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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:

MatSciBERT: A materials domain language model for text mining and information extraction
Tanishq Gupta, Mohd Zaki, N. M. Anoop Krishnan, et al.
npj Computational Materials (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 160

Showing 1-25 of 160 citing articles:

A general-purpose material property data extraction pipeline from large polymer corpora using natural language processing
Pranav Shetty, Arunkumar Chitteth Rajan, Chris Kuenneth, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 64
Deep language models for interpretative and predictive materials science
Yiwen Hu, Markus J. Buehler
APL Machine Learning (2023) Vol. 1, Iss. 1
Open Access | Times Cited: 59
Materials science in the era of large language models: a perspective
Ge Lei, R. Docherty, Samuel J. Cooper
Digital Discovery (2024) Vol. 3, Iss. 7, pp. 1257-1272
Open Access | Times Cited: 23
Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures
Vera Kuznetsova, Áine Coogan, Dmitry Botov, et al.
Advanced Materials (2024) Vol. 36, Iss. 18
Open Access | Times Cited: 22
Accelerating materials language processing with large language models
Jaewoong Choi, Byungju Lee
Communications Materials (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 18
BatteryBERT: A Pretrained Language Model for Battery Database Enhancement
Shu Huang, Jacqueline M. Cole
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 24, pp. 6365-6377
Open Access | Times Cited: 63
Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation
Xiliang Yan, Tongtao Yue, David A. Winkler, et al.
Chemical Reviews (2023) Vol. 123, Iss. 13, pp. 8575-8637
Closed Access | Times Cited: 32
What is missing in autonomous discovery: open challenges for the community
Phillip M. Maffettone, Pascal Friederich, Sterling G. Baird, et al.
Digital Discovery (2023) Vol. 2, Iss. 6, pp. 1644-1659
Open Access | Times Cited: 25
Leveraging language representation for materials exploration and discovery
Jiaxing Qu, Yuxuan Richard Xie, Kamil Ciesielski, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 13
Harnessing GPT-3.5 for text parsing in solid-state synthesis – case study of ternary chalcogenides
Maung Thway, Kai Yuan Andre Low, Samyak Khetan, et al.
Digital Discovery (2024) Vol. 3, Iss. 2, pp. 328-336
Open Access | Times Cited: 12
Advances in materials informatics: a review
Dawn Sivan, K. Satheesh Kumar, Aziman Abdullah, et al.
Journal of Materials Science (2024) Vol. 59, Iss. 7, pp. 2602-2643
Closed Access | Times Cited: 12
MatKG: An autonomously generated knowledge graph in Material Science
Vineeth Venugopal, Elsa Olivetti
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 11
Machine learning for analyses and automation of structural characterization of polymer materials
Shizhao Lu, Arthi Jayaraman
Progress in Polymer Science (2024) Vol. 153, pp. 101828-101828
Closed Access | Times Cited: 10
A Review of Large Language Models and Autonomous Agents in Chemistry
Mayk Caldas Ramos, Christopher J. Collison, Andrew Dickson White
Chemical Science (2024)
Open Access | Times Cited: 10
Flexible, model-agnostic method for materials data extraction from text using general purpose language models
Maciej P. Polak, Shrey Modi, Anna Latosinska, et al.
Digital Discovery (2024) Vol. 3, Iss. 6, pp. 1221-1235
Open Access | Times Cited: 9
Crystal Composition Transformer: Self‐Learning Neural Language Model for Generative and Tinkering Design of Materials
Lai Wei, Qinyang Li, Yuqi Song, et al.
Advanced Science (2024)
Open Access | Times Cited: 9
Roadmap on data-centric materials science
Sebastian Bauer, Peter Benner, Tristan Bereau, et al.
Modelling and Simulation in Materials Science and Engineering (2024) Vol. 32, Iss. 6, pp. 063301-063301
Open Access | Times Cited: 8
A prompt-engineered large language model, deep learning workflow for materials classification
Siyu Liu, Tongqi Wen, Arvind Pattamatta, et al.
Materials Today (2024)
Closed Access | Times Cited: 8
CataLM: empowering catalyst design through large language models
Ludi Wang, Xueqing Chen, Yi Du, et al.
International Journal of Machine Learning and Cybernetics (2025)
Open Access | Times Cited: 1
Large language models for reticular chemistry
Zhiling Zheng, Nakul Rampal, Theo Jaffrelot Inizan, et al.
Nature Reviews Materials (2025)
Closed Access | Times Cited: 1
Seaweed-Based Bioplastics: Data Mining Ingredient–Property Relations from the Scientific Literature
Fernanda Véliz, Thulasi Bikku, Davor Ibarra-Pérez, et al.
Data (2025) Vol. 10, Iss. 2, pp. 20-20
Open Access | Times Cited: 1
Accurate, interpretable predictions of materials properties within transformer language models
Vadim Korolev, Pavel Protsenko
Patterns (2023) Vol. 4, Iss. 10, pp. 100803-100803
Open Access | Times Cited: 18
Perspective: Large Language Models in Applied Mechanics
Neal R. Brodnik, Samuel Carton, C. Muir, et al.
Journal of Applied Mechanics (2023) Vol. 90, Iss. 10
Closed Access | Times Cited: 17
Natural Language Processing
N. M. Anoop Krishnan, Hariprasad Kodamana, Ravinder Bhattoo
Springer eBooks (2024), pp. 263-275
Closed Access | Times Cited: 7
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