Sergei V Kalinin Collaborator, University of Tennessee Contact kalininsv@ornl.gov | 865.241.0236 All Publications Identification and correction of temporal and spatial distortions in Scanning Transmission Electron Microscopy... Bayesian Learning of Adatom Interactions from Atomically Resolved Imaging Data... Exploring the physics of cesium lead halide perovskite quantum dots via Bayesian inference of the photoluminescence spectra i... Ferroic Halide Perovskite Optoelectronics... Role of Decomposition Product Ions in Hysteretic Behavior of Metal Halide Perovskite... Probing atomic-scale symmetry breaking by rotationally invariant machine learning of multidimensional electron scattering... Ferroelectric and Charge Transport Properties in Strain-Engineered Two-Dimensional Lead Iodide Perovskites... Exploring Responses of Contact Kelvin Probe Force Microscopy in Triple-Cation Double-Halide Perovskites... Disentangling Rotational Dynamics and Ordering Transitions in a System of Self-Organizing Protein Nanorods via Rotationally I... Separating Physically Distinct Mechanisms in Complex Infrared Plasmonic Nanostructures via Machine Learning Enhanced Electron... Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hy... Predictability of Localized Plasmonic Responses in Nanoparticle Assemblies... Correlation Between Corrugation-Induced Flexoelectric Polarization and Conductivity of Low-Dimensional Transition Metal Dicha... Exploring order parameters and dynamic processes in disordered systems via variational autoencoders... Investigating phase transitions from local crystallographic analysis based on statistical learning of atomic environments in ... Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging... Predictability as a probe of manifest and latent physics: The case of atomic scale structural, chemical, and polarization beh... Toward Decoding the Relationship between Domain Structure and Functionality in Ferroelectrics via Hidden Latent Variables... Probing potential energy landscapes via electron-beam-induced single atom dynamics... Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality... Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution mani... Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data... Reconstruction and uncertainty quantification of lattice Hamiltonian model parameters from observations of microscopic degree... Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening... Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data... Pagination First page « First Previous page ‹‹ … Page 2 Current page 3 Page 4 … Next page ›› Last page Last » Key Links ORCID