Topic: Application of Machine Learning to 2D Materials
A Special Issue of Journal of Materials Informatics
ISSN 2770-372X (Online)
Submission deadline: 12 May 2024
Special Issue Introduction
However, conventional experimental and computational methods are difficult to keep up with the rapidly growing demands in the study of 2D materials. In response, machine learning (ML) approaches have proven to be effective tools for studying a wide variety of materials, with 2D materials no exception. Therefore, high-throughput experimental or computational methods are desperately needed to provide extensive datasets for ML applications, which can, in return, complement experimental work. Although abundant studies have focused on 2D materials in recent years, more aspects on microstructures, properties, and applications still call for ML and other approaches to provide more insights. The huge compositional space of 2D materials offers limitless opportunities for academic and industrial research and development.
This Special Issue aims to present the most recent advancements in ML-based approaches for the study of 2D materials. The scope includes a wide range of topics but not limited to:
● Data-driven approaches;
● ML algorithms;
● Multiscale modeling;
● ML interatomic potentials;
● High-throughput experiments.
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=JMI231020
Submission Deadline: 12 May 2024
Contacts: Yanira, Assistant Editor, Yanira@oaeservice.com