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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:

Recent advances and applications of deep learning methods in materials science
Kamal Choudhary, Brian DeCost, Chi Chen, et al.
npj Computational Materials (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 576

Showing 26-50 of 576 citing articles:

Artificial Intelligence in Drug Discovery and Development
Kit‐Kay Mak, Yi-Hang Wong, Mallikarjuna Rao Pichika
Springer eBooks (2023), pp. 1-38
Closed Access | Times Cited: 30
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: 29
Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification
Nathan J. Szymanski, Christopher J. Bartel, Yan Zeng, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 29
Accelerating the prediction of stable materials with machine learning
Sean D. Griesemer, Yi Xia, Chris Wolverton
Nature Computational Science (2023) Vol. 3, Iss. 11, pp. 934-945
Closed Access | Times Cited: 29
ChemNLP: A Natural Language-Processing-Based Library for Materials Chemistry Text Data
Kamal Choudhary, Mathew L. Kelley
The Journal of Physical Chemistry C (2023) Vol. 127, Iss. 35, pp. 17545-17555
Closed Access | Times Cited: 27
Barely visible impact damage detection in composite structures using deep learning networks with varying complexities
Ali Tabatabaeian, Bruno Jerkovic, Philip G. Harrison, et al.
Composites Part B Engineering (2023) Vol. 264, pp. 110907-110907
Open Access | Times Cited: 25
Accelerated Discovery of Novel Garnet-Type Solid-State Electrolyte Candidates via Machine Learning
Jiwon Sun, Seungpyo Kang, Joonchul Kim, et al.
ACS Applied Materials & Interfaces (2023) Vol. 15, Iss. 4, pp. 5049-5057
Closed Access | Times Cited: 24
Advances of machine learning in materials science: Ideas and techniques
Sue Sin Chong, Yi Sheng Ng, Hui‐Qiong Wang, et al.
Frontiers of Physics (2023) Vol. 19, Iss. 1
Open Access | Times Cited: 22
A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies
Krishnendu Sinha, Nabanita Ghosh, Parames C. Sil
Chemical Research in Toxicology (2023) Vol. 36, Iss. 8, pp. 1174-1205
Closed Access | Times Cited: 22
JARVIS-Leaderboard: a large scale benchmark of materials design methods
Kamal Choudhary, Daniel Wines, Kangming Li, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 14
Different applications of machine learning approaches in materials science and engineering: Comprehensive review
Yan Cao, Ali Taghvaie Nakhjiri, Mahdi Ghadiri
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108783-108783
Closed Access | Times Cited: 14
AtomGPT: Atomistic Generative Pretrained Transformer for Forward and Inverse Materials Design
Kamal Choudhary
The Journal of Physical Chemistry Letters (2024) Vol. 15, Iss. 27, pp. 6909-6917
Open Access | Times Cited: 14
Crystal structure generation with autoregressive large language modeling
Luis M. Antunes, Keith T. Butler, Ricardo Grau‐Crespo
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 13
Uncertainty quantification in multivariable regression for material property prediction with Bayesian neural networks
Longze Li, Jiang Chang, Aleksandar Vakanski, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 12
Well-defined high entropy-metal nanoparticles: Detection of the multi-element particles by deep learning
Manar Alnaasan, Wail Al Zoubi, Salh Alhammadi, et al.
Journal of Energy Chemistry (2024) Vol. 98, pp. 262-273
Closed Access | Times Cited: 12
Machine learning based hybrid ensemble models for prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths, and quantum yields
Kapil Dev Mahato, Shraban Das, Chandrashekhar Azad, et al.
APL Machine Learning (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 11
Application of artificial intelligence in the materials science, with a special focus on fuel cells and electrolyzers
Mariah Batool, Oluwafemi Joseph Sanumi, Jasna Janković
Energy and AI (2024) Vol. 18, pp. 100424-100424
Open Access | Times Cited: 11
Evaluation of Structural, Electronic, Optical and Mechanical Properties of Na-based Oxide‐Perovskites NaXO3 (X = Co, Be, Ba): A DFT study
Ruyhan, Muhammad Usman, Nazia Bibi, et al.
Materials Today Communications (2024) Vol. 39, pp. 108908-108908
Closed Access | Times Cited: 10
Statistical analysis of metastable pitting behavior of 2024 aluminum alloy based on deep learning
Zhenchang Xu, Baoyu Cai, Luchun Yan, et al.
Corrosion Science (2024) Vol. 233, pp. 112077-112077
Closed Access | Times Cited: 10
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
Systematic assessment of various universal machine‐learning interatomic potentials
Haochen Yu, Matteo Giantomassi, Giuliana Materzanini, et al.
Materials Genome Engineering Advances (2024) Vol. 2, Iss. 3
Open 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
New insight of thermodynamic cycle in thermoelectric power generation analyses: Literature review and perspectives
Xianhua Nie, Juan Xue, Li Zhao, et al.
Energy (2024) Vol. 292, pp. 130553-130553
Closed Access | Times Cited: 9
Automated Generation and Analysis of Molecular Images Using Generative Artificial Intelligence Models
Zhiwen Zhu, Jiayi Lu, Shaoxuan Yuan, et al.
The Journal of Physical Chemistry Letters (2024) Vol. 15, Iss. 7, pp. 1985-1992
Closed Access | Times Cited: 9
Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization
Yiming Chen, Chi Chen, Inhui Hwang, et al.
Chemistry of Materials (2024) Vol. 36, Iss. 5, pp. 2304-2313
Open Access | Times Cited: 9

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