2 papers
cs.LG2026
Universal and efficient graph neural networks with dynamic attention for machine learning interatomic potentials
Shuyu Bi, Zhede Zhao, Qiangchao Sun +3
The core of molecular dynamics simulation fundamentally lies in the interatomic potential. Traditional empirical potentials lack accuracy, while first-principles methods are comput…
cond-mat.mtrl-sci2025
First-principles prediction of altermagnetism in transition metal graphite intercalation compounds
Weida Fu, Guo-Dong Zhao, Tao Hu +5
We report the emergence of altermagnetism, a magnetic phase characterized by the coexistence of compensated spin ordering and momentum-dependent spin splitting, in graphite interca…