16 citations · 16 across the 2 of their papers we have counts for
3 papers · 1 filter
Exploring the formation of gold/silver nanoalloys with gas-phase synthesis and machine-learning assisted simulations
Quentin Gromoff, Patrizio Benzo, Wissam A. Saidi +6
While nanoalloys are of paramount scientific and practical interests, the main processes leading to their formation are still poorly understood. Key structural features in the allo…
Convergence Acceleration in Machine Learning Potentials for Atomistic Simulations
Dylan Bayerl, Christopher M. Andolina, Shyam Dwaraknath +1
Machine learning potentials (MLPs) for atomistic simulations have an enormous prospective impact on materials modeling, offering orders of magnitude speedup over density functional…
Optimization and Validation of a Deep Learning CuZr Atomistic Potential: Robust Applications for Crystalline and Amorphous Phases with near-DFT Accuracy
Christopher M. Andolina, Philip Williamson, Wissam A. Saidi
We show that a deep-learning neural network potential (DP) based on density functional theory (DFT) calculations can well describe Cu-Zr materials, an example of a binary alloy sys…