55 citations · 58 across the 5 of their papers we have counts for
5 papers
ALKEMIE Agent: an autonomous platform for computational materials design
Hongfu Huang, Yuzhe Li, Ao Xu +14
Despite the powerful multi-scale modeling methods and high-throughput infrastructures established in the materials community, real material computation workflows remain fragmented…
AI2Pot: A scalable and unified framework for machine-learning interatomic potential development and large-scale molecular dynamic simulations
Hanyu Liu, Linggang Zhu, Xuanguang Zhang +3
Machine-learning interatomic potentials (MLIPs) bridge the accuracy of first-principles calculations and the efficiency required for large-scale molecular dynamics (MD) simulations…
Efficient GPU-Accelerated Training of a Neuroevolution Potential with Analytical Gradients
Hongfu Huang, Junhao Peng, Kaiqi Li +2
Machine-learning interatomic potentials (MLIPs) such as neuroevolution potentials (NEP) combine quantum-mechanical accuracy with computational efficiency significantly accelerate a…
Deep Learning Models for Colloidal Nanocrystal Synthesis
Kai Gu, Yingping Liang, Jiaming Su +7
Colloidal synthesis of nanocrystals usually includes complex chemical reactions and multi-step crystallization processes. Despite the great success in the past 30 years, it remains…
Magnetic moments and transition magnetic moments of and states
Ming-Wei Li, Zhan-Wei Liu, Zhi-Feng Sun +1
We study the magnetic moments and transition magnetic moments of and states in the molecular picture. We first revisit the magnetic moments of states as the $S…