A neuromorphic visual system integrating optoelectronic synapses to perform the in-sensor computing is triggering a revolution due to the reduction of latency and energy consumption. Here it is demonstrated that the dwell time of photon-generated carriers in the space-charge region can be effectively extended by embedding a potential well on the shoulder of Schottky energy barrier. It permits the nonlinear interaction of photocurrents stimulated by spatiotemporal optical signals, which is necessary for in-sensor reservoir computing (RC). The machine vision with the sensor reservoir constituted by designed self-powered Au/P(VDF-TrFE)/Cs 2 AgBiBr 6 /ITO devices is competent for both static and dynamic vision tasks. It shows an accuracy of 99.97% for face classification and 100% for dynamic vehicle flow recognition. The in-sensor RC system takes advantage of near-zero energy consumption in the reservoir, resulting in decades-time lower training costs than a conventional neural network. This work paves the way for ultralow-power machine vision using photonic devices.

Halide perovskites (HPs) are promising materials for preparing nonvolatile memory and artificial synapse devices. However, the instability and toxicity of lead HPs seriously restrict their further application. Herein, a lead-free...

A protective PbBrOH matrix grows rapidly on the surface of perovskites, leading to composites with high-stability fluorescence triggered by imidazole derivatives.

Artificial synapse of neuromorphic computing has been attracting significant attention as an alternative concept for next‐generation computing. Here, a two‐terminal synaptic device based on potassium iodide (KI) and CH3NH3PbI3 (MAPbI3) hybrid film (KI–MAPbI3) is reported. The use of KI as an additive in the film preparation process greatly reduces grain boundaries, facilitating the improvement of device performance. The prepared synaptic device exhibits dual response to electric and light stimuli due to the unique properties of MAPbI3. Besides the successful simulation of biological synaptic functionalities such as paired‐pulse facilitation (PPF), plasticity in long‐term potentiation (LTP), and long‐term depression (LTD), the learning behavior of human under different moods and Pavlov's dog experiment are also simulated by combining electric and light stimuli. For image recognition, the simulation result shows that the device achieves an accuracy of 84.2% under light illumination after only 1500 learning phases.

A luminescent organic–inorganic ferroelectric, with a high Curie temperature (421 K), a high PL QY (88.52%) and excellent film forming ability, can be regarded as a very interesting multifunctional material for fabricating new optoelectronic devices.

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Layered cobalt hydroxides are cost-efficient electrocatalysts for oxygen evolution reaction (OER) in the field of energy conversion. Herein, we developed a facile synthesis method of 3d transition-metal-doped α-Co(OH)2 nanomaterials mediated with ammonia in water–methanol at room temperature. The doping of Cu2+ and Ni2+ leads to flower-like nanostructures similar to pure α-Co(OH)2, whereas the doping of Fe2+ produces nanoparticles with more than 2 times larger surface area in comparison with the Cu2+- and Ni2+-doped nanoflowers. The obtained dispersion with the addition of Nafion can be used directly as an electrocatalyst for OER with excellent catalytic activity, especially that the overpotential of Fe2+ doped is as low as 290 mV at 10 mA cm–2 and the turnover frequency is improved by 3 times as compared with that of α-Co(OH)2. Furthermore, the catalyst can be loaded onto foam nickel, which presents excellent durability with the current density unchanged under continuous chronoamperometry reaction for as long as 12 h and almost quantitative faradaic efficiency. The superior electrocatalytic properties combined with the simple synthesis without the tedious purification procedure is very promising for OER.