224 citations · 654 across the 20 of their papers we have counts for
Showing 2020 · cond-mat.mtrl-sciShow all
2 papers · 2 filters
cond-mat.mtrl-sci2020★ 224 cited
Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution
Bohayra Mortazavi, Evgeny P. Podryabinkin, Ivan S. Nvikovb +3
Accurate evaluation of the thermal conductivity of a material can be a challenging task from both experimental and theoretical points of view. In particular for the nanostructured…
cond-mat.mtrl-sci2020★ 156 cited
Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials
Bohayra Mortazavi, Ivan S. Novikov, Evgeny V. Podryabinkin +4
Phononic properties are commonly studied by calculating force constants using the density functional theory (DFT) simulations. Although DFT simulations offer accurate estimations o…