Topic: Data-driven Modeling and Design of Quantum Functional Materials

The Journal of Materials Informatics is planning to publish a thematic issue on data-driven modeling and design of quantum functional materials due to the increasingly important role of data-driven (such as, artificial intelligence, machine-learning, data science, big data) techniques in materials innovations. The thematic issue aims to collect the most frontier progress on this research topic. Both theoretical and experimental research articles, reviews, highlights, perspectives, viewpoints are welcomed.

Research areas of particular interest covered by the thematic issues include, but are not limited to:
1) data-driven algorithms and codes for quantum functional materials (QFM)
2) data-driven design and architecture of QFM
3) data-driven study on the diverse physicochemical properties of QFM
4) data-driven modeling and understanding the growth and formation mechanism and dynamic evolution process of QFM at the molecular level
5) data-driven exploration on the functional devices based on QFM
6) data-driven study on the applications of QFM for catalysis, energy, environment, and sustainable development
7) data-driven experimental preparation, characterization and functionalization of QFM

Timeline: Researchers are encouraged to submit their new and unpublished work by 29 Feb 2024.

If you have any questions about the thematic issue, please contact the Guest Editor (Lmyang@hust.edu.cn ).

29 Feb 2024