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cond-mat.mtrl-sci2020
Quantitative prediction of the fracture toughness of amorphous carbon from atomic-scale simulations
S. Mostafa Khosrownejad, James R. Kermode, Lars Pastewka
Fracture is the ultimate source of failure of amorphous carbon (a-C) films, however it is challenging to measure fracture properties of a-C from nano-indentation tests and results…
cond-mat.mtrl-sci2020
Sensitivity and Dimensionality of Atomic Environment Representations used for Machine Learning Interatomic Potentials
Berk Onat, Christoph Ortner, James R. Kermode
Faithfully representing chemical environments is essential for describing materials and molecules with machine learning approaches. Here, we present a systematic classification of…