Machine-learning-driven prediction of flow curves and development of processing maps for hot-deformed Ni–Cu–Co–Ti–Ta alloy

Machine-learning-driven prediction of flow curves and development of processing maps for hot-deformed Ni–Cu–Co–Ti–Ta alloy

Optimizing hot deformation conditions is critical for achieving efficient thermo-mechanical processing of advanced alloy systems. In this study, a multicomponent Ni48Cu10Co2Ti38Ta2 alloy was developed, exhibiting a refined eutectic microstructure composed of NiTi and Ni3Ti phases, along with coarse...

Full description

Saved in:
Bibliographic Details
Main Authors: Reliance Jain, Sandeep Jain, Sheetal Kumar Dewangan, M.R. Rahul, Sumanta Samal, Eunhyo Song, Younggeon Lee, Yongho Jeon, Krishanu Biswas, Gandham Phanikumar, Byungmin Ahn
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Journal of Materials Research and Technology
Subjects:
Ni–Ti-Based alloy
Hot deformation
Kinetic analysis
Processing map
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2238785425011494
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items