Topic: Machine Learning Approach for Design, Development and Application of High Entropy Materials
A Special Issue of Journal of Materials Informatics
ISSN 2770-372X (Online)
Submission deadline: 31 Mar 2023
Guest Editor
Department of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Kowloon, Hong Kong, China.
Special Issue Introduction
In this Special Issue, we will emphasize the use of machine learning approaches in tackling the challenging issues in the field of high entropy materials. We welcome original contributions as well as topical reviews. The topics that we are going to cover include, but are not limited to, the following:
● Development of high throughput experimental/computational methods for the establishment of high-fidelity databases
● Machine learning-enabled structural characterizations for high entropy materials
● Machine learning-enabled understanding of thermodynamics and kinetics in high entropy materials
● Machine learning guided the design and development of high entropy materials (i.e., compositional design, processing design, microstructural characterization, etc. )
● Machine learning guided applications of high entropy materials (i.e., structural versus functional applications)
Submission Deadline
Submission Information
For Author Instructions, please refer to
https://www.oaepublish.com/jmi/author_instructions
For Online Submission, please login at
https://oaemesas.com/login?JournalId=jmi&SpecialIssueId=JMI220407
Submission Deadline:
31 Mar 2023
Contacts:
Lijun Jin, Managing Editor,
[email protected]
Published Articles
Data-driven prediction of the glass-forming ability of modeled alloys by supervised machine learning
, Jiachuan Tian
, ... Jun Shen