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Chemical Science|August 14, 2025
AIQM2: organic reaction simulations beyond DFTYuxinxin Chen, Pavlo O DralJournal of Chemical Theory and Computation|September 12, 2025
One to Rule Them All: A Universal Interatomic Potential Learning across Quantum Chemical LevelsYuxinxin Chen, Pavlo O DralJournal of Chemical Theory and Computation|February 12, 2026
Artificial Intelligence for Direct Prediction of Molecular Dynamics across Chemical SpaceFuchun Ge, Yuxinxin Chen, Pavlo O DralJournal of Chemical Theory and Computation|February 14, 2026
AIQM3: Targeting Coupled-Cluster Accuracy with Semi-Empirical Speed across Seven Main-Group ElementsYuxinxin Chen, Yi-Fan Hou, Roman Zubatyuk, et al.The Journal of Chemical Physics|February 22, 2023
Benchmark of general-purpose machine learning-based quantum mechanical method AIQM1 on reaction barrier heightsYuxinxin Chen, Yanchi Ou, Peikun Zheng, et al.The Journal of Physical Chemistry Letters|August 22, 2023
Four-Dimensional-Spacetime Atomistic Artificial Intelligence ModelsFuchun Ge, Lina Zhang, Yi-Fan Hou, et al.The Journal of Physical Chemistry. B|May 4, 2026
Integrating Machine Learning Interatomic Potentials with MMPBSA for Accurate Protein-Ligand Binding Free Energy CalculationsXue-Xin Wei, Yuxinxin Chen, Yuedong Yang, et al.The Journal of Physical Chemistry Letters|January 3, 2025
ANI-1ccx-gelu Universal Interatomic Potential and Its Fine-Tuning: Toward Accurate and Efficient Anharmonic Vibrational FrequenciesSeyedeh Fatemeh Alavi, Yuxinxin Chen, Yi-Fan Hou, et al.Chemical Communications (Cambridge, England)|March 6, 2024
AI in computational chemistry through the lens of a decade-long journeyPavlo O DralThe Journal of Physical Chemistry Letters|March 4, 2020
Quantum Chemistry in the Age of Machine LearningPavlo O DralPageof 9