Title: 

Multi-objective parametrization of interatomic potentials for large deformation pathways and fracture of two-dimensional materials

Year of Publication:

2021

Authors:

Xu Zhang, Hoang Nguyen, Jeffrey T Paci, Subramanian KRS Sankaranarayanan, Jose L Mendoza-Cortes, Horacio D Espinosa

Journal:

Nature Computational Materials

Abstract:

This investigation presents a generally applicable framework for parameterizing interatomic potentials to accurately capture large deformation pathways. It incorporates a multi-objective genetic algorithm, training and screening property sets, and correlation and principal component analyses. The framework enables iterative definition of properties in the training and screening sets, guided by correlation relationships between properties, aiming to achieve optimal parametrizations for properties of interest. Specifically, the performance of increasingly complex potentials, Buckingham, Stillinger-Weber, Tersoff, and modified reactive empirical bond-order potentials are compared. Using MoSe₂ as a case study, we demonstrate good reproducibility of training/screening properties and superior transferability. For MoSe₂, the best performance is achieved using the Tersoff potential, which is ascribed to its apparent higher …

URL:

https://www.nature.com/articles/s41524-021-00573-x