RESUMO
Touch is a general term to describe mechanical stimuli. It is extremely difficult to develop touch sensors that can detect different modes of contact forces due to their low sensitivity and data decoupling. Simultaneously conducting tactile and slip sensing presents significant challenges for the design, structure, and performance of sensors. In this work, a highly sensitive sandwich-structured sensor is achieved by exploiting the porosity and compressive modulus of the sensor's functional layer materials. The sensor shows an ultra-high sensitivity of 1167 kPa-1 and a low-pressure detection limit of 1.34 Pa due to its considerably low compression modulus of 23.8 Pa. Due to this ultra-high sensitivity, coupled with spectral analysis, it allows for dual-mode detection of both tactile and slip sensations simultaneously. This novel fabrication strategy and signal analysis method provides a new direction for the development of tactile/slip sensors.
RESUMO
An all-fibrous large-area (20 × 50 cm2 ) tailorable triboelectric nanogenerator (LT-TENG) is prepared using a one-step solution blow spinning technology, which has the advantages of easy operation, scale-up in the area, and high production efficiency. The prepared LT-TENG is composed of polyvinylidene fluoride (PVDF)/MXene (Ti3 C2 Tx ) nanofibers (NFs) and conductive textile. Benefiting from the fibrous materials and large-area properties, the LT-TENG possesses the merits of good tailorability, breathability, hydrophobicity, and washability. When optimized by mixing the MXene into PVDF NFs, the LT-TENG has a preferable output and sensing property, with a detection range over 16 kPa and a relatively high sensitivity of 12.33 V KPa-1 . At maximum applied pressure, the voltage, current, and charge are 108 V, 38 µA, and 35 nC, respectively. This LT-TENG can serve as a biomechanical energy harvester when used as wearable devices with an output power density of 12.6 mW m-2 at an external load resistance of 500 MΩ, and it also has the ability of self-powered tactile sensing for pressure mapping and slide sensing. Thus, this LT-TENG exhibits great potential prospects in wearable devices, intelligent robots, and human-machine interaction.
