Structural reconstruction of electrocatalysts plays a pivotal role in catalytic performances for CO2 reduction reaction (CO2RR), whereas the behavior is by far superficially understood. Here, we report that CO2 accessibility results in a universal self-adaptive structural reconstruction from Cu2O to Cu@CuxO composites, ending with feeding gas-dependent microstructures and catalytic performances. The

A method is proposed for the modulation of electrical pathways in the cracks of stretchable electrodes using liquid metals, based on which ultra-high sensitivity (> 108) and large-range (> 100%) strain sensors are realised. A secondary modulation of the response (or performance) of the sensor is proposed, allowing not only electrical modulation by liquid metal patterning during fabrication, but also

An alternative electromagnetic attenuation pathway is proposed in the MXene-polymer hybrid structure, distinct from conduction loss, for generalizing the results to a wider range of electromagnetic-thermal driven soft materials and devices. By efficiently harvesting and converting electromagnetic energy, the response time of the hybrid polymer to microwave exhibits 87% reduction with merely 0.15 wt%

The complex wiring, bulky data collection devices, and difficulty in fast and on-site data interpretation significantly limit the practical application of flexible strain sensors as wearable devices. To tackle these challenges, this work develops an artificial intelligence-assisted, wireless, flexible, and wearable mechanoluminescent strain sensor system (AIFWMLS) by integration of deep learning neural

Low-temperature fabrication of black-phase CsPbI3 perovskite films is first demonstrated by using diphenylphosphinic chloride additive under 30–50 °C, arising from the steric effect and chloride insertion engineering. Large-area high-quality all-inorganic perovskite films with fewer defects enhanced crystallographic orientation, and excellent environmental stability is fabricated. The record performances

Spike-based neural networks, which use spikes or action potentials to represent information, have gained a lot of attention because of their high energy efficiency and low power consumption. To fully leverage its advantages, converting the external analog signals to spikes is an essential prerequisite. Conventional approaches including analog-to-digital converters or ring oscillators, and sensors suffer