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Peikun Zheng

Showing results (1-10 of 15) with videos related to

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Chemical Science|October 9, 2025
High-throughput electronic property prediction of cyclic molecules with 3D-enhanced machine learningPeikun Zheng, Olexandr Isayev
Journal of Chemical Theory and Computation|August 4, 2025
Symmetric Group Semiempirical Valence Bond Method for Large Conjugated MoleculesPeikun Zheng, Fuming Ying, Wei Wu, et al.
The Journal of Chemical Physics|June 1, 2022
λ-DFVB(U): A hybrid density functional valence bond method based on unpaired electron densityPeikun Zheng, Zixi Gan, Chen Zhou, et al.
Molecules (Basel, Switzerland)|January 27, 2021
A Valence-Bond-Based Multiconfigurational Density Functional Theory: The λ-DFVB Method RevisitedPeikun Zheng, Chenru Ji, Fuming Ying, et al.
Chemical Science|June 24, 2026
Exploring celecoxib polymorph landscape using AIMNet2 machine learning interatomic potentialPeikun Zheng, Yuriy A Abramov, Changquan Calvin Sun, et al.
The Journal of Physical Chemistry Letters|April 13, 2022
Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven MethodsPeikun Zheng, Wudi Yang, Wei Wu, et al.
Nature Communications|December 3, 2021
Artificial intelligence-enhanced quantum chemical method with broad applicabilityPeikun Zheng, Roman Zubatyuk, Wei Wu, et al.
Molecules (Basel, Switzerland)|February 13, 2025
A Density Functional Valence Bond Study on the Excited StatesXun Wu, Peikun Zheng, Tingzhen Chen, et al.
Frontiers in Chemistry|May 2, 2019
λ-Density Functional Valence Bond: A Valence Bond-Based Multiconfigurational Density Functional Theory With a Single Variable Hybrid ParameterFuming Ying, Chen Zhou, Peikun Zheng, 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.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Chemical Science|October 9, 2025
High-throughput electronic property prediction of cyclic molecules with 3D-enhanced machine learningPeikun Zheng, Olexandr Isayev
Journal of Chemical Theory and Computation|August 4, 2025
Symmetric Group Semiempirical Valence Bond Method for Large Conjugated MoleculesPeikun Zheng, Fuming Ying, Wei Wu, et al.
The Journal of Chemical Physics|June 1, 2022
λ-DFVB(U): A hybrid density functional valence bond method based on unpaired electron densityPeikun Zheng, Zixi Gan, Chen Zhou, et al.
Molecules (Basel, Switzerland)|January 27, 2021
A Valence-Bond-Based Multiconfigurational Density Functional Theory: The λ-DFVB Method RevisitedPeikun Zheng, Chenru Ji, Fuming Ying, et al.
Chemical Science|June 24, 2026
Exploring celecoxib polymorph landscape using AIMNet2 machine learning interatomic potentialPeikun Zheng, Yuriy A Abramov, Changquan Calvin Sun, et al.
The Journal of Physical Chemistry Letters|April 13, 2022
Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven MethodsPeikun Zheng, Wudi Yang, Wei Wu, et al.
Nature Communications|December 3, 2021
Artificial intelligence-enhanced quantum chemical method with broad applicabilityPeikun Zheng, Roman Zubatyuk, Wei Wu, et al.
Molecules (Basel, Switzerland)|February 13, 2025
A Density Functional Valence Bond Study on the Excited StatesXun Wu, Peikun Zheng, Tingzhen Chen, et al.
Frontiers in Chemistry|May 2, 2019
λ-Density Functional Valence Bond: A Valence Bond-Based Multiconfigurational Density Functional Theory With a Single Variable Hybrid ParameterFuming Ying, Chen Zhou, Peikun Zheng, 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.
Pageof 2