most citedAccelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution

224 citations · 441 across the 4 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci2020224 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…

physics.comp-ph2020

The MLIP package: Moment Tensor Potentials with MPI and Active Learning

Ivan S. Novikov, Konstantin Gubaev, Evgeny V. Podryabinkin +1

The subject of this paper is the technology (the "how") of constructing machine-learning interatomic potentials, rather than science (the "what" and "why") of atomistic simulations…

cond-mat.mtrl-sci2020

Predicting the propensity for thermally activated events in metallic glasses via interpretable machine learning

Qi Wang, Jun Ding, Evan Ma

The elementary excitations in metallic glasses (MGs), i.e., processes that involve hopping between nearby sub-basins, underlie many unusual properties of the amorphous alloys.…

cond-mat.mtrl-sci202061 cited

High thermal conductivity in semiconducting Janus and non-Janus diamanes

Mostafa Raeisi, Bohayra Mortazavi, Evgeny V. Podryabinkin +3

Most recently, F-diamane monolayer was experimentally realized by the fluorination of bilayer graphene. In this work we elaborately explore the electronic and thermal conductivity…

cond-mat.mtrl-sci2020156 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…

physics.comp-ph2018

Moment tensor Potentials as a Promising Tool to Study Diffusion Processes

I. I. Novoselov, A. V. Yanilkin, A. V. Shapeev +1

A recently proposed class of machine-learning interatomic potentials --- Moment tensor potentials (MTPs) --- is investigated in this work. MTPs are able to actively select configur…