Yuxinxin Chen

Solid State Physics Laboratory — India

Materials Science · Physical Sciences

8h-index180citations29works6.12yr avg
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Research Topics

Machine Learning in Materials Science(23), Computational Drug Discovery Methods(9), Various Chemistry Research Topics(6), Advanced Chemical Physics Studies(4), Catalysis and Oxidation Reactions(4)

Publications29 total

AIQM3: Targeting Coupled-Cluster Accuracy with Semi-Empirical Speed across Seven Main-Group Elements
Journal of Chemical Theory and Computation·2026
Artificial Intelligence for Direct Prediction of Molecular Dynamics across Chemical Space
Journal of Chemical Theory and Computation·2026
Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space
2026Open Access
AIQM-PBSA: Integrating Machine Learning InteratomicPotentials with MMPBSA for Accurate Protein–Ligand Binding Free Energy Calculations
2026Open Access
AIQM3: Targeting Coupled-Cluster Accuracy with Semi-Empirical Speed Across Seven Main Group Elements
2025Open Access
One to Rule Them All: A Universal Interatomic Potential Learning across Quantum Chemical Levels
Journal of Chemical Theory and Computation·2025· 1 cited
One To Rule Them All: A Universal Interatomic Potential Learning Across Quantum Chemical Levels
2025· 2 citedOpen Access
Author response for "AIQM2: organic reaction simulations beyond DFT"
2025
One To Rule Them All: A Universal Interatomic Potential Learning Across Quantum Chemical Levels
2025
AIQM2: Organic Reaction Simulations Beyond DFT
2025· 1 citedOpen Access
ANI-1ccx-gelu Universal Interatomic Potential and Its Fine-Tuning: Toward Accurate and Efficient Anharmonic Vibrational Frequencies
The Journal of Physical Chemistry Letters·2025· 12 cited
AIQM2: organic reaction simulations beyond DFT
Chemical Science·2025· 8 citedOpen Access
Molecular quantum chemical data sets and databases for machine learning potentials
Machine Learning Science and Technology·2024· 15 citedOpen Access
Universal and Updatable Artificial Intelligence-Enhanced Quantum Chemical Foundational Models
2024· 5 citedOpen Access
The Best DFT Functional Is the Ensemble of Functionals
Advanced Science·2024· 8 citedOpen Access
Molecular Quantum Chemical Data Sets and Databases for Machine Learning Potentials
2024· 2 citedOpen Access
Towards Accurate and Efficient Anharmonic Vibrational Frequencies with the Universal Interatomic Potential ANI-1ccx-gelu and Its Fine-Tuning
2024Open Access
AIQM2: Better Reaction Simulations with the 2nd Generation of General-Purpose AI-enhanced Quantum Mechanical Method
2024· 5 citedOpen Access
All-in-one foundational models learning across quantum chemical levels
2024· 4 cited
All-in-one foundational models learning across quantum chemical levels
arXiv (Cornell University)·2024Open Access
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Frequent Co-authors

Pavlo O. Dral(26), Fuchun Ge(11), Yi-Fan Hou(11), Peikun Zheng(6), Olexandr Isayev(5), Arif Ullah(5), Lina Zhang(4), Yanchi Ou(4), Mario Barbatti(3), Max Pinheiro(2), Yuming Su(2), Yiheng Dai(2), Yangtao Chen(2), Shuang Zhang(2), Yaohuang Huang(2), Seyedeh Fatemeh Alavi(2), Yuting Rui(2), Elena B. Ivanova(2), Ireneusz Grabowski(2), R.I. Zubatyuk(2)