Mesh-channel-integrated transparent devices with hybrid conductive networks for enhanced electromechanical sensing
Source abstract
Abstract
Flexible and transparent strain sensors with high sensitivity were fabricated by embedding hybrid networks of carbon nanotubes (CNTs) and carbon (C) nanoparticles into micro-mesh polydimethylsiloxane (PDMS) substrates. The resulting devices exhibited optical transmittance above 70% and haze below 7%, ensuring unobtrusive integration on skin. Systematic variation of CNT:C ratios (0:1, 1:1, 2:1, 3:1) revealed that the 2:1 hybrid achieved optimal performance, combining uniform dispersion, strong interfacial adhesion, and robust conductive pathways. The optimized device (S2-PDMS) demonstrated a maximum gauge factor of 465.35 at 32.5% strain, and reliable cycling stability for repeatability of stretching, bending, and twisting deformations. Mechanical tests confirmed high tensile strength (2.63 MPa) and durability under repeated deformation, outperforming polyethylene terephthalate (PET)-based counterparts. The sensor also exhibited response times in the range of ∼158–557 ms and recovery times between ∼110–697 ms, depending on the type and complexity of the human motion. As such, the sensors successfully monitored diverse human motions, subtle muscle activity, and vocal vibrations, and enabled wireless data transmission via Bluetooth, underscoring their potential for real-time health monitoring, human–machine interfaces, and Internet of Things-enabled wearable electronics. • Transparent devices with micro-mesh conductive networks were fabricated using UV imprint lithography and coating. • These devices achieved outstanding sensitivity and reliability in monitoring complex electromechanical signals. • Wireless operation was achieved through integration with Bluetooth and Arduino, enabling smartphone control.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Advanced Materials and Mechanics · Conducting polymers and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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