Halide Perovskites for Memristive Data Storage and Artificial Synapses

Transient N-GQDs/PVA nanocomposite thin film for memristor application

In recent years quantum dot (QDs) based resistive switching devices(memristors) have gained a lot of attention. Here we report the resistive switching behavior of nitrogen-doped graphene quantum dots/Polyvinyl alcohol (N-GQDs/PVA) degradable nanocomposite thin film with different weight percentages (wt.%) of N-GQDs. The memristor device was fabricated by a simple spin coating technique. It was found that 1 wt% N-GQDs/PVA device shows a prominent resistive switching phenomenon with good cyclic stability, high on/off ratio of ~102and retention time of ∼104s. From a detailed experimental study of band structure, we conclude that memristive behavior originates from the space charge controlled conduction (SCLC) mechanism. Further transient property of built memristive device was studied. Within three minutes of being submerged in distilled water, the fabricated memory device was destroyed. This phenomenon facilitates the usage of fabricated memristor devices to develop memory devices for military and security purposes.

Electrical Impedance Spectroscopy with Bacterial Biofilms: Neuronal-like Behavior

Negative capacitance at low frequencies for spiking neurons was first demonstrated in 1941 (K. S. Cole) by using extracellular electrodes. The phenomenon subsequently was explained by using the Hodgkin-Huxley model and is due to the activity of voltage-gated potassium ion channels. We show that Escherichia coli (E. coli) biofilms exhibit significant stable negative capacitances at low frequencies when they experience a small DC bias voltage in electrical impedance spectroscopy experiments. Using a frequency domain Hodgkin-Huxley model, we characterize the conditions for the emergence of this feature and demonstrate that the negative capacitance exists only in biofilms containing living cells. Furthermore, we establish the importance of the voltage-gated potassium ion channel, Kch, using knock-down mutants. The experiments provide further evidence for voltage-gated ion channels in E. coli and a new, low-cost method to probe biofilm electrophysiology, e.g., to understand the efficacy of antibiotics. We expect that the majority of bacterial biofilms will demonstrate negative capacitances.

Quasi-2D Lead-Tin Perovskite Memory Devices Fabricated by Blade Coating

Two terminal passive devices are regarded as one of the promising candidates to solve the processor-memory bottleneck in the Von Neumann computing architectures. Many different materials are used to fabricate memory devices, which have the potential to act as synapses in future neuromorphic electronics. Metal halide perovskites are attractive for memory devices as they display high density of defects with a low migration barrier. However, to become promising for a future neuromorphic technology, attention should be paid on non-toxic materials and scalable deposition processes. Herein, it is reported for the first time the successful fabrication of resistive memory devices using quasi-2D tin-lead perovskite of composition (BA)2 MA4 (Pb0.5 Sn0.5 )5 I16 by blade coating. The devices show typical memory characteristics with excellent endurance (2000 cycles), retention (105  s), and storage stability (3 months). Importantly, the memory devices successfully emulate synaptic behaviors such as spike-timing-dependent plasticity, paired-pulse facilitation, short-term potentiation, and long-term potentiation. A mix of slow (ionic) transport and fast (electronic) transport (charge trapping and de-trapping) is proven to be responsible for the observed resistive switching behavior.

Ion Migration in Lead-Halide Perovskites: Cation Matters

Metal halide perovskites exhibit remarkable properties for optoelectronic applications, yet their susceptibility to ion migration poses challenges for device stability. Previous research has predominantly focused on the migration of the halide ions. However, the migration of cations, which also has a significant influence on the device performance, is largely overlooked. In this Perspective, we review the migration of cations and their impacts on perovskite materials and devices. Special attention shall be devoted to recent insights into the migration of L-site organic cations in 2D/3D perovskites. We outline inspirations and directions for further research into the cation migration of perovskites, highlighting new possibilities in advancing perovskite optoelectronics.

Organic High-Temperature Synaptic Phototransistors for Energy-Efficient Neuromorphic Computing

Organic optoelectronic synaptic devices that can reliably operate in high-temperature environments (i.e., beyond 121°C) or remain stable after high-temperature treatments have significant potential in biomedical electronics and bionic robotic engineering. However, it is challenging to acquire this type of organic devices considering the thermal instability of conventional organic materials and the degradation of photoresponse mechanisms at high temperatures. Here, high-temperature synaptic phototransistors (HTSPs) based on thermally stable semiconductor polymer blends as the photosensitive layer are developed, successfully simulating fundamental optical-modulated synaptic characteristics at a wide operating temperature range from room temperature to 220°C. Robust optoelectronic performance can be observed in HTSPs even after experiencing 750 h of the double 85 testing due to the enhanced operational reliability. Using HTSPs, Morse-code optical decoding scheme and the visual object recognition capability are also verified at elevated temperatures. Furthermore, flexible HTSPs are fabricated, demonstrating an ultralow power consumption of 12.3 aJ per synaptic event at a low operating voltage of -0.05 mV. Overall, the conundrum of achieving reliable optical-modulated neuromorphic applications while balancing low power consumption can be effectively addressed. This research opens up a simple but effective avenue for the development of high-temperature and energy-efficient wearable optoelectronic devices in neuromorphic computing applications.

Reconfigurable Neuromorphic Computing: Materials, Devices, and Integration

Neuromorphic computing has been attracting ever-increasing attention due to superior energy efficiency, with great promise to promote the next wave of artificial general intelligence in the post-Moore era. Current approaches are, however, broadly designed for stationary and unitary assignments, thus encountering reluctant interconnections, power consumption, and data-intensive computing in that domain. Reconfigurable neuromorphic computing, an on-demand paradigm inspired by the inherent programmability of brain, can maximally reallocate finite resources to perform the proliferation of reproducibly brain-inspired functions, highlighting a disruptive framework for bridging the gap between different primitives. Although relevant research has flourished in diverse materials and devices with novel mechanisms and architectures, a precise overview remains blank and urgently desirable. Herein, the recent strides along this pursuit are systematically reviewed from material, device, and integration perspectives. At the material and device level, one comprehensively conclude the dominant mechanisms for reconfigurability, categorized into ion migration, carrier migration, phase transition, spintronics, and photonics. Integration-level developments for reconfigurable neuromorphic computing are also exhibited. Finally, a perspective on the future challenges for reconfigurable neuromorphic computing is discussed, definitely expanding its horizon for scientific communities.

Bimodal ionic photomemristor based on a high-temperature oxide superconductor/semiconductor junction

Memristors, a cornerstone for neuromorphic electronics, respond to the history of electrical stimuli by varying their electrical resistance across a continuum of states. Much effort has been recently devoted to developing an analogous response to optical excitation. Here we realize a novel tunnelling photo-memristor whose behaviour is bimodal: its resistance is determined by the dual electrical-optical history. This is obtained in a device of ultimate simplicity: an interface between a high-temperature superconductor and a transparent semiconductor. The exploited mechanism is a reversible nanoscale redox reaction between both materials, whose oxygen content determines the electron tunnelling rate across their interface. The redox reaction is optically driven via an interplay between electrochemistry, photovoltaic effects and photo-assisted ion migration. Besides their fundamental interest, the unveiled electro-optic memory effects have considerable technological potential. Especially in combination with high-temperature superconductivity which, in addition to facilitating low-dissipation connectivity, brings photo-memristive effects to the realm of superconducting electronics.

Achieving adjustable digital-to-analog conversion in memristors with embedded Cs2AgSbBr6 nanoparticles

In this work, the proportions of Cs₂AgSbBr₆ nanoparticles (NPs) mixed in a PMMA film are adjusted to the digital and analog types of resistive switching (RS) behaviors in Ag/PMMA&Cs₂AgSbBr₆-NPs/ITO memristor devices. It is confirmed that when the concentration of NPs doped in the PMMA film is about 5 wt%, the memristor devices demonstrate bipolar digital RS behaviors with excellent electrical characteristics such as low operating voltage, high ON/OFF ratio (>500), good endurance (>800 cycles), and stable retention ability (>10⁴ s). However, the devices showed a transition to analog-type memristive behavior when the concentration of NPs doped in the PMMA film is around 10 wt%, and several artificial synapse behaviors are successfully simulated. The device model simulation is also used to explore the effect of the NPs on the local electric field and growing filaments. Our work provides an opportunity to explore next-generation artificial synapse devices based on lead-free halide perovskites.

Two-Terminal Lithium-Mediated Artificial Synapses with Enhanced Weight Modulation for Feasible Hardware Neural Networks

Recently, artificial synapses involving an electrochemical reaction of Li-ion have been attributed to have remarkable synaptic properties. Three-terminal synaptic transistors utilizing Li-ion intercalation exhibits reliable synaptic characteristics by exploiting the advantage of non-distributed weight updates owing to stable ion migrations. However, the three-terminal configurations with large and complex structures impede the crossbar array implementation required for hardware neuromorphic systems. Meanwhile, achieving adequate synaptic performances through effective Li-ion intercalation in vertical two-terminal synaptic devices for array integration remains challenging. Here, two-terminal Au/LixCoO2/Pt artificial synapses are proposed with the potential for practical implementation of hardware neural networks. The Au/LixCoO2/Pt devices demonstrated extraordinary neuromorphic behaviors based on a progressive dearth of Li in LixCoO2 films. The intercalation and deintercalation of Li-ion inside the films are precisely controlled over the weight control spike, resulting in improved weight control functionality. Various types of synaptic plasticity were imitated and assessed in terms of key factors such as nonlinearity, symmetricity, and dynamic range. Notably, the LixCoO2-based neuromorphic system outperformed three-terminal synaptic transistors in simulations of convolutional neural networks and multilayer perceptrons due to the high linearity and low programming error. These impressive performances suggest the vertical two-terminal Au/LixCoO2/Pt artificial synapses as promising candidates for hardware neural networks.

Halide perovskite photoelectric artificial synapses: materials, devices, and applications

In recent years, there has been a research boom on halide perovskites (HPs) whose outstanding performance in photovoltaic and optoelectronic fields is obvious to all. In particular, HP materials find application in the development of artificial synapses. HP-based synapses have great potential for artificial neuromorphic systems, which is due to their outstanding optoelectronic properties, femtojoule-level energy consumption, and simple fabrication process. In this review, we present the physical properties of HPs and describe two types of synaptic devices including two-terminal (2T) memristors and three-terminal (3T) transistors. The HP layer in 2T memristors can realize the change in the device conductance through physical mechanisms dominated by ion migration. On the other hand, HPs in 3T transistors can be used as efficient light-absorbing layers and rely on some special device structures to provide reliable current changes. In the final section of the article, we discuss some of the existing applications of HP-based synapses and bottlenecks to be solved.

Electrical Charge Coupling Dominates the Hysteresis Effect of Halide Perovskite Devices

Hysteresis effects in ionic-electronic devices are a valuable resource for the development of switching memory devices that can be used in information storage and brain-like computation. Halide perovskite devices show frequent hysteresis in current-voltage curves that can be harnessed to build effective memristors. These phenomena can be often described by a set of highly nonlinear differential equations that involve current, voltage, and internal state variables, in the style of the famous Hodgkin-Huxley model that accounts for the initiation and temporal response of action potentials in biological neurons. Here we extend the neuron-style models that lead to chemical inductors by introducing a capacitive coupling in the slow relaxation variable. The extended model is able to explain naturally previous observations concerning the transition from capacitor to inductor in impedance spectroscopy of MAPbBr solar cells and memristors in the dark. The model also generates new types of oscillating systems by the generation of a truly negative capacitance distinct from the usual inductive effect.

Enhanced Resistive Switching Performance through Air-Stable Cu2AgSbI6 Thin Films for Flexible and Multilevel Storage Application

Herein, the lead-free halide perovskite films with different Cu-to-Ag ratios (Cu_3-xAg_xSbI₆, x = 0, 1, 2, or 3) have been prepared by a spin-coating method at low temperature. The enhanced resistive switching (RS) performance of more uniform SET/RESET voltages and the endurance up to at least 1600 cycles are found in the RS memory with a device structure of Ag/PMMA/Cu₂AgSbI₆/ITO. The device performance is not degraded under different bending angles and after 10³ bending cycles, which is beneficial for flexible memory applications. The appropriately increased activation energy of the perovskites with the partial substitution of Ag atoms, which would lead to a more robust filament formed, is proposed to explain the enhanced RS mechanism. Importantly, the effective size and number of filaments measured by conductive AFM are introduced to confirm the multilevel storage effect of Cu₂AgSbI₆. The multilevel storage characteristics with four resistance levels are demonstrated by various compliance currents. Moreover, the Cu₂AgSbI₆ memory devices still exhibit enhanced RS properties and multilevel storage after 75 days of exposure to ambient conditions. Our study provides a strategy for improving the stability and high-density storage applications of halide perovskite RS memory devices.

Recent progress and future prospects on halide perovskite nanocrystals for optoelectronics and beyond

As an emerging new class of semiconductor nanomaterials, halide perovskite (ABX₃, X = Cl, Br, or I) nanocrystals (NCs) are attracting increasing attention owing to their great potential in optoelectronics and beyond. This field has experienced rapid breakthroughs over the past few years. In this comprehensive review, halide perovskite NCs that are either freestanding or embedded in a matrix (e.g., perovskites, metal-organic frameworks, glass) will be discussed. We will summarize recent progress on the synthesis and post-synthesis methods of halide perovskite NCs. Characterizations of halide perovskite NCs by using a variety of techniques will be present. Tremendous efforts to tailor the optical and electronic properties of halide perovskite NCs in terms of manipulating their size, surface, and component will be highlighted. Physical insights gained on the unique optical and charge-carrier transport properties will be provided. Importantly, the growing potential of halide perovskite NCs for advancing optoelectronic applications and beyond including light-emitting devices (LEDs), solar cells, scintillators and X-ray imaging, lasers, thin-film transistors (TFTs), artificial synapses, and light communication will be extensively discussed, along with prospecting their development in the future.

Low-Dimensional Metal-Halide Perovskites as High-Performance Materials for Memory Applications

Metal-halide perovskites have drawn profuse attention during the past decade, owing to their excellent electrical and optical properties, facile synthesis, efficient energy conversion, and so on. Meanwhile, the development of information storage technologies and digital communications has fueled the demand for novel semiconductor materials. Low-dimensional perovskites have offered a new force to propel the developments of the memory field due to the excellent physical and electrical properties associated with the reduced dimensionality. In this review, the mechanisms, properties, as well as stability and performance of low-dimensional perovskite memories, involving both molecular-level perovskites and structure-level nanostructures, are comprehensively reviewed. The property-performance correlation is discussed in-depth, aiming to present effective strategies for designing memory devices based on this new class of high-performance materials. Finally, the existing challenges and future opportunities are presented.

Dynamic Instability and Time Domain Response of a Model Halide Perovskite Memristor for Artificial Neurons

Memristors are candidate devices for constructing artificial neurons, synapses, and computational networks for brainlike information processing and sensory-motor autonomous systems. However, the dynamics of natural neurons and synapses are challenging and cannot be well reproduced with standard electronic components. Halide perovskite memristors operate by mixed ionic-electronic properties that may lead to replicate the live computation elements. Here we explore the dynamical behavior of a halide perovskite memristor model to evaluate the response to a step perturbation and the self-sustained oscillations that produce analog neuron spiking. As the system contains a capacitor and a voltage-dependent chemical inductor, it can mimic an action potential in response to a square current pulse. Furthermore, we discover a property that cannot occur in the standard two-dimensional model systems: a three-dimensional model shows a dynamical instability that produces a spiking regime without the need for an intrinsic negative resistance. These results open a new pathway to create spiking neurons without the support of electronic circuits.

Chemical Inductor

A multitude of chemical, biological, and material systems present an inductive behavior that is not electromagnetic in origin. Here, it is termed a chemical inductor. We show that the structure of the chemical inductor consists of a two-dimensional system that couples a fast conduction mode and a slowing down element. Therefore, it is generally defined in dynamical terms rather than by a specific physicochemical mechanism. The chemical inductor produces many familiar features in electrochemical reactions, including catalytic, electrodeposition, and corrosion reactions in batteries and fuel cells, and in solid-state semiconductor devices such as solar cells, organic light-emitting diodes, and memristors. It generates the widespread phenomenon of negative capacitance, it causes negative spikes in voltage transient measurements, and it creates inverted hysteresis effects in current–voltage curves and cyclic voltammetry. Furthermore, it determines stability, bifurcations, and chaotic properties associated to self-sustained oscillations in biological neurons and electrochemical systems. As these properties emerge in different types of measurement techniques such as impedance spectroscopy and time-transient decays, the chemical inductor becomes a useful framework for the interpretation of the electrical, optoelectronic, and electrochemical responses in a wide variety of systems. In the paper, we describe the general dynamical structure of the chemical inductor and we comment on a broad range of examples from different research areas.