Computational Materials Science

Aims & Scope

The aim of the journal is to publish papers that advance the field of computational materials science through the application of modern computational methods alone or in conjunction with experimental techniques to discover new materials and investigate existing inorganic materials, such as metals, ceramics, composites, semiconductors, nanostructures, 2D materials, metamaterials, and organic materials, such as polymers, liquid crystals, surfactants, emulsions, and also hybrid materials combining both inorganic and organic components such as polymer nanocomposites, nanocrystal superlattices or surfactant nanoparticle mixtures.

Papers that report on the development of new methods or the enhancement of existing approaches are of interest.

The scope of the journal includes: obtaining new or enhanced insights into material behavior, properties and phenomena, predicting structure-property relationships for new materials in conjunction with data informatics, novel capabilities of computational tools, technical software and shareware, or cyberinfrastructures.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3.3

SJR (SCImago Journal Rank)

Year	Value
2024	0.782

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	154

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Chemistry, Computer Science, Engineering, Materials Science, Mathematics and Physics and Astronomy, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set

  Citation: 66243

  Authors: G., J.

• A fast and robust algorithm for Bader decomposition of charge density

  Citation: 9236

  Authors: Graeme, Andri, Hannes

• Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis

  Citation: 3334

  Authors: Shyue Ping, William Davidson, Anubhav, Geoffroy, Michael, Shreyas, Dan, Vincent L., Kristin A., Gerbrand

• First-principles computation of material properties: the ABINIT software project

  Citation: 2822

  Authors: X., J.-M., R., F., M., G.-M., L., M., G., F., M., A., M., Ph., J.-Y., D.C.

• Computer graphics and graphical user interfaces as tools in simulations of matter at the atomic scale

  Citation: 1716

  Authors: Anton

• MOLCAS: a program package for computational chemistry

  Citation: 1678

  Authors: Gunnar, Roland, Per-Åke, Björn O, Ulf, Valera, Per-Olof, Maurizio, Bernd, Pavel, Luis

• Pseudopotentials periodic table: From H to Pu

  Citation: 1579

  Authors: Andrea

• Pseudopotentials for high-throughput DFT calculations

  Citation: 1383

  Authors: Kevin F., Joseph W., Karin M., David

• High-throughput electronic band structure calculations: Challenges and tools

  Citation: 1355

  Authors: Wahyu, Stefano

• Systematic analysis of local atomic structure combined with 3D computer graphics

  Citation: 1287

  Authors: Daniel, Hannes

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