Enhancing high-entropy alloy performance: Predictive modelling of wear rates with machine learning-Reference-Cited by-同舟云学术

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Enhancing high-entropy alloy performance: Predictive modelling of wear rates with machine learning

Published:2024-09 Issue: Volume:23 Page:102387
ISSN:2590-1230
Container-title:Results in Engineering
language:en
Short-container-title:Results in Engineering

Author:

Niketh Madabhushi Siri,Radhika N.,Adediran Adeolu Adesoji,Jen Tien-Chien

Publisher

Elsevier BV

Reference73 articles.

1. High-entropy alloys;George;Nat. Rev. Mater.,2019

2. High-entropy alloy: challenges and prospects;Ye;Mater. Today,2016

3. Synthesis of high entropy alloy for surface modification by friction stir process: recent advances and future directions;Ragunath;Met. Mater. Int.,2023

4. Data driving design of high-entropy alloys for lightweight and dynamic applications;Cui;Sci. China Phys. Mech. Astron.,2024

5. Advancements and future prospects of additive manufacturing in high-entropy alloy applications;Ragunath;J. Alloys Compd.,2024

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. High entropy alloys for hydrogen storage applications: A machine learning-based approach;Results in Engineering;2024-09

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