669 citations · 3.8k across the 43 of their papers we have counts for
44 papers
Symmetry Relation Database and Its Application to Ferroelectric Materials Discovery
Qiang Zhu, Byungkyun Kang, Kevin Parrish
The ability to understand the atomistic mechanisms that occur in the solid phase transition is of crucial importance in materials research. To investigate the displacive phase tran…
Size-Dependent Nucleation in Crystal Phase Transition from Machine Learning Metadynamics
Pedro A. Santos-Florez, Howard Yanxon, Byungkyun Kang +2
In this work, we present an efficient framework that combines machine learning potential (MLP) and metadynamics to explore multi-dimensional free energy surfaces for investigating…
Switchable Atomically Thin 2D Electrides from First-principles Prediction
Xuhui Yang, Kevin Parrish, Yan-Ling Li +3
Electrides, with excess anionic electrons confined in their empty space, are promising for uses in catalysis, nonlinear optics and spin-electronics. However, the application of ele…
PyXtal FF: a Python Library for Automated Force Field Generation
Howard Yanxon, David Zagaceta, Binh Tang +2
We present PyXtal FF, a package based on Python programming language, for developing machine learning potentials (MLPs). The aim of PyXtal FF is to promote the application of atomi…
Spectral Neural Network Potentials for Binary Alloys
David Zagaceta, Howard Yanxon, Qiang Zhu
In this work, we present a numerical implementation to compute the atom centered descriptors introduced by Bartok et al (Phys. Rev. B, 87, 184115, 2013) based on the harmonic analy…
Computation and data driven discovery of topological phononic materials
Jiangxu Li, Jiaxi Liu, Stanley A. Baronett +4
The discovery of topological quantum states marks a new chapter in both condensed matter physics and materials sciences. By analogy to spin electronic system, topological concepts…