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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:

Data‐driven modeling for predicting tribo‐performance of graphene‐incorporated glass‐fabric reinforced epoxy composites using machine learning algorithms
Santosh Kumar, K. Sourabh K. Singh, Kalyan Kumar Singh
Polymer Composites (2022) Vol. 43, Iss. 9, pp. 6599-6610
Closed Access | Times Cited: 21

Showing 21 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
TRACING THE EVOLUTION OF AI AND MACHINE LEARNING APPLICATIONS IN ADVANCING MATERIALS DISCOVERY AND PRODUCTION PROCESSES
Nwakamma Ninduwezuor-Ehiobu, Olawe Alaba Tula, Chibuike Daraojimba, et al.
Engineering Science & Technology Journal (2023) Vol. 4, Iss. 3, pp. 66-83
Open Access | Times Cited: 33
Compression after multiple impact strength of composite laminates prediction method based on machine learning approach
Jingyu Zhao, Ben Wang, Qihui Lyu, et al.
Aerospace Science and Technology (2023) Vol. 136, pp. 108243-108243
Closed Access | Times Cited: 28
Study of Friction and Wear Behavior of Graphene-Reinforced AA7075 Nanocomposites by Machine Learning
I. S. N. V. R. Prasanth, Prabahar Jeevanandam, P. Selvaraju, et al.
Journal of Nanomaterials (2023) Vol. 2023, pp. 1-15
Open Access | Times Cited: 27
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
A novel framework to predict transversal and shear parameters of unidirectional composites by combining experimental, numerical and machine learning methods
Siqi Cheng, Xiaoyu Wang, Yuxuan Gao, et al.
Polymer Composites (2025)
Closed Access | Times Cited: 1
Influence of fiber areal density on mechanical behavior of basalt fiber/epoxy composites under varying loading rates: An experimental and statistical approach
Rahul Biswas, Nisha Sharma, Kalyan Kumar Singh
Polymer Composites (2023) Vol. 44, Iss. 4, pp. 2222-2235
Closed Access | Times Cited: 18
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
Deep Transfer Learning Approach for Localization of Damage Area in Composite Laminates Using Acoustic Emission Signal
Jingyu Zhao, Weihua Xie, Dong Yu, et al.
Polymers (2023) Vol. 15, Iss. 6, pp. 1520-1520
Open Access | Times Cited: 13
Structural design optimization of CFRP/Al hybrid co‐cured high‐speed flywheel with the particle swarm optimization algorithm
Bingfu Zhong, Junli Li, Xiaojiang Cai, et al.
Polymer Composites (2023) Vol. 44, Iss. 4, pp. 2161-2172
Closed Access | Times Cited: 11
Development of Robust Machine Learning Models for Predicting Flexural Strengths of Fiber-Reinforced Polymeric Composites
Abdulhammed K. Hamzat, Umar Salman, Md Shafinur Murad, et al.
Hybrid Advances (2025), pp. 100385-100385
Open Access
Data‐driven machine learning regression methods to predict the residual strength in FRP composites subjected to fatigue
Anand Gaurav
Polymer Composites (2025)
Closed Access
The Role of Morphology on Thermal and Electrical Properties of MWCNT-Doped-PVDF Nanocomposites
Raj Agarwal, H. K. Mehtani, Rishi Kumar, et al.
Journal of Inorganic and Organometallic Polymers and Materials (2023) Vol. 33, Iss. 3, pp. 771-782
Closed Access | Times Cited: 9
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
Introduction to data‐driven systems for plastics and composites manufacturing
Saeed Farahani, Srikanth Pilla, Yun Zhang, et al.
Polymer Composites (2023)
Open Access | Times Cited: 4
Enhancement of mechanical and tribological properties in glass fiber-reinforced polymer composites with multi-walled carbon nanotubes and ANN-based COF prediction
Mayank Singh, Srihari Dodla, Rakesh Kumar Gautam, et al.
Composite Interfaces (2024), pp. 1-21
Closed Access | Times Cited: 1
Taguchi approach for comparative optimization of tribological behavior of glass fabric reinforced epoxy composite with and without graphene-nano platelets filler
Prabhat Kumar Prajapati, Santosh Kumar, Kalyan Kumar Singh
Materials Today Proceedings (2022) Vol. 72, pp. 1605-1612
Closed Access | Times Cited: 4
GNBoost-Based Ensemble Machine Learning for Predicting Tribological Properties of Liquid-Crystal Lubricants
Hongfei Shi, Hanglin Li, Zhaoyang Guo, et al.
Langmuir (2024) Vol. 40, Iss. 20, pp. 10705-10717
Closed Access
Effect of the addition of CNT on the flexural, inter laminar shear strength and abrasive wear behaviour of glass fiber/epoxy composite
Komal A. Ekka, Santosh Kumar, Kalyan Kumar Singh
AIP conference proceedings (2024) Vol. 3245, pp. 090004-090004
Closed Access
Advanced Machine Learning and Experimental Studies of Polypropylene Based Polyesters Tribological Composite Systems for Sustainable Recycling Automation and Digitalization
Abrar Hussain, Jakob Kübarsepp, Fjodor Sergejev, et al.
International Journal of Lightweight Materials and Manufacture (2024)
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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