42 citations · 94 across the 3 of their papers we have counts for
3 papers
physics.comp-ph2020★ 40 cited
Development of a general-purpose machine-learning interatomic potential for aluminum by the physically-informed neural network method
G. P. Purja Pun, V. Yamakov, J. Hickman +2
Abstract Interatomic potentials constitute the key component of large-scale atomistic simulations of materials. The recently proposed physically-informed neural network (PINN) meth…
cond-mat.stat-mech2016★ 42 cited
Temperature fluctuations in canonical systems: Insights from molecular dynamics simulations
J. Hickman, Y. Mishin
Molecular dynamics simulations of a quasi-harmonic solid are conducted to elucidate the meaning of temperature fluctuations in canonical systems and validate a well-known but frequ…
cond-mat.other2016★ 12 cited
Energy spectrum of a Langevin oscillator
Y. Mishin, J. Hickman
We derive analytical solutions for the autocorrelation and cross-correlation functions of the kinetic, potential and total energy of a Langevin oscillator. These functions are pres…