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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:

Application of machine learning methods on dynamic strength analysis for additive manufactured polypropylene-based composites
Ruijun Cai, Kui Wang, Wei Wen, et al.
Polymer Testing (2022) Vol. 110, pp. 107580-107580
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Machine learning-based heat deflection temperature prediction and effect analysis in polypropylene composites using catboost and shapley additive explanations
Chonghyo Joo, Hyundo Park, Jongkoo Lim, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106873-106873
Closed Access | Times Cited: 32
Methods, progresses, and opportunities of materials informatics
Chen Li, Kun Zheng
InfoMat (2023) Vol. 5, Iss. 8
Open Access | Times Cited: 28
Machine learning for predicting fatigue properties of additively manufactured materials
Min Yi, Ming Xue, Peihong Cong, et al.
Chinese Journal of Aeronautics (2023) Vol. 37, Iss. 4, pp. 1-22
Open Access | Times Cited: 25
Applications of artificial intelligence/machine learning to high-performance composites
Yifeng Wang, Wang Kan, Chuck Zhang
Composites Part B Engineering (2024) Vol. 285, pp. 111740-111740
Closed Access | Times Cited: 13
A machine learning-enabled prediction of damage properties for fiber-reinforced polymer composites under out-of-plane loading
Norman Osa-uwagboe, Amadi Gabriel Udu, Maryam Khaksar Ghalati, et al.
Engineering Structures (2024) Vol. 308, pp. 117970-117970
Open Access | Times Cited: 10
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: 9
A machine learning approach to characterise fabrication porosity effects on the mechanical properties of additively manufactured thermoplastic composites
Amadi Gabriel Udu, Norman Osa-uwagboe, Olusanmi Adeniran, et al.
Journal of Reinforced Plastics and Composites (2024)
Open Access | Times Cited: 7
Tailoring interfacial properties of 3D-printed continuous natural fiber reinforced polypropylene composites through parameter optimization using machine learning methods
Ruijun Cai, Wei Wen, Kui Wang, et al.
Materials Today Communications (2022) Vol. 32, pp. 103985-103985
Open Access | Times Cited: 31
Mechanical performance of non-reinforced, carbon fiber reinforced and glass bubbles reinforced 3D printed PA12 polyamide
Łukasz Pejkowski, Jan Seyda, Krzysztof Nowicki, et al.
Polymer Testing (2022) Vol. 118, pp. 107891-107891
Open Access | Times Cited: 30
Investigation on dynamic strength of 3D‐printed continuous ramie fiber reinforced biocomposites at various strain rates using machine learning methods
Ruijun Cai, Hao Lin, Ping Cheng, et al.
Polymer Composites (2022) Vol. 43, Iss. 8, pp. 5235-5249
Closed Access | Times Cited: 29
Machine learning models to predict the relationship between printing parameters and tensile strength of 3D Poly (lactic acid) scaffolds for tissue engineering applications
Duygu Ege, Seda Sertturk, Berk Acarkan, et al.
Biomedical Physics & Engineering Express (2023) Vol. 9, Iss. 6, pp. 065014-065014
Open 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: 5
Effects of the printing parameters on geometric accuracy and mechanical properties of digital light processing printed polymer
Ruijun Cai, Xiaobo Luo, Guoquan Xie, et al.
Journal of Materials Science (2024) Vol. 59, Iss. 31, pp. 14807-14819
Closed Access | Times Cited: 5
Machine Learning Study of the Effect of Process Parameters on Tensile Strength of FFF PLA and PLA-CF
Abdelhamid Ziadia, Mohamed Habibi, Sousso Kélouwani
Eng—Advances in Engineering (2023) Vol. 4, Iss. 4, pp. 2741-2763
Open Access | Times Cited: 15
Deep neural operator for learning transient response of interpenetrating phase composites subject to dynamic loading
Minglei Lu, Ali Mohammadi, Zhaoxu Meng, et al.
Computational Mechanics (2023) Vol. 72, Iss. 3, pp. 563-576
Closed Access | Times Cited: 13
A novel machine learning-based approach for in-situ surface roughness prediction in laser powder-bed fusion
Sahar Toorandaz, Katayoon Taherkhani, Farima Liravi, et al.
Additive manufacturing (2024) Vol. 91, pp. 104354-104354
Open Access | Times Cited: 4
A comprehensive analysis and prediction of the effect of groove shape and volume fraction of multi-walled carbon nanotubes on the polymer 3D-printed parts in the friction stir welding process
Mohammad Sadegh Javadi, Mohammad Vahid Ehteshamfar, Hamed Adibi
Polymer Testing (2022) Vol. 117, pp. 107844-107844
Open Access | Times Cited: 21
3D printing continuous natural fiber reinforced polymer composites: A review
Ping Cheng, Yong Peng, Kui Wang, et al.
Polymers for Advanced Technologies (2023) Vol. 35, Iss. 1
Closed Access | Times Cited: 12
An improvement in the mechanical properties of polypropylene/ethylene-propylene-diene monomer/titanium dioxide nanocomposite obtained by fused filament fabrication
Lei Xu, Wenzhen Chen, Xiang Zheng, et al.
Journal of Thermoplastic Composite Materials (2024)
Closed Access | Times Cited: 3
Potentials and challenges of additive manufacturing techniques in the fabrication of polymer composites
Smith Salifu, Olugbenga Ogunbiyi, Peter Apata Olubambi
The International Journal of Advanced Manufacturing Technology (2022) Vol. 122, Iss. 2, pp. 577-600
Closed Access | Times Cited: 16
Geometric Accuracy and Energy Absorption Characteristics of 3D Printed Continuous Ramie Fiber Reinforced Thin-Walled Composite Structures
Kui Wang, Hao Lin, Antoine Le Duigou, et al.
Chinese Journal of Mechanical Engineering (2023) Vol. 36, Iss. 1
Open Access | Times Cited: 10
Evaluation of defect-related fatigue performance of additive manufacturing GH4169 via small punch test
Xun Wang, Lianyong Xu, Lei Zhao, et al.
Theoretical and Applied Fracture Mechanics (2023) Vol. 128, pp. 104162-104162
Closed Access | Times Cited: 9
XGB Modeling Reveals Improvement of Compressive Strength of Cement-Based Composites with Addition of HPMC and Chitosan
Duygu Ege, Ali Reza Kamali
Materials (2024) Vol. 17, Iss. 2, pp. 374-374
Open Access | Times Cited: 3
Remanufacturing and mechanical property restoration of post-used polypropylene-based composites based on in-situ impregnated 3D printing
Jiangyang Xiang, Hao Lin, Zejun Zhang, et al.
Sustainable materials and technologies (2024) Vol. 40, pp. e00916-e00916
Closed Access | Times Cited: 3
Simultaneous enhancement of the impact strength and tensile modulus of PP/EPDM/TiO2 nanocomposite fabricated by fused filament fabrication
Fatemeh Taher, Mahmoud Afshari, Ali Houmani, et al.
Colloid & Polymer Science (2023) Vol. 302, Iss. 3, pp. 393-407
Closed Access | Times Cited: 7
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