. ACM Great Lakes Symposium on VLSI 201\u2013206 (Association for Computing Machinery, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR183\">Yamauchi, K. et al. Conductance variation-assisted adversarial attack robustness on 40\u2009nm TaOx-based ReRAM CiM. In Proc. 2025 IEEE International Reliability Physics Symposium 1\u20136 (IEEE, 2025).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR184\">Lin, Y. et al. Demonstration of generative adversarial network by intrinsic random noises of analog RRAM devices. In Proc. 2018 IEEE International Electron Devices Meeting 3.4.1\u20133.4.4 (IEEE, 2018).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR185\">Lammie, C., B\u00fcchel, J., Vasilopoulos, A., Le Gallo, M. &amp; Sebastian, A. The inherent adversarial robustness of analog in-memory computing. Nat. Commun. 16, 1756 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2025NatCo..16.1756L\" aria-label=\"ADS reference 185\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 185\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=The%20inherent%20adversarial%20robustness%20of%20analog%20in-memory%20computing&amp;journal=Nat.%20Commun.&amp;volume=16&amp;publication_year=2025&amp;author=Lammie%2CC&amp;author=B%C3%BCchel%2CJ&amp;author=Vasilopoulos%2CA&amp;author=Gallo%2CM&amp;author=Sebastian%2CA\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR186\">Rajasekharan, D., Rangarajan, N., Patnaik, S., Sinanoglu, O. &amp; Chauhan, Y. S. SCANet: securing the weights with superparamagnetic-MTJ crossbar array networks. IEEE Trans. Neural Netw. Learn. Syst. 34, 5693\u20135707 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 186\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=SCANet%3A%20securing%20the%20weights%20with%20superparamagnetic-MTJ%20crossbar%20array%20networks.&amp;journal=IEEE%20Trans.%20Neural%20Netw.%20Learn.%20Syst.&amp;volume=34&amp;pages=5693-5707&amp;publication_year=2023&amp;author=Rajasekharan%2CD&amp;author=Rangarajan%2CN&amp;author=Patnaik%2CS&amp;author=Sinanoglu%2CO&amp;author=Chauhan%2CYS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR187\">Koh, D. et al. Closed loop superparamagnetic tunnel junctions for reliable true randomness and generative artificial intelligence. Nano Lett. 25, 3799\u20133806 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2025NanoL..25.3799K\" aria-label=\"ADS reference 187\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 187\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Closed%20loop%20superparamagnetic%20tunnel%20junctions%20for%20reliable%20true%20randomness%20and%20generative%20artificial%20intelligence&amp;journal=Nano%20Lett.&amp;volume=25&amp;pages=3799-3806&amp;publication_year=2025&amp;author=Koh%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR188\">Berdan, R. et al. Emulating short-term synaptic dynamics with memristive devices. Sci. Rep. 6, 18639 (2016).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2016NatSR...618639B\" aria-label=\"ADS reference 188\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 188\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Emulating%20short-term%20synaptic%20dynamics%20with%20memristive%20devices&amp;journal=Sci.%20Rep.&amp;volume=6&amp;publication_year=2016&amp;author=Berdan%2CR\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR189\">Zohora, F. T., Karia, V., Soures, N. &amp; Kudithipudi, D. Probabilistic metaplasticity for continual learning with memristors. Sci. Rep. 14, 29496 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024NatSR..1429496Z\" aria-label=\"ADS reference 189\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 189\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Probabilistic%20metaplasticity%20for%20continual%20learning%20with%20memristors&amp;journal=Sci.%20Rep.&amp;volume=14&amp;publication_year=2024&amp;author=Zohora%2CFT&amp;author=Karia%2CV&amp;author=Soures%2CN&amp;author=Kudithipudi%2CD\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR190\">Lee, J. K., Kwon, O., Jeon, B. &amp; Kim, S. Reservoir computing for temporal data processing using resistive switching memory devices based on ITO treated with O2 plasma. IEEE Trans. Electron Devices 70, 5651\u20135656 (2023).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2023ITED...70.5651L\" aria-label=\"ADS reference 190\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 190\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Reservoir%20computing%20for%20temporal%20data%20processing%20using%20resistive%20switching%20memory%20devices%20based%20on%20ITO%20treated%20with%20O2%20plasma&amp;journal=IEEE%20Trans.%20Electron%20Devices&amp;volume=70&amp;pages=5651-5656&amp;publication_year=2023&amp;author=Lee%2CJK&amp;author=Kwon%2CO&amp;author=Jeon%2CB&amp;author=Kim%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR191\">Fan, X. et al. Metaplasticity-enabled graphene quantum dot devices for mitigating catastrophic forgetting in artificial neural networks. Adv. Mater. 37, 2411237 (2025).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 191\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Metaplasticity-enabled%20graphene%20quantum%20dot%20devices%20for%20mitigating%20catastrophic%20forgetting%20in%20artificial%20neural%20networks&amp;journal=Adv.%20Mater.&amp;volume=37&amp;publication_year=2025&amp;author=Fan%2CX\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR192\">Park, S. et al. Neuromorphic speech systems using advanced ReRAM-based synapse. In Proc. 2013 IEEE International Electron Devices Meeting 25.6.1\u201325.6.4 (IEEE, 2013).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR193\">Doevenspeck, J. et al. Multi-pillar SOT-MRAM for accurate analog in-memory DNN inference. In Proc. 2021 Symposium on VLSI Technology 1\u20132 (IEEE, 2021).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR194\">Kim, M. K. &amp; Lee, J. S. Ferroelectric analog synaptic transistors. Nano Lett. 19, 2044\u20132050 (2019).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2019NanoL..19.2044K\" aria-label=\"ADS reference 194\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 194\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Ferroelectric%20analog%20synaptic%20transistors&amp;journal=Nano%20Lett.&amp;volume=19&amp;pages=2044-2050&amp;publication_year=2019&amp;author=Kim%2CMK&amp;author=Lee%2CJS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR195\">Wu, W. et al. Improving analog switching in HfOx-based resistive memory with a thermal enhanced layer. IEEE Electron Device Lett. 38, 1019\u20131022 (2017).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2017IEDL...38.1019W\" aria-label=\"ADS reference 195\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 195\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Improving%20analog%20switching%20in%20HfOx-based%20resistive%20memory%20with%20a%20thermal%20enhanced%20layer&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=38&amp;pages=1019-1022&amp;publication_year=2017&amp;author=Wu%2CW\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR196\">Kumar, A. et al. Filament-free bulk RRAM with high endurance and long retention for neuromorphic few-shot learning on-chip. In Proc. 2024 IEEE International Electron Devices Meeting 1\u20134 (IEEE, 2024).<\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR197\">Zhou, Y. et al. A compact writing scheme for the reliability challenges in 1T multi-level FeFET array: variation, endurance, and write disturb. IEEE Electron Device Lett. 45, 2387\u20132390 (2024).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2024IEDL...45.2387Z\" aria-label=\"ADS reference 197\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 197\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=A%20compact%20writing%20scheme%20for%20the%20reliability%20challenges%20in%201T%20multi-level%20FeFET%20array%3A%20variation%2C%20endurance%2C%20and%20write%20disturb&amp;journal=IEEE%20Electron%20Device%20Lett.&amp;volume=45&amp;pages=2387-2390&amp;publication_year=2024&amp;author=Zhou%2CY\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR198\">Chen, P. Y., Peng, X. &amp; Yu, S. NeuroSim: a circuit-level macro model for benchmarking neuro-inspired architectures in online learning.  IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.\u00a037, 3067\u20133080 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018ITCAD..37.3067C\" aria-label=\"ADS reference 198\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 198\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=NeuroSim%3A%20a%20circuit-level%20macro%20model%20for%20benchmarking%20neuro-inspired%20architectures%20in%20online%20learning&amp;journal=IEEE%20Trans.%20Comput.%20Aided%20Des.%20Integr.%20Circuits%20Syst.&amp;volume=37&amp;pages=3067-3080&amp;publication_year=2018&amp;author=Chen%2CPY&amp;author=Peng%2CX&amp;author=Yu%2CS\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n<p class=\"c-article-references__text\" id=\"ref-CR199\">Kim, S., Lim, M., Kim, Y., Kim, H. D. &amp; Choi, S. J. Impact of synaptic device variations on pattern recognition accuracy in a hardware neural network. Sci. Rep. 8, 2638 (2018).<\/p>\n<p class=\"c-article-references__links u-hide-print\"><a data-track=\"click_references\" rel=\"nofollow noopener\" data-track-label=\"link\" data-track-item_id=\"link\" data-track-value=\"ads reference\" data-track-action=\"ads reference\" href=\"http:\/\/adsabs.harvard.edu\/cgi-bin\/nph-data_query?link_type=ABSTRACT&amp;bibcode=2018NatSR...8.2638K\" aria-label=\"ADS reference 199\" target=\"_blank\">ADS<\/a>\u00a0<br \/>\n    <a data-track=\"click_references\" data-track-action=\"google scholar reference\" data-track-value=\"google scholar reference\" data-track-label=\"link\" data-track-item_id=\"link\" rel=\"nofollow noopener\" aria-label=\"Google Scholar reference 199\" href=\"http:\/\/scholar.google.com\/scholar_lookup?&amp;title=Impact%20of%20synaptic%20device%20variations%20on%20pattern%20recognition%20accuracy%20in%20a%20hardware%20neural%20network&amp;journal=Sci.%20Rep.&amp;volume=8&amp;publication_year=2018&amp;author=Kim%2CS&amp;author=Lim%2CM&amp;author=Kim%2CY&amp;author=Kim%2CHD&amp;author=Choi%2CSJ\" target=\"_blank\"><br \/>\n                    Google Scholar<\/a>\u00a0\n                <\/p>\n","protected":false},"excerpt":{"rendered":"Lecun, Y., Bengio, Y. &amp; Hinton, G. Deep learning. Nature 521, 436\u2013444 (2015). ADS\u00a0 Google Scholar\u00a0 Krizhevsky, A.,&hellip;\n","protected":false},"author":2,"featured_media":100102,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[24,25,45251,52139,617,963,164],"class_list":["post-100101","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","tag-ai","tag-artificial-intelligence","tag-electrical-and-electronic-engineering","tag-electronic-devices","tag-general","tag-information-technology","tag-physics"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/100101","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=100101"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/100101\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/100102"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=100101"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=100101"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=100101"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}