1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.DC2025★ 1 cited
Deep Learning-Enabled Supercritical Flame Simulation at Detailed Chemistry and Real-Fluid Accuracy Towards Trillion-Cell Scale
Zhuoqiang Guo, Runze Mao, Lijun Liu +3
For decades, supercritical flame simulations incorporating detailed chemistry and real-fluid transport have been limited to millions of cells, constraining the resolved spatial and…
cs.DC2025
Scaling Neural-Network-Based Molecular Dynamics with Long-Range Electrostatic Interactions to 51 Nanoseconds per Day
Jianxiong Li, Beining Zhang, Mingzhen Li +7
Neural network-based molecular dynamics (NNMD) simulations incorporating long-range electrostatic interactions have significantly extended the applicability to heterogeneous and io…
physics.comp-ph2024
ALKPU: an active learning method for the DeePMD model with Kalman filter
Haibo Li, Xingxing Wu, Liping Liu +4
Neural network force field models such as DeePMD have enabled highly efficient large-scale molecular dynamics simulations with ab initio accuracy. However, building such models hea…