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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Deep learning of dynamically responsive chemical Hamiltonians with semiempirical quantum mechanics
Guoqing Zhou, Nicholas Lubbers, Kipton Barros, et al.
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 27
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials
Peter Eastman, Raimondas Galvelis, Raúl P. Peláez, et al.
The Journal of Physical Chemistry B (2023) Vol. 128, Iss. 1, pp. 109-116
Open Access | Times Cited: 104
Extending machine learning beyond interatomic potentials for predicting molecular properties
Nikita Fedik, R.I. Zubatyuk, Maksim Kulichenko, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 9, pp. 653-672
Closed Access | Times Cited: 94
Data Generation for Machine Learning Interatomic Potentials and Beyond
Maksim Kulichenko, Benjamin Nebgen, Nicholas Lubbers, et al.
Chemical Reviews (2024) Vol. 124, Iss. 24, pp. 13681-13714
Closed Access | Times Cited: 17
Breaking the size limitation of nonadiabatic molecular dynamics in condensed matter systems with local descriptor machine learning
Dongyu Liu, Bipeng Wang, Yifan Wu, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 36
Open Access | Times Cited: 13
Machine-Learned Kohn–Sham Hamiltonian Mapping for Nonadiabatic Molecular Dynamics
Mohammad Shakiba, Alexey V. Akimov
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 8, pp. 2992-3007
Closed Access | Times Cited: 10
The emergence of machine learning force fields in drug design
Mingan Chen, Xinyu Jiang, Lehan Zhang, et al.
Medicinal Research Reviews (2024) Vol. 44, Iss. 3, pp. 1147-1182
Closed Access | Times Cited: 9
NEXMD v2.0 Software Package for Nonadiabatic Excited State Molecular Dynamics Simulations
Victor M. Freixas, Walter Malone, Xinyang Li, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 16, pp. 5356-5368
Closed Access | Times Cited: 18
Ultra-fast semi-empirical quantum chemistry for high-throughput computational campaigns with Sparrow
Francesco Bosia, Peikun Zheng, Alain C. Vaucher, et al.
The Journal of Chemical Physics (2023) Vol. 158, Iss. 5
Open Access | Times Cited: 14
Ab initio quantum dynamics of plasmonic charge carriers
Wei Li, Ting Xue, Carlos Mora Perez, et al.
Trends in Chemistry (2023) Vol. 5, Iss. 8, pp. 634-645
Open Access | Times Cited: 13
Inverse molecular design and parameter optimization with Hückel theory using automatic differentiation
Rodrigo A. Vargas–Hernández, Kjell Jorner, Robert Pollice, et al.
The Journal of Chemical Physics (2023) Vol. 158, Iss. 10
Open Access | Times Cited: 12
Putting Chemical Knowledge to Work in Machine Learning for Reactivity
Kjell Jorner
CHIMIA International Journal for Chemistry (2023) Vol. 77, Iss. 1/2, pp. 22-22
Open Access | Times Cited: 10
Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials
Nir Goldman, Laurence E. Fried, Rebecca Lindsey, et al.
The Journal of Chemical Physics (2023) Vol. 158, Iss. 14
Open Access | Times Cited: 10
Machine Learning Enhanced DFTB Method for Periodic Systems: Learning from Electronic Density of States
Wenbo Sun, Guozheng Fan, Tammo van der Heide, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 13, pp. 3877-3888
Closed Access | Times Cited: 10
Understanding hydrogen and heat diffusion across c-Si/a-Si:H heterojunctions for improved thermal management in solar cells fabrication
Riccardo Dettori, Claudio Melis, Luciano Colombo
Nanotechnology (2025) Vol. 36, Iss. 15, pp. 155703-155703
Closed Access
Overview on Building Blocks and Applications of Efficient and Robust Extended Tight Binding
Abylay Katbashev, Marcel Stahn, Thomas Rose, et al.
The Journal of Physical Chemistry A (2025)
Closed Access
Shadow Molecular Dynamics for a Charge-Potential Equilibration Model
Robert V. Stanton, Mehmet Cagri Kaymak, Anders M. N. Niklasson
Journal of Chemical Theory and Computation (2025)
Open Access
An Accurate, Affordable Density Functional Tight-Binding Model for Excited State Hydrocarbon Polymer Molecular Dynamics
Gautam D. Stroscio, C. Huy Pham, Thomas A. Niehaus, et al.
Journal of Chemical Theory and Computation (2025)
Closed Access
Treating Semiempirical Hamiltonians as Flexible Machine Learning Models Yields Accurate and Interpretable Results
Frank Hu, Hanqing He, David Yaron
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 18, pp. 6185-6196
Open Access | Times Cited: 9
Synergy of semiempirical models and machine learning in computational chemistry
Nikita Fedik, Benjamin Nebgen, Nicholas Lubbers, et al.
The Journal of Chemical Physics (2023) Vol. 159, Iss. 11
Open Access | Times Cited: 9
dxtb—An efficient and fully differentiable framework for extended tight-binding
Marvin Friede, Christian Hölzer, Sebastian Ehlert, et al.
The Journal of Chemical Physics (2024) Vol. 161, Iss. 6
Closed Access | Times Cited: 3
Efficient Modeling of Quantum Dynamics of Charge Carriers in Materials Using Short Nonequilibrium Molecular Dynamics
Bipeng Wang, Yifan Wu, Dongyu Liu, et al.
The Journal of Physical Chemistry Letters (2023) Vol. 14, Iss. 37, pp. 8289-8295
Open Access | Times Cited: 7
Functionality Optimization for Singlet Fission Rate Screening in the Full-Dimensional Molecular and Inter- molecular Coordinate Space
Johannes Greiner, Anurag Singh, Merle I. S. Röhr
Physical Chemistry Chemical Physics (2024) Vol. 26, Iss. 28, pp. 19257-19265
Open Access | Times Cited: 2
Graph-based quantum response theory and shadow Born–Oppenheimer molecular dynamics
Christian F. A. Negre, Michael E. Wall, Anders M. N. Niklasson
The Journal of Chemical Physics (2023) Vol. 158, Iss. 7
Open Access | Times Cited: 5
Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 11, pp. 3209-3222
Open Access | Times Cited: 5
Combining Molecular Quantum Mechanical Modeling and Machine Learning for Accelerated Reaction Screening and Discovery
Nicholas Casetti, Javier Emilio Alfonso Ramos, Connor W. Coley, et al.
Chemistry - A European Journal (2023) Vol. 29, Iss. 60
Closed Access | Times Cited: 5
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