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International Journal of Computational Materials Science and Engineering - World Scientific | 2024 Impact Factor:1.2 | Cite Score:2.8 | Q3

International Journal of Computational Materials Science and Engineering With Cite Score

Cite Score and Journal Rank of International Journal of Computational Materials Science and Engineering

  • About: The International Journal of Computational Materials Science and Engineering (IJCMSE) is a peer-reviewed journal that focuses on computational approaches in materials science and engineering. Published by World Scientific Publishing, the journal covers research on computational models, simulations, and methods used to understand and predict the behavior of materials.
  • Objective:
    The primary objective of IJCMSE is to advance the field of materials science through computational techniques. The journal aims to disseminate high-quality research that explores the application of computational models and simulations to solve complex problems related to materials design, processing, and performance.
  • Interdisciplinary Approach:
    IJCMSE employs an interdisciplinary approach by integrating computational methods with materials science and engineering. This integration helps in the development of innovative solutions and deeper insights into the properties and behaviors of materials, bridging the gap between theoretical research and practical applications.
  • Impact and Significance:
    The journal significantly impacts the field by providing a platform for cutting-edge research that pushes the boundaries of materials science through computational techniques. IJCMSE contributes to the advancement of materials engineering by offering insights that lead to the development of new materials, improved performance, and enhanced understanding of material behavior.

  • Editor-in-Chief:  Teng Yong NG

  • Scope: The International Journal of Computational Materials Science and Engineering focuses on the application of computational methods and techniques in the study and engineering of materials. It aims to advance the understanding of material properties and behaviors through computational simulations and modeling.
  • Computational Material Modeling: Research on the development and application of computational models for predicting the properties and behavior of materials at various scales, from atomic to macroscopic.
  • Materials Design and Optimization: Studies on computational techniques for designing and optimizing materials with desired properties, including materials for specific applications in engineering and technology.
  • Multiscale Modeling: Exploration of approaches that integrate models at different scales, such as atomistic, mesoscopic, and continuum levels, to provide a comprehensive understanding of material behavior.
  • Machine Learning and Data-Driven Methods: Research on the application of machine learning and data-driven techniques to materials science, including predictive modeling, data analysis, and the discovery of new materials.
  • Computational Nanotechnology: Studies focused on the computational analysis of nanomaterials and nanostructures, including their synthesis, properties, and applications in various fields.
  • Computational Mechanics of Materials: Research on the application of computational mechanics to study the deformation, failure, and performance of materials under different loading conditions.
  • Simulation of Phase Transformations: Exploration of computational methods for simulating phase transformations in materials, such as solidification, crystallization, and phase changes under different conditions.
  • Quantum Mechanics and Density Functional Theory: Studies on the use of quantum mechanical approaches and density functional theory (DFT) to understand and predict material properties at the atomic level.
  • High-Performance Computing in Materials Science: Research on the use of high-performance computing (HPC) techniques and resources to perform large-scale simulations and analyses of materials.
  • Experimental and Computational Integration: Exploration of methods for integrating computational predictions with experimental data to validate models and improve material design and understanding.
  • Computational Thermodynamics and Kinetics: Studies on the application of computational methods to understand thermodynamic and kinetic processes in materials, including phase equilibria and reaction kinetics.
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  2047-6841

    Electronic ISSN:  2047-685X

  • Abstracting and Indexing:  Scopus

  • Imapct Factor 2024:  1.2

  • Subject Area and Category:  Computer Science, Computer Science Applications, Engineering, Mechanics of Materials, Materials Science, Materials Science (miscellaneous), Mathematics, Modeling and Simulation, Numerical Analysis

  • Publication Frequency:  

  • H Index:  16

  • Best Quartile:

    Q1:  

    Q2:  

    Q3:  Materials Science (miscellaneous)

    Q4:  

  • Cite Score:  2.8

  • SNIP:  0.357

  • Journal Rank(SJR):  0.231