Flexible skin-attachable strain-gauge sensors are an essential component in the development of artificial systems that can mimic the complex characteristics of the human skin. In general, such sensors contain a number of circuits or complex layered matrix arrays. Here, we present a simple architecture for a flexible and highly sensitive strain sensor that enables the detection of pressure, shear and torsion. The device is based on two interlocked arrays of high-aspect-ratio Pt-coated polymeric nanofibres that are supported on thin polydimethylsiloxane layers. When different sensing stimuli are applied, the degree of interconnection and the electrical resistance of the sensor changes in a reversible, directional manner with specific, discernible strain-gauge factors. The sensor response is highly repeatable and reproducible up to 10,000 cycles with excellent on/off switching behaviour. We show that the sensor can be used to monitor signals ranging from human heartbeats to the impact of a bouncing water droplet on a superhydrophobic surface.

By employing the neutral plane concept, we demonstrated ultra-flexible perovskite solar cells that can withstand 100 cycles of crumpling.

A reversible interlocker that is inspired by the wing locking device of beetles is presented. It exploits the van der Waals force-assisted binding between high-aspect-ratio polymer fibers. The two-layered interlocker is highly flexible and displays an extremely high shear locking force and easy normal lift-off.

Recently, a mechanical crack-based strain sensor with high sensitivity was proposed by producing free cracks via bending metal coated film with a known curvature. To further enhance sensitivity and controllability, a guided crack formation is needed. Herein, we demonstrate such a ultra-sensitive sensor based on the guided formation of straight mechanical cracks. The sensor has patterned holes on the surface of the device, which concentrate the stress near patterned holes leading to generate uniform cracks connecting the holes throughout the surface. We found that such a guided straight crack formation resulted in an exponential dependence of the resistance against the strain, overriding known linear or power law dependences. Consequently, the sensors are highly sensitive to pressure (with a sensitivity of over 1 × 105 at pressures of 8–9.5 kPa range) as well as strain (with a gauge factor of over 2 × 106 at strains of 0–10% range). A new theoretical model for the guided crack system has been suggested to be in a good agreement with experiments. Durability and reproducibility have been also confirmed.

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The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area.

Sensors to detect motion with high precision have been extensively studied in diverse engineering research fields.

functionalities could be mimicked by using and fine tuning (by spikes) the conductance of two-terminal memristive devices. [4,6,7] Therefore, a broad range of materials, for instance, metal oxides, organic/inorganic perovskites, 2D layered materials, etc., have been used to build memristive devices, which were further employed as artificial synapses. [8][9][10][11] Despite the achievements made so far, the immediate development in particular for metal-oxide-based artificial synapses faces several major problems: a great degree of variability (both from device to device and cycle to cycle) and trivial range of linearly programmable conductance states. [12] All these obstacles must be resolved to implement error-free neuromorphic functioning. These objectives could be achieved by either exploring new material architecture or improving the performance of existing ones with a detailed understanding of fundamental change dynamics.The realization of memristive properties in metal oxide hinges on the distribution of well-known intrinsic defects or ions, mainly oxygen vacancies (O V ). [10,11,13,14] Generally, under the influence of applied electric field, local oxygen vacancy density distribution changes and thus modifies the total (two-terminal) resistance of the device. [6,15,16] Therefore, to realize the reproducible (cycle-to-cycle) and stable (device-to-device) performance, it is essential to have a better control on the oxygen vacancy/ion distribution and its movement with applied field. As a matter of fact, researchers have made several attempts to confine the oxygen ion dynamics along the preferential sites. For instance, the insertion of metal nanodots or nanoparticles, and embedded nanotip electrodes have been found to be effective in improving the cycle-to-cycle uniformity. [17][18][19] However, large size and random distribution of metal nanoparticles generate hindrance to realize reproducible performance from device to device over a larger area. Indeed, the key challenges to design metal-oxidebased artificial synapse are to have reproducible and robust (against electric pulses) performance along with large number of linearly programmable states, which is yet to be achieved.As a promising strategy, the insertion of 2D layered materials into memristive device structure offers a new possibility to improve the performance. In this scenario, few attempts have been made; however, most of them used planar configurations, which occupy relatively large space and are difficult to stack in 3D Inspired by the human brain, the quest for high-performing neuromorphic architecture has recently gained more attention, which can be achieved by two-terminal memristors. However, due to random and uncontrolled filament formation during a typical switching process, conventional memristors suffer from severe shortcomings such as temporal/spatial reproducibility as well as trivial sensitivity against applied spikes, however all these properties are crucial for accurate and quick information processing. Here, reproducible and robust...