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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:

AdsorbML: a leap in efficiency for adsorption energy calculations using generalizable machine learning potentials
Janice Lan, Aini Palizhati, Muhammed Shuaibi, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 24

Showing 24 citing articles:

Microalloying induced stable welded interfaces for highly reversible zero-excess sodium metal batteries
Chunlin Xie, Hao Wu, Kang Liang, et al.
Energy & Environmental Science (2024) Vol. 17, Iss. 12, pp. 4228-4237
Closed Access | Times Cited: 13
Density Functional Theory-Guided Synthesis of Cu-N-TiO2 for Overall Water Splitting by Breaking the Scaling Relationship
Wenhao Jing, Guiwei He, Shengjie Bai, et al.
ACS Materials Letters (2024) Vol. 6, Iss. 4, pp. 1347-1355
Closed Access | Times Cited: 8
Enhancing the Quality and Reliability of Machine Learning Interatomic Potentials through Better Reporting Practices
Tristan Maxson, Ademola Soyemi, Benjamin W. J. Chen, et al.
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 16, pp. 6524-6537
Open Access | Times Cited: 7
Rise of machine learning potentials in heterogeneous catalysis: Developments, applications, and prospects
Seokhyun Choung, Wongyu Park, Jinuk Moon, et al.
Chemical Engineering Journal (2024) Vol. 494, pp. 152757-152757
Closed Access | Times Cited: 7
Peaks and pitfalls of electrocatalytic descriptor models at the example of CO2 reduction
Jihun Oh, Beom-Il Kim, Sheng Han, et al.
Research Square (Research Square) (2025)
Closed Access
Stable adsorption configuration searching in hetero-catalysis based on similar distribution and active learning
Jiaqiang Yang, Xiaofei Zhang, Xiaofeng Zhang, et al.
Journal of Catalysis (2025), pp. 115971-115971
Closed Access
Accessing Numerical Energy Hessians with Graph Neural Network Potentials and Their Application in Heterogeneous Catalysis
Brook Wander, Joseph Musielewicz, Raffaele Cheula, et al.
The Journal of Physical Chemistry C (2025)
Closed Access
Machine-learning structural reconstructions for accelerated point defect calculations
Irea Mosquera‐Lois, Seán R. Kavanagh, Alex M. Ganose, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 5
Chemical Properties from Graph Neural Network-Predicted Electron Densities
Ethan M. Sunshine, Muhammed Shuaibi, Zachary W. Ulissi, et al.
The Journal of Physical Chemistry C (2023) Vol. 127, Iss. 48, pp. 23459-23466
Open Access | Times Cited: 11
Adapting OC20-Trained EquiformerV2 Models for High-Entropy Materials
Christian M. Clausen, Jan Rossmeisl, Zachary W. Ulissi
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 27, pp. 11190-11195
Open Access | Times Cited: 4
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
AI‐Driven Electrolyte Additive Selection to Boost Aqueous Zn‐Ion Batteries Stability
Haobo Li, Junnan Hao, Shi Zhang Qiao
Advanced Materials (2024)
Open Access | Times Cited: 2
CatEmbed: A Machine-Learned Representation Obtained via Categorical Entity Embedding for Predicting Adsorption and Reaction Energies on Bimetallic Alloy Surfaces
Clara Kirkvold, Brianna Collins, Jason D. Goodpaster
(2024)
Open Access | Times Cited: 1
AdsMT: A multi-modal transformer for predicting global minimum adsorption energy
Junwu Chen, Xu Huang, Hua Cheng, et al.
(2024)
Open Access | Times Cited: 1
In Situ Derivation of Dual-Active Co/CoO Heterojunction Nanoarrays for Synergistic Catalytic NH3 Synthesis
Changxu Ma, Yimeng Li, Dan Zhao, et al.
ACS Sustainable Chemistry & Engineering (2024)
Closed 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
Artificial Intelligence Driven Molecule Adsorption Prediction (AIMAP) Applied to Chirality Recognition of Amino Acids Adsorption on Metals
Z.‐X. GUO, Guoliang Song, Zhi‐Pan Liu
Chemical Science (2024) Vol. 15, Iss. 33, pp. 13369-13380
Open Access
AdsMT: A multi-modal transformer for predicting global minimum adsorption energy
Junwu Chen, Xu Huang, Hua Cheng, et al.
(2024)
Open Access
Investigating the Error Imbalance of Large-Scale Machine Learning Potentials in Catalysis
Kareem Abdelmaqsoud, Muhammed Shuaibi, Adeesh Kolluru, et al.
Catalysis Science & Technology (2024) Vol. 14, Iss. 20, pp. 5899-5908
Open Access
Application of graph neural network in computational heterogeneous catalysis
Zihao Jiao, Ya Liu, Ziyun Wang
The Journal of Chemical Physics (2024) Vol. 161, Iss. 17
Closed Access
Autonomous Exploitation of Reaction Pathways for Electrochemical C–N Coupling on Single-Atom Catalysts
Junjie Pan, Haowen Ding, Xiaoling Yang, et al.
ACS Catalysis (2024), pp. 457-467
Closed Access
CatEmbed: A Machine-Learned Representation Obtained via Categorical Entity Embedding for Predicting Adsorption and Reaction Energies on Bimetallic Alloy Surfaces
Clara Kirkvold, Brianna Collins, Jason D. Goodpaster
The Journal of Physical Chemistry Letters (2024) Vol. 15, Iss. 26, pp. 6791-6797
Closed Access
Influence of hydrogen passivation, vacancies, and dopants on the electronic and magnetic properties of MgO nanoribbons
Shuying Kang, Fangguang Kuang, Wei Huang, et al.
Applied Physics A (2024) Vol. 130, Iss. 9
Closed Access
Improved Uncertainty Estimation of Graph Neural Network Potentials Using Engineered Latent Space Distances
Joseph Musielewicz, Janice Lan, Matt Uyttendaele, et al.
The Journal of Physical Chemistry C (2024)
Open Access
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