Data-Driven Smart Materials: From Green/Conductive Composites to Intelligent Durability Monitoring
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Smart Materials".
Deadline for manuscript submissions: 20 September 2026
Special Issue Editor
Interests: green/smart construction materials; rebar corrosion; maintenance; structural health monitoring; durability; bayesian inference; artificial neural networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid advancement of data-driven technologies is fundamentally transforming the field of construction materials science. This evolution is marked by a shift towards intelligent material systems, from novel green and conductive composites to integrated platforms for intelligent durability monitoring. Contemporary research in this domain focuses explicitly on analyzing and optimizing the performance, properties, and characteristics of these smart materials—such as self-sensing concrete, multifunctional composites, and eco-friendly formulations—to enhance their structural integrity, environmental footprint, and long-term resilience.
By leveraging machine learning, artificial neural networks, and data analytics, researchers are able to examine material behavior and durability under varied conditions with unprecedented precision. This data-driven approach enables the identification of potential weaknesses and facilitates the development of novel solutions that meet heightened performance and sustainability requirements. Ultimately, this contributes to a new paradigm of intelligent infrastructure management.
With this Special Issue, we aim to collate excellent technical articles. We actively welcome your submissions on topics including, but not limited to, the following:
- Data-driven design and characterization of smart construction materials;
- Green and conductive composite materials;
- Machine learning and AI for material performance prediction;
- Intelligent structural health and corrosion monitoring;
- Smart sensors and data analytics for durability assessment.
Dr. Byeong Hun Woo
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.
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
- data-driven smart materials
- self-sensing cement composites
- thermal properties of cement composites
- smart snow-melting systems
- rebar corrosion monitoring
- durability analysis
- machine learning
- advanced statistical approaches
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