The rapid development of information technology has led to urgent requirements for high efficiency and ultralow power consumption. In the past few decades, neuromorphic computing has drawn extensive attention due to its promising capability in processing massive data with extremely low power consumption. Here, we offer a comprehensive review on emerging artificial neuromorphic devices and their applications. In light of the inner physical processes, we classify the devices into nine major categories and discuss their respective strengths and weaknesses. We will show that anion/cation migration-based memristive devices, phase change, and spintronic synapses have been quite mature and possess excellent stability as a memory device, yet they still suffer from challenges in weight updating linearity and symmetry. Meanwhile, the recently developed electrolyte-gated synaptic transistors have demonstrated outstanding energy efficiency, linearity, and symmetry, but their stability and scalability still need to be optimized. Other emerging synaptic structures, such as ferroelectric, metal–insulator transition based, photonic, and purely electronic devices also have limitations in some aspects, therefore leading to the need for further developing high-performance synaptic devices. Additional efforts are also demanded to enhance the functionality of artificial neurons while maintaining a relatively low cost in area and power, and it will be of significance to explore the intrinsic neuronal stochasticity in computing and optimize their driving capability, etc. Finally, by looking into the correlations between the operation mechanisms, material systems, device structures, and performance, we provide clues to future material selections, device designs, and integrations for artificial synapses and neurons.

A comprehensive review on emerging artificial neuromorphic devices

p-Type ZnO materials: Theory, growth, properties and devices

Abstract In the past 10 years, ZnO as a semiconductor has attracted considerable attention due to its unique properties, such as high electron mobility, wide and direct band gap and large exciton binding energy. ZnO has been considered a promising material for optoelectronic device applications, and the fabrications of high quality p-type ZnO and p–n junction are the key steps to realize these applications. However, the reliable p-type doping of the material remains a major challenge because of the self-compensation from native donor defects (V O and Zn i ) and/or hydrogen incorporation. Considerable efforts have been made to obtain p-type ZnO by doping different elements with various techniques. Remarkable progresses have been achieved, both theoretically and experimentally. In this paper, we discuss p-type ZnO materials: theory, growth, properties and devices, comprehensively. We first discuss the native defects in ZnO. Among the native defects in ZnO, V Zn and O i act as acceptors. We then present the theory of p-type doping in ZnO, and summarize the growth techniques for p-type ZnO and the properties of p-type ZnO materials. Theoretically, the principles of selection of p-type dopant, codoping method and X Zn –2V Zn acceptor model are introduced. Experimentally, besides the intrinsic p-type ZnO grown at O-rich ambient, p-type ZnO (MgZnO) materials have been prepared by various techniques using Group-I, IV and V elements. We pay a special attention to the band gap of p-type ZnO by band-gap engineering and room temperature ferromagnetism observed in p-type ZnO. Finally, we summarize the devices based on p-type ZnO materials.

RaoP-Type ZnO Materials: Theory, Growth, Properties, and Devices

The authors report first a new type of nitrogen-triggered Zn single atom catalyst, demonstrating high catalytic activity and remarkable durability for the oxygen reduction reaction process. Both X-ray absorption fine structure spectra and theoretical calculations suggest that the atomically dispersed Zn-N4 site is the main, as well as the most active, component with O adsorption as the rate-limiting step at a low overpotential of 1.70 V. This work opens a new field for the exploration of high-performance Pt-free electrochemical oxygen reduction catalysts for fuel cells.

Zn Single Atom Catalyst for Highly Efficient Oxygen Reduction Reaction

A novel high power symmetric ZnO/carbon aerogel composite electrode for electrochemical supercapacitor

The close replication of synaptic functions is an important objective for achieving a highly realistic memristor-based cognitive computation. The emulation of neurobiological learning rules may allow the development of neuromorphic systems that continuously learn without supervision. In this work, the Bienenstock-Cooper-Munro learning rule, as a typical case of spike-rate-dependent plasticity, is mimicked using a generalized triplet-spike-timing-dependent plasticity scheme in a WO3-x memristive synapse. It demonstrates both presynaptic and postsynaptic activities and remedies the absence of the enhanced depression effect in the depression region, allowing a better description of the biological counterpart. The threshold sliding effect of Bienenstock-Cooper-Munro rule is realized using a history-dependent property of the second-order memristor. Rate-based orientation selectivity is demonstrated in a simulated feedforward memristive network with this generalized Bienenstock-Cooper-Munro framework. These findings provide a feasible approach for mimicking Bienenstock-Cooper-Munro learning rules in memristors, and support the applications of spatiotemporal coding and learning using memristive networks.

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Toward a generalized Bienenstock-Cooper-Munro rule for spatiotemporal learning via triplet-STDP in memristive devices

Thin films of p-type ZnO:N have been obtained by thermally oxidizing zinc oxynitride films prepared by plasma enhanced chemical vapour deposition (PECVD). The p-type ZnO:N thin film with a hole concentration of 2.7 × 1016 cm−3 was obtained after an annealing process was conducted at 600 °C. A conductivity transition from n-type to p-type was observed, which was systematically researched via structural and compositional analyses. In terms of these analyses, it helped to better understand the properties and behaviour of nitrogen in ZnO. First, nitrogen was incorporated into ZnO films during the growth process to occupy oxygen positions, and also partly compensated some donors induced from non-stoichiometric (ZnO1–x) composition. Second, the amount of activated nitrogen gradually increased in an oxidizing atmosphere and exceeded those donor states to realize an effective compensation, yielding p-type conductivity during the course of thermal oxidation.

Electrical and structural properties of p-type ZnO:N thin films prepared by plasma enhanced chemical vapour deposition

Nanocrystalline ZnO films have been grown by cathodic electrodeposition from dimethylsulfoxide solutions containing ZnCl2 on Si substrates at room temperature. The effects of ZnCl2 concentration on the structural and optical properties of the films were studied. The mean grain size of ZnO particles increases with the increase of ZnCl2 concentration. The exciton emission dominated in the photoluminescence spectra.

Structural and optical properties of nanocrystalline ZnO films grown by cathodic electrodeposition on Si substrates

Cycling-Induced Degradation of Organic–Inorganic Perovskite-Based Resistive Switching Memory

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Yichun Liu

Papers

Toward a generalized Bienenstock-Cooper-Munro rule for spatiotemporal learning via triplet-STDP in memristive devices

Electrical and structural properties of p-type ZnO:N thin films prepared by plasma enhanced chemical vapour deposition

Structural and optical properties of nanocrystalline ZnO films grown by cathodic electrodeposition on Si substrates

Cycling-Induced Degradation of Organic–Inorganic Perovskite-Based Resistive Switching Memory

Analytical Modeling of Organic–Inorganic CH3NH3PbI3 Perovskite Resistive Switching and its Application for Neuromorphic Recognition