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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 study of tyrosine reveals that roaming can lead to photodamage
Julia Westermayr, Michael Gastegger, Dóra Vörös, et al.
Nature Chemistry (2022) Vol. 14, Iss. 8, pp. 914-919
Closed Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry
Giovanni Li Manni, Ignacio Fdez. Galván, Ali Alavi, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 20, pp. 6933-6991
Open Access | Times Cited: 153
How to validate machine-learned interatomic potentials
Joe D. Morrow, John L. A. Gardner, Volker L. Deringer
The Journal of Chemical Physics (2023) Vol. 158, Iss. 12
Open Access | Times Cited: 68
Recent Advances in 3D Printing of Smart Scaffolds for Bone Tissue Engineering and Regeneration
Xun Yuan, Wei Zhu, Zhongyuan Yang, et al.
Advanced Materials (2024) Vol. 36, Iss. 34
Closed Access | Times Cited: 60
Machine Learning of Reactive Potentials
Yinuo Yang, Shuhao Zhang, Kavindri Ranasinghe, et al.
Annual Review of Physical Chemistry (2024) Vol. 75, Iss. 1, pp. 371-395
Closed Access | Times Cited: 21
Neural network potentials for chemistry: concepts, applications and prospects
Silvan Käser, Luis Itza Vazquez-Salazar, Markus Meuwly, et al.
Digital Discovery (2022) Vol. 2, Iss. 1, pp. 28-58
Open Access | Times Cited: 67
In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back
Abdulrahman Aldossary, Jorge A. Campos-Gonzalez-Angulo, Sergio Pablo‐García, et al.
Advanced Materials (2024) Vol. 36, Iss. 30
Closed Access | Times Cited: 15
Artificial-Intelligence-Enhanced On-the-Fly Simulation of Nonlinear Time-Resolved Spectra
Sebastian V. Pios, Maxim F. Gelin, Arif Ullah, et al.
The Journal of Physical Chemistry Letters (2024) Vol. 15, Iss. 9, pp. 2325-2331
Closed Access | Times Cited: 14
MLatom Software Ecosystem for Surface Hopping Dynamics in Python with Quantum Mechanical and Machine Learning Methods
Lina Zhang, Sebastian V. Pios, Mikołaj Martyka, et al.
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 12, pp. 5043-5057
Open Access | Times Cited: 11
A Look Inside the Black Box of Machine Learning Photodynamics Simulations
Jingbai Li, Steven A. Lopez
Accounts of Chemical Research (2022) Vol. 55, Iss. 14, pp. 1972-1984
Closed Access | Times Cited: 33
Science‐Driven Atomistic Machine Learning
Johannes T. Margraf
Angewandte Chemie International Edition (2023) Vol. 62, Iss. 26
Open Access | Times Cited: 22
Machine learning photodynamics uncover blocked non-radiative mechanisms in aggregation-induced emission
Li Wang, Christian Salguero, Steven A. Lopez, et al.
Chem (2024) Vol. 10, Iss. 7, pp. 2295-2310
Closed Access | Times Cited: 7
Machine learning accelerated photodynamics simulations
Jingbai Li, Steven A. Lopez
Chemical Physics Reviews (2023) Vol. 4, Iss. 3
Open Access | Times Cited: 16
Synthetic pre-training for neural-network interatomic potentials
John L. A. Gardner, Kathryn T. Baker, Volker L. Deringer
Machine Learning Science and Technology (2023) Vol. 5, Iss. 1, pp. 015003-015003
Open Access | Times Cited: 14
PhysNet meets CHARMM: A framework for routine machine learning/molecular mechanics simulations
K. Song, Silvan Käser, Kai Töpfer, et al.
The Journal of Chemical Physics (2023) Vol. 159, Iss. 2
Open Access | Times Cited: 13
Data efficiency and extrapolation trends in neural network interatomic potentials
Joshua A. Vita, Daniel Schwalbe‐Koda
Machine Learning Science and Technology (2023) Vol. 4, Iss. 3, pp. 035031-035031
Open Access | Times Cited: 12
SpaiNN: equivariant message passing for excited-state nonadiabatic molecular dynamics
Sascha Mausenberger, Carolin Müller, Alexandre Tkatchenko, et al.
Chemical Science (2024) Vol. 15, Iss. 38, pp. 15880-15890
Open Access | Times Cited: 4
Excited-state nonadiabatic dynamics in explicit solvent using machine learned interatomic potentials
Maximilian Xaver Tiefenbacher, Brigitta Bachmair, Cheng Giuseppe Chen, et al.
Digital Discovery (2025)
Open Access
Charting electronic-state manifolds across molecules with multi-state learning and gap-driven dynamics via efficient and robust active learning
Mikołaj Martyka, Lina Zhang, Fuchun Ge, et al.
npj Computational Materials (2025) Vol. 11, Iss. 1
Open Access
Machine Learning Seams of Conical Intersection: A Characteristic Polynomial Approach
Tzu Yu Wang, Simon P. Neville, Michael S. Schuurman
The Journal of Physical Chemistry Letters (2023) Vol. 14, Iss. 35, pp. 7780-7786
Open Access | Times Cited: 9
Time‐resolved photoelectron spectroscopy via trajectory surface hopping
Pratip Chakraborty, Spiridoula Matsika
Wiley Interdisciplinary Reviews Computational Molecular Science (2024) Vol. 14, Iss. 3
Closed Access | Times Cited: 3
Charting electronic-state manifolds across molecules with multi-state learning and gap-driven dynamics via efficient and robust active learning
Mikołaj Martyka, Lina Zhang, Fuchun Ge, et al.
(2024)
Open Access | Times Cited: 3
The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry
Giovanni Li Manni, Ignacio Fdez. Galván, Ali Alavi, et al.
(2023)
Open Access | Times Cited: 8
Surprising new dynamics phenomena in Diels–Alder reaction of C60 uncovered with AI
Yi-Fan Hou, Quanhao Zhang, Pavlo O. Dral
(2024)
Open Access | Times Cited: 2
Photodegradation Kinetics and Deep Learning-Based Intelligent Colorimetric Method for Bioavailability-Based Dissolved Iron Speciation
Jiayi Luo, Zhaojing Huang, Shunxing Li, et al.
Analytical Chemistry (2022) Vol. 94, Iss. 42, pp. 14801-14809
Closed Access | Times Cited: 9
Ultrafast Photocontrolled Rotation in a Molecular Motor Investigated by Machine Learning-Based Nonadiabatic Dynamics Simulations
Haoyang Xu, Boyuan Zhang, Yuanda Tao, et al.
The Journal of Physical Chemistry A (2023) Vol. 127, Iss. 37, pp. 7682-7693
Closed Access | Times Cited: 4
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