ISSN: 3149-8957
Abbreviated Title: J. Artif. Intell. Mater. Sci.
Current Issue: Vol 5, Issue 1 (2026)
The Journal of Artificial Intelligence for Materials Science (JAIMS), ISSN: 3149-8957, is an international, peer-reviewed, open-access journal published by Institute for Advanced Materials Research Press. The journal focuses on research at the intersection of artificial intelligence, data science, computational methods, and materials science and engineering.
JAIMS provides an interdisciplinary platform for materials scientists, engineers, physicists, chemists, data scientists, computer scientists, experimental researchers, and industry professionals to publish research on the development, evaluation, implementation, and responsible use of intelligent computational methods in materials research.
The journal covers subjects including Materials Informatics, Data-Driven Materials Design, Computational Materials Science, Materials Modeling and Simulation, Predictive Modeling of Material Properties, High-Throughput Materials Screening, Digital Materials Engineering, Artificial Intelligence in Materials Science, Machine Learning for Materials Discovery, Materials Characterization and Analysis, AI-Assisted Materials Synthesis, Smart Materials, Nanomaterials, Advanced Functional Materials, and Sustainable Materials Development.
JAIMS publishes Original Research Articles, Review Articles, Systematic Reviews, Materials or Engineering Case Studies. Submissions must demonstrate a clear and substantial connection between artificial intelligence, machine learning, materials informatics, data-driven methods, or computational intelligence and a relevant materials-science or materials-engineering problem.
Research published in JAIMS may address materials discovery, design, synthesis, characterization, modeling, simulation, optimization, manufacturing, and performance prediction. The journal also welcomes studies concerning autonomous experimentation, high-throughput screening, intelligent laboratories, model interpretability, uncertainty quantification, data quality, scientific reproducibility, responsible artificial intelligence, and the experimental validation of computational predictions.
All manuscripts undergo an initial editorial assessment to determine their relevance to the journal’s aims and scope, academic quality, methodological clarity, and compliance with publication ethics. Manuscripts considered suitable proceed to internal assessment and external peer review by subject specialists. A minimum of two positive reviews is generally required for publication, and an additional reviewer may be consulted when reviewer recommendations conflict.
Editorial decisions are based on academic quality, originality, methodological soundness, scientific relevance, ethical compliance, clarity of reporting, and the significance of the manuscript’s contribution to artificial intelligence and materials science.
All accepted articles are published open access, making the journal’s content freely available online to readers worldwide in accordance with the journal’s copyright and licensing policies.
Publication Schedule
The Journal of Artificial Intelligence for Materials Science is published biannually, with two issues per year.
Editor-in-Chief
Professor Katsuhiko Ariga
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Journal metrics can be a useful tool for readers, as well as for authors who are deciding where to submit their next manuscript for publication. However, any one metric only tells a part of the story of a journal’s quality and impact. Each metric has its limitations which means that it should never be considered in isolation, and metrics should be used to support and not replace qualitative review.
We strongly recommend that you always use a number of metrics, alongside other qualitative factors such as a journal’s aims & scope, its readership, and a review of past content published in the journal. In addition, a single article should always be assessed on its own merits and never based on the metrics of the journal it was published in.
Speed data is updated every six months, based on the prior six months. Speed data is only available where a journal has made more than 10 decisions of that type in the time period. Speed metrics are averages; some manuscripts will take longer than this. Citation metrics are updated annually mid-year. Please note that some journals do not display all of the following metrics.
Content Access: the total number of times articles in the journal were viewed/downloaded by users of Institute for Advanced Materials Research Press.
Impact Factor: the average number of citations received by articles published in the journal within a two-year window. Only journals in the Clarivate Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), Arts and Humanities Citation Index (AHCI) and the Emerging Sources Citation Index (ESCI) have an Impact Factor.
Impact Factor Best Quartile: the journal’s highest subject category ranking in the Journal Citation Reports. Q1 = 25% of journals with the highest Impact Factors.
5 Year Impact Factor: the average number of citations received by articles in the journal within a five-year window.
CiteScore (Scopus)†: the average number of citations received by articles in the journal over a four-year period.
CiteScore Best Quartile†: the journal’s highest CiteScore ranking in a Scopus subject category. Q1 = 25% of journals with the highest CiteScores.
SNIP (Source Normalized Impact per Paper): the number of citations per paper in the journal, divided by citation potential in the field.
SJR (Scimago Journal Rank): Average number of (weighted) citations in one year, divided by the number of articles published in the journal in the previous three years.
From submission to first decision: the average (median) number of days for a manuscript submitted to the journal to receive a first decision. Based on manuscripts receiving a first decision in the last six months. This includes manuscripts which are not sent for peer review (desk rejections). Manuscripts which are sent out for review can therefore have a significantly longer wait than this metric indicates.
From submission to first post-review decision: the average (median) number of days for a manuscript submitted to the journal to receive a first decision if it is sent out for peer review. Based on manuscripts receiving a post-review first decision in the last six months.
From acceptance to online publication: the average (median) number of days from acceptance of a manuscript to online publication of the Version of Record. Based on articles published in the last six months.
Acceptance rate: articles accepted for publication by the journal in the previous calendar year as percentage of all papers receiving a final decision.
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