activity
20182024
most citedInvestigating phase transitions from local crystallographic analysis based on machine learning of atomic environments

9 citations · 16 across the 9 of their papers we have counts for

collaborators

9 papers

cond-mat.soft2024

Behavior of water and aqueous LiCl solutions confined in cylindrical silica pores: A wide temperature range molecular dynamics simulation study

Siddharth Gautam, Lukas Vlcek, Eugene Mamontov +1

We report here a molecular dynamics simulation study on water and aqueous LiCl solutions confined in 1.6 nm cylindrical pores of silica to investigate a dynamical cross-over, obser…

cond-mat.mtrl-sci2020

Bayesian learning of adatom interactions from atomically-resolved imaging data

Mani Valleti, Qiang Zou, Rui Xue +8

Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be capture…

physics.comp-ph2020★ 2 cited

Application of variational policy gradient to atomic-scale materials synthesis

Siyan Liu, Nikolay Borodinov, Lukas Vlcek +3

Atomic-scale materials synthesis via layer deposition techniques present a unique opportunity to control material structures and yield systems that display unique functional proper…

cond-mat.mtrl-sci2020★ 9 cited

Investigating phase transitions from local crystallographic analysis based on machine learning of atomic environments

Rama K. Vasudevan, Maxim Ziatdinov, Lukas Vlcek +8

Traditionally, phase transitions are explored using a combination of macroscopic functional characterization and scattering techniques, providing insight into average properties an…

physics.comp-ph2020★ 1 cited

Off-the-shelf deep learning is not enough: parsimony, Bayes and causality

Rama K. Vasudevan, Maxim Ziatdinov, Lukas Vlcek +1

Deep neural networks ("deep learning") have emerged as a technology of choice to tackle problems in natural language processing, computer vision, speech recognition and gameplay, a…

cond-mat.stat-mech2020★ 1 cited

Reconstruction of the lattice Hamiltonian models from the observations of microscopic degrees of freedom in the presence of competing interactions

Sai Mani Prudhvi Valleti, Lukas Vlcek, Maxim Ziatdinov +2

The emergence of scanning probe and electron beam imaging techniques have allowed quantitative studies of atomic structure and minute details of electronic and vibrational structur…

cond-mat.stat-mech2019★ 2 cited

Inversion of lattice models from the observations of microscopic degrees of freedom: parameter estimation with uncertainty quantification

Sai Mani Prudhvi Valleti, Lukas Vlcek, Rama K. Vasudevan +1

Experimental advances in condensed matter physics and material science have enabled ready access to atomic-resolution images, with resolution of modern tools often sufficient to ex…

cond-mat.mtrl-sci2019★ 1 cited

Order and randomness in dopant distributions: exploring the thermodynamics of solid solutions from atomically resolved imaging

Lukas Vlcek, Shize Yang, Yongji Gong +6

Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work…

cond-mat.mtrl-sci2018

Learning from imperfections: constructing phase diagrams from atomic imaging of fluctuations

Lukas Vlcek, Maxim A. Ziatdinov, Alexander Tselev +3

Materials characterization and property measurements are a cornerstone of material science, providing feedback from synthesis to applications. Traditionally, a single sample is use…