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Low efficiency in recovering low-grade heat remains unresolved despite decades of attempts. In this research, we designed and fabricated a novel thermo-osmotic ionogel (TOI) composite to recover low-grade heat to generate electric power through a thermo-induced ion gradient and selective ion diffusion. The TOI composite was assembled with a crystalline ionogel (polymer-confined LiNO 3 –3H 2 O) film, ion selective membrane, and hydrogel film. With a 90 °C heat supply, the single TOI composite produced a high open-circuit voltage of 0.52 V, a differential thermal voltage of ∼26 mV K −1 , a peak power density of 0.4 W m −2 , and a ground-breaking peak energy conversion efficiency of 11.17%. Eight pieces of such a TOI composite were connected in series, demonstrating an open-circuit voltage of 3.25 volts. Such a TOI system was also demonstrated to harvest body temperature for powering a LED, opening numerous opportunities in powering wearable devices. 

Lip‐reading provides an effective speech communication interface for people with voice disorders and for intuitive human–machine interactions. Existing systems are generally challenged by bulkiness, obtrusiveness, and poor robustness against environmental interferences. The lack of a truly natural and unobtrusive system for converting lip movements to speech precludes the continuous use and wide‐scale deployment of such devices. Here, the design of a hardware–software architecture to capture, analyze, and interpret lip movements associated with either normal or silent speech is presented. The system can recognize different and similar visemes. It is robust in a noisy or dark environment. Self‐adhesive, skin‐conformable, and semi‐transparent dry electrodes are developed to track high‐fidelity speech‐relevant electromyogram signals without impeding daily activities. The resulting skin‐like sensors can form seamless contact with the curvilinear and dynamic surfaces of the skin, which is crucial for a high signal‐to‐noise ratio and minimal interference. Machine learning algorithms are employed to decode electromyogram signals and convert them to spoken words. Finally, the applications of the developed lip‐reading system in augmented reality and medical service are demonstrated, which illustrate the great potential in immersive interaction and healthcare applications.