Various materials incorporated into SiNW-based anodes for LIBs through doping or compositing and their electrochemical effects are discussed.

Softening of piezoelectric materials facilitates the development of flexible wearables and energy harvesting devices. However, as one of the most competitive candidates, piezoelectric ceramic-polymer composites inevitably exhibit reduced power-generation capability and weak mechanical strength due to the mismatch of strength and permittivity between the two phases inside. Herein a flexible, air-permeable, and high-performance piezoceramic textile composite with a mechanically reinforced hierarchical porous structure is introduced. Based on a template-assisted sol-gel method, a three-order hierarchical ceramic textile is constructed by intertwining submillimeter-scale multi-ply ceramic fibers that are further formed by twisting micrometer-scale one-ply ceramic fibrils. Theoretical analysis indicates that large mechanical stress can be easily induced in the multi-order hierarchical structure, which greatly benefits the electrical output. Fabricated samples generate an opencircuit voltage of 128 V, a short-circuit current of 120 µA, and an instantaneous power density of 0.75 mW cm −2 , much higher than the previously reported works. The developed multi-order and 3D-interconnected piezoceramic textile shows satisfactory piezoelectricity (d 33 of 190 pm V −1 ), air permeability (45.1 mm s −1 ), flexibility (Young's modulus of 0.35 GPa), and toughness (0.125 MJ m −3 ), collectively. The design strategy of obtaining balanced properties promotes the practicality of smart/functional materials in wearables and flexible electronics.

The human somatosensory system is capable of extracting features with millimeter-scale spatial resolution and submillisecond temporal precision. Current technologies that can render tactile stimuli with such high definition are neither portable nor easily accessible. Here, we present a wearable electrotactile rendering system that elicits tactile stimuli with both high spatial resolution (76 dots/cm 2 ) and rapid refresh rates (4 kHz), because of a previously unexplored current-steering super-resolution stimulation technique. For user safety, we present a high-frequency modulation method to reduce the stimulation voltage to as low as 13 V. The utility of our high spatiotemporal tactile rendering system is highlighted in applications such as braille display, virtual reality shopping, and digital virtual experiences. Furthermore, we integrate our setup with tactile sensors to transmit fine tactile features through thick gloves used by firefighters, allowing tiny objects to be localized based on tactile sensing alone.

Wearing masks has been a recommended protective measure due to the risks of coronavirus disease 2019 (COVID-19) even in its coming endemic phase. Therefore, deploying a "smart mask" to monitor human physiological signals is highly beneficial for personal and public health. This work presents a smart mask integrating an ultrathin nanocomposite sponge structure-based soundwave sensor (≈400 μm), which allows the high sensitivity in a wide-bandwidth dynamic pressure range, i.e., capable of detecting various respiratory sounds of breathing, speaking, and coughing. Thirty-one subjects test the smart mask in recording their respiratory activities. Machine/deep learning methods, i.e., support vector machine and convolutional neural networks, are used to recognize these activities, which show average macro-recalls of ≈95% in both individual and generalized models. With rich high-frequency (≈4000 Hz) information recorded, the two-/tri-phase coughs can be mapped while speaking words can be identified, demonstrating that the smart mask can be applicable as a daily wearable Internet of Things (IoT) device for respiratory disease identification, voice interaction tool, etc. in the future. This work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and processing, and machining/deep learning to demonstrate a wearable device for potential applications in continual health monitoring in daily life.

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