4 citations · 6 across the 5 of their papers we have counts for
5 papers
Machine-Learned Leftmost Hessian Eigenvectors for Robust Transition State Finding
Guanchen Wu, Chung-Yueh Yuan, Kareem Hegazy +2
The reliable determination of transition states (TSs) benefits from second-order information for robust convergence and validation, but the computational expense of Hessians prohib…
Teachers that teach the irrelevant: Pre-training machine learned interaction potentials with classical force fields for robust molecular dynamics simulations
Eric C. -Y. Yuan, Teresa Head-Gordon
Machine learned interaction potentials (MLIPs) have become a critical component of large-scale, high-quality simulations for a range of chemical and biochemical systems. Yet, despi…
Foundation Models for Atomistic Simulation of Chemistry and Materials
Eric C. -Y. Yuan, Yunsheng Liu, Junmin Chen +11
Given the power of large language and large vision models, it is of profound and fundamental interest to ask if a foundational model based on data and parameter scaling laws and pr…
Deep Learning of ab initio Hessians for Transition State Optimization
Eric C. -Y. Yuan, Anup Kumar, Xingyi Guan +5
Identifying transition states -- saddle points on the potential energy surface connecting reactant and product minima -- is central to predicting kinetic barriers and understanding…
Solid-state heteronuclear multiple-quantum spectroscopy under a magic-angle spinning frequency of 150 kHz
Eric Chung-Yueh Yuan, Po-Wen Chen, Shing-Jong Huang +3
We hereby demonstrate that 1H detected 15N-1H heteronuclear multiple-quantum spectroscopy can be carried out at a magic angle spinning frequency of 150 kHz. While the 15N-1H multip…