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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:

Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks
Sergio Pablo‐García, Santiago Morandi, Rodrigo A. Vargas–Hernández, et al.
Nature Computational Science (2023) Vol. 3, Iss. 5, pp. 433-442
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Distinguish MnO2/Mn2+ Conversion/ Zn2+ Intercalation/ H+ Conversion Chemistries at Different Potentials in Aqueous Zn||MnO2 Batteries
Chuan Li, Haonan Yuan, Ying Liu, et al.
Angewandte Chemie International Edition (2024) Vol. 63, Iss. 22
Closed Access | Times Cited: 10
Supervised AI and Deep Neural Networks to Evaluate High-Entropy Alloys as Reduction Catalysts in Aqueous Environments
Rafael B. Araujo, Tomas Edvinsson
ACS Catalysis (2024) Vol. 14, Iss. 6, pp. 3742-3755
Open Access | Times Cited: 6
Electrochemical CO2 Reduction: Predicting the Selectivity
Michael Mirabueno Albrechtsen, Alexander Bagger
Current Opinion in Electrochemistry (2025), pp. 101642-101642
Closed Access
MOSAEC-DB: a comprehensive database of experimental metal–organic frameworks with verified chemical accuracy suitable for molecular simulations
Marco Gibaldi, Anna Kapeliukha, Andrew J. P. White, et al.
Chemical Science (2025)
Open Access
A physics-informed cluster graph neural network enables generalizable and interpretable prediction for material discovery
Ming Yang, Hao Cheng, Tong Yang, et al.
Research Square (Research Square) (2025)
Closed Access
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: 5
Towards rational design of organic copper corrosion inhibitors: High-throughput computational evaluation of standard adsorption Gibbs energy
Zhongheng Fu, Xin Guo, Xinzheng Zhang, et al.
Corrosion Science (2023) Vol. 227, pp. 111783-111783
Closed Access | Times Cited: 12
Distinguish MnO2/Mn2+ Conversion/ Zn2+ Intercalation/ H+ Conversion Chemistries at Different Potentials in Aqueous Zn||MnO2 Batteries
Chuan Li, Haonan Yuan, Ying Liu, et al.
Angewandte Chemie (2024) Vol. 136, Iss. 22
Closed Access | Times Cited: 4
A review on the applications of graph neural networks in materials science at the atomic scale
Xingyue Shi, Linming Zhou, Yuhui Huang, et al.
Materials Genome Engineering Advances (2024) Vol. 2, Iss. 2
Open Access | Times Cited: 4
Toward Next-Generation Heterogeneous Catalysts: Empowering Surface Reactivity Prediction with Machine Learning
Xinyan Liu, Hong‐Jie Peng
Engineering (2024) Vol. 39, pp. 25-44
Open Access | Times Cited: 3
Catalysis in the digital age: Unlocking the power of data with machine learning
B. Moses Abraham, M. V. Jyothirmai, Priyanka Sinha, et al.
Wiley Interdisciplinary Reviews Computational Molecular Science (2024) Vol. 14, Iss. 5
Open Access | Times Cited: 3
A review of mechanistic insights into CO2 reduction to higher alcohols for rational catalyst design
Yao Sheng, Mikhail V. Polynski, Mathan K. Eswaran, et al.
Applied Catalysis B Environment and Energy (2023) Vol. 343, pp. 123550-123550
Closed Access | Times Cited: 9
Revealing Local and Directional Aspects of Catalytic Active Sites by the Nuclear and Surface Electrostatic Potential
Joakim Halldin Stenlid, Frank Abild‐Pedersen
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 11, pp. 4544-4558
Closed Access | Times Cited: 2
A cyclical route linking fundamental mechanism and AI algorithm: An example from tuning Poisson's ratio in amorphous networks
Changliang Zhu, Chenchao Fang, Zhipeng Jin, et al.
Applied Physics Reviews (2024) Vol. 11, Iss. 3
Open Access | Times Cited: 2
Directional Multiobjective Optimization of Metal Complexes at the Billion-Scale with the tmQMg-L Dataset and PL-MOGA Algorithm
Hannes Kneiding, Ainara Nova, David Balcells
(2023)
Open Access | Times Cited: 6
Bringing down the heat in methanol synthesis
Andrew Wang, Athanasios A. Tountas, Alán Aspuru‐Guzik, et al.
Matter (2023) Vol. 6, Iss. 7, pp. 2106-2135
Open Access | Times Cited: 5
Machine-learning prediction of facet-dependent CO coverage on Cu electrocatalysts
Shanglin Wu, Shisheng Zheng, Wentao Zhang, et al.
(2024)
Open Access | Times Cited: 1
Accelerating the design of catalysts for CO2 electroreduction to HCOOH: A data-driven DFT-ML screening of dual atom catalysts
Huiwen Zhu, Zeyu Guo, Dawei Lan, et al.
Journal of Energy Chemistry (2024) Vol. 99, pp. 627-635
Open Access | Times Cited: 1
Review of External Field Effects on Electrocatalysis: Machine Learning Guided Design
Lei Wang, Xuyan Zhou, Zihan Luo, et al.
Advanced Functional Materials (2024)
Closed Access | Times Cited: 1
Scalable crystal structure relaxation using an iteration-free deep generative model with uncertainty quantification
Ziduo Yang, Yiming Zhao, Xian Wang, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning
Shang Zhu, Bharath Ramsundar, Emil Annevelink, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Multimodal language and graph learning of adsorption configuration in catalysis
Janghoon Ock, Srivathsan Badrinarayanan, Rishikesh Magar, et al.
Nature Machine Intelligence (2024)
Closed Access | Times Cited: 1
Local descriptors-based machine learning model refined by cluster analysis for accurately predicting adsorption energies on bimetallic alloys
Andres Felipe Usuga, C. S. Praveen, Aleix Comas‐Vives
Journal of Materials Chemistry A (2023) Vol. 12, Iss. 5, pp. 2708-2721
Open Access | Times Cited: 2
Lightweight equivariant model for efficient interatomic potential predictions
Lei Shen, Ziduo Yang, Xian Wang, et al.
Research Square (Research Square) (2024)
Open Access
Quantitative nanoscopic imaging of adsorbent-aggregation-state dependent molecular binding cooperativity
Jin Xie, Kanglu Li, Nafil Zuhair B Nizzar, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 35, pp. 23697-23711
Closed Access
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