Guest Editor(s)
Prof. Micheal Arockiaraj
Email: marockiaraj@gmail.com
Affiliation: Department of Mathematics, Loyola College, Chennai ,India
Homepage:
Research Interests: graph labelling, embedding, mathematical chemistry, computational materials
Dr. Joseph Clement
Email: clementjmail@gmail.com
Affiliation: Department of Mathematics, School of Advanced Sciences,
VIT, Vellore , India
Homepage:
Research Interests: computational modelling, topological indices, entropy measures
Summary
Computational materials science and chemical graph theory, focusing on graph-based methodologies for the analysis of molecular and material systems. Research in this area involves the development of novel topological descriptors, information entropy measures, and computational algorithms for characterizing nanomaterials, porous frameworks, and advanced functional materials. Quantitative Structure–Activity Relationship (QSAR) and Quantitative Structure–Property Relationship (QSPR) modeling are employed to predict the physicochemical, electronic, and structural properties of molecular systems. By integrating graph analytics and computational intelligence, these methodologies enable intelligent materials characterization, predictive modeling, and data-driven analysis, contributing to advances in computational materials science and scientific computing.
The interdisciplinary nature of this expertise closely aligns with the scope of Computers, Materials & Continua, particularly in computational materials science, mathematical modeling, graph algorithms, and intelligent computational techniques. Research contributions in these areas encompass computational frameworks, predictive modeling, optimization methods, and data-driven approaches for material characterization. This background provides a solid foundation for evaluating manuscripts that integrate advanced computational methodologies with materials science, artificial intelligence, and scientific computing.
Scope:
This article collection welcomes contributions addressing, but not limited to, the following topics:
· Computational Materials Science and Materials Informatics
· Graph-Theoretical Modeling of Molecular and Materials Systems
· QSAR/QSPR Modeling and Molecular Property Prediction
· Graph Algorithms for Complex Networks and Materials Analysis
· Computational and algorithmic methods for network analysis
· Integration of graph-theoretical and combinatorial approaches in data-driven modelling
· Optimization of functional materials using graph models
· Materials modelling using graph-theoretical and discrete approaches
Keywords
materials informatics, graph analytics, mathematical modeling, topological descriptors, QSAR/QSPR modeling, computational algorithms, AI-driven molecular modeling.
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