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:
Optimizing the Powder Metallurgy Parameters to Enhance the Mechanical Properties of Al-4Cu/xAl2O3 Composites Using Machine Learning and Response Surface Approaches
Sally Elkatatny, Mohammed F. Alsharekh, A. I. Alateyah, et al.
Applied Sciences (2023) Vol. 13, Iss. 13, pp. 7483-7483
Open Access | Times Cited: 7
Sally Elkatatny, Mohammed F. Alsharekh, A. I. Alateyah, et al.
Applied Sciences (2023) Vol. 13, Iss. 13, pp. 7483-7483
Open Access | Times Cited: 7
Showing 7 citing articles:
Enhancement of mechanical and physical properties of Cu–Ni composites by various contents of Y2O3 reinforcement
Walaa Abd‐Elaziem, Atef Hamada, Tarek Allam, et al.
Journal of Materials Research and Technology (2024) Vol. 30, pp. 473-484
Open Access | Times Cited: 5
Walaa Abd‐Elaziem, Atef Hamada, Tarek Allam, et al.
Journal of Materials Research and Technology (2024) Vol. 30, pp. 473-484
Open Access | Times Cited: 5
Machine-Learning Synergy in High-Entropy Alloys: A Review
Sally Elkatatny, Walaa Abd‐Elaziem, Tamer A. Sebaey, et al.
Journal of Materials Research and Technology (2024) Vol. 33, pp. 3976-3997
Closed Access | Times Cited: 4
Sally Elkatatny, Walaa Abd‐Elaziem, Tamer A. Sebaey, et al.
Journal of Materials Research and Technology (2024) Vol. 33, pp. 3976-3997
Closed Access | Times Cited: 4
A Comprehensive Prediction Method for Pore Pressure in Abnormally High-Pressure Blocks Based on Machine Learning
H. Li, Qiang Tan, Jingen Deng, et al.
Processes (2023) Vol. 11, Iss. 9, pp. 2603-2603
Open Access | Times Cited: 10
H. Li, Qiang Tan, Jingen Deng, et al.
Processes (2023) Vol. 11, Iss. 9, pp. 2603-2603
Open Access | Times Cited: 10
Optimization methods in powder metallurgy for enhancing the mechanical properties: A systematic literature review
Divnesh Lingam, Rajeshkannan Ananthanarayanan, A.K. Jeevanantham, et al.
Engineering Research Express (2024) Vol. 6, Iss. 2, pp. 022504-022504
Open Access | Times Cited: 2
Divnesh Lingam, Rajeshkannan Ananthanarayanan, A.K. Jeevanantham, et al.
Engineering Research Express (2024) Vol. 6, Iss. 2, pp. 022504-022504
Open Access | Times Cited: 2
Simulation and Algorithmic Optimization of the Cutting Process for the Green Machining of PM Green Compacts
Yuchen Zhang, Dayong Yang, Lingxin Zeng, et al.
Materials (2024) Vol. 17, Iss. 16, pp. 3963-3963
Open Access | Times Cited: 1
Yuchen Zhang, Dayong Yang, Lingxin Zeng, et al.
Materials (2024) Vol. 17, Iss. 16, pp. 3963-3963
Open Access | Times Cited: 1
Effects of Cu Content and Sintering Temperature on Microstructure and Mechanical Properties of SiCp/Al-Cu-Mg Composites through experimental study, CALPHAD-type simulation and machine learning
Wei Yang, Yiwei Wang, Xiaozhong Huang, et al.
Journal of Materials Research and Technology (2024) Vol. 33, pp. 2216-2225
Open Access
Wei Yang, Yiwei Wang, Xiaozhong Huang, et al.
Journal of Materials Research and Technology (2024) Vol. 33, pp. 2216-2225
Open Access
Computer Modeling and Machine Learning in Chemistry and Materials Science: From Properties and Reactions of Small Organic and Inorganic Molecules to the Smart Design of Polymers and Composites
Alexander S. Novikov
Compounds (2023) Vol. 3, Iss. 3, pp. 459-463
Open Access
Alexander S. Novikov
Compounds (2023) Vol. 3, Iss. 3, pp. 459-463
Open Access
