4 papers
Universal Machine-learning Molecular Dynamics at the Speed of Empirical Potentials
Tiancheng Li, Jianming Xue, Linfeng Zhang +2
No interatomic potential has offered universality across chemistry, near-first-principles accuracy and the speed of empirical potentials at once. Here we introduce DPA4C, an equiva…
DPA4: Pushing the Accuracy-Cost Frontier of Interatomic Potentials with EMFA SO(2) Convolution
Tiancheng Li, Wentao Li, Anyang Peng +4
Machine-learning interatomic potentials now approach quantum-mechanical accuracy, but the most expressive equivariant architectures are costly to evaluate, and the leading ones dep…
Stress-driven dynamic evolution of core-shell structured cavities with H and He in BCC-Fe under fusion conditions
Jin Wang, Fengping Luo, Yiheng Chen +11
Understanding the dynamic behavior of microstructures formed under fusion conditions is critical for designing high-performance structural materials for fusion reactors. Under fusi…
Evolution of cavities in BCC-Fe with coexisting H and He under fusion environments
Jin Wang, Fengping Luo, Tao Zheng +10
In the fusion environment, understanding the synergistic effects of transmutation-produced hydrogen (H), helium (He), and irradiation-induced displacement damage in iron-based allo…