Sergei V Kalinin Collaborator, University of Tennessee Contact kalininsv@ornl.gov All Publications Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hysteresis Correlation Between Corrugation-Induced Flexoelectric Polarization and Conductivity of Low-Dimensional Transition Metal Dichalcogenides Exploring order parameters and dynamic processes in disordered systems via variational autoencoders Predictability of Localized Plasmonic Responses in Nanoparticle Assemblies Separating Physically Distinct Mechanisms in Complex Infrared Plasmonic Nanostructures via Machine Learning Enhanced Electron Energy Loss Spectroscopy Disentangling Rotational Dynamics and Ordering Transitions in a System of Self-Organizing Protein Nanorods via Rotationally Invariant Latent Representations Investigating phase transitions from local crystallographic analysis based on statistical learning of atomic environments in 2D MoS 2 -ReS 2 Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration Predictability as a probe of manifest and latent physics: The case of atomic scale structural, chemical, and polarization behaviors in multiferroic Sm-doped BiFeO3 Computational scanning tunneling microscope image database... Probing potential energy landscapes via electron-beam-induced single atom dynamics Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution manifold learning Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality Toward Decoding the Relationship between Domain Structure and Functionality in Ferroelectrics via Hidden Latent Variables Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening 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 degrees of freedom Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design Direct Observation of Photoinduced Ion Migration in Lead Halide Perovskites Piezoresponse amplitude and phase quantified for electromechanical characterization Phenomenological description of bright domain walls in ferroelectric-antiferroelectric layered chalcogenides Mesoscopic structure of mixed type domain walls in multiaxial ferroelectrics Exploration of lattice Hamiltonians for functional and structural discovery via Gaussian process-based exploration–exploitation Pagination First page « First Previous page ‹â¶Ä¹ … Page 3 Current page 4 Page 5 … Next page ›â¶Äº Last page Last » Key Links
