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Self‐Repairable Hybrid Piezoresistive‐Triboelectric Sensor Cum Nanogenerator Utilizing Dual‐Dynamic Reversible Network in Mechanically Robust Modified Natural Rubber
- Source :
- Advanced Sensor Research, Vol 3, Iss 10, Pp n/a-n/a (2024)
- Publication Year :
- 2024
- Publisher :
- Wiley-VCH, 2024.
-
Abstract
- Abstract The greener alternatives to tactile‐integrated multimodal sensors with self‐powered and self‐healing abilities are highly desirable for all‐in‐one autonomous sensing systems, particularly impressive in diverse application ranges including smart home, healthcare, and e‐skin. The dynamically self‐healable, stretchable piezoresistive sensors, and triboelectric nanogenerators (TENGs) reported herein are constructed by a facile, industrially viable method of grafting imidazolium ions on epoxidized natural rubber (ENR) backbone. Owing to cation‐π and π–π interaction between the percolated carbon nanotubes (CNTs)‐network and the imidazolium ions formed by non‐covalent interactions, the interfacial adhesion between the filler and elastomer is shown to improve considerably. The sensors show high piezoresistive strain sensitivity, reversible ionic network‐assisted self‐healability (efficiency ≈80%) and wide‐ranging detectability for precise monitoring of human movements. Both the healed and pristine sensors feature low hysteresis and stable electrical outputs over a wide strain range (≤200%). While achieving rapid self‐healing efficiency, the substrates are shown to exhibit remarkable robustness for harsh climates owing to significant mechanical toughness. Supported by excellent triboelectric tactile sensitivity (2.12 V N−1), the multifunctional TENG‐enabled sensor yields superior power density (0.16 mW cm−2). Moreover, the TENG module exhibits high force sensitivity and ease of operation that are considered versatile for all‐weather integrated tactile solutions for future technology.
Details
- Language :
- English
- ISSN :
- 27511219
- Volume :
- 3
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Advanced Sensor Research
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.587f1bde80482781762e40c495bae1
- Document Type :
- article
- Full Text :
- https://doi.org/10.1002/adsr.202400036