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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:

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

Showing 18 citing articles:

The Influence of Roughness of Surfaces on Wear Mechanisms in Metal–Rock Interactions
Vlad Alexandru Florea, Mihaela Toderaş, Ciprian Danciu
Coatings (2025) Vol. 15, Iss. 2, pp. 150-150
Open Access | Times Cited: 1
Solving Real-Life Wear Problems: Streamlined Lab Tests for Diverse Industrial Applications. Can AI help ?
Dirk Drees, Lais Lopes, Pedro Baião, et al.
Wear (2025), pp. 205853-205853
Closed Access
Enhancing forecasting of current-carrying performance through spatial frequency analysis of interface morphology
Nian Yin, Zishuai Wu, Zhangli Hou, et al.
Science China Technological Sciences (2025) Vol. 68, Iss. 2
Closed Access
Influence of Abrasive Wear on Reliability and Maintainability of Components in Quarry Technological Equipment: A Case Study
Vlad Alexandru Florea, Mihaela Toderaş, Daniel Tihanov-Tănăsache
Applied Sciences (2025) Vol. 15, Iss. 7, pp. 3603-3603
Open Access
Tribological Characteristics of Polyethersulphone-Based Nanocomposites in Ceramic-Polymer Linear Contacts
D. G. Buslovich, Changjun He, С. В. Панин
Advanced structured materials (2025), pp. 373-387
Closed Access
Wear on steel tillage tools: A review of material, soil and dynamic conditions
Aysel Yazıcı
Soil and Tillage Research (2024) Vol. 242, pp. 106161-106161
Closed Access | Times Cited: 3
Fully unsupervised wear anomaly assessment of aero-bearings enhanced by multi-representation learning of deep features
Tao Shao, Luning Zhang, Shuo Wang, et al.
Tribology International (2024) Vol. 196, pp. 109724-109724
Closed Access | Times Cited: 2
Enhancing practical modeling: A neural network approach for locally-resolved prediction of elastohydrodynamic line contacts
Josephine Kelley, Volker Schneider, Gerhard Poll, et al.
Tribology International (2024) Vol. 199, pp. 109988-109988
Open Access | Times Cited: 2
Machine-Learning-Based Wear Prediction in Journal Bearings under Start–Stop Conditions
Florian König, Florian Wirsing, Ankit Singh, et al.
Lubricants (2024) Vol. 12, Iss. 8, pp. 290-290
Open Access | Times Cited: 2
A Neural Network for Fast Modeling of Elastohydrodynamic Line Contacts
Josephine Kelley, Volker Schneider, Max Marian, et al.
(2024)
Closed Access | Times Cited: 1
A novel extension model for predicting the friction coefficient of fluorinated ethylene propylene based on temporal convolutional networks expansion algorithms
Jiayu Liao, Honghao Zhao, Pengxiang Zhou, et al.
Journal of Intelligent Manufacturing (2024)
Closed Access | Times Cited: 1
Optimization of twin grooved two-lobe textured hydrodynamic journal bearing design by using genetic algorithm
Saurabh Kumar Yadav, Chandra B. Khatri, Abhishek Kumar, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2024) Vol. 238, Iss. 20, pp. 10205-10221
Closed Access
Recent Advances in Tribology: A Review
Mayank Choubey, Shweta Mishra, Dinesh Deshwal
Journal of Molecular and Engineering Materials (2024)
Closed Access
Prior-shape-guided photometric stereo model for 3D damage measurement of worn surfaceiks
Shuo Wang, K. Hu, Linyu Xia, et al.
Tribology International (2024) Vol. 201, pp. 110219-110219
Closed Access
Regulatory Framework and Standards for Adapting AI Systems: Interplay Between AI and Environmental Policies
Sini Kuriakose, Yukti Monga
(2024), pp. 265-279
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
Designing of Ti3C2Tx/NiCo-MOF nanocomposite electrode: a versatile platform for electrochemical-based energy storage devices
M. Mumtaz, Amir Muhammad Afzal, Muhammad Hamza Waris, et al.
Journal of Materials Science Materials in Electronics (2024) Vol. 35, Iss. 31
Closed Access
Tribo-informatics empowered research on triboelectrification
Nian Yin, Zhangli Hou, Xin Wang, et al.
Friction (2024) Vol. 13, Iss. 2, pp. 9441045-9441045
Open Access
Prediction of Tribological Performance of Ti-3Al-2.5 V-xWC Composite using Machine Learning Models
T. Ramkumar, V. Sudha, M. Selvakumar, et al.
Journal of Materials Engineering and Performance (2024)
Closed Access
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