NiO/SWCNT-Based Spiral Yarn Sensor with Strain Compensation for Reliable Temperature Detection in Dynamic Environments

Textile-based temperature sensors often suffer from signal distortion due to strain interference in practical applications, severely limiting their reliability in dynamic environments. To address this challenge, this study developed a strain-insensitive resistive temperature-sensing yarn with a helical structure, named CNAS. The yarn utilizes aramid fiber as the substrate. After modification with polydopamine (PDA), single-walled carbon nanotubes (SWCNTs) were loaded onto the substrate through five cycles of dipping and drying. Subsequently, a uniform nickel oxide (NiO) sensitive layer was constructed on its surface via electrodeposition followed by thermal decomposition. The sensitive yarn (CNA) was then helically wrapped onto a prestretched Spandex core yarn to form the CNAS composite yarn. Experimental results demonstrate that CNAS exhibits a resistance variation below 4% within a strain range of 0–93% and maintains stable performance after 500 stretching cycles. It displays a significant negative temperature coefficient (NTC) behavior within a temperature range of −20 to 70 °C, with its sensitivity markedly superior to that of pure carbon nanotube (CNT) or graphene (GR) yarns. Human wear trials further confirmed that the yarn can effectively distinguish temperature changes from strain interference induced by joint movements. An alarm system built using CNAS enables reliable visual alerts for ambient temperature changes. This research provides an innovative and practical solution for anti-interference wearable temperature sensors.

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Publication Details

Journal
ACS Applied Electronic Materials
Published
2026-02-03
DOI
https://doi.org/10.1021/acsaelm.5c02546
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
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article

NiO/SWCNT-Based Spiral Yarn Sensor with Strain Compensation for Reliable Temperature Detection in Dynamic Environments

Yingcun Liu, Yawen Wei, Jian Fang, Zhe Sun et al.
ACS Applied Electronic Materials
Advanced Sensor and Energy Harvesting Materials
article

NiO/SWCNT-Based Spiral Yarn Sensor with Strain Compensation for Reliable Temperature Detection in Dynamic Environments

Yingcun Liu, Yawen Wei, Jian Fang, Zhe Sun, Zhe Li, Li Niu
article en

Abstract

Textile-based temperature sensors often suffer from signal distortion due to strain interference in practical applications, severely limiting their reliability in dynamic environments. To address this challenge, this study developed a strain-insensitive resistive temperature-sensing yarn with a helical structure, named CNAS. The yarn utilizes aramid fiber as the substrate. After modification with polydopamine (PDA), single-walled carbon nanotubes (SWCNTs) were loaded onto the substrate through five cycles of dipping and drying. Subsequently, a uniform nickel oxide (NiO) sensitive layer was constructed on its surface via electrodeposition followed by thermal decomposition. The sensitive yarn (CNA) was then helically wrapped onto a prestretched Spandex core yarn to form the CNAS composite yarn. Experimental results demonstrate that CNAS exhibits a resistance variation below 4% within a strain range of 0–93% and maintains stable performance after 500 stretching cycles. It displays a significant negative temperature coefficient (NTC) behavior within a temperature range of −20 to 70 °C, with its sensitivity markedly superior to that of pure carbon nanotube (CNT) or graphene (GR) yarns. Human wear trials further confirmed that the yarn can effectively distinguish temperature changes from strain interference induced by joint movements. An alarm system built using CNAS enables reliable visual alerts for ambient temperature changes. This research provides an innovative and practical solution for anti-interference wearable temperature sensors.

ACS Applied Electronic MaterialsVol. 8(4)
Bangladesh University of Textiles (BD)
Openalex Percentile: Top 69%
Advanced Sensor and Energy Harvesting Materials
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