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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:

Deep materials informatics: Applications of deep learning in materials science
Ankit Agrawal, Alok Choudhary
MRS Communications (2019) Vol. 9, Iss. 3, pp. 779-792
Open Access | Times Cited: 214

Showing 1-25 of 214 citing articles:

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: 590
Emerging materials intelligence ecosystems propelled by machine learning
Rohit Batra, Le Song, Rampi Ramprasad
Nature Reviews Materials (2020) Vol. 6, Iss. 8, pp. 655-678
Closed Access | Times Cited: 252
Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning
Dipendra Jha, Kamal Choudhary, Francesca Tavazza, et al.
Nature Communications (2019) Vol. 10, Iss. 1
Open Access | Times Cited: 244
Polymer informatics: Current status and critical next steps
Lihua Chen, Ghanshyam Pilania, Rohit Batra, et al.
Materials Science and Engineering R Reports (2020) Vol. 144, pp. 100595-100595
Open Access | Times Cited: 212
Deep learning analysis on microscopic imaging in materials science
M. Ge, Fei Su, Zhicheng Zhao, et al.
Materials Today Nano (2020) Vol. 11, pp. 100087-100087
Closed Access | Times Cited: 151
Fatigue life prediction of aluminum alloy via knowledge-based machine learning
Zhengheng Lian, Minjie Li, Wencong Lu
International Journal of Fatigue (2022) Vol. 157, pp. 106716-106716
Closed Access | Times Cited: 80
Machine learning in nuclear materials research
Dane Morgan, Ghanshyam Pilania, Adrien Couet, et al.
Current Opinion in Solid State and Materials Science (2022) Vol. 26, Iss. 2, pp. 100975-100975
Open Access | Times Cited: 75
Artificial Intelligence in Predicting Mechanical Properties of Composite Materials
Fasikaw Kibrete, Tomasz Trzepieciński, Hailu Shimels Gebremedhen, et al.
Journal of Composites Science (2023) Vol. 7, Iss. 9, pp. 364-364
Open Access | Times Cited: 70
Data-Driven Design of Polymer-Based Biomaterials: High-throughput Simulation, Experimentation, and Machine Learning
Roshan Patel, Michael Webb
ACS Applied Bio Materials (2023) Vol. 7, Iss. 2, pp. 510-527
Closed Access | Times Cited: 50
Application of Machine Learning in Material Synthesis and Property Prediction
Guannan Huang, Yani Guo, Ye Chen, et al.
Materials (2023) Vol. 16, Iss. 17, pp. 5977-5977
Open Access | Times Cited: 41
A machine learning approach to predict the efficiency of corrosion inhibition by natural product-based organic inhibitors
Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
Physica Scripta (2024) Vol. 99, Iss. 3, pp. 036006-036006
Closed Access | Times Cited: 28
Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets
Vishu Gupta, Kamal Choudhary, Brian DeCost, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 26
Prediction of Anti-Corrosion performance of new triazole derivatives via Machine learning
Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
Computational and Theoretical Chemistry (2024) Vol. 1236, pp. 114599-114599
Closed Access | Times Cited: 23
Machine Learning Design of Perovskite Catalytic Properties
Ryan Jacobs, Jian Liu, Harry Abernathy, et al.
Advanced Energy Materials (2024) Vol. 14, Iss. 12
Open Access | Times Cited: 17
Accelerating materials discovery: combinatorial synthesis, high-throughput characterization, and computational advances
Khurram Shahzad, Andrei Ionut Mardare, Achim Walter Hassel
Science and Technology of Advanced Materials Methods (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 15
Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data
Vishu Gupta, Kamal Choudhary, Francesca Tavazza, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 98
ChemDataExtractor 2.0: Autopopulated Ontologies for Materials Science
Juraj Mavračić, Callum J. Court, Taketomo Isazawa, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 9, pp. 4280-4289
Closed Access | Times Cited: 86
Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery
Changwon Suh, Clyde Fare, James A. Warren, et al.
Annual Review of Materials Research (2020) Vol. 50, Iss. 1, pp. 1-25
Closed Access | Times Cited: 75
Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: A review
Luis Enrique Vivanco-Benavides, Claudia Lizbeth Martínez‐González, C. Mercado-Zúñiga, et al.
Computational Materials Science (2021) Vol. 201, pp. 110939-110939
Closed Access | Times Cited: 75
Machine learning for materials design and discovery
Rama K. Vasudevan, Ghanshyam Pilania, Prasanna V. Balachandran
Journal of Applied Physics (2021) Vol. 129, Iss. 7
Open Access | Times Cited: 74
Machine Learning for Transition-Metal-Based Hydrogen Generation Electrocatalysts
Min Wang, Hongwei Zhu
ACS Catalysis (2021) Vol. 11, Iss. 7, pp. 3930-3937
Closed Access | Times Cited: 67
Featurization strategies for polymer sequence or composition design by machine learning
Roshan Patel, Carlos H. Borca, Michael Webb
Molecular Systems Design & Engineering (2022) Vol. 7, Iss. 6, pp. 661-676
Closed Access | Times Cited: 66
On the application of physics informed neural networks (PINN) to solve boundary layer thermal-fluid problems
H. Bararnia, Mehdi Esmaeilpour
International Communications in Heat and Mass Transfer (2022) Vol. 132, pp. 105890-105890
Closed Access | Times Cited: 58
Surface science of cosmetic substrates, cleansing actives and formulations
Gustavo S. Luengo, Anne‐Laure Fameau, Fabien Léonforte, et al.
Advances in Colloid and Interface Science (2021) Vol. 290, pp. 102383-102383
Closed Access | Times Cited: 56
A micromechanics-based artificial neural networks model for elastic properties of short fiber composites
N. Mentges, Behdad Dashtbozorg, Mohsen Mirkhalaf
Composites Part B Engineering (2021) Vol. 213, pp. 108736-108736
Open Access | Times Cited: 56
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