{"id":646212,"date":"2026-08-19T22:33:15","date_gmt":"2026-08-19T22:33:15","guid":{"rendered":"https:\/\/www.europesays.com\/ie\/646212\/"},"modified":"2026-08-19T22:33:15","modified_gmt":"2026-08-19T22:33:15","slug":"atomic-scale-double-slit-interferometry-with-a-focused-electron-probe","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ie\/646212\/","title":{"rendered":"Atomic-scale double-slit interferometry with a focused electron probe"},"content":{"rendered":"<p>Sample preparation and 4D-STEM<\/p>\n<p>A high-purity (99.999%), undoped, commercially available Si single crystal (Crystal Base Co., Ltd.) was mechanically crushed in a mortar and the resulting fragments dispersed onto a molybdenum TEM grid with a carbon support film and the grid was immediately transferred into the microscope to avoid surface oxidation. To remove hydrocarbon contamination, the TEM grid was annealed overnight at 300\u2009\u00b0C under high-vacuum conditions using an in situ TEM heating holder (JEOL, Ltd.) inside the microscope and subsequently cooled to room temperature before observation. STEM observations were performed using a JEM ARM300CF (JEOL, Ltd.) equipped with a cold field emission gun and a JEOL DELTA corrector, operated at an accelerating voltage of 300\u2009kV. The probe-forming aperture semi-angle was set to 9.1\u2009mrad and the probe current was estimated to be approximately 9.1\u2009pA. This convergence semi-angle was chosen so that the probe size matches the Si\u2009[110] dumbbell spacing; for substantially larger or smaller probes, the double-slit condition is not satisfied and the characteristic interference fringes do not appear (Supplementary Note\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">9<\/a>). 4D-STEM datasets were acquired using a pixelated detector (ARINA<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 37\" title=\"Zambon, P. et al. High-frame rate and high-count rate hybrid pixel detector for 4D STEM applications. Front. Phys. 11, 1308321 (2023).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR37\" id=\"ref-link-section-d36566011e1712\" rel=\"nofollow noopener\" target=\"_blank\">37<\/a>, DECTRIS Ltd.) with 192\u2009\u00d7\u2009192\u2009pixels to record the full CBED pattern at each probe position. The scan sampling interval was set to 12\u2009pm for all 4D-STEM measurements.<\/p>\n<p>To realize the atomic-scale double-slit geometry, the crystal was precisely oriented to the [110] zone axis using Kikuchi lines and position-averaged convergent beam electron diffraction (PACBED). The electron-probe position at the centre of the Si\u2009[110] dumbbell was determined a posteriori with 12-pm precision from the acquired 4D-STEM dataset using a two-step numerical procedure. We note that the high-angle interference fringes used for correlation extraction are inherently robust against small probe positioning offsets, as the fringe visibility is governed by the intercolumn optical-path difference rather than the absolute probe position, and any residual positional uncertainty is already subsumed within the finite effective source size accounted for in the simulations (Supplementary Note\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">3<\/a>). First, initial atomic column positions were estimated from the reconstructed annular dark-field images using 2D Gaussian peak fitting (Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig12\" rel=\"nofollow noopener\" target=\"_blank\">8a<\/a>). Then, to overcome precision limits imposed by scan noise and sample drift, we refined the dumbbell centre positions by exploiting the crystallographic symmetry of the CBED patterns<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 38\" title=\"Krajnak, M. &amp; Etheridge, J. A symmetry-derived mechanism for atomic resolution imaging. Proc. Natl Acad. Sci. USA 117, 27805&#x2013;27810 (2020).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR38\" id=\"ref-link-section-d36566011e1725\" rel=\"nofollow noopener\" target=\"_blank\">38<\/a>. Using the twofold rotational symmetry (C2) of the Si\u2009[110] projection, we calculated a symmetry score S(<b>r<\/b>) at each probe position <b>r<\/b>, defined as 1 minus the normalized MSE between the CBED intensity and its 180\u00b0-rotated counterpart:<\/p>\n<p>$$S({\\bf{r}})=1-\\frac{\\sum _{{\\bf{k}}}{|I({\\bf{k}};{\\bf{r}})-{\\hat{R}}_{180}I({\\bf{k}};{\\bf{r}})|}^{2}}{\\sum _{{\\bf{k}}}{|I({\\bf{k}};{\\bf{r}})|}^{2}},$$<\/p>\n<p>in which S(<b>r<\/b>)\u2009=\u20091 (S\u2009\u2208\u2009[\u22121,\u20091]) corresponds to exact twofold rotational symmetry. As shown in Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig12\" rel=\"nofollow noopener\" target=\"_blank\">8b<\/a>, this score exhibits sharp local maxima at high-symmetry points. We identified the refined dumbbell centres by locating these maxima in the vicinity of the coarse estimates. To achieve high signal-to-noise ratios while minimizing the impact of sample drift at each temperature, we acquired several 4D-STEM datasets (typically 10\u201315 scans within the same tens of nanometres field of view) under identical experimental conditions. For each temperature, equivalent CBED patterns corresponding to the refined dumbbell centres identified across these datasets were extracted and averaged to produce the high signal-to-noise ratio experimental patterns used for quantitative visibility analysis.<\/p>\n<p>In situ heating experiments<\/p>\n<p>Temperature-dependent observations were conducted using the same in situ TEM heating holder. The sample was sequentially heated to 300\u2009K (room temperature), 500\u2009K and 900\u2009K, with sufficient time allowed at each temperature set point to ensure thermal equilibrium before image acquisition. STEM images and 4D-STEM datasets were recorded at each temperature under identical optical conditions to enable quantitative comparison of temperature-dependent changes.<\/p>\n<p>Scattering simulations<\/p>\n<p>CBED patterns were simulated using the multislice method implemented in the abTEM<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 39\" title=\"Madsen, J. &amp; Susi, T. The abTEM code: transmission electron microscopy from first principles. Open Res. Eur. 1, 24 (2021).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR39\" id=\"ref-link-section-d36566011e2001\" rel=\"nofollow noopener\" target=\"_blank\">39<\/a> code. The microscope parameters were set to match the experimental conditions: an accelerating voltage of 300\u2009kV and a probe-forming aperture semi-angle of 9.1\u2009mrad. The electron probe was positioned at the centre of the Si\u2009[110] dumbbell. To account for the finite source size and effective probe instability, we mix adjacent diffraction patterns using Gaussian weights with a FWHM of 0.8\u2009\u00c5 as a function of the distance between the probe positions at which the patterns were simulated. No aberrations (defocus, spherical or chromatic) were applied, as the effect of typical residual aberrations was found to be negligible (Supplementary Note\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">3<\/a>). The sample thickness for each temperature dataset was determined by maximizing the cross-correlation coefficient between experimental and simulated PACBED patterns<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 40\" title=\"LeBeau, J. M., Findlay, S. D., Allen, L. J. &amp; Stemmer, S. Position averaged convergent beam electron diffraction: theory and applications. Ultramicroscopy 110, 118&#x2013;125 (2010).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR40\" id=\"ref-link-section-d36566011e2008\" rel=\"nofollow noopener\" target=\"_blank\">40<\/a> (Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig13\" rel=\"nofollow noopener\" target=\"_blank\">9<\/a>). We confirmed by simulation that whether the left or the right atomic column terminates last at the exit surface makes no notable difference to the resulting patterns (Supplementary Note\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">10<\/a>). The estimated thicknesses were 12.7\u2009nm at 300\u2009K, 10.8\u2009nm at 500\u2009K and 10.4\u2009nm at 900\u2009K. For all simulations, thermal diffuse scattering was calculated by averaging over 1,000 frozen-phonon configurations. In the full correlated model, phonon vibrations in all directions are included. Note that atomic displacements parallel to the beam have a negligible first-order effect on the projected potential and hence on the CBED intensities, so the lateral displacements are the dominant factors governing fringe visibility (Supplementary Note\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">11<\/a>).<\/p>\n<p>Phonon-displacement models<\/p>\n<p>We used three distinct approaches to model atomic displacements for the frozen-phonon calculations, ranging from independent vibrations to full ab initio-derived correlations.<\/p>\n<p>Independent displacements (Einstein) model: as a baseline for uncorrelated motion, atomic displacements were sampled from isotropic Gaussian distributions with zero interatomic correlation (\u03c1\u2009=\u20090). The vibrational amplitudes were determined from the full phonon calculations described below to provide a consistent reference for comparison with the correlated model. We used nominal root mean square displacements of \\(\\sqrt{\\langle {u}^{2}\\rangle }=0.08\\,\\mathring{{\\rm{A}}}\\) at 300\u2009K, 0.10\u2009\u00c5 at 500\u2009K and 0.13\u2009\u00c5 at 900\u2009K, which are in good agreement with the experimental Si Debye\u2013Waller values tabulated by Peng et al.<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 41\" title=\"Peng, L.-M., Ren, G., Dudarev, S. L. &amp; Whelan, M. J. Debye&#x2013;Waller factors and absorptive scattering factors of elemental crystals. Acta Crystallogr. A 52, 456&#x2013;470 (1996).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR41\" id=\"ref-link-section-d36566011e2091\" rel=\"nofollow noopener\" target=\"_blank\">41<\/a>, derived from experimentally determined phonon densities of states.<\/p>\n<p>Full phonon-based correlation model: to capture realistic vibrational correlations of the periodic crystal, we performed phonon calculations. We used a machine-learned Gaussian approximation potential<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 42\" title=\"Bart&#xF3;k, A. P., Payne, M. C., Kondor, R. &amp; Cs&#xE1;nyi, G. Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons. Phys. Rev. Lett. 104, 136403 (2010).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR42\" id=\"ref-link-section-d36566011e2098\" rel=\"nofollow noopener\" target=\"_blank\">42<\/a> trained on density functional theory simulations for silicon<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 43\" title=\"Bart&#xF3;k, A. P., Kermode, J., Bernstein, N. &amp; Cs&#xE1;nyi, G. Machine learning a general-purpose interatomic potential for silicon. Phys. Rev. X 8, 041048 (2018).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR43\" id=\"ref-link-section-d36566011e2102\" rel=\"nofollow noopener\" target=\"_blank\">43<\/a>. Interatomic force evaluations were performed in QUIP<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 44\" title=\"Cs&#xE1;nyi, G. et al. Expressive programming for computational physics in Fortran 95+. Institute of Physics, Computational Physics Group. Newsletter, Spring 2007, 1&#x2013;24 (2007).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR44\" id=\"ref-link-section-d36566011e2106\" rel=\"nofollow noopener\" target=\"_blank\">44<\/a> through its Python interface, quippy<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 45\" title=\"Kermode, J. R. f90wrap: an automated tool for constructing deep Python interfaces to modern Fortran codes. J. Phys. Condens. Matter 32, 305901 (2020).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR45\" id=\"ref-link-section-d36566011e2110\" rel=\"nofollow noopener\" target=\"_blank\">45<\/a>. Second-order harmonic force constants were then extracted by means of finite-displacement calculations in a 4\u2009\u00d7\u20094\u2009\u00d7\u20094 supercell using the hiPhive<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 46\" title=\"Eriksson, F., Fransson, E. &amp; Erhart, P. The Hiphive package for the extraction of high-order force constants by machine learning. Adv. Theory Simul. 2, 1800184 (2019).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR46\" id=\"ref-link-section-d36566011e2114\" rel=\"nofollow noopener\" target=\"_blank\">46<\/a> package, including two-body terms with a cut-off of 4\u2009\u00c5 (a higher cut-off or the inclusion of three-body terms did not appreciably alter the results). The calculated phonon dispersion relation derived from these force constants using phonopy<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 47\" title=\"Togo, A., Chaput, L., Tadano, T. &amp; Tanaka, I. Implementation strategies in phonopy and phono3py. J. Phys. Condens. Matter 35, 353001 (2023).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR47\" id=\"ref-link-section-d36566011e2119\" rel=\"nofollow noopener\" target=\"_blank\">47<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 48\" title=\"Togo, A. First-principles phonon calculations with phonopy and phono3py. J. Phys. Soc. Jpn. 92, 012001 (2023).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR48\" id=\"ref-link-section-d36566011e2122\" rel=\"nofollow noopener\" target=\"_blank\">48<\/a> (Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig14\" rel=\"nofollow noopener\" target=\"_blank\">10<\/a>) shows excellent agreement with established theoretical and experimental data, confirming that the force constants extracted from the Gaussian approximation potential appropriately reproduce the vibrational properties of silicon.<\/p>\n<p>Thermal atomic displacements with correlated phonons were generated by superimposing harmonic normal modes with amplitudes and phases sampled to satisfy canonical ensemble statistics. Correlated displacement snapshots were generated in a 10\u2009\u00d7\u200914\u2009\u00d7\u2009Nz supercell constructed by repeating the Si\u2009[110] conventional unit cell, in which Nz is the supercell dimension along the beam-propagation direction and was set to correspond to the specimen thickness used in the experiment. To account for nuclear quantum zero-point motion, which is non-negligible especially at lower temperatures, we used the QM_statistics option in hiPhive<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 46\" title=\"Eriksson, F., Fransson, E. &amp; Erhart, P. The Hiphive package for the extraction of high-order force constants by machine learning. Adv. Theory Simul. 2, 1800184 (2019).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR46\" id=\"ref-link-section-d36566011e2144\" rel=\"nofollow noopener\" target=\"_blank\">46<\/a>, in which the classical phonon amplitudes are replaced by quantum-statistical harmonic-oscillator amplitudes<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 49\" title=\"West, D. &amp; Estreicher, S. K. First-principles calculations of vibrational lifetimes and decay channels: hydrogen-related modes in Si. Phys. Rev. Lett. 96, 115504 (2006).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR49\" id=\"ref-link-section-d36566011e2148\" rel=\"nofollow noopener\" target=\"_blank\">49<\/a>. Equivalently, this can be written in terms of a mode-dependent effective temperature Teff (in which \u0127 is the reduced Planck constant, kB the Boltzmann constant and \u03c9 the mode frequency):<\/p>\n<p>$${T}_{\\mathrm{eff}}(\\omega )=\\frac{\\hbar \\omega }{{2k}_{{\\rm{B}}}}\\coth \\,\\left(\\frac{\\hbar \\omega }{{2k}_{{\\rm{B}}}T}\\right).$$<\/p>\n<p>Nearest-neighbour chain model: for parametric studies, we constructed a simplified model that captures the essential physics of nearest-neighbour coupling within the two adjacent Si columns. This model enables us to generate atomic displacements for frozen-phonon simulation at a given temperature using specific correlation coefficients. Although the full phonon calculation involves the entire crystal, we modelled the lattice vibrations along the beam direction effectively as a harmonic chain with nearest-neighbour interactions. In this picture, the cumulative interaction with the surrounding bulk crystal\u2014atoms other than those in the two columns\u2014is renormalized into an effective on-site potential. We separately treated the intercolumn (x) and perpendicular (y) correlated displacements as independent 1D harmonic chains. The effective Hamiltonian is defined by an on-site spring constant K (representing the mean-field stiffness provided by the surrounding lattice) and an interatomic spring constant k (coupling adjacent atoms within the chain):<\/p>\n<p>$$H=\\sum _{i}\\left[\\frac{{p}_{\\alpha ,i}^{2}}{2m}+\\frac{{K}_{\\alpha }}{2}{u}_{\\alpha ,i}^{2}+\\frac{{k}_{\\alpha }}{2}{({u}_{\\alpha ,i}-{u}_{\\alpha ,i+1})}^{2}\\right],$$<\/p>\n<p>in which u\u03b1,i represents the displacement of the ith atom along the \u03b1\u2009\u2208\u2009{x,\u2009y} axis.<\/p>\n<p>In the language of statistical mechanics, we consider the collective displacement vector <b>u<\/b>\u03b1\u2009=\u2009[u\u03b1,1,\u2009u\u03b1,2,\u2026,\u2009u\u03b1,N]T for a chain of N atoms. The potential energy term can be written in matrix form as \\({{V}}_{\\alpha }=\\frac{{\\rm{1}}}{{\\rm{2}}}{{{\\bf{u}}}_{\\alpha }}^{{\\rm{T}}}{{\\Phi }}_{\\alpha }{{\\bf{u}}}_{\\alpha }\\). Here \u03a6\u03b1 is the tridiagonal force-constant matrix along the \u03b1 axis, which explicitly takes the form:<\/p>\n<p>$${{\\Phi }}_{\\alpha }=\\left(\\begin{array}{cccc}{K}_{\\alpha }+2{k}_{\\alpha } &amp; -{k}_{\\alpha } &amp; 0 &amp; \\cdots \\\\ -{k}_{\\alpha } &amp; {K}_{\\alpha }+2{k}_{\\alpha } &amp; -{k}_{\\alpha } &amp; \\cdots \\\\ 0 &amp; -{k}_{\\alpha } &amp; {K}_{\\alpha }+2{k}_{\\alpha } &amp; \\cdots \\\\ \\vdots  &amp; \\vdots  &amp; \\vdots  &amp; \\ddots \\end{array}\\right).$$<\/p>\n<p>Here we assume periodic boundary conditions (or focus on the bulk limit N\u2009\u2192\u2009\u221e), so that each atom has two nearest neighbours along the chain. The diagonal elements (K\u03b1\u2009+\u20092k\u03b1) represent the total stiffness felt by an atom owing to the on-site potential and bonds to both neighbours, whereas the off-diagonal elements (\u2212k\u03b1) represent the coupling. In the classical canonical ensemble, harmonic vibrations at temperature T follow the Boltzmann distribution P(<b>u<\/b>\u03b1)\u2009\u221d\u2009exp(\u2212V\u03b1\/kBT), which is mathematically equivalent to a multivariate normal distribution with the precision matrix \\({{\\varSigma }_{\\alpha }}^{-1}={{\\Phi }}_{\\alpha }\/{k}_{{\\rm{B}}}T\\). The correlation coefficient \u03c1\u03b1 between nearest-neighbour atoms A and B is formally defined as the normalized covariance of their displacements:<\/p>\n<p>$${\\rho }_{\\alpha }=\\frac{\\langle {u}_{\\alpha ,A}{u}_{\\alpha ,B}\\rangle }{\\sqrt{\\langle {u}_{\\alpha ,A}^{2}\\rangle \\langle {u}_{\\alpha ,B}^{2}\\rangle }},$$<\/p>\n<p>in which \u27e8\u2026\u27e9 denotes the ensemble average. Analytical solution of this linear-chain system yields a direct relationship between the correlation coefficient \u03c1\u03b1 and the stiffness ratio \u03ba\u03b1\u2009\u2261\u2009k\u03b1\/K\u03b1:<\/p>\n<p>$${\\rho }_{\\alpha }=\\frac{2{\\kappa }_{\\alpha }}{2{\\kappa }_{\\alpha }+1+\\sqrt{{4\\kappa }_{\\alpha }+1}},$$<\/p>\n<p>with the exact inverse relation<\/p>\n<p>$${\\kappa }_{\\alpha }=\\frac{{\\rho }_{\\alpha }}{{(1-{\\rho }_{\\alpha })}^{2}}.$$<\/p>\n<p>This relationship allows us to bridge the statistical and physical pictures: extracting the correlation coefficient from the interference pattern is equivalent to determining the local stiffness ratio \u03ba\u03b1 of the atomic bonds. For the frozen-phonon simulations, we generated the displacements of atoms within two Si columns from the multivariate normal distribution defined by the precision matrix \\({{\\varSigma }_{\\alpha }}^{-1}\\) derived from \u03c1\u03b1.<\/p>\n<p>Correlation extraction workflow<\/p>\n<p>To extract the correlation coefficients from experimental data (Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig4\" rel=\"nofollow noopener\" target=\"_blank\">4<\/a>), we performed a systematic grid search. For each temperature, we simulated CBED patterns on a 41\u2009\u00d7\u200941 grid of (\u03c1x,\u2009\u03c1y) values ranging from 0.0 to 0.8 in steps of 0.02. To specifically isolate the atomic-scale double-slit interference fringes emerging on the thermal diffuse scattering background, we masked out the bright-field disc and the low-angle Bragg diffraction regions (&lt;27.3\u2009mrad). This masking strategy effectively excludes low-angle intensities that are highly sensitive to experimental imperfections (such as residual aberrations and sample mistilt). The agreement between experiment and simulation was evaluated using the MSE of the normalized intensity distributions within this unmasked high-angle region. The optimal parameters were determined by fitting the discrete MSE landscape with a bicubic spline function and finding the global minimum of the function using the L-BFGS-B (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 50\" title=\"Zhu, C., Byrd, R. H., Lu, P. &amp; Nocedal, J. Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization. ACM Trans. Math. Softw. 23, 550&#x2013;560 (1997).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR50\" id=\"ref-link-section-d36566011e3525\" rel=\"nofollow noopener\" target=\"_blank\">50<\/a>) optimization algorithm implemented in the SciPy (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 51\" title=\"Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat. Methods 17, 261&#x2013;272 (2020).\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#ref-CR51\" id=\"ref-link-section-d36566011e3530\" rel=\"nofollow noopener\" target=\"_blank\">51<\/a>) package. To estimate the statistical uncertainties of the extracted coefficients, we randomly partitioned the total averaged CBED patterns into five independent subsets. The entire extraction procedure was repeated for each subset and the 95% CI for both \u03c1x and \u03c1y was calculated from the resulting variance. Note that this precision was achieved from a total dose of about 3\u2009\u00d7\u2009107 electrons. Because the uncertainty is limited by shot noise and scales with the inverse square root of the dose, and averaging over equivalent pairs simply accumulates dose, tuning the total dose to the precision required for a given problem could make single-position acquisition at an individual column pair feasible.<\/p>\n<p>Spectral analysis of vibrational correlations<\/p>\n<p>To identify which phonon modes contribute to the interference visibility, we decomposed the projected MSRD (see Supplementary Note\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">4<\/a> for derivation) into individual mode contributions and visualized them on the phonon dispersion relation, presented in Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig11\" rel=\"nofollow noopener\" target=\"_blank\">7<\/a>.<\/p>\n<p>In STEM, the electron beam interacts with the atomic potential integrated along the column. To account for this projective geometry, we define the column-averaged projected-mass-normalized eigenvector \\({\\mathop{{\\bf{e}}}\\limits^{ \\sim }}_{j,{\\bf{q}}\\nu }\\) for atom j (j\u2009=\u2009A,\u2009B for the two columns) in mode (<b>q<\/b>,\u2009\u03bd) as<\/p>\n<p>$${\\mathop{{\\bf{e}}}\\limits^{ \\sim }}_{j,{\\bf{q}}\\nu }=\\frac{1}{{N}_{z}\\sqrt{{m}_{j}}}\\mathop{\\sum }\\limits_{l=1}^{{N}_{z}}{{\\bf{e}}}_{j,{\\bf{q}}\\nu }\\exp ({\\rm{i}}{\\bf{q}}\\cdot {{\\bf{R}}}_{l}),$$<\/p>\n<p>in which <b>e<\/b>j,<b>q<\/b>\u03bd is the phonon eigenvector from phonon calculations, mj is the atomic mass and <b>R<\/b>l denotes lattice translation vectors along the beam direction. The summation runs over Nz unit cells corresponding to the specimen thickness. The Bloch phase factor exp(i<b>q<\/b>\u2009\u00b7\u2009<b>R<\/b>l) determines whether displacements in successive unit cells interfere constructively or destructively in the projected signal.<\/p>\n<p>For directionally resolved analysis (Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig4\" rel=\"nofollow noopener\" target=\"_blank\">4e,h<\/a>), we extract the Cartesian component \u03b1\u2009\u2208\u2009{x,\u2009y}:<\/p>\n<p>$${\\mathop{e}\\limits^{ \\sim }}_{j,{\\bf{q}}\\nu }^{(\\alpha )}={\\hat{{\\bf{n}}}}_{\\alpha }\\cdot {\\mathop{{\\bf{e}}}\\limits^{ \\sim }}_{j,{\\bf{q}}\\nu },$$<\/p>\n<p>in which \\({\\hat{{\\bf{n}}}}_{x}\\) is aligned with the Si\u2013Si bond axis and \\({\\hat{{\\bf{n}}}}_{y}\\) is perpendicular to it within the imaging plane.<\/p>\n<p>For visualization of the phonon dispersion, we group modes into spectral bins \\({{\\mathcal{D}}}_{{\\bf{q}},\\omega }\\), defined as the set of modes at wavevector q with frequency within a small window centred at \u03c9. The contribution of each bin to the projected MSRD along direction \u03b1 is given by:<\/p>\n<p>$${W}_{{\\rm{MSRD}}}^{(\\alpha )}({{\\mathcal{D}}}_{{\\bf{q}},\\omega })=\\sum _{\\nu \\in {\\mathcal{D}}}{|{\\mathop{e}\\limits^{ \\sim }}_{A,{\\bf{q}}\\nu }^{(\\alpha )}-{\\mathop{e}\\limits^{ \\sim }}_{B,{\\bf{q}}\\nu }^{(\\alpha )}|}^{2}A(\\omega ),$$<\/p>\n<p>in which<\/p>\n<p>$$A(\\omega )=\\frac{\\hbar }{2\\omega }\\coth \\left(\\frac{\\hbar \\omega }{2{k}_{{\\rm{B}}}T}\\right)$$<\/p>\n<p>is the quantum harmonic oscillator amplitude factor, arising from the variance \\(\\langle {|{\\bf{u}}|}^{2}\\rangle =\\frac{\\hbar }{2m\\omega }\\coth \\left(\\frac{\\hbar \\omega }{2{k}_{{\\rm{B}}}T}\\right)\\). For the Si\u2009[110] dumbbell structure, inversion symmetry about the bond midpoint ensures \\({|{\\mathop{e}\\limits^{ \\sim }}_{A,{\\bf{q}}\\nu }^{(\\alpha )}|}^{2}={|{\\mathop{e}\\limits^{ \\sim }}_{B,{\\bf{q}}\\nu }^{(\\alpha )}|}^{2}\\). Under this symmetry, the MSRD contribution factorizes exactly into a thermal population term \\({B}_{{\\mathcal{D}}}^{(\\alpha )}\\) (i) and a spectral correlation coefficient term \\({c}_{{\\mathcal{D}}}^{(\\alpha )}\\) (ii):<\/p>\n<p>$${W}_{{\\rm{MSRD}}}^{(\\alpha )}={B}_{{\\mathcal{D}}}^{(\\alpha )}\\times (1-{c}_{{\\mathcal{D}}}^{(\\alpha )}).$$<\/p>\n<ol class=\"u-list-style-none\">\n<li>\n                  (i)<\/p>\n<p>Thermal population \\({B}_{{\\mathcal{D}}}^{(\\alpha )}\\): the thermally excited mean squared displacement is quantified by<\/p>\n<p>$${B}_{{\\mathcal{D}}}^{(\\alpha )}({\\bf{q}},\\omega )=\\left(\\sum _{\\nu \\in {\\mathcal{D}}}{|{\\mathop{e}\\limits^{ \\sim }}_{A,{\\bf{q}}\\nu }^{(\\alpha )}|}^{2}+\\sum _{\\nu \\in {\\mathcal{D}}}{|{\\mathop{e}\\limits^{ \\sim }}_{B,{\\bf{q}}\\nu }^{(\\alpha )}|}^{2}\\right)\\,A(\\omega ).$$<\/p>\n<p>This quantity represents the vibrational power available from each mode, combining the zero-point amplitude (\u221d\u20091\/\u03c9) and thermal occupation. In the high-temperature (classical) limit, the thermal part scales as \\({B}_{{\\mathcal{D}}}^{(\\alpha )}\\propto 1\/{\\omega }^{2}\\).<\/p>\n<\/li>\n<li>\n                  (ii)<\/p>\n<p>Spectral correlation coefficient: the extent to which a mode generates relative displacement between the two columns is quantified by the correlation coefficient:<\/p>\n<\/li>\n<\/ol>\n<p>$${c}_{{\\mathcal{D}}}^{(\\alpha )}({\\bf{q}},\\omega )=\\frac{\\sum _{\\nu \\in {\\mathcal{D}}}{\\rm{Re}}\\,\\left[{\\mathop{e}\\limits^{ \\sim }}_{A,{\\bf{q}}\\nu }^{(\\alpha )}\\cdot {({\\mathop{e}\\limits^{ \\sim }}_{B,{\\bf{q}}\\nu }^{(\\alpha )})}^{* }\\right]}{\\sqrt{\\left(\\sum _{\\nu \\in {\\mathcal{D}}}{|{\\mathop{e}\\limits^{ \\sim }}_{A,{\\bf{q}}\\nu }^{(\\alpha )}|}^{2}\\right)\\left(\\sum _{\\nu \\in {\\mathcal{D}}}{|{\\mathop{e}\\limits^{ \\sim }}_{B,{\\bf{q}}\\nu }^{(\\alpha )}|}^{2}\\right)}}.$$<\/p>\n<p>This coefficient ranges from +1 (perfectly in-phase motion, generating no relative displacement) to \u22121 (perfectly out-of-phase motion, generating maximum relative displacement). The factor \\((1-{c}_{{\\mathcal{D}}}^{(\\alpha )})\\) thus represents the capacity of the mode to induce relative motion between the two columns along direction \u03b1.<\/p>\n<p>This factorization confirms the spectral filtering mechanism: marked contribution to the MSRD (and hence to visibility loss) requires both substantial thermal population (\\({B}_{{\\mathcal{D}}}\\) large) and substantial relative-motion capacity (\\((1-{c}_{{\\mathcal{D}}})\\) large).<\/p>\n<p>The mode-resolved analysis is shown in Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig4\" rel=\"nofollow noopener\" target=\"_blank\">4e,h<\/a> and Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig11\" rel=\"nofollow noopener\" target=\"_blank\">7<\/a>. In Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig11\" rel=\"nofollow noopener\" target=\"_blank\">7a,c<\/a>, the thermal population factor is encoded in the line width of the dispersion curves and the spectral correlation coefficient is shown by the line colour (red: in-phase, \\({c}_{{\\mathcal{D}}}\\simeq 1\\); grey: no correlation, \\({c}_{{\\mathcal{D}}}\\simeq 0\\); blue: out-of-phase, \\({c}_{{\\mathcal{D}}}\\simeq -1\\)). The resulting MSRD contribution WMSRD is visualized by the colour intensity in Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig4\" rel=\"nofollow noopener\" target=\"_blank\">4e,h<\/a> and Extended Data Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-026-10914-9#Fig11\" rel=\"nofollow noopener\" target=\"_blank\">7b,d<\/a>, highlighting the modes that dominate visibility loss.<\/p>\n","protected":false},"excerpt":{"rendered":"Sample preparation and 4D-STEM A high-purity (99.999%), undoped, commercially available Si single crystal (Crystal Base Co., Ltd.) was&hellip;\n","protected":false},"author":2,"featured_media":646213,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_share_on_mastodon":"0"},"categories":[271],"tags":[18,1099,19,17,54971,1100,452,13729,133,7016,28288],"class_list":["post-646212","post","type-post","status-publish","format-standard","has-post-thumbnail","category-physics","tag-eire","tag-humanities-and-social-sciences","tag-ie","tag-ireland","tag-matter-waves-and-particle-beams","tag-multidisciplinary","tag-physics","tag-quantum-mechanics","tag-science","tag-thermodynamics","tag-transmission-electron-microscopy"],"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@ie\/117124556833626715","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/646212","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=646212"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/646212\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/646213"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=646212"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=646212"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=646212"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}