Composite Materials in the Data-Driven Era
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Advanced Composites".
Deadline for manuscript submissions: 20 December 2026 | Viewed by 20
Special Issue Editors
Interests: anti-microbial; photoluminescence; photo- and thermochromic properties; hybrid nanomaterials; nanomaterials synthesis and functionalization; textiles functionalization; smart and technical textiles; characterization techniques; X-ray shielding materials and textiles
2. LAETA—Associated Laboratory of Energy, Transports and Aerospace, 4200-265 Porto, Portugal
Interests: automation; control; thermal analysis; data-driven modelling; physics-informed neural networks; optimisation
Special Issue Information
Dear Colleagues,
The ongoing digital revolution is reshaping the landscape of material sciences, with composite materials becoming a focus of research and development. With the advent of advanced data-driven analysis and artificial intelligence, the potential for accelerated discovery, deeper understanding, and optimised performance of composite materials has never been greater. Integrating machine learning, big data analytics, and AI-driven modelling with new characterisation techniques is enabling researchers to uncover complex structure–property relationships and predict material behaviour with remarkable accuracy.
For this Special Issue, entitled "Composite Materials in the Data-Driven Era", we especially welcome contributions that bridge experimental and computational studies, demonstrate methodological rigour, and highlight the value of data-centric approaches to advancing composite materials. By fostering interdisciplinary collaboration, this Special Issue aims to define the state of the art and future directions for composite materials in the data-driven era.
This Special Issue seeks to present innovative research at the crossroads of materials science, data science, and advanced manufacturing. Its scope includes, but is not limited to, the following topics:
- Data-driven approaches and artificial intelligence for the characterisation and modelling of composite materials.
- Development and application of new characterisation techniques for composites, including high-throughput and in situ methods.
- Machine learning- and AI-enabled property prediction, digital twins, and process–structure–property optimisation.
- Material modelling for additive manufacturing, including the design and simulation of composite structures.
- Advanced additive manufacturing techniques for composite materials, with an emphasis on process monitoring and performance evaluation, quality control, and the reliability of the final product in various applications.
Dr. Tânia V. Pinto
Guest Editor
Dr. Jhonny Rodrigues
Guest Editor Assistant
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- composites
- manufacturing techniques
- mechanical properties
- thermal properties
- additive manufacturing
- automated manufacturing
- machine learning
- data-driven characterisation
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