Fang Liu

Emory University — United States

Materials Science · Physical Sciences

31h-index3.5kcitations153works1.52yr avg
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Research Topics

Machine Learning in Materials Science(57), Computational Drug Discovery Methods(41), Spectroscopy and Quantum Chemical Studies(24), Protein Structure and Dynamics(15), Advanced Chemical Physics Studies(12)

Publications153 total

Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/Vis Absorption Energy Prediction
Journal of Chemical Theory and Computation·2025· 1 citedOpen Access
Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/vis Absorption Energy Prediction
2025
Synthesis of Collinoketones via Biomimetic [6+4] Cycloaddition
2025
Synthesis of Collinoketones via Biomimetic [6+4] Cycloaddition
2025Open Access
Streamlining Coding Assignments and Grading on the Cloud: A Preconfigured JupyterHub Image for Chemistry Education
Journal of Chemical Education·2025Open Access
Determining the complex second-order optical susceptibility in macroscale van der Waals heterobilayers
ArXiv.org·2025Open Access
ACES-GNN: Can Graph Neural Network Learn to Explain Activity Cliffs?
2025Open Access
Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/vis Absorption Energy Prediction
2025Open Access
Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution Phase Absorption Energy Prediction
2025Open Access
Stimulus-Driven Tuning of Multipathway Emission in 9-Fluorenone Derivatives: Elucidating Charge Transfer Dynamics in Higher Excited Singlet and Triplet States
ACS Applied Energy Materials·2025· 4 cited
Streamlining Coding Assignments and Grading on the Cloud: A Preconfigured JupyterHub Image for Chemistry Education
2025Open Access
Size-Transferable Prediction of Excited State Properties for Molecular Assemblies with a Machine Learning Exciton Model
The Journal of Physical Chemistry Letters·2025· 2 citedOpen Access
Author Correction: Approaching coupled-cluster accuracy for molecular electronic structures with multi-task learning
Nature Computational Science·2025Open Access
ACES-GNN: Can Graph Neural Network Learn to Explain Activity Cliffs?
2025Open Access
Chatbot-assisted quantum chemistry for explicitly solvated molecules
Chemical Science·2025· 6 citedOpen Access
ACES-GNN: can graph neural network learn to explain activity cliffs?
Digital Discovery·2025· 4 citedOpen Access
Approaching coupled-cluster accuracy for molecular electronic structures with multi-task learning
Nature Computational Science·2024· 14 citedOpen Access
Chatbot-Assisted Quantum Chemistry for Explicitly Solvated Molecules
2024Open Access
Size-transferable prediction of excited state properties for molecular assemblies with machine-learned exciton model
2024Open Access
Acoustic Detection Algorithm of Train Bearings Based on Phased Derivative of CFD and the Fallow-GSC
2024
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Frequent Co-authors

Heather J. Kulik(18), Todd J. Martı́nez(13), Chenru Duan(9), Aditya Nandy(7), Ruibin Liang(4), Lee‐Ping Wang(3), Adam H. Steeves(3), Zhongyue Yang(3), Jon Paul Janet(3), David M. Sanchez(3), Eugen Hruška(3), A.V. Titov(2), Michael G. Taylor(2), Sara Kokkila-Schumacher(2), Xin Li(2), Nathan Luehr(2), Tzuhsiung Yang(2), Chunxing She(2), Jianchang Guo(2), Debra L. Mohler(2)