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Sensitive and flexible pressure sensors have invoked considerable interest for a broad range of applications in tactile sensing, physiological sensing, and flexible electronics. The barrier between high sensitivity and low fabrication cost needs to be addressed to commercialize such flexible pressure sensors. A low-cost sacrificial template-assisted method for the capacitive sensor has been reported herein, utilizing a porous Polydimethylsiloxane (PDMS) polymer and a multiwalled carbon nanotube (MWCNT) composite-based dielectric layer. The sensor shows high sensitivity of 2.42 kPa−1 along with a low limit of detection of 1.46 Pa. The high sensitivity originates from adding MWCNT to PDMS, increasing the composite polymer’s dielectric constant. Besides this, the pressure sensor shows excellent stability at a cyclic loading of 9000 cycles, proving its reliability for long-lasting application in tactile and physiological sensing. The high sensitivity of the sensor is suitable for the detection of small deformations such as pulse waveforms as well as tactile pressure sensing. In addition, the paper demonstrates a simultaneous contact and non-contact sensing capability suitable for dual sensing (pressure and proximity) with a single data readout system. The dual-mode sensing capability may open opportunities for realizing compact systems in robotics, gesture control, contactless applications, and many more. The practicality of the sensor was shown in applications such as tactile sensing, Morse code generator, proximity sensing, and pulse wave sensing.
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Deep-learning-assisted printed liquid metal sensory system for wearable applications and boxing training
Abstract Liquid metal (LM) exhibits a distinct combination of high electrical conductivity comparable to that of metals and exceptional deformability derived from its liquid state, thus it is considered a promising material for high-performance soft electronics. However, rapid patterning LM to achieve a sensory system with high sensitivity remains a challenge, mainly attributed to the poor rheological property and wettability. Here, we report a rheological modification strategy of LM and strain redistribution mechanics to simultaneously simplify the scalable manufacturing process and significantly enhance the sensitivity of LM sensors. By incorporating SiO2particles into LM, the modulus, yield stress, and viscosity of the LM-SiO2composite are drastically enhanced, enabling 3D printability on soft materials for stretchable electronics. The sensors based on printed LM-SiO2composite show excellent mechanical flexibility, robustness, strain, and pressure sensing performances. Such sensors are integrated onto different locations of the human body for wearable applications. Furthermore, by integrating onto a tactile glove, the synergistic effect of strain and pressure sensing can decode the clenching posture and hitting strength in boxing training. When assisted by a deep-learning algorithm, this tactile glove can achieve recognition of the technical execution of boxing punches, such as jab, swing, uppercut, and combination punches, with 90.5% accuracy. This integrated multifunctional sensory system can find wide applications in smart sport-training, intelligent soft robotics, and human-machine interfaces.
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- Award ID(s):
- 1762324
- PAR ID:
- 10439613
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- npj Flexible Electronics
- Volume:
- 7
- Issue:
- 1
- ISSN:
- 2397-4621
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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