Journal of Multiscale Materials Informatics

About the Journal

Journal of Multiscale Materials Informatics (JIMAT) is a peer-reviewed international journal that covers all aspects of foundations, theories, and applications in computer and materials sciences. All accepted articles are published online, assigned a DOI via CrossRef, and made freely accessible (Open Access) with no APC. The journal follows a rapid peer-review process, with the first decision typically provided within two to four weeks.

JIMAT focuses on the latest research that combines computer science, artificial intelligence, quantum technologies, and data-driven scientific discovery, highlighting the importance of working across different fields and making a real difference in the world. The scope includes, but is not limited to:

1. Artificial Intelligence and Data-Driven Intelligence:
- machine learning
- deep learning
- statistical learning
- intelligent systems
- natural language processing
- computer vision
- pattern recognition
- speech processing
- hybrid AI models.
2. Quantum Computing and Quantum Information Science:
- quantum technologies
- quantum computing
- quantum information
- quantum simulation
- quantum machine learning
- quantum error correction,
- quantum sensing and metrology
- bridging classical and quantum paradigms.
3. Data Science, Big Data, and Knowledge Discovery:
- data mining
- big data analytics
- database systems
- scalable data infrastructures.
4. Materials Informatics and Scientific Machine Learning:
- data-driven materials discovery and design
- machine learning and AI for materials property prediction and optimization
- materials databases and high-throughput data generation
- structure–property–activity relationship modeling,
- scientific machine learning for physics-informed and chemistry-informed systems
- Integration of computational modeling, experimental data, and AI.
5. Interdisciplinary Informatics (cross-domain innovation through informatics approaches in):
- materials informatics
- bioinformatics
- chemoinformatics
- medical informatics
- agri-informatics
- geoinformatics
- astroinformatics
- physics informatics.
6. Computational Methods and Scientific Modeling:
- theoretical modeling
- numerical methods
- algorithm development for complex systems, including simulation-driven and hybrid (theory–experiment–AI) approaches.
7. Secure, Scalable, and Intelligent Systems:
- cloud computing
- Internet of Things (IoT)
- distributed systems
- cybersecurity
- cryptography
- biometrics
- intelligent networked systems that support large-scale scientific and industrial applications.