Composition design and optimization of Fe–C–Mn–Al steel based on machine learning-Reference-Cited by-同舟云学术

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Composition design and optimization of Fe–C–Mn–Al steel based on machine learning

Published:2024 Issue:10 Volume:26 Page:8219-8227
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Cheng Hong¹,He Zhongping¹^ORCID,Ge Meiling¹,Che Lun¹,Zheng Kaiyuan¹,Si Tianyu¹,Zhao Feng²

Affiliation:

1. School of Mechanical Engineering, Chengdu University, Chengdu, 610106, China

2. Institute for Advanced Study, Chengdu University, Chengdu 610106, China

Abstract

The purpose of this study is to explore the composition space of Fe–C–Mn–Al steel using machine learning in order to identify materials with high-strength mechanical properties.

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/CP/D3CP05453E

Reference38 articles.

1. Characterization of fracture in medium Mn steel

2. Dependence of strength–ductility characteristics on thermal history in lowcarbon, 5 wt-%Mn steels

3. The effects of the heating rate on the reverse transformation mechanism and the phase stability of reverted austenite in medium Mn steels

4. Constitutive Modeling of the Mechanical Properties of V-added Medium Manganese TRIP Steel

5. Current opinion in medium manganese steel

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