Aims & Scope

Journal of AI for Materials (JAM) is an international, peer-reviewed journal publishing original research and reviews on the application of artificial intelligence and machine learning in materials science.

The journal covers all aspects of AI-driven materials research, including:

AI-accelerated materials discovery and design

Machine learning potentials and simulations

Data-driven materials characterization

Autonomous experimentation and self-driving labs

Materials informatics and databases

AI for sustainable materials and energy

Explainable AI and uncertainty quantification

AI in materials processing and manufacturing