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:
Influence of tensile properties on hole expansion ratio investigated using a generative adversarial imputation network with explainable artificial intelligence
Jeong‐Ah Lee, Jaejung Park, Yeon Taek Choi, et al.
Journal of Materials Science (2023) Vol. 58, Iss. 11, pp. 4780-4794
Closed Access | Times Cited: 7
Jeong‐Ah Lee, Jaejung Park, Yeon Taek Choi, et al.
Journal of Materials Science (2023) Vol. 58, Iss. 11, pp. 4780-4794
Closed Access | Times Cited: 7
Showing 7 citing articles:
Unveiling yield strength of metallic materials using physics-enhanced machine learning under diverse experimental conditions
Jeong‐Ah Lee, Roberto B. Figueiredo, Hyojin Park, et al.
Acta Materialia (2024) Vol. 275, pp. 120046-120046
Closed Access | Times Cited: 6
Jeong‐Ah Lee, Roberto B. Figueiredo, Hyojin Park, et al.
Acta Materialia (2024) Vol. 275, pp. 120046-120046
Closed Access | Times Cited: 6
Prediction and Optimization of Stretch-Flangeability of Advanced High Strength Steels through Microstructure-Property Correlations Utilizing Machine Learning Approaches
Tianyang Li, Zheng Yang, Junyi Cui, et al.
Research Square (Research Square) (2025)
Closed Access
Tianyang Li, Zheng Yang, Junyi Cui, et al.
Research Square (Research Square) (2025)
Closed Access
Prediction of multi-stage recrystallization behavior of AerMet100 high-strength steel based on deep learning
Z.J. Wang, Hongwu Chen, Jingyu Zhang, et al.
Journal of Materials Research and Technology (2025)
Open Access
Z.J. Wang, Hongwu Chen, Jingyu Zhang, et al.
Journal of Materials Research and Technology (2025)
Open Access
New approach to hole-expansion ratio in complex phase and martensitic steels: Understanding the role of punching damage
Woojin Cho, Byeong-Seok Jeong, Kyeongjae Jeong, et al.
Journal of Materials Research and Technology (2023) Vol. 26, pp. 837-849
Open Access | Times Cited: 8
Woojin Cho, Byeong-Seok Jeong, Kyeongjae Jeong, et al.
Journal of Materials Research and Technology (2023) Vol. 26, pp. 837-849
Open Access | Times Cited: 8
Active Learning Framework for Expediting the Search of Thermodynamically Stable MXenes in the Extensive Chemical Space
Jaejung Park, Jongmok Lee, Jaejun Lee, et al.
ACS Nano (2024) Vol. 18, Iss. 43, pp. 29678-29688
Closed Access | Times Cited: 2
Jaejung Park, Jongmok Lee, Jaejun Lee, et al.
ACS Nano (2024) Vol. 18, Iss. 43, pp. 29678-29688
Closed Access | Times Cited: 2
Surface heterostructuring in laser-treated alloys through local austenitization for high strength and formability
Rae Eon Kim, Gang Hee Gu, Jeong‐Ah Lee, et al.
Materials Research Letters (2024) Vol. 12, Iss. 8, pp. 606-615
Open Access | Times Cited: 2
Rae Eon Kim, Gang Hee Gu, Jeong‐Ah Lee, et al.
Materials Research Letters (2024) Vol. 12, Iss. 8, pp. 606-615
Open Access | Times Cited: 2
Machine learning investigation of high-k metal gate processes for dynamic random access memory peripheral transistor
Namyong Kwon, Joonho Bang, Won Ju Sung, et al.
APL Materials (2024) Vol. 12, Iss. 2
Open Access
Namyong Kwon, Joonho Bang, Won Ju Sung, et al.
APL Materials (2024) Vol. 12, Iss. 2
Open Access
