If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures impedes the achievement of three-dimensional interconnectivity, high-device density, or flexibility. Here we report flexible three-dimensional artificial chemical synapse networks, in which two-terminal memristive devices, namely, electronic synapses (e-synapses), are connected by vertically stacking crossbar electrodes. The e-synapses resemble the key features of biological synapses: unilateral connection, long-term potentiation/depression, a spike-timing-dependent plasticity learning rule, paired-pulse facilitation, and ultralow-power consumption. The three-dimensional artificial synapse networks enable a direct emulation of correlated learning and trainable memory capability with strong tolerances to input faults and variations, which shows the feasibility of using them in futuristic electronic devices and can provide a physical platform for the realization of smart memories and machine learning and for operation of the complex algorithms involving hierarchical neural networks.

Perovskite materials have exhibited promising potential for universal applications including backlighting, color conversion, and anticounterfeiting labels fabricated using solution processes. However, owing to the tendency of those materials to have uncontrollable morphologies and to form large crystals, they cannot be utilized in discontinuous microminiaturization, which is crucial for practical optoelectronic applications. In this research, combining the effects of adding polyvinylpyrrolidone (PVP), precisely controlling the inkjet printing technique, and using a postprocessing procedure, we were able to fabricate in situ crystallized perovskite–PVP nanocomposite microarrays with perfect morphologies. The viscosity of the perovskite precursor increased with the addition of PVP, eliminating the outward capillary flow that induces the coffee-ring effect. In addition, because of the presence of metallic bonds with the CO groups in PVP and the spatial confinement of such a polymer, we were able to fabricate regulated CsPbBr3 nanocrystals capped with PVP and with a uniform size distribution. The as-printed patterns showed excellent homogeneity on a macroscale and high reproducibility on a microscale; furthermore, those patterns were invisible in the ambient environment, compatible with flexible substrates, and cost-efficient to produce, indicating that this technique holds promising potential for applications such as anticounterfeiting labels.

As one of their major goals, researchers attempting to harvest mechanical energy efficiently have continuously sought ways to integrate mature technologies with cutting-edge designs to enhance the performances of triboelectric nanogenerators (TENGs). In this research, we introduced monolayer molybdenum-disulfide (MoS) into the friction layer of a TENG as the triboelectric electron-acceptor layer in an attempt to dramatically enhance its output performance. As a proof of the concept, we fabricated a vertical contact-separation mode TENG containing monolayer MoS as an electron-acceptor layer and found that the TENG exhibited a peak power density as large as 25.7 W/m, which is 120 times larger than that of the device without monolayer MoS. The mechanisms behind the performance enhancement, which are related to the highly efficient capture of triboelectric electrons in monolayer MoS, are discussed in detail. This study indicates that monolayer MoS can be used as a functional material for efficient energy harvesting.

Simulating the human brain for neuromorphic computing has attractive prospects in the field of artificial intelligence. Optoelectronic synapses have been considered to be important cornerstones of neuromorphic computing due to their ability to process optoelectronic input signals intelligently. In this work, optoelectronic synapses based on all‐inorganic perovskite nanoplates are fabricated, and the electronic and photonic synaptic plasticity is investigated. Versatile synaptic functions of the nervous system, including paired‐pulse facilitation, short‐term plasticity, long‐term plasticity, transition from short‐ to long‐term memory, and learning‐experience behavior, are successfully emulated. Furthermore, the synapses exhibit a unique memory backtracking function that can extract historical optoelectronic information. This work could be conducive to the development of artificial intelligence and inspire more research on optoelectronic synapses.

The technological realization of wearable triboelectric generators is attractive because of their promising applications in wearable self-powered intelligent systems. However, the low electrical conductivity, the low electrical stability, and the low compatibility of current electronic textiles (e-textiles) and clothing restrict the comfortable and aesthetic integration of wearable generators into human clothing. Here, we present high-performance, transparent, smart e-textiles that employ commercial textiles coated with silver nanowire/graphene sheets fabricated by using a scalable, environmentally friendly, full-solution process. The smart e-textiles show superb and stable conduction of below 20 Ω/square as well as excellent flexibility, stretchability, foldability, and washability. In addition, wearable electricity-generating textiles, in which the e-textiles act as electrodes as well as wearable substrates, are presented. Because of the high compatibility of smart e-textiles and clothing, the electricity-generating textiles can be easily integrated into a glove to harvest the mechanical energy induced by the motion of the fingers. The effective output power generated by a single generator due to that motion reached as high as 7 nW/cm(2). The successful demonstration of the electricity-generating glove suggests a promising future for polyester/Ag nanowire/graphene core-shell nanocomposite-based smart e-textiles for real wearable electronic systems and self-powered clothing.

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Fabrication of human-like intelligent tactile sensors is an intriguing challenge for developing human–machine interfaces. As inspired by somatosensory signal generation and neuroplasticity-based signal processing, intelligent neuromorphic tactile sensors with learning and memory based on the principle of a triboelectric nanogenerator are demonstrated. The tactile sensors can actively produce signals with various amplitudes on the basis of the history of pressure stimulations because of their capacity to mimic neuromorphic functions of synaptic potentiation and memory. The time over which these tactile sensors can retain the memorized information is alterable, enabling cascaded devices to have a multilevel forgetting process and to memorize a rich amount of information. Furthermore, smart fingers by using the tactile sensors are constructed to record a rich amount of information related to the fingers’ current actions and previous actions. This intelligent active tactile sensor can be used as a functional element for artificial intelligence.

Hybrid perovskite CHNHPbI has attracted extensive research interests in optoelectronic devices in recent years. Herein an inkjet printing method has been employed to deposit a perovskite CHNHPbI layer. By choosing the proper solvent and controlling the crystal growth rate, hybrid perovskite CHNHPbI nanowires, microwires, a network, and islands were synthesized by means of inkjet printing. Electrode-gap-electrode lateral-structured photodetectors were fabricated with these different crystals, of which a hybrid perovskite microwire-based photodetector would balance the uniformity and low defects to obtain a switching ratio of 16000%, responsivity of 1.2 A/W, and normalized detectivity of 2.39 × 10 Jones at a light power density of 0.1 mW/cm. Furthermore, the hybrid perovskite microwire-based photodetector arrays were fabricated and applied in an imaging sensor, from which the clear mapping of the light source signal was successfully obtained. This work paves the way for the realization of low-cost, solution-processed, and high-performance hybrid perovskite-based photodetector arrays.