Effect of morphology, topology and structural configuration of piezoresistive glass textile sensors on its electromechanical performance for in situ damage detection in glass textile reinforced composites

Advanced sensing materials have been developed to address the demands for structural health monitoring (SHM) in composites. This work presents a systematic investigation of dual-topology piezoresistive glass textile sensors employing reduced graphene oxide (rGO) with chitosan as a biocompatible binding agent. The study uniquely compares surface-coating and matrix-impregnation fabrication methods, exploring the effects of nanoparticle concentration (0.2–3% rGO), sensor geometry and spatial positioning on electromechanical performance. Core contributions include the following: demonstration that rGO (1%) achieves gauge factors of upto 22, substantially exceeding conventional strain gauges and approaching fibre Bragg grating capabilities; titanium dioxide/rGO hybrid mechanism that amplifies strain sensitivity through controlled disruption of conductive pathways; identification of topology-specific performance characteristics enabling application-specific sensor customisation for aerospace, automotive and civil infrastructure domains; seamless in situ integration during composite manufacturing without requiring post-production attachment. The electromechanical response validates real-time strain sensing capability in glass fibre-reinforced composites, establishing an effective in situ damage detection platform with quantifiable performance advantages over conventional SHM methodologies.

Authors

Institutions

Publication Details

Journal
Structural Health Monitoring
Published
2026-01-08
DOI
https://doi.org/10.1177/14759217251408059
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effect of morphology, topology and structural configuration of piezoresistive glass textile sensors on its electromechanical performance for in situ damage detection in glass textile reinforced composites

Zunjarrao Kamble, Ghanshyam Neje, Sudhanshu Singh
Structural Health Monitoring
Advanced Sensor and Energy Harvesting Materials
article

Effect of morphology, topology and structural configuration of piezoresistive glass textile sensors on its electromechanical performance for in situ damage detection in glass textile reinforced composites

Zunjarrao Kamble, Ghanshyam Neje, Sudhanshu Singh
article en

Abstract

Advanced sensing materials have been developed to address the demands for structural health monitoring (SHM) in composites. This work presents a systematic investigation of dual-topology piezoresistive glass textile sensors employing reduced graphene oxide (rGO) with chitosan as a biocompatible binding agent. The study uniquely compares surface-coating and matrix-impregnation fabrication methods, exploring the effects of nanoparticle concentration (0.2–3% rGO), sensor geometry and spatial positioning on electromechanical performance. Core contributions include the following: demonstration that rGO (1%) achieves gauge factors of upto 22, substantially exceeding conventional strain gauges and approaching fibre Bragg grating capabilities; titanium dioxide/rGO hybrid mechanism that amplifies strain sensitivity through controlled disruption of conductive pathways; identification of topology-specific performance characteristics enabling application-specific sensor customisation for aerospace, automotive and civil infrastructure domains; seamless in situ integration during composite manufacturing without requiring post-production attachment. The electromechanical response validates real-time strain sensing capability in glass fibre-reinforced composites, establishing an effective in situ damage detection platform with quantifiable performance advantages over conventional SHM methodologies.

Structural Health Monitoring
Dr. B. R. Ambedkar National Institute of Technology Jalandhar (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 95%
Advanced Sensor and Energy Harvesting Materials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.