Aim and Scope
The journal welcomes theoretical, computational, experimental, and applied studies focusing on the development and application of intelligent systems in chemical and materials science. It particularly encourages contributions that explore how data-centric and AI-driven methods can improve scientific understanding, accelerate innovation, enhance prediction accuracy, optimize experimental design, and contribute to sustainable and efficient chemical and materials technologies.
The journal values research that addresses the scientific, technological, and industrial dimensions of intelligent methods in chemistry and materials science, while also fostering dialogue between fundamental science, engineering practice, and digital transformation.
The journal welcomes original and high-quality contributions in the following areas:
Artificial Intelligence in Chemistry and Materials Science
Machine Learning for Molecular and Materials Design
Data-Driven Modeling and Scientific Prediction
Computational Chemistry and Materials Informatics
Intelligent Systems for Chemical Process Optimization
Smart Manufacturing and Digitalization in Materials Engineering
Reaction Prediction, Kinetics, and Mechanistic Modeling
Structure–Property–Performance Relationships
Materials Discovery and High-Throughput Screening
AI-Assisted Spectroscopy, Imaging, and Characterization
Intelligent Sensors, Monitoring, and Diagnostic Systems
Sustainable Materials and Green Chemical Technologies
Multi-Scale Modeling and Simulation
Autonomous Laboratories and Intelligent Experimental Design
Explainable AI, Scientific Interpretation, and Decision Support
Digital Twins and Smart Systems for Chemical and Materials Processes
Interdisciplinary Research in Intelligent Scientific Systems
Emerging Topics in Chemical and Materials Data Science
Guided by the principles of academic integrity, scientific quality, originality, methodological rigor, and ethical publishing, Intelligent Systems for Chemical and Materials Science publishes research articles, review articles, methodological studies, application-oriented papers, and theoretical contributions. The journal aims to strengthen interdisciplinary academic collaboration, promote innovation in intelligent scientific systems, and contribute meaningfully to the future of chemical and materials research.