Researchers in the United States have successfully demonstrated an artificial intelligence (AI)-driven system to automate a powerful simulation method that predicts how atoms in materials interact. <\/p>\n
Called atomistic simulations, this method can potentially accelerate discovery of materials for areas such as batteries, aerospace and electronics.<\/p>\n
Fundamental shift in the discovery pipeline<\/p>\n
\u201cThis multi-agent framework represents a fundamental shift in the discovery pipeline. We are moving away from the manual orchestration of fragmented tools toward an era of autonomous, collaborative AI,\u201d said Uma Kornu, University of Illinois Chicago research specialist.<\/p>\n
Researchers from U.S. Department of Energy\u2019s (DOE) Argonne National Laboratory revealed that the AI-driven system automates a powerful simulation method used to discover new materials. The system can potentially reduce discovery time from months or years to just days.<\/p>\n
\u201cBy automating these exhaustive investigations, we can potentially reduce the time requirements for discovering new materials from months or years to just days,\u201d said Aditya Koneru, one of the study\u2019s authors and an Argonne Scholar at the Argonne Leadership Computing Facility (ALCF).<\/p>\n
This approach is particularly powerful because scientific discovery is inherently iterative. A failed experiment is not necessarily a dead end\u2014it can provide information that changes the next hypothesis.<\/p>\n
System lowers the barrier to use atomistic simulations<\/p>\n
\u201cOur system lowers the barrier to use atomistic simulations and enables them to be much more widely adopted across the scientific community,\u201d said Subramanian Sankaranarayanan, one of the study\u2019s lead authors. Sankaranarayanan is an Argonne materials scientist and a professor in the Department of Mechanical and Industrial Engineering at the University of Illinois Chicago.<\/p>\n
The collaborative AI system efficiently performs complex simulations from start to finish.<\/p>\n
The framework is a team of collaborating agents: AI systems that perform tasks, interpret data and make decisions with limited human intervention. The framework\u2019s architecture was designed in collaboration with researchers at the Advanced Photon Source (APS), another DOE Office of Science user facility at Argonne, according to a press release.<\/p>\n
\u201cThe multiagent AI framework streamlines the use of diverse tools to perform and analyze simulations,\u201d said Katerina Vriza, a former CNM staff scientist at Argonne.<\/p>\n
Using the framework is simple and straightforward. A human user enters a high-level prompt. The prompt can be a brief instruction like, \u200b\u201ccalculate the melting point of a gold-copper alloy.\u201d In as little as a few minutes, the framework provides a detailed answer. The framework\u2019s execution of the simulation is\u00a0much faster and results in fewer errors compared to what a human can do, as per the release.<\/p>\n
A multi-agent workflow can divide a complicated research problem into smaller tasks. Agents can then communicate with one another, critique results and combine information from different sources.<\/p>\n","protected":false},"excerpt":{"rendered":"Researchers in the United States have successfully demonstrated an artificial intelligence (AI)-driven system to automate a powerful simulation…\n","protected":false},"author":2,"featured_media":627997,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_share_on_mastodon":"0"},"categories":[77],"tags":[61338,18,84825,19,17,265095,265096,133],"class_list":["post-627996","post","type-post","status-publish","format-standard","has-post-thumbnail","category-science","tag-argonne-national-laboratory","tag-eire","tag-framework","tag-ie","tag-ireland","tag-materials-discovery","tag-multi-agent-framework","tag-science"],"share_on_mastodon":{"url":"","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/627996","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/comments?post=627996"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/627996\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/627997"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=627996"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=627996"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=627996"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}