4 papers · 1 filter
Shadow Molecular Dynamics for Flexible Multipole Models
Rae A. Corrigan Grove, Robert Stanton, Michael E. Wall +1
Shadow molecular dynamics provide an efficient and stable atomistic simulation framework for flexible charge models with long-range electrostatic interactions. While previous imple…
Enhancing Molecular Dipole Moment Prediction with Multitask Machine Learning
William Colglazier, Nicholas Lubbers, Sergei Tretiak +2
We present a multitask machine learning strategy for improving the prediction of molecular dipole moments by simultaneously training on quantum dipole magnitudes and inexpensive Mu…
GPU-Accelerated Charge-Equilibration for Shadow Molecular Dynamics in Python
Mehmet Cagri Kaymak, Nicholas Lubbers, Christian F. A. Negre +2
With recent advancements in machine learning for interatomic potentials, Python has become the go-to programming language for exploring new ideas. While machine-learning potentials…
Modeling Reactions on the Solid-Liquid Interface With Next Generation Extended Lagrangian Quantum-Based Molecular Dynamics
Rae A. Corrigan Grove, Kevin G. Kleiner, Joshua Finkelstein +5
We present a series of simulations of the oxygen reduction reaction (ORR) using a novel framework for atomistic simulations of surface catalysis under electrochemical bias. The fra…