73 citations · 74 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2019★ 1 cited
Ab initio phonon transport across grain boundaries in graphene using machine learning based on small dataset
Amirreza Hashemi, Ruiqiang Guo, Keivan Esfarjani +1
Establishing the structure-property relationship for grain boundaries (GBs) is critical for developing next generation functional materials, but has been severely hampered due to i…
cond-mat.mtrl-sci2019★ 73 cited
Machine-learning based interatomic potential for phonon transport in perfect crystalline Si and crystalline Si with vacancies
Hasan Babaei, Ruiqiang Guo, Amirreza Hashemi +1
We report that single interatomic potential, developed using Gaussian regression of density functional theory calculation data, has high accuracy and flexibility to describe phonon…