Special Issue
Topic: AI-Empowered Materials Science
A Special Issue of Journal of Materials Informatics
ISSN 2770-372X (Online)
Submission deadline: 31 Jul 2025
Guest Editor(s)
Prof. Likun Pan
School of Physics and Electronic Science, East China Normal University, Shanghai, China.
Prof. Jinlaing Li
Department of Physics, School of Physics & Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong, China.
Special Issue Introduction
Artificial Intelligence (AI)-Empowered Materials Science is an emerging field that accelerates the discovery and development of new materials through the use of AI technologies. Although still in its infancy, this field holds tremendous potential to revolutionize how we design and manufacture materials. Here are some specific issues that AI Materials Science can address:
(1) Accelerating Material Discovery: Traditional material discovery processes are time-consuming and costly. By leveraging AI, we can efficiently screen large-scale materials databases and rapidly identify potential new materials with desired properties. (2) Designing New Materials with Special Properties: AI technologies can assist in designing materials with specific attributes, such as high strength, low weight, or corrosion resistance, to meet a wider range of application needs. (3) Optimizing Material Processing: Through AI, we can improve material processing techniques, such as casting, forging, and machining, to enhance efficiency and product quality. (4) Predicting Material Performance: AI can predict material behavior under various environmental conditions, such as at specific temperatures, stress levels, or corrosive environments, providing essential references for material applications.
In this Special Issue, we will emphasize the challenges in accelerating material discovery and development using AI. We welcome original articles and topical reviews. The topics to be covered include, but are not limited to:
● High-throughput experimental/computational methods for building high-fidelity databases;
● AI-driven structural characterization of materials;
● Machine learning applications in additive manufacturing design;
● AI-guided applications of materials;
● AI optimization of material processing methods;
● AI-based predictions of material performance;
● AI-driven design of new materials with special properties.
(1) Accelerating Material Discovery: Traditional material discovery processes are time-consuming and costly. By leveraging AI, we can efficiently screen large-scale materials databases and rapidly identify potential new materials with desired properties. (2) Designing New Materials with Special Properties: AI technologies can assist in designing materials with specific attributes, such as high strength, low weight, or corrosion resistance, to meet a wider range of application needs. (3) Optimizing Material Processing: Through AI, we can improve material processing techniques, such as casting, forging, and machining, to enhance efficiency and product quality. (4) Predicting Material Performance: AI can predict material behavior under various environmental conditions, such as at specific temperatures, stress levels, or corrosive environments, providing essential references for material applications.
In this Special Issue, we will emphasize the challenges in accelerating material discovery and development using AI. We welcome original articles and topical reviews. The topics to be covered include, but are not limited to:
● High-throughput experimental/computational methods for building high-fidelity databases;
● AI-driven structural characterization of materials;
● Machine learning applications in additive manufacturing design;
● AI-guided applications of materials;
● AI optimization of material processing methods;
● AI-based predictions of material performance;
● AI-driven design of new materials with special properties.
Keywords
AI, materials science, design and prediction, manufacturing design
Submission Deadline
31 Jul 2025
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=JMI241023
Submission Deadline: 31 Jul 2025
Contacts: Linda Cui, Assistant Editor, Editor@jmijournal.com
Published Articles
Coming soon