ML potentials & 2D materials · 2021
Computation of the Thermal Expansion Coefficient of Graphene with Gaussian Approximation Potentials
İlker Demiroğlu, Yenal Karaaslan, Tuğbey Kocabaş, Murat Keçeli, Álvaro Vázquez-Mayagoitia, Cem Sevik
J. Phys. Chem. C 125, 14409–14415 (2021)
Summary
Uses a Gaussian approximation potential trained on ab initio data to compute the temperature-dependent thermal expansion coefficient of graphene via molecular dynamics at a fraction of the cost of ab initio MD.
Keywords
graphenethermal expansionGaussian approximation potentialsmachine-learning potentialsmolecular dynamics2D materials
Cite
@article{2021_demiroglu_graphene_thermal_expansion_gap,
title = {Computation of the Thermal Expansion Coefficient of Graphene with Gaussian Approximation Potentials},
author = {İlker Demiroğlu and Yenal Karaaslan and Tuğbey Kocabaş and Murat Keçeli and Álvaro Vázquez-Mayagoitia and Cem Sevik},
journal = {J. Phys. Chem. C 125, 14409–14415 (2021)},
year = {2021}
}