High-Throughput Manufacturing of Multimodal Epidermal Mechanosensors with Superior Detectability Enabled by a Continuous Microcracking Strategy.

Non-invasive human-machine interactions (HMIs) are expected to be promoted by epidermal tactile receptive devices that can accurately perceive human activities. In reality, however, the HMI efficiency is limited by the unsatisfactory perception capability of mechanosensors and the complicated techniques for device fabrication and integration. Herein, a paradigm is presented for high-throughput fabrication of multimodal epidermal mechanosensors based on a sequential "femtosecond laser patterning-elastomer infiltration-physical transfer" process. The resilient mechanosensor features a unique hybrid sensing layer of rigid cellular graphitic flakes (CGF)-soft elastomer. The continuous microcracking of CGF under strain enables a sharp reduction in conductive pathways, while the soft elastomer within the framework sustains mechanical robustness of the structure. As a result, the mechanosensor achieves an ultrahigh sensitivity in a broad strain range (GF of 371.4 in the first linear range of 0-50%, and maximum GF of 8922.6 in the range of 61-70%), a low detection limit (0.01%), and a fast response/recovery behavior (2.6/2.1 ms). The device also exhibits excellent sensing performances to multimodal mechanical stimuli, enabling high-fidelity monitoring of full-range human motions. As proof-of-concept demonstrations, multi-pixel mechanosensor arrays are constructed and implemented in a robot hand controlling system and a security system, providing a platform toward efficient HMIs.

Solution-Processed Sensing Textiles with Adjustable Sensitivity and Linear Detection Range Enabled by Twisting Structure.

Wearable strain sensors are emerging rapidly for their promising applications in human motion detection for diagnosis, healthcare, training instruction, and rehabilitation exercise assessment. However, it remains a bottleneck in gaining comfortable and breathable devices with the features of high sensitivity, linear response, and tunable detection range. Textiles possess fascinating advantages of good breathability, aesthetic property, tailorability, and excellent mechanical compliance to conformably attach to human body. As the meandering loops in a textile can be extended in different directions, it provides plenty of room for exploring ideal sensors by tuning a twisting structure with rationally selected yarn materials. Herein, textile sensors with twisting architecture are designed via a solution-based process by using a stable water-based conductive ink that is composed of polypyrrole/polyvinyl alcohol nanoparticles with a mean diameter of 50 nm. Depending on the predesigned twisting models, the thus-fabricated textile sensors show adjustable performances, exhibiting a high sensitivity of 38.9 with good linearity and a broad detection range of 200%. Such sensors can be integrated into fabrics and conformably attached to skin for monitoring subtle (facial expressions, breathing, and speaking) and large (stretching, jumping, running and jogging, and sign language) human motions. As a proof-of-concept application, by integrating with a wireless transmitter, the signals detected by our sensors during exercise (e.g., running) can be remotely received and displayed on a smartphone. It is believed that the integration of our textile sensors with selected twisting models into a cloth promises full-range motion detection for wearable electronics and human-machine interfaces.

Ultrasensitive Anti-Interference Voice Recognition by Bio-Inspired Skin-Attachable Self-Cleaning Acoustic Sensors.

Human voice recognition systems (VRSs) are a prerequisite for voice-controlled human-machine interfaces (HMIs). In order to avoid interference from unexpected background noises, skin-attachable VRSs are proposed to directly detect physiological mechanoacoustic signals based on the vibrations of vocal cords. However, the sensitivity and response time of existing VRSs are bottlenecks for efficient HMIs. In addition, water-based contaminants in our daily lives, such as skin moisture and raindrops, normally result in performance degradation or even functional failure of VRSs. Herein, we present a skin-attachable self-cleaning ultrasensitive and ultrafast acoustic sensor based on a reduced graphene oxide/polydimethylsiloxane composite film with bioinspired microcracks and hierarchical surface textures. Benefitting from the synergetic effect of the spider-slit-organ-like multiscale jagged microcracks and the lotus-leaf-like hierarchical structures, our superhydrophobic VRS exhibits an ultrahigh sensitivity (gauge factor, GF = 8699), an ultralow detection limit (ε = 0.000 064%), an ultrafast response/recovery behavior, an excellent device durability (>10 000 cycles), and reliable detection of acoustic vibrations over the audible frequency range (20-20 000 Hz) with high signal-to-noise ratios. These superb performances endow our skin-attachable VRS with anti-interference perception of human voices with high precision even in noisy environments, which will expedite the voice-controlled HMIs.