Microstructure Design of Materials via Machine Learning: Advantage, Challenges, Applications, and Perspectives
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".
Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 240
Special Issue Editors
Interests: decoration of metal microstructure; aritificial intellegience in microstructure design; engineering metal fatigue; failure analysis
Special Issues, Collections and Topics in MDPI journals
Interests: additive manufacturing of metals and alloys: high temperature applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims to gather the latest advances in the field of the microstructure design of materials using machine learning techniques. Machine learning has emerged as a powerful tool in optimizing material properties through data-driven approaches. It offers several advantages, including accelerated discovery, improved performance, and reduced fabrication time and cost.
This Special Issue intends to focus on the advantages, challenges, applications, and perspectives of the microstructure design of materials using machine learning. We are particularly interested in novel structures, algorithms, and methodologies that exploit the potential of machine learning to optimize material microstructures for achieving enhanced properties. Additionally, unconventional applications, such as measurement techniques and computational models, that contribute to microstructure development are also encouraged.
The collection aims to present recent and important results that will be beneficial for both young investigators and leading experts in the field. It will provide valuable insights and inspiration for researchers interested in the design and development of materials with improved properties using machine learning techniques.
We encourage submissions that explore various material systems and properties, as well as studies that highlight the potential and limitations of machine learning in the microstructure design of materials. We believe that this Special Issue will offer a comprehensive overview of the advantages, challenges, and future perspectives of material design through machine learning.
Dr. Sugrib K. Shaha
Dr. Dyuti Sarker
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- microstructure design of materials
- machine learning
- data-driven approaches
- optimization
- enhanced properties
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