Computational Materials Science Journal: Guide

What it is

Computational Materials Science (ISSN 0927-0256, e-ISSN 1879-0801) is an international peer-reviewed academic journal published by Elsevier. Established in 1992, the periodical serves as an archival publication venue for research advancing the computer-aided exploration, synthesis, characterization, and design of materials. Within modern materials science, computational approaches function alongside laboratory synthesis to predict crystalline structures, calculate thermodynamic equilibria, simulate phase transformations, and evaluate mechanical, electronic, optical, and magnetic properties.

The journal bridges theoretical condensed matter physics, physical chemistry, applied mathematics, and materials engineering. It publishes original research articles, letters, and focused review papers applying numerical algorithms to solve fundamental problems in materials behavior. Papers published in the journal emphasize new computational methodologies, physical insights into complex microstructures, or predictive models accelerating structural and functional materials development.

Who runs it and what it covers

Computational Materials Science is published by Elsevier B.V. and led by Editor-in-Chief Susan B. Sinnott (The Pennsylvania State University, USA), supported by an international board of associate editors. Submissions undergo single-blind peer review managed through Elsevier’s Editorial Manager platform, evaluated on scientific rigor, methodological clarity, and physical significance.

The journal is indexed in the Science Citation Index Expanded (SCIE) within Clarivate’s Web of Science Core Collection, Scopus, Inspec, Compendex, and Chemical Abstracts Service (CAS). It holds a Clarivate Journal Citation Reports Impact Factor of 3.7 and a Scopus CiteScore of 6.3.

The journal’s editorial scope encompasses multiscale modeling across spatial and temporal dimensions:

• Electronic and quantum scales: Density Functional Theory (DFT), post-Hartree-Fock methods, tight-binding models, electronic band structures, and quantum Monte Carlo simulations of solids and interfaces.
• Atomistic and molecular scales: Classical molecular dynamics (MD), empirical interatomic potentials, ab initio molecular dynamics, reactive force fields, and Monte Carlo sampling for defects and thermal transport.
• Mesoscale and microstructural scales: Phase-field modeling, dislocation dynamics, cellular automata, and Potts models analyzing microstructure evolution, solidification, and domain switching.
• Continuum and macro scales: Crystal plasticity finite element modeling (CPFEM), computational mechanics, homogenization, and CALPHAD thermodynamic assessments.
• Materials informatics and machine learning: High-throughput computational screening, artificial intelligence surrogate models, neural network potentials, and data-driven property prediction.

The journal covers metals, alloys, functional ceramics, semiconductors, 2D nanomaterials, metamaterials, battery electrodes, and hybrid composites. The editorial board enforces clear scope boundaries: routine parameter adjustments without fundamental physical insights, standard commercial software simulations lacking validation, and empirical studies on concrete or unreinforced polymers are outside the journal’s mission and face desk rejection.

How to search or use it

Researchers, authors, and librarians interact with Computational Materials Science through ScienceDirect and the Editorial Manager submission portal:

1. Locate the journal portal and access sign-in: Navigate to the Computational Materials Science homepage on ScienceDirect. The sign-in link is located in the top navigation header under “Sign in” or “Institutional access” via Shibboleth or OpenAthens.
2. Execute targeted methodology searches: Use the ScienceDirect search box or “Advanced search” interface to combine material systems with specific computational frameworks, such as entering "density functional theory" AND "high-entropy alloys" in the keyword field.
3. Filter by article type and open access status: On search result pages, utilize left-hand sidebar filters to isolate “Review articles”, “Research articles”, or “Open access” papers, sorting by relevance or publication date.
4. Browse special issues and topical collections: Select the “Special issues and article collections” tab to review curated collections on focused topics, such as machine learning for materials discovery or phase-field modeling.
5. Establish automated citation and content alerts: Click “Set up journal alerts” on the overview page to configure automated email notifications or RSS feeds for newly released volumes, pre-proof articles, and accepted manuscripts.
6. Review the official Guide for Authors: Prior to submission, access the “Guide for Authors” from the publisher menu to verify manuscript formatting, word counts, mandatory graphical abstract dimensions, and highlight bullet point standards.
7. Submit manuscript via Editorial Manager: Click “Submit your article” to enter the Editorial Manager platform (commat portal). Authors sign in using their Elsevier profile or ORCID, select the article type, provide suggested reviewers, and upload manuscript files.
8. Register data and code transparency statements: During submission, authors complete the Research Data section, stating whether underlying simulation inputs, atomic geometries, or analysis scripts are archived in public repositories to reinforce research transparency and open science principles.

Strengths and limits

Evaluating Computational Materials Science requires balancing editorial visibility against publication costs and scope constraints.

Strengths:

• Archival reputation: Operating continuously since 1992, the journal possesses a vast backfile of materials modeling literature and stable indexing across SCIE and Scopus.
• Multiscale breadth: Unlike venues restricted to chemical physics or mechanical continuum modeling, the journal accepts manuscripts spanning sub-nanometer electron density to macroscale deformation.
• Hybrid publication flexibility: Authors can publish under the traditional subscription model with zero author-facing fees, or choose Gold Open Access supported by institutional agreements or dedicated open access publishing funds.
• Article-based publishing speed: Accepted articles receive a digital object identifier (DOI) and appear online in final citable form with volume and pagination quickly after proof review.

Limits:

• Subscription paywall: Articles published under the subscription track remain behind an institutional paywall, restricting access for non-affiliated researchers.
• Single-blind review format: Reviewers know author identities and institutional affiliations, lacking the double-blind protections against implicit bias available in certain society journals.
• Rigorous desk screening: Manuscripts applying standard algorithms to routine composition variations without providing physical insight or methodological advancement are screened out prior to external peer review.
• Exclusion of civil engineering media: Standard empirical testing of concrete mixtures, bituminous binders, or unreinforced civil engineering materials is explicitly excluded unless presenting computational modeling breakthroughs.

Alternatives

Authors selecting a submission venue or literature source in computational materials science can compare Computational Materials Science against prominent alternative journals:

Journal Title	Publisher	Publishing Model	Core Methodological Focus	Impact Factor / CiteScore	Data and Code Policy
Computational Materials Science	Elsevier	Hybrid (Subscription / Gold OA)	Multiscale modeling (DFT, MD, phase-field, continuum, AI)	IF 3.7 / CiteScore 6.3	Mandatory Data Availability Statement; repository deposit supported
npj Computational Materials	Springer Nature	Gold Open Access (APC required)	High-impact computational discovery, materials informatics, autonomous design	IF 9.4 / CiteScore 18.2	Open data and code sharing strongly encouraged; FAIR compliance
Modelling and Simulation in Materials Science and Engineering (MSMSE)	IOP Publishing	Hybrid (Subscription / Gold OA)	Mechanics, microstructure, atomistic-to-continuum physical modeling	IF 2.1 / CiteScore 4.0	Mandatory data statement; IOP open science policy
Journal of Chemical Theory and Computation (JCTC)	ACS Publications	Hybrid (Subscription / Gold OA)	Quantum mechanics, chemical force fields, biomolecular simulation	IF 5.5 / CiteScore 9.5	Strict computational method reproducibility and benchmark requirements
Physical Review Materials	American Physical Society (APS)	Hybrid (Subscription / Gold OA)	Fundamental materials physics, electronic structure, ab initio theory	IF 3.1 / CiteScore 5.2	Encourages public repository deposition of raw data and scripts

Manuscripts declined by Computational Materials Science may be offered cascading peer review transfer to sister journals such as Materials Today Communications. When managing computational outputs, researchers frequently archive raw simulation trajectories and structural files in specialized disciplinary repositories such as NOMAD and Materials Data Facility to satisfy FAIR data principles.

FAQ

Is Computational Materials Science a peer-reviewed journal?

Yes. Computational Materials Science is a fully peer-reviewed academic journal. Submissions are screened by the Editor-in-Chief or associate editors and evaluated by independent external subject-matter experts using a single-blind review workflow.

Does Computational Materials Science require an author publication fee?

No fee is required for subscription publication. Authors can publish their accepted work under the traditional subscription model at no cost. Authors who select Gold Open Access pay an Article Publishing Charge (APC) or cover the charge through institutional transformative agreements.

What computational methods are acceptable for publication?

The journal accepts studies employing density functional theory, molecular dynamics, Monte Carlo techniques, phase-field simulations, crystal plasticity, finite element analysis, CALPHAD calculations, and materials informatics or machine learning models, provided they contribute physical understanding or methodological advancement.

Are purely experimental manuscripts accepted?

No. Manuscripts submitted to Computational Materials Science must center on computational or theoretical modeling. Experimental results are welcome when used to calibrate, validate, or substantiate computational predictions, but purely experimental characterization studies are out of scope.

Where should authors deposit simulation data and codes?

Elsevier encourages authors to deposit simulation input files, coordinates, interatomic potential parameterizations, and analysis scripts in trusted data repositories such as NOMAD, Materials Project, Zenodo, or Mendeley Data, referencing the dataset via a formal DOI in the manuscript Data Availability Statement.

Sources

• Elsevier B.V. — Computational Materials Science: Aims and Scope, Journal Overview. URL: https://www.sciencedirect.com/journal/computational-materials-science (Read November 11, 2026).
• Elsevier B.V. — Guide for Authors: Computational Materials Science. URL: https://www.elsevier.com/journals/computational-materials-science/0927-0256/guide-for-authors (Read November 11, 2026).
• Clarivate Analytics — Web of Science Master Journal List: Computational Materials Science (ISSN 0927-0256). URL: https://mjl.clarivate.com/ (Read November 11, 2026).
• Scopus / Elsevier — Source Details: Computational Materials Science. URL: https://www.scopus.com/sourceid/28773 (Read November 11, 2026).