Structural materials in Frontiers in Materials, 10 years on

The Structural Materials section of Frontiers in Materials has published almost 1000 articles during the past 10 years, and this article commemorates and assesses the development of thematic trends among this body of works. The three “grand challenges” identified upon launching the section in 2015 remain relevant: Bottom-up design of materials; Sustainable materials supply; Durable materials for extreme environments. Additional topics that have featured extensively in the journal include Natural materials; AI and machine learning; Materials characterisation and performance; Composites and manufacturing. It is anticipated that each of these topics will continue to contribute to the future of Structural Materials research, taking advantage of advances in computational capabilities and the ever-stronger impetus for sustainable selection and use of materials to drive future innovation in this discipline.

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Publication Details

Journal
Frontiers in Materials
Published
2026-01-07
DOI
https://doi.org/10.3389/fmats.2025.1713993
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

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Structural materials in Frontiers in Materials, 10 years on

John L. Provis
Frontiers in Materials
Machine Learning in Materials Science
article

Structural materials in Frontiers in Materials, 10 years on

John L. Provis
article en

Abstract

The Structural Materials section of Frontiers in Materials has published almost 1000 articles during the past 10 years, and this article commemorates and assesses the development of thematic trends among this body of works. The three “grand challenges” identified upon launching the section in 2015 remain relevant: Bottom-up design of materials; Sustainable materials supply; Durable materials for extreme environments. Additional topics that have featured extensively in the journal include Natural materials; AI and machine learning; Materials characterisation and performance; Composites and manufacturing. It is anticipated that each of these topics will continue to contribute to the future of Structural Materials research, taking advantage of advances in computational capabilities and the ever-stronger impetus for sustainable selection and use of materials to drive future innovation in this discipline.

Frontiers in MaterialsVol. 12
Paul Scherrer Institute (CH)
Paul Scherrer Institut
Industry, innovation and infrastructure
Openalex Percentile: Top 96%
Machine Learning in Materials Science
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