Digital Transformation in Materials Science: Data-Driven Approaches to Metal Matrix Composites

A special issue of Data (ISSN 2306-5729).

Deadline for manuscript submissions: 31 October 2025 | Viewed by 91

Special Issue Editors


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Guest Editor
Department of Mathematics, University of Architecture, Civil Engineering and Geodesy (UACG), 1 Hr. Smirnenski Boulevard, 1046 Sofia, Bulgaria
Interests: differential equations and inclusions; optimal control; impulsive systems; non-smooth analysis; set-valued analysis

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Guest Editor
Institute of Metal Science, Equipment and Technologies With Hydroaerodynamics Centre, Bulgarian Academy of Sciences—67 “Shipchenski Prohod” Str., 1574 Sofia, Bulgaria
Interests: tribology; high-porosity metallic materials; metal matrix composites; machine learning modeling of tribological characteristics
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Special Issue Information

Dear Colleagues, 

This Special Issue, “Digital Transformation in Materials Science: Data-Driven Approaches to Metal Matrix Composites”, seeks to consolidate pioneering research that leverages digital technologies and data-centric methodologies to advance the understanding and optimization of metal matrix composites (MMCs) and other advanced materials. MMCs play a pivotal role in diverse industrial applications, from the aerospace to the automotive industry, owing to their superior mechanical properties and lightweight characteristics. However, the intricate microstructures and multifaceted properties of MMCs present significant challenges that necessitate the adoption of innovative digital strategies, including sophisticated data collection techniques, computational modeling, and machine learning algorithms.

We believe this Special Issue will resonate strongly with Data’s readership by promoting reproducibility and openness in MMC research, fostering collaboration between data scientists and materials researchers, and advancing the development of next-generation materials through data-driven innovations.

Prof. Dr. Tzanko Donchev
Dr. Mihail Kolev
Guest Editors

Manuscript Submission Information

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Keywords

  • digital transformation
  • materials science
  • metal matrix composites
  • data-driven approaches
  • computational modeling
  • machine learning in materials
  • advanced materials optimization
  • microstructure analysis
  • industrial applications of mmcs
  • aerospace and automotive materials

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Published Papers

This special issue is now open for submission.
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