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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:

Prediction of friction coefficient of su-8 and its composite coatings using machine learning techniques
Anwaruddin Siddiqui Mohammed, Srihari Dodla, Jitendra Kumar Katiyar, et al.
Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (2022) Vol. 237, Iss. 4, pp. 943-953
Closed Access | Times Cited: 16

Showing 16 citing articles:

AI for tribology: Present and future
Nian Yin, Pufan Yang, Songkai Liu, et al.
Friction (2024) Vol. 12, Iss. 6, pp. 1060-1097
Open Access | Times Cited: 18
Development of machine learning models for the prediction of erosion wear of hybrid composites
Sourav Kumar Mahapatra, Alok Satapathy
Polymer Composites (2024) Vol. 45, Iss. 9, pp. 7950-7966
Closed Access | Times Cited: 11
Machine Learning in Commercialized Coatings
Harshit Mittal, Omkar Singh Kushwaha
(2024), pp. 450-474
Closed Access | Times Cited: 7
Analysis and prediction of erosion behavior of epoxy composites using statistical and machine learning techniques
Sourav Kumar Mahapatra, Alok Satapathy
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2024)
Closed Access | Times Cited: 6
Predictive modeling of compressive strength for additively manufactured PEEK spinal fusion cages using machine learning techniques
Narain Kumar Sivakumar, Sabarinathan Palaniyappan, Mahdi Bodaghi, et al.
Materials Today Communications (2024) Vol. 38, pp. 108307-108307
Closed Access | Times Cited: 5
A Machine Learning Approach for Analyzing Residual Stress Distribution in Cold Spray Coatings
Rosa Huaraca Aparco, Fidelia Tapia-Tadeo, Yajhayda Bellido Ascarza, et al.
Journal of Thermal Spray Technology (2024) Vol. 33, Iss. 5, pp. 1292-1307
Closed Access | Times Cited: 4
Sustainable tribology for reliability and efficiency
Jitendra Kumar Katiyar, T. V. V. L. N. Rao
Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (2023) Vol. 237, Iss. 8, pp. 1670-1679
Closed Access | Times Cited: 7
Artificial Neural Network technique to assess tribological performance of GFRP composites incorporated with graphene nano-platelets
Santosh Kumar, Nikhil Sharma, Kalyan Kumar Singh
Tribology International (2022) Vol. 179, pp. 108194-108194
Closed Access | Times Cited: 11
Prediction of friction coefficient and torque in self-lubricating polymer radial bearings produced by additive manufacturing: A machine learning approach
Hasan Baş, Yunus Emre Karabacak
Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (2023) Vol. 237, Iss. 11, pp. 2014-2038
Closed Access | Times Cited: 4
Prediction of Tribological Properties of UHMWPE/SiC Polymer Composites Using Machine Learning Techniques
Abdul Jawad Mohammed, Anwaruddin Siddiqui Mohammed, Mohammed Abdul Samad
Polymers (2023) Vol. 15, Iss. 20, pp. 4057-4057
Open Access | Times Cited: 4
Machine learning-assisted analysis of dry and lubricated tribological properties of Al–Co–Cr–Fe–Ni high entropy alloy
Saurabh Vashistha, Bashista Kumar Mahanta, Vivek K. Singh, et al.
Digital Discovery (2024)
Open Access | Times Cited: 1
Solar energy generation and power prediction through computer vision and machine intelligence
Dipanjan Rout, Naman Shyamsukha, Harshit Mittal, et al.
Elsevier eBooks (2024), pp. 103-123
Closed Access | Times Cited: 1
Triboinformatic Approaches for Composite Coatings on Titanium Alloys
Kamal Kumar, Utpal Barman, Patrick J. Masset, et al.
Lecture notes in mechanical engineering (2024), pp. 235-243
Closed Access
Integration of machine learning prediction and optimization for determination of the coefficient of friction of textured UHMWPE surfaces
Huihui Feng, Jing Liu, Ron A.J. van Ostayen, et al.
Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (2024)
Closed Access
Application of the Gradient-Boosting with Regression Trees to Predict the Coefficient of Friction on Drawbead in Sheet Metal Forming
Sherwan Mohammed Najm, Tomasz Trzepieciński, Salah Eddine Laouini, et al.
Materials (2024) Vol. 17, Iss. 18, pp. 4540-4540
Open Access
Erosion wear performance of titania filled ramie-epoxy composites: A data driven optimization study using supervised machine learning approach
Sourav Kumar Mahapatra, Alok Satapathy
Journal of Elastomers & Plastics (2024)
Closed Access
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