Tailoring Classical Conditioning Behavior in TiO2 Nanowires: ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware.

Neuromorphic hardware equipped with associative learning capabilities presents fascinating applications in the next generation of artificial intelligence. However, research into synaptic devices exhibiting complex associative learning behaviors is still nascent. Here, an optoelectronic memristor based on Ag/TiO2 Nanowires: ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors. Effective implementation of synaptic behaviors, including long and short-term plasticity, and learning-forgetting-relearning behaviors, were achieved in the device through the application of light and electrical stimuli. Leveraging the optoelectronic co-modulated characteristics, a simulation of neuromorphic computing was conducted, resulting in a handwriting digit recognition accuracy of 88.9%. Furthermore, a 3 × 7 memristor array was constructed, confirming its application in artificial visual memory. Most importantly, complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli, respectively. After training through associative pairs, reflexes could be triggered solely using light stimuli. Comprehensively, under specific optoelectronic signal applications, the four features of classical conditioning, namely acquisition, extinction, recovery, and generalization, were elegantly emulated. This work provides an optoelectronic memristor with associative behavior capabilities, offering a pathway for advancing brain-machine interfaces, autonomous robots, and machine self-learning in the future.

Intuition-and-Tactile Bimodal Sensing Based on Artificial-Intelligence-Motivated All-Fabric Bionic Electronic Skin for Intelligent Material Perception.

Developing electronic skins (e-skins) with extraordinary perception through bionic strategies has far-reaching significance for the intellectualization of robot skins. Here, an artificial intelligence (AI)-motivated all-fabric bionic (AFB) e-skin is proposed, where the overall structure is inspired by the interlocked bionics of the epidermis-dermis interface inside the skin, while the structural design inspiration of the dielectric layer derives from the branch-needle structure of conifers. More importantly, AFB e-skin achieves intuition sensing in proximity mode and tactile sensing in pressure mode based on the fringing and iontronic effects, respectively, and is simulated and verified through COMSOL finite element analysis. The proposed AFB e-skin in pressure mode exhibits maximum sensitivity of 15.06 kPa-1 (<50 kPa), linear sensitivity of 6.06 kPa-1 (50-200 kPa), and fast response/recovery time of 5.6 ms (40 kPa). By integrating AFB e-skin with AI algorithm, and with the support of material inference mechanisms based on dielectric constant and softness/hardness, an intelligent material perception system capable of recognizing nine materials with indistinguishable surfaces within one proximity-pressure cycle is established, demonstrating abilities that surpass human perception.

Micropyramid Array Bimodal Electronic Skin for Intelligent Material and Surface Shape Perception Based on Capacitive Sensing.

Developing electronic skins (e-skins) that are comparable to or even beyond human tactile perception holds significant importance in advancing the process of intellectualization. In this context, a machine-learning-motivated micropyramid array bimodal (MAB) e-skin based on capacitive sensing is reported, which enables spatial mapping applications based on bimodal sensing (proximity and pressure) implemented via fringing and iontronic effects, such as contactless measurement of 3D objects and contact recognition of Braille letters. Benefiting from the iontronic effect and single-micropyramid structure, the MAB e-skin in pressure mode yields impressive features: a maximum sensitivity of 655.3 kPa-1 (below 0.5 kPa), a linear sensitivity of 327.9 kPa-1 (0.5-15 kPa), and an ultralow limit of detection of 0.2 Pa. With the assistance of multilayer perceptron and convolutional neural network, the MAB e-skin can accurately perceive 6 materials and 10 surface shapes based on the training and learning using the collected datasets from proximity and pressure modes, thus allowing it to achieve the precise perception of different objects within one proximity-pressure cycle. The development of this MAB e-skin opens a new avenue for robotic skin and the expansion of advanced applications.

Pulsed-Laser-Triggered Piezoelectric Photocatalytic CO2 Reduction over Tetragonal BaTiO3 Nanocubes.

The recombination of photoinduced carriers in photocatalysts is considered one of the biggest barriers to the increase of photocatalytic efficiency. Piezoelectric photocatalysts open a new route to realize rapid carrier separation by mechanically distorting the lattice of piezoelectric nanocrystals to form a piezoelectric potential within the nanocrystals, generally requiring external force (e.g., ultrasonic radiation, mechanical stirring, and ball milling). In this study, a low-power UV pulsed laser (PL) (3 W, 355 nm) as a UV light source can trigger piezoelectric photocatalytic CO2 reduction of tetragonal BaTiO3 (BTO-T) in the absence of an applied force. The tremendous transient light pressure (5.7 × 107  Pa, 2.7 W) of 355 nm PL not only bends the energy band of BTO-T, thus allowing reactions that cannot theoretically occur to take place, but also induces a pulsed built-in electric field to determine an efficient photoinduced carrier separation. On that basis, the PL-triggered piezoelectric photocatalytic CO2 reduction realizes the highest reported performance, reaching a millimole level CO yield of 52.9 mmol g-1 h-1 and achieving efficient photocatalytic CO2 reduction in the continuous catalytic system. The method in this study is promising to contribute to the design of efficient piezoelectric photocatalytic reactions.

Advances in Emerging Photonic Memristive and Memristive-Like Devices.

Possessing the merits of high efficiency, low consumption, and versatility, emerging photonic memristive and memristive-like devices exhibit an attractive future in constructing novel neuromorphic computing and miniaturized bionic electronic system. Recently, the potential of various emerging materials and structures for photonic memristive and memristive-like devices has attracted tremendous research efforts, generating various novel theories, mechanisms, and applications. Limited by the ambiguity of the mechanism and the reliability of the material, the development and commercialization of such devices are still rare and in their infancy. Therefore, a detailed and systematic review of photonic memristive and memristive-like devices is needed to further promote its development. In this review, the resistive switching mechanisms of photonic memristive and memristive-like devices are first elaborated. Then, a systematic investigation of the active materials, which induce a pivotal influence in the overall performance of photonic memristive and memristive-like devices, is highlighted and evaluated in various indicators. Finally, the recent advanced applications are summarized and discussed. In a word, it is believed that this review provides an extensive impact on many fields of photonic memristive and memristive-like devices, and lay a foundation for academic research and commercial applications.

Perception-to-Cognition Tactile Sensing Based on Artificial-Intelligence-Motivated Human Full-Skin Bionic Electronic Skin.

Traditional electronic skin (e-skin), due to the lack of human-brain-like thinking and judging capability, is powerless to accelerate the pace to the intelligent era. Herein, artificial intelligence (AI)-motivated full-skin bionic (FSB) e-skin consisting of the structures of human vellus hair, epidermis-dermis-hypodermis, is proposed. Benefiting from the double interlocked layered microcone structure and supercapacitive iontronic effect, the FSB e-skin exhibits ultrahigh sensitivity of 8053.1 kPa-1 (<1 kPa), linear sensitivity of 3103.5 kPa-1 (1-34 kPa), and fast response/recovery time of <5.6 ms. In addition, it can realize the evolution from tactile perception to advanced intelligent tactile cognition after being equipped with a "brain". First, static/dynamic contactless tactile perception is achieved based on the triboelectric effect of the vellus hair bionics. Second, the supercapacitive iontronic effect based structural bionics of the epidermis-dermis-hypodermis and a five-layer multilayer perception (MLP) enable the general intelligent tactile cognition of gesture cognition and robot interaction. Most importantly, by making full use of the FSB e-skin with a six-layer MLP neural network, an advanced intelligent material cognition system is developed for real-time cognition of the object material species and locations via one contact, which surpasses the capability of humans.

Underfocus Laser Induced Ni Nanoparticles Embedded Metallic MoN Microrods as Patterned Electrode for Efficient Overall Water Splitting.

Transition metal nitrides have shown large potential in industrial application for realization of the high active and large current density toward overall water splitting, a strategy to synthesize an inexpensive electrocatalyst consisting of Ni nanoparticles embedded metallic MoN microrods cultured on roughened nickel sheet (Ni/MoN/rNS) through underfocus laser heating on NiMoO4 ·xH2 O under NH3 atmosphere is posited. The proposed laser preparation mechanism of infocus and underfocus modes confirms that the laser induced stress and local high temperature controllably and rapidly prepared the patterned Ni/MoN/rNS electrodes in large size. The designed Ni/MoN/rNS presents outstanding catalytic performance for hydrogen evolution reaction (HER) with a low overpotential of 67 mV to deliver a current density of 10 mA cm-2 and for the oxygen evolution reaction (OER) with a small overpotential of 533 mV to deliver 200 mA cm-2 . Density functional theory (DFT) calculations and Kelvin probe force microscopy (KPFM) further verify that the constructed interface of Ni/MoN with small hydrogen absorption Gibbs free energy (ΔGH* ) (-0.19 eV) and similar electrical conductivity between Ni and metallic MoN, which can explain the high intrinsic catalytic activity of Ni/MoN. Further, the constructed two-electrode system (-) Ni/MoN/rNS||Ni/MoN/rNS (+) is employed in an industrial water-splitting electrolyzer (460 mA cm-2 for 120 h), being superior to the performance of commercial nickel electrode.

Micro-Nano Processing of Active Layers in Flexible Tactile Sensors via Template Methods: A Review.

Template methods are regarded as an important method for micro-nano processing in the active layer of flexible tactile sensors. These template methods use physical/chemical processes to introduce micro-nano structures on the active layer, which improves many properties including sensitivity, response/recovery time, and detection limit. However, since the processing process and applicable conditions of the template method have not yet formed a perfect system, the development and commercialization of flexible tactile sensors based on the template method are still at a relatively slow stage. Despite the above obstacles, advances in microelectronics, materials science, nanoscience, and other disciplines have laid the foundation for various template methods, enabling the continuous development of flexible tactile sensors. Therefore, a comprehensive and systematic review of flexible tactile sensors based on the template method is needed to further promote progress in this field. Here, the unique advantages and shortcomings of various template methods are summarized in detail and discuss the research progress and challenges in this field. It is believed that this review will have a significant impact on many fields of flexible electronics, which is beneficial to promote the cross-integration of multiple fields and accelerate the development of flexible electronic devices.

Highly Morphology-Controllable and Highly Sensitive Capacitive Tactile Sensor Based on Epidermis-Dermis-Inspired Interlocked Asymmetric-Nanocone Arrays for Detection of Tiny Pressure.

The tactile sensor lies at the heart of electronic skin and is of great importance in the development of flexible electronic devices. To date, it still remains a critical challenge to develop a large-scale capacitive tactile sensor with high sensitivity and controllable morphology in an economical way. Inspired by the interlocked microridges between the epidermis and dermis, herein, a highly sensitive capacitive tactile sensor by creating interlocked asymmetric-nanocones in poly(vinylidenefluoride-co-trifluoroethylene) film is proposed. Particularly, a facile method based on cone-shaped nanoporous anodized aluminum oxide templates is proposed to cost-effectively fabricate the highly ordered nanocones in a controllable manner and on a large scale. Finite-element analysis reveals that under vertical forces, the strain/stress can be highly strengthened and localized at the contact apexes, resulting in an amplified variation of film permittivity and thickness. Benefiting from this, the developed tactile sensor presents several conspicuous features, including the maximum sensitivity (6.583 kPa-1 ) in the low pressure region (0-100 Pa), ultralow detection limit (≈3 Pa), rapid response/recovery time (48/36 ms), excellent stability and reproducibility (10 000 cycles). These salient merits enable the sensor to be successfully applied in a variety of applications including sign language gesture detection, spatial pressure mapping, Braille recognition, and physiological signal monitoring.