Recent advances in flexible and stretchable electronics have led to a surge of electronic skin (e-skin)–based health monitoring platforms. Conventional wireless e-skins rely on rigid integrated circuit chips that compromise the overall flexibility and consume considerable power. Chip-less wireless e-skins based on inductor-capacitor resonators are limited to mechanical sensors with low sensitivities. We report a chip-less wireless e-skin based on surface acoustic wave sensors made of freestanding ultrathin single-crystalline piezoelectric gallium nitride membranes. Surface acoustic wave–based e-skin offers highly sensitive, low-power, and long-term sensing of strain, ultraviolet light, and ion concentrations in sweat. We demonstrate weeklong monitoring of pulse. These results present routes to inexpensive and versatile low-power, high-sensitivity platforms for wireless health monitoring devices.

Remote epitaxy is a recently discovered type of epitaxy, wherein single-crystalline thin films can be grown on graphene-coated substrates following the crystallinity of the substrate via remote interaction through graphene. Although remote epitaxy provides a pathway to form freestanding membranes by controlled exfoliation of grown film at the graphene interface, implementing remote epitaxy is not straightforward because atomically precise control of interface is required. Here, we unveil the role of the graphene–substrate interface on the remote epitaxy of GaAs by investigating the interface at the atomic scale. By comparing remote epitaxy on wet-transferred and dry-transferred graphene, we show that interfacial oxide layer formed at the graphene–substrate interface hinders remote interaction through graphene when wet-transferred graphene is employed, which is confirmed by an increase of interatomic distance through graphene and also by the formation of polycrystalline films on graphene. On the other hand, when dry-transferred graphene is employed, the interface is free of native oxide, and single-crystalline remote epitaxial films are formed on graphene, with the interatomic distance between the epilayer and the substrate matching with the theoretically predicted value. The first atomic layer of the grown film on graphene is vertically aligned with the top layer of the substrate with these atoms having different polarities, substantiating the remote interaction of adatoms with the substrate through graphene. These results directly show the impact of interface properties formed by different graphene transfer methods on remote epitaxy.

Emerging energy-efficient neuromorphic circuits are based on hardware implementation of artificial neural networks (ANNs) that employ the biomimetic functions of memristors. Specifically, crossbar array memristive architectures are able to perform ANN vector-matrix multiplication more efficiently than conventional CMOS hardware. Memristors with specific characteristics, such as ohmic behavior in all resistance states in addition to symmetric and linear long-term potentiation/depression (LTP/LTD), are required in order to fully realize these benefits. Here, we demonstrate a Li-based composite memristor (LCM) that achieves these objectives. The LCM consists of three phases: Li-doped TiO 2 as a Li reservoir, Li 4 Ti 5 O 12 as the insulating phase, and Li 7 Ti 5 O 12 as the metallic phase, where resistive switching correlates with the change in the relative fraction of the metallic and insulating phases. The LCM exhibits a symmetric and gradual resistive switching behavior for both set and reset operations during a full bias sweep cycle. This symmetric and linear weight update is uniquely enabled by the symmetric bidirectional migration of Li ions, which leads to gradual changes in the relative fraction of the metallic phase in the film. The optimized LCM in ANN simulation showed that exceptionally high accuracy in image classification is realized in fewer training steps compared to the nonlinear behavior of conventional memristors.

Epitaxial lift-off techniques, which aim to separate ultrathin single-crystalline epitaxial layers off of the substrate, are becoming increasingly important due to the need of lightweight and flexible devices for heterogeneously integrated ultracompact semiconductor platforms and bioelectronics. Remote epitaxy is a relatively newly discovered epitaxial lift-off technique that allows substrate-seeded epitaxial growth of ultrathin films through few layers of graphene. This universal epitaxial lift-off technique allows freestanding single-crystal membrane fabrication very quickly at low cost. However, the conventional method of remote epitaxy requires transfer of graphene grown on another substrate to the target single-crystalline substrate, which results in organic and metallic residues as well as macroscopic defects such as cracks and wrinkles, significantly reducing the yield of remote epitaxy. Here, we show that direct growth of thick graphene on the target single-crystalline substrate (SrTiO3 for this study) followed by atomic layer etching (ALE) of the graphene layers create a defect- and residue-free graphene surface for high yield remote epitaxy. We find that the ALE efficiently removes one atomic layer of graphene per cycle, while also clearing multi-dots (clumps of carbon atoms) that form during nucleation of the graphene layers. Our results show that direct-grown graphene on the desired substrate accompanied by ALE might potentially be an ideal pathway toward commercialization of remote epitaxy.

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