Autonomous Sensing Architected Materials (Adv. Funct. Mater. 11/2025)
Autonomous Sensing Materials In article number 2411975, Shanmugam Kumar, Mattia Utzeri, and Hülya Cebeci introduce a novel framework combining theory, experiments, and finite element modeling to develop multiscale, multiphysics models for additive manufacturing-enabled piezoresistive lattice composites. By incorporating stress-dependent electrical resistivity and accounting for material, geometric, and contact nonlinearities, the model accurately predicts architecture-dependent responses, validated through infrared thermography. A closed-form gauge factor expression optimizes piezoresistive performance, while an Ashby chart analysis reveals a scaling law, opening doors to smart orthopaedics, structural health monitoring, and more.
Authors
- S. Kumar (ORCID: https://orcid.org/0000-0002-3386-8012)
- Hülya Cebeci (ORCID: https://orcid.org/0000-0002-0264-6484)
- Mattia Utzeri (ORCID: https://orcid.org/0000-0003-1394-9875)
Institutions
- Marche Polytechnic University (IT)
- Istanbul Technical University (TR)
- University of Glasgow (GB)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1002/adfm.202570062
- Citations
- 1
- Primary Topic
- Smart Materials for Construction
- Type
- article
- Field-Weighted Citation Impact
- 0.50