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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:

Machine-learning driven global optimization of surface adsorbate geometries
Hyunwook Jung, Lena Sauerland, Sina Stocker, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 24

Showing 24 citing articles:

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
MatGPT: A Vane of Materials Informatics from Past, Present, to Future
Zhilong Wang, An Chen, Kehao Tao, et al.
Advanced Materials (2023) Vol. 36, Iss. 6
Closed Access | Times Cited: 23
From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design
Jorge Benavides-Hernández, Franck Dumeignil
ACS Catalysis (2024) Vol. 14, Iss. 15, pp. 11749-11779
Closed Access | Times Cited: 9
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
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
Role of the human-in-the-loop in emerging self-driving laboratories for heterogeneous catalysis
Christoph Scheurer, Karsten Reuter
Nature Catalysis (2025) Vol. 8, Iss. 1, pp. 13-19
Closed Access
Compositional design and phase formation capability of high-entropy rare-earth disilicates from machine learning and decision fusion
Yun Fan, Yuelei Bai, Qian Li, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 5
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
Data-efficient modeling of catalytic reactions via enhanced sampling and on-the-fly learning of machine learning potentials
Simone Perego, Luigi Bonati
(2024)
Open Access | Times Cited: 4
Staged Training of Machine-Learning Potentials from Small to Large Surface Unit Cells: Efficient Global Structure Determination of the RuO2(100)-c(2 × 2) Reconstruction and (410) Vicinal
Yonghyuk Lee, Jakob Timmermann, Chiara Panosetti, et al.
The Journal of Physical Chemistry C (2023) Vol. 127, Iss. 35, pp. 17599-17608
Open Access | Times Cited: 12
Automated design of hybrid halide perovskite monolayers for band gap engineering
Jie Hu, Jianwei Wang, Haiyuan Chen, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 2
Machine Learning, Density Functional Theory, and Experiments to Understand the Photocatalytic Reduction of CO2 on CuPt/TiO2
Vaidish Sumaria, Takat B. Rawal, Young Feng Li, et al.
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 34, pp. 14247-14258
Closed Access | Times Cited: 2
Unraveling Multiscale Kinetics over Subnanometer Cluster Catalysts: H2 Desorption from Pt3(-H)2/γ-Al2O3(110)
George Yan, Dionisios G. Vlachos
ACS Catalysis (2023) Vol. 13, Iss. 16, pp. 10602-10614
Closed Access | Times Cited: 5
Recalibrating the Experimentally Derived Structure of the Metastable Surface Oxide on Copper via Machine Learning-Accelerated In Silico Global Optimization
Hyun Jun Kim, Giyeok Lee, Seung‐Hyun Victor Oh, et al.
ACS Nano (2024) Vol. 18, Iss. 5, pp. 4559-4569
Closed Access | Times Cited: 1
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
Data efficient machine learning potentials for modeling catalytic reactivity via active learning and enhanced sampling
Simone Perego, Luigi Bonati
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 1
Accelerated Lignocellulosic Molecule Adsorption Structure Determination
Joakim S. Jestilä, Nian Wu, Fabio Priante, et al.
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 5, pp. 2297-2312
Open Access
Bird’s-Eye View of the Activity Distribution on a Catalyst Surface via a Machine Learning-Driven Adequate Sampling Algorithm
Hui Yang, Pengju Ren, Xiaobin Geng, et al.
The Journal of Physical Chemistry Letters (2024) Vol. 15, Iss. 16, pp. 4384-4390
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
Hydrogen, Oxygen, and Lead Adsorbates on Al13Co4(100): Accurate Potential Energy Surfaces at Low Computational Cost by Machine Learning and DFT-Based Data
Nathan Boulangeot, Florian Brix, Frédéric Sur, et al.
Journal of Chemical Theory and Computation (2024)
Closed Access
A configuration sampling study of reaction intermediates constituting catalytic cycles for CO oxidation with Pt1/TiO2
Nicholas Humphrey, Selin Bac, Shaama Mallikarjun Sharada
The Journal of Chemical Physics (2024) Vol. 161, Iss. 11
Closed Access
Graph Neural Network Model Accelerates Biomass Adsorption Energy Prediction on Iron-group Hydrotalcite Electrocatalysts
Xinghai Li, Wei Huang, Yuechang Lian, et al.
The Journal of Physical Chemistry Letters (2024) Vol. 15, Iss. 42, pp. 10725-10733
Closed Access
Computational Design of Catalysts with Experimental Validation: Recent Successes, Effective Strategies, and Pitfalls
Hajar Hosseini, Connor J. Herring, Chukwudi F. Nwaokorie, et al.
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 43, pp. 18144-18157
Open Access
Trendbericht Theoretische Chemie 2023 (1/3): Maschinelles Lernen jenseits von Potenzialenergiehyperflächen
Johannes T. Margraf
Nachrichten aus der Chemie (2023) Vol. 71, Iss. 11, pp. 60-62
Open Access
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