Journal Overview

Intelligent Systems for Chemical and Materials Science is a peer-reviewed academic journal that brings together scientific inquiry and reflective thought. The journal aims to publish original studies that address fundamental issues such as knowledge, truth, ethics, humanity, society, civilization, nature, and technology through an interdisciplinary perspective. By valuing the intellectual, moral, and cultural dimensions of scientific research, the journal seeks to make meaningful contributions to academic scholarship.

Plagiarism and Originality Check Policy: The originality of the manuscript submitted is the responsibility of the publisher. Submission, plagiarism, and self-plagiarism must be avoided by writers. Manuscript submission in the CrossCheck server ( http:/www.ithenticate.com/ ) will be checked for plagiarism. iThenticate is a system that tests the originality of the submitted material and helps detect plagiarism. Authors can also use iThenticate to display their own credentials prior to submission. The similarity percentage must be less than 25% without bibliography.

Ethical Principles and Publication Policy: 

https://www.adbajournals.com/journals/iscms/privacy

The journal is an open-access journal , which is means that all content is freely available to users and their institutions. Users may read, download, copy, search, or provide links to the full text of papers in this journal without permission from the publisher or the authors and except for commercial purposes. They can also rearrange them, provided that the original work is properly cited.

Licensing Policy: CC BY-NC 4.0,

https://creativecommons.org/licenses/by-nc/4.0/ 

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.

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