GPU-MetaD: Full-Life-Cycle GPU Accelerated Metadynamics with Machine Learning Potentials
Haoting Zhang, Qiuhan Jia(Collaborative Innovation Center of Advanced Microstructures), Jianping Sun, Junjie Wang(China Pharmaceutical University), Jiuyang Shi(Collaborative Innovation Center of Advanced Microstructures)
Cited by 1
Related Papers
General-purpose machine-learned potential for 16 elemental metals and their alloys
|Nature Communications|2024|161
GPUMD 4.0: A high‐performance molecular dynamics package for versatile materials simulations with machine‐learned potentials
|Materials Genome Engineering Advances|2025|68
Mixed Coordination Silica at Megabar Pressure
|Physical Review Letters|2021|55
Superionic Silica-Water and Silica-Hydrogen Compounds in the Deep Interiors of Uranus and Neptune
|Physical Review Letters|2022|46
Double-Shock Compression Pathways from Diamond to BC8 Carbon
|Physical Review Letters|2023|36