Controllable Organic Resistive Switching Achieved by One-Step Integration of Cone-Shaped Contact

Multilevel resistive switching in hydrothermally synthesized FeWO4 thin film-based memristive device for non-volatile memory application

The memristors offer significant advantages as a key element in non-volatile and brain-inspired neuromorphic systems because of their salient features such as remarkable endurance, ability to store multiple bits, fast operation speed, and extremely low energy usage. This work reports the resistive switching (RS) characteristics of the hydrothermally synthesized iron tungstate (FeWO4) based thin film memristive device. The detailed physicochemical analysis was investigated using Rietveld's refinement, X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM) techniques. The fabricated Ag/FWO/FTO memristive device exhibits bipolar resistive switching (BRS) behavior. In addition, the devices exhibit negative differential resistance (NDR) at both positive and negative bias. The charge-flux relation portrayed the non-ideal or memristive nature of the devices. The reliability in the RS process was analyzed in detail using Weibull distribution and time series analysis techniques. The device exhibits stable and multilevel endurance and retention characteristics which demonstrates the suitability of the device for the high-density non-volatile memory application. The current conduction of the device was dominated by Ohmic and trap controlled-space charge limited current (TC-SCLC) mechanisms and filamentary RS process responsible for the BRS in the device. In a nutshell, the present investigations reveal the potential use of the iron tungstate for the fabrication of memristive devices for the non-volatile memory application.

A memristive-photoconductive transduction methodology for accurately nondestructive memory readout

Crossbar resistive memory architectures enable high-capacity storage and neuromorphic computing, accurate retrieval of the stored information is a prerequisite during read operation. However, conventional electrical readout normally suffer from complicated process, inaccurate and destructive reading due to crosstalk effect from sneak path current. Here we report a memristive-photoconductive transduction (MPT) methodology for precise and nondestructive readout in a memristive crossbar array. The individual devices present dynamic filament form/fuse for resistance modulation under electric stimulation, which leads to photogenerated carrier transport for tunable photoconductive response under subsequently light pulse stimuli. This coherent signal transduction can be used to directly detect the memorized on/off states stored in each cell, and a prototype 4 * 4 crossbar memories has been constructed and validated for the fidelity of crosstalk-free readout in recall process.

Rational Design of Fluorinated 2D Polymer Film Based on Donor-Accepter Architecture toward Multilevel Memory Device for Neuromorphic Computing

Fluorine-containing 2D polymer (F-2DP) film is a desired system to regulate the charge transport in organic electronics but rather rarely reports due to the limited fluorine-containing building blocks and difficulties in synthesis. Herein, a novel polar molecule with antiparallel columnar stacking is synthesized and further embedded into an F-2DP system to control over the crystallinity of F-2DP film through self-complementary π-electronic forces. The donor-accepter-accepter'-donor' (D-A-A'-D') structure regulates the charge transportation efficiently, inducing multilevel memory behavior through stepwise charge capture and transfer processes. Thus, the device exhibits ternary memory behavior with low threshold voltage (Vth1 of 1.1 V, Vth2 of 2.0 V), clearly distinguishable resistance states (1:102:104) and ternary yield (83%). Furthermore, the stepwise formation of the charge complex endows the device with a wider range to regulate the conductive state, which allows its application in brain-inspired neuromorphic computing. Modified National Institute of Standards and Technology recognition can reach an accuracy of 86%, showing great potential in neuromorphic computing applications in the post-Moore era.

Resistive Memristors Using Robust Electropolymerized Porous Organic Polymer Films as Switchable Materials

Porous organic polymers (POPs) with inherent porosity, tunable pore environment, and semiconductive property are ideally suitable for application in various advanced semiconductor-related devices. However, owing to the lack of processability, POPs are usually prepared in powder forms, which limits their application in advanced devices. Herein, we demonstrate an example of information storage application of POPs with film form prepared by an electrochemical method. The growth process of the electropolymerized films in accordance with the Volmer-Weber model was proposed by observation of atomic force microscopy. Given the mechanism of the electron transfer system, we verified and mainly emphasized the importance of porosity and interfacial properties of porous polymer films for memristor. As expected, the as-fabricated memristors exhibit good performance on low turn-on voltage (0.65 ± 0.10 V), reliable data storage, and high on/off current ratio (104). This work offers inspiration for applying POPs in the form of electropolymerized films in various advanced semiconductor-related devices.

Memristor-Based Neuromorphic Chips

In the era of information, characterized by an exponential growth in data volume and an escalating level of data abstraction, there has been a substantial focus on brain-like chips, which are known for their robust processing power and energy-efficient operation. Memristors are widely acknowledged as the optimal electronic devices for the realization of neuromorphic computing, due to their innate ability to emulate the interconnection and information transfer processes witnessed among neurons. This review paper focuses on memristor-based neuromorphic chips, which provide an extensive description of the working principle and characteristic features of memristors, along with their applications in the realm of neuromorphic chips. Subsequently, a thorough discussion of the memristor array, which serves as the pivotal component of the neuromorphic chip, as well as an examination of the present mainstream neural networks, is delved. Furthermore, the design of the neuromorphic chip is categorized into three crucial sections, including synapse-neuron cores, networks on chip (NoC), and neural network design. Finally, the key performance metrics of the chip is highlighted, as well as the key metrics related to the memristor devices are employed to realize both the synaptic and neuronal components.

A carbon conductive filament-induced robust resistance switching behavior for brain-inspired computing

Memristors have revolutionized the path forward for brain-inspired computing. However, the instability of the nucleation process of conductive filaments based on active metal electrodes leads to the discrete distribution of switching parameters, which hinders the realization of high-performance and low-power devices for neuromorphic computing. In response, a carbon conductive filament-induced robust memristor is demonstrated with variation coefficients as low as 3.9%/-1.18%, a threshold power as low as 10-9 W, and 3 × 106 s retention and 107 cycle endurance behaviors can be maintained. The recognition accuracy for Modified National Institute of Standards and Technology (MNIST) handwriting is as high as 96.87%, attributed to the high linearity of the iterative updating of synaptic weights. The demodulation and storage functions of the American Standard Code for Information Interchange (ASCII) are demonstrated by programmable pulse modulation. Notably, the transmission electron microscopy (TEM) images allow the observation of carbon conductive filament paths formed in the low resistance state. First-principles calculations analyze the energetics of defects involved in the diffusion of carbon atoms into MoTe2 films. This work presents a novel guideline for studying memristor-based neuromorphic computing.

Highly Reliable Performance of Flexible Synaptic Devices Based on PVP-GO QD Nanocomposites Due to the Formation of Directional Filaments

The metallic conductive filament (CF) model, which serves as an important conduction mechanism for realizing synaptic functions in electronic devices, has gained recognition and is the subject of extensive research. However, the formation of CFs within the active layer is plagued by issues such as uncontrolled and random growth, which severely impacts the stability of the devices. Therefore, controlling the growth of CFs and improving the performance of the devices have become the focus of that research. Herein, a synaptic device based on polyvinylpyrrolidone (PVP)/graphene oxide quantum dot (GO QD) nanocomposites is proposed. Doping GO QDs in the PVP provides a large number of active centers for the reduction of silver ions, which allows, to a certain extent, the growth of CFs to be controlled. Because of this, the proposed device can simulate a variety of synaptic functions, including the transition from long-term potentiation to long-term depression, paired-pulse facilitation, post-tetanic potentiation, transition from short-term memory to long-term memory, and the behavior of the "learning experience". Furthermore, after being bent repeatedly, the devices were still able to simulate multiple synaptic functions accurately. Finally, the devices achieved a high recognition accuracy rate of 89.39% in the learning and inference tests, producing clear digit classification results.

Memristor-Based Artificial Chips

Memristors, promising nanoelectronic devices with in-memory resistive switching behavior that is assembled with a physically integrated core processing unit (CPU) and memory unit and even possesses highly possible multistate electrical behavior, could avoid the von Neumann bottleneck of traditional computing devices and show a highly efficient ability of parallel computation and high information storage. These advantages position them as potential candidates for future data-centric computing requirements and add remarkable vigor to the research of next-generation artificial intelligence (AI) systems, particularly those that involve brain-like intelligence applications. This work provides an overview of the evolution of memristor-based devices, from their initial use in creating artificial synapses and neural networks to their application in developing advanced AI systems and brain-like chips. It offers a broad perspective of the key device primitives enabling their special applications from the view of materials, nanostructure, and mechanism models. We highlight these demonstrations of memristor-based nanoelectronic devices that have potential for use in the field of brain-like AI, point out the existing challenges of memristor-based nanodevices toward brain-like chips, and propose the guiding principle and promising outlook for future device promotion and system optimization in the biomedical AI field.

Noncytotoxic WORM Memory Using Lysozyme with Ultrahigh Stability for Transient and Sustainable Electronics Applications

Biocompatibility and transient nature of electronic devices have been the matter of attention in recent times due to their immense potential for sustainable solutions toward hazardous e-wastes. In order to fulfill the requirement of high-density data-storage devices due to explosive growth in digital data, a resistive switching (RS)-based memory device could be the promising alternative to the present Si-based electronics. In this research work, we employed a biocompatible enzymatic protein lysozyme (Lyso) as the active layer to design a RS memory device having a device structure Au/Lyso/ITO. Interestingly the device showed transient, WORM memory behavior. It has been observed that the WORM memory performance of the device was very good with high memory window (2.78 × 102), data retention (up to 300 min), device yield (∼73.8%), read cyclability, as well as very high device stability (experimentally >700 days, extrapolated to 3000 days). Bias-induced charge trapping followed by conducting filament formation was the key behind such switching behavior. Transient behavior analysis showed that electronic as well as optical behaviors completely disappeared after 10 s dissolution of the device in luke warm water. Cytotoxicity of the as-prepared device was tested by challenging two environmentally derived bacteria, S. aureus and P. aeruginosa, and was found to have no biocidal effects. Hence, the device would cause no harm to the microbial flora when it is discarded. As a whole, this work suggests that Lyso-based WORM memory device could play a key role for the design of transient WORM memory device for sustainable electronic applications.

Multilevel Reset Dependent Set of a Biodegradable Memristor with Physically Transient

The electronic device, with its biocompatibility, biodegradability, and ease of fabrication process, shows great potential to embed into health monitoring and hardware data security systems. Herein, polyvinylpyrrolidone (PVP) biopolymer is presented as an active layer, electrochemically active magnesium (Mg) as a metal electrode, and chitosan-based substrate (CHS) to fabricate biocompatible and biodegradable physically transient neuromorphic device (W/Mg/PVP/Mg/CHS). The I-V curve of device is non-volatile bipolar in nature and shows a unique compliance-induced multilevel RESET-dependent-SET behavior while sweeping the compliance current from a few microamperes to milliamperes. Non-volatile and stable switching properties are demonstrated with a long endurance test (100 sweeps) and retention time of over 104  s. The physically transient memristor (PTM) has remarkably high dynamic RON /ROFF (ON/OFF state resistance) ratio (106 Ω), and when placed in deionized (DI) water, the device is observed to completely dissolve within 10 min. The pulse transient measurements demonstrate the neuromorphic computation capabilities of the device in the form of excitatory post synaptic current (EPSC), potentiation, depression, and learning behavior, which resemble the biological function of neurons. The results demonstrate the potential of W/Mg/PVP/Mg/CHS device for use in future healthcare and physically transient electronics.

Gradual conductance modulation by defect reorganization in amorphous oxide memristors

Amorphous oxides show great prospects in revolutionizing memristors benefiting from their abundant non-stoichiometric composition. However, an in-depth investigation of the memristive characteristics in amorphous oxides is inadequate and the resistive switching mechanism is still controversial. In this study, aiming to clearly understand the gradual conductance modulation that is deeply bound to the evolution of defects-mainly oxygen vacancies, forming-free memristors based on amorphous ZnAlSnO are fabricated, which exhibit high reproducibility with an initial low-resistance state. Pulse depression reveals the logarithmic-exponential mixed relaxation during RESET owing to the diffusion of oxygen vacancies in orthogonal directions. The remnants of conductive filaments formed through aggregation of oxygen vacancies induced by high-electric-field are identified using ex situ TEM. Especially, the conductance of the filament, including the remnant filament, is larger than that of the hopping conductive channel derived from the diffusion of oxygen vacancies. The Fermi level in the conduction band rationalizes the decay of the high resistance state. Rare oxidation-migration of Au occurs upon device failure, resulting in numerous gold nanoclusters in the functional layer. These comprehensive revelations on the reorganization of oxygen vacancies could provide original ideas for the design of memristors.

Rationally Designing High-Performance Versatile Organic Memristors through Molecule-Mediated Ion Movements

Organic memory has attracted tremendous attention for next-generation electronic elements for the molecules' striking ease of structural design. However, due to them being hardly controllable and their low ion transport, it is always essential and challenge to effectively control their random migration, pathway, and duration. There are very few effective strategies, and specific platforms with a view to molecules with specific coordination-groups-regulating ions have been rarely reported. In this work, as a generalized rational design strategy, the well-known tetracyanoquinodimethane (TCNQ) is introduced with multiple coordination groups and small plane structure into a stable polymers framework to modulate Ag migration and then achieve high-performance devices with ideal productivity, low operation voltage and power, stable switching cycles, and state retention. Raman mapping demonstrates that the migrated Ag can specially coordinate with the embedded TCNQ molecules. Notably, the TCNQ molecule distribution can be modulated inside the polymer framework and regulate the memristive behaviors through controlling the formed Ag conductive filaments (CFs) as demonstrated by Raman mapping, in situ conductive atomic force microscopy (C-AFM), X-ray diffraction (XRD) and depth-profiling X-ray photoelectron spectroscopy (XPS). Thus the controllable molecule-mediated Ag movements show its potential in rationally designing high-performance devices and versatile functions and is enlightening in constructing memristors with molecule-mediated ion movements.

Double-Forming Mechanism of TaOx-Based Resistive Memory Device and Its Synaptic Applications

The bipolar resistive switching properties of Pt/TaOx/InOx/ITO-resistive random-access memory devices under DC and pulse measurement conditions are explored in this work. Transmission electron microscopy and X-ray photoelectron spectroscopy were used to confirm the structure and chemical compositions of the devices. A unique two-step forming process referred to as the double-forming phenomenon and self-compliance characteristics are demonstrated under a DC sweep. A model based on oxygen vacancy migration is proposed to explain its conduction mechanism. Varying reset voltages and compliance currents were applied to evaluate multilevel cell characteristics. Furthermore, pulses were applied to the devices to demonstrate the neuromorphic system's application via testing potentiation, depression, spike-timing-dependent plasticity, and spike-rate-dependent plasticity.

Covalent Organic Frameworks for Neuromorphic Devices

Neuromorphic computing could enable the potential to break the inherent limitations of conventional von Neumann architectures, which has led to widespread research interest in developing novel neuromorphic memory devices, such as memristors and bioinspired artificial synaptic devices. Covalent organic frameworks (COFs), as crystalline porous polymers, have tailorable skeletons and pores, providing unique platforms for the interplay with photons, excitons, electrons, holes, ions, spins, and molecules. Such features encourage the rising research interest in COF materials in neuromorphic electronics. To develop high-performance COF-based neuromorphic memory devices, it is necessary to comprehensively understand materials, devices, and applications. Therefore, this Perspective focuses on discussing the use of COF materials for neuromorphic memory devices in terms of molecular design, thin-film processing, and neuromorphic applications. Finally, we provide an outlook for future directions and potential applications of COF-based neuromorphic electronics.

Neotype kuramite optoelectronic memristor for bio-synaptic plasticity simulations

Memristive devices with both electrically and optically induced synaptic dynamic behaviors will be crucial to the accomplishment of brain-inspired neuromorphic computing systems, in which the resistive materials and device architectures are two of the most important cornerstones, but still under challenge. Herein, kuramite Cu3SnS4 is newly introduced into poly-methacrylate as the switching medium to construct memristive devices, and the expected high-performance bio-mimicry of diverse optoelectronic synaptic plasticity is demonstrated. In addition to the excellent basic performances, such as stable bipolar resistive switching with On/Off ratio of ∼486, Set/Reset voltage of ∼-0.88/+0.96 V, and good retention feature of up to 104 s, the new designs of memristors possess not only the multi-level controllable resistive-switching memory property but also the capability of mimicking optoelectronic synaptic plasticity, including electrically and visible/near-infrared light-induced excitatory postsynaptic currents, short-/long-term memory, spike-timing-dependent plasticity, long-term plasticity/depression, short-term plasticity, paired-pulse facilitation, and "learning-forgetting-learning" behavior as well. Predictably, as a new class of switching medium material, such proposed kuramite-based artificial optoelectronic synaptic device has great potential to be applied to construct neuromorphic architectures in simulating human brain functions.

Pseudo-transistors for emerging neuromorphic electronics

Artificial synaptic devices are the cornerstone of neuromorphic electronics. The development of new artificial synaptic devices and the simulation of biological synaptic computational functions are important tasks in the field of neuromorphic electronics. Although two-terminal memristors and three-terminal synaptic transistors have exhibited significant capabilities in the artificial synapse, more stable devices and simpler integration are needed in practical applications. Combining the configuration advantages of memristors and transistors, a novel pseudo-transistor is proposed. Here, recent advances in the development of pseudo-transistor-based neuromorphic electronics in recent years are reviewed. The working mechanisms, device structures and materials of three typical pseudo-transistors, including tunneling random access memory (TRAM), memflash and memtransistor, are comprehensively discussed. Finally, the future development and challenges in this field are emphasized.

In Situ Synthesis of Two-Dimensional Lateral Semiconducting-Mo:Se//Metallic-Mo Junctions Using Controlled Diffusion of Se for High-Performance Large-Scaled Memristor

Two-dimensional (2D) materials are favorable candidates for resistive memories in high-density nanoelectronics owing to their ultrathin scaling and controllable interfacial characteristics. However, high processing temperatures and difficulties in mechanical transfer are intriguing challenges associated with their implementation in large areas with crossbar architecture. A high processing temperature may damage the electrical functionalities of the bottom electrode, and mechanical transfer of 2D materials may introduce undesirable microscopic defects and macroscopic discontinuities. In this study, an in situ fabrication of an electrode and 2D-molybdenum diselenide (MoSe₂) is reported. The controlled diffusion of selenium (Se) in the predeposited molybdenum (Mo) produces Mo//Mo:Se stacks with a few layers of MoSe₂ on top and MoSe_x on the bottom. Diffusion-assisted Mo//Mo:Se fabrication is observed over a large area (4 in. wafer). Additionally, a 5 × 5 array of crossbar memristors (Mo//Mo:Se//Ag) is fabricated using the diffusion of Se in patterned Mo. These memristors exhibit a small switching voltage (∼1.1 V), high endurance (>250 cycles), and excellent retention (>15 000 s) with minimum cycle-to-cycle and device-to-device variation. Thus, the proposed nondestructive in situ technique not only simplifies the fabrication but also minimizes the number of required stages.

A Highly Crystalline Single Layer 2D Polymer for Low Variability and Excellent Scalability Molecular Memristors

Large-scale growth of highly crystalline single layer 2D polymers (SL-2DPs) and their subsequent integration into memristors is key to advancing the development of high-density data storage devices. However, leakage problems resulting from the porous structure of 2DPs continue to make such advances extremely challenging. Herein, we overcome this issue by incorporating long alkoxy chains into key molecular building blocks to obtain a highly crystalline 2DP, as visualized by scanning tunneling microscopy, and prevent metal permeation in the subsequent device fabrication process. SL-2DP memristors constructed via direct evaporation of the top electrodes exhibit low variability (σ_Vset  = 0.14) due to the single-monomer-thick feature together with the high regular structure and coordination ability which minimizes the stochastic spatial distribution of conductive filaments (CFs) in both vertical and lateral dimensions. The variability is further decreased to 0.04 by confining the formation and fracture of CFs to the interface through the utilization of bilayer junctions. Using peak force tunneling atomic force microscopy, the nanometer scalability (< 50 nm² ) and low power consumption of these molecular memristor devices are demonstrated.

Directional Formation of Conductive Filaments for a Reliable Organic-Based Artificial Synapse by Doping Molybdenum Disulfide Quantum Dots into a Polymer Matrix

The conductive filament (CF) model, as an important means to realize synaptic functions, has received extensive attention and has been the subject of intense research. However, the random and uncontrollable growth of CFs seriously affects the performances of such devices. In this work, we prepared a neural synaptic device based on polyvinyl pyrrolidone-molybdenum disulfide quantum dot (MoS₂ QD) nanocomposites. The doping with MoS₂ QDs was found to control the growth mode of Ag CFs by providing active centers for the formation of Ag clusters, thus reducing the uncertainty surrounding the growth of Ag CFs. As a result, the device, with a low power consumption of 32.8 pJ/event, could be used to emulate a variety of synaptic functions, including long-term potentiation (LTP), long-term depression (LTD), paired-pulse facilitation, post-tetanic potentiation, short-term memory to long-term memory conversion, and "learning experience" behavior. After having undergone consecutive stimulation with different numbers of pulses, the device stably realized a "multi-level LTP to LTD conversion" function. Moreover, the synaptic characteristics of the device experienced no degradation due to mechanical stress. Finally, the simulation result based on the synaptic characteristics of our devices achieved a high recognition accuracy of 91.77% in learning and inference tests and showed clear digital classification results.

High-Performance Flexible Polymer Memristor Based on Stable Filamentary Switching

Polymer-based atomic switch memristors via the formation/dissolution of atomic-scale conductive filaments are considered as the leading candidate for next-generation nonvolatile memory. However, the instability of conductive filaments of incomplete bridge makes their switching performances unsatisfied. In this work, we report a flexible polymeric memristor using polyethylenimine incorporated with silver salt. The memristor device exhibited superior performances at room temperature with a favorable endurance, high ON/OFF ratio, good retention, and low operating voltage. These satisfactory performances are attributed to the pre-existing Ag ions in the polymer, guiding the formation of a robust Ag filament. In addition, the device shows stable bipolar switching behavior in bending conditions or after hundreds of bending cycles. In our work, we provide a simple and efficient method to construct robust filament-based memristors for flexible electronics.

A Bioinspired Artificial Injury Response System Based on a Robust Polymer Memristor to Mimic a Sense of Pain, Sign of Injury, and Healing

Flexible electronic skin with features that include sensing, processing, and responding to stimuli have transformed human-robot interactions. However, more advanced capabilities, such as human-like self-protection modalities with a sense of pain, sign of injury, and healing, are more challenging. Herein, a novel, flexible, and robust diffusive memristor based on a copolymer of chlorotrifluoroethylene and vinylidene fluoride (FK-800) as an artificial nociceptor (pain sensor) is reported. Devices composed of Ag/FK-800/Pt have outstanding switching endurance >10⁶  cycles, orders of magnitude higher than any other two-terminal polymer/organic memristors in literature (typically 10² -10³ cycles). In situ conductive atomic force microscopy is employed to dynamically switch individual filaments, which demonstrates that conductive filaments correlate with polymer grain boundaries and FK-800 has superior morphological stability under repeated switching cycles. It is hypothesized that the high thermal stability and high elasticity of FK-800 contribute to the stability under local Joule heating associated with electrical switching. To mimic biological nociceptors, four signature nociceptive characteristics are demonstrated: threshold triggering, no adaptation, relaxation, and sensitization. Lastly, by integrating a triboelectric generator (artificial mechanoreceptor), memristor (artificial nociceptor), and light emitting diode (artificial bruise), the first bioinspired injury response system capable of sensing pain, showing signs of injury, and healing, is demonstrated.

Site-Specific Regulated Memristors via Electron-Beam-Induced Functionalization of HfO2

Emerging nonvolatile resistive switching, also known as the memristor, works with a distinct concept that relies mainly on the change in the composition of the active materials, rather than to store the charge. Particularly for oxide-based memristors, the switching is often governed by the random and unpredicted temporal/spatial migration of oxygen defects, resulting in possessing limitations in terms of control over conduction channel formation and inability to regulate hysteresis loop opening. Therefore, site specific dynamic control of defect concentration in the active materials can offer a unique opportunity to realize on-demand regulation of memory storage and artificial intelligence capabilities. Here, high-performance, site-specific spatially scalable memristor devices are fabricated by stabilizing the conduction channel via manipulation of oxygen defects using electron-beam irradiation. Specifically, the memristors exhibit highly stable and electron-beam dose-regulated multilevel analog hysteresis loop opening with adjustable switching ratios even higher than 10⁴ . Additionally, broad modulation of neural activities, including short- and long-term plasticity, paired-pulse facilitation, spike-timing-dependent plasticity, and dynamic multipattern memory processing, are demonstrated. The work opens a new possibility to regulate the resistive switching behavior and control mimicking of neural activities, providing a hitherto unseen tunability in two-terminal oxide-based memristors.

Solution-Processed Light Induced Multilevel Non-volatile Wearable Memory Device Based on CsPb2Br5 Perovskite

Despite of the recent advancements on memory devices, quest for the building materials having low-power consumption is still on with the ultimate focus over durability of system and reliability and...

Natural Acidic Polysaccharide-Based Memristors for Transient Electronics: Highly Controllable Quantized Conductance for Integrated Memory and Nonvolatile Logic Applications

As a leading candidate for further memory and computing applications, memristors are being developed in an important direction of transient electronics. Herein, wafer-scale acidic polysaccharide thin films are reported as promising materials for memristors with remarkable transient characteristics. The memristor shows freestanding and lightweight features, and can be fully dissolved in deionized water within 3.5 s. More importantly, the ion-confinement capability of acidic polysaccharides where the cations can interact with the ionizable acid groups enables atomic manipulation of conductive filament. As a result, (i) a single device can produce 16 highly controllable and independent quantized conductance (QC) states with quasi-nonvolatile and nonvolatile characteristics and (ii) QC switching can be performed with ultrafast speed (2-5 ns) and low energy consumption (0.6-16 pJ). These remarkable features make the memristor promising for fast, low-power, and high-density memory and computing applications. Based on QC switching, the encoding/decoding and nonvolatile basic Boolean logic are designed and implemented. More importantly, "stateful" material implication logic which is promising for future in-memory computing is demonstrated with QC switching. These results significantly advance acidic polysaccharides to develop nanodevices with quantum effects.

Stimuli-Responsive Memristive Materials for Artificial Synapses and Neuromorphic Computing

Neuromorphic computing holds promise for building next-generation intelligent systems in a more energy-efficient way than the conventional von Neumann computing architecture. Memristive hardware, which mimics biological neurons and synapses, offers high-speed operation and low power consumption, enabling energy- and area-efficient, brain-inspired computing. Here, recent advances in memristive materials and strategies that emulate synaptic functions for neuromorphic computing are highlighted. The working principles and characteristics of biological neurons and synapses, which can be mimicked by memristive devices, are presented. Besides device structures and operation with different external stimuli such as electric, magnetic, and optical fields, how memristive materials with a rich variety of underlying physical mechanisms can allow fast, reliable, and low-power neuromorphic applications is also discussed. Finally, device requirements are examined and a perspective on challenges in developing memristive materials for device engineering and computing science is given.

Towards High-Performance Resistive Switching Behavior through Embedding a D-A System into 2D Imine-Linked Covalent Organic Frameworks

Developing new materials for the fabrication of resistive random-access memory is of great significance in this period of big data. Herein, we present a novel design strategy of embedding donor (D) and acceptor (A) fragments into imine-linked frameworks to construct resistive switching covalent organic frameworks (COFs) for high-performance memristors. Two D-A-type two-dimensional COFs, COF-BT-TT and COF-TT-TVT, were designed and synthesized using a conventional solvothermal approach, and high-quality thin films of these materials deposited on ITO substrate exhibited great potential as an active layer for memristors. Rewritable memristors based on 100 nm thick COF-TT-BT and COF-TT-TVT films showed a high ON/OFF current ratio (ca. 10⁵ and 10⁴ ) and low driving voltage (1.30 and 1.60 V). The cycle period and retention time for COF-TT-BT-based rewritable devices were as high as 319 cycles and 3.3×10⁴  s at a constant voltage of 0.1 V (160 cycles and 1.2×10⁴  s for the COF-TT-TVT memristor).

Advances in Flexible Memristors with Hybrid Perovskites

Hybrid organic-inorganic metal halide perovskite (HOIP)-based memristors have captured strong attention not only as an emerging candidate for next-generation high-density information storage technology but also for use in healthcare technology and the Internet of Things (IoT) because of their unique properties: low weight, flexibility, compatibility, stretchability, and low power consumption. In this Perspective, we review the recent advances of various aspects of flexible memristors focusing on the selection of the flexible substrates, materials, interfaces, several resistive switching mechanisms, and different methodologies of perovskite growth. The current state of the art of the memristor as an artificial synapse, light-induced resistive switching, and logic gates is comprehensively and systematically reviewed. Finally, we briefly discuss the stability factors of perovskites and present the conclusion with a broad outlook on the progress and challenges in the field of perovskite-based flexible memristors.

Stacked Two-Dimensional MXene Composites for an Energy-Efficient Memory and Digital Comparator

Two-dimensional MXene has enormous potential for application in industry and academia owing to its surface hydrophilicity and excellent electrochemical properties. However, the application of MXene in optoelectronic memory and logical computing is still facing challenges. In this study, an optoelectronic resistive random access memory (RRAM) based on silver nanoparticles (Ag NPs)@MXene-TiO₂ nanosheets (AMT) was prepared through a low-cost and facile hydrothermal oxidation process. The fabricated device exhibited a typical bipolar switching behavior and controllable SET voltage. Furthermore, we successfully demonstrated a 4-bit in-memory digital comparator with AMT RRAMs, which can replace five logic gates in a traditional approach. The AMT-based digital comparator may open the door for future integrated functions and applications in optoelectronic data storage and simplify the complex logic operations.

Boost of the Bio-memristor Performance for Artificial Electronic Synapses by Surface Reconstruction

Biomaterial-based memristors (bio-memristors) are often adopted to emulate biological synapse functions and applied to construct neural computing networks in brain-inspired chip systems. However, the randomness of conductive filament formation in bio-memristors inhibits their switching performance by causing the dispersion of the device-switching parameters. In this case, a facile porous silk fibroin (p-SF) memristor was obtained through a protein surface reconstruction strategy, in which the size of the hole can be adjusted by the density of hybrid nanoseeds. The porous SF memristors exhibit greatly enhanced electrical characteristics, including uniform I-V cycles, centralized distribution of the switching voltages, and both high and low resistances, compared to devices without pores. The results of three-dimensional (3D) simulations based on classical density functional theory (cDFT) suggest that the reconstructed pores in the SF layers guide the formation and fracture of Ag filaments under an electric field and enhance the overall conductivity by separating Ag⁺ ion and electron diffusion pathways. Ag⁺ ions are predicted to preferentially diffuse through pores, whereas electrons diffuse through the SF network. Interestingly, the device conductance can be bidirectionally modulated gradually by positive and negative voltages, can faithfully simulate short-term and long-term plasticity, and can even realize the triplet-spike-timing-dependent plasticity (triplet-STDP) rule, which can be used for pattern recognition in biological systems. The simulation results reveal that a memristor network of this type has an accuracy of ∼95.78% in memory learning and the capability of pattern learning. This work provides a facile technology route to improve the performance of bionic-material memristors.

Down-Scalable and Ultra-fast Memristors with Ultra-high Density Three-Dimensional Arrays of Perovskite Quantum Wires

With strikingly high speed, data retention ability and storage density, resistive RAMs have emerged as a forerunning nonvolatile memory. Here we developed a Re-RAM with ultra-high density array of monocrystalline perovskite quantum wires (QWs) as the switching matrix with a metallic silver conducting pathway. The devices demonstrated high ON/OFF ratio of ∼10⁷ and ultra-fast switching speed of ∼100 ps which is among the fastest in literature. The devices also possess long retention time of over 2 years and record high endurance of ∼6 × 10⁶ cycles for all perovskite Re-RAMs reported. As a concept proof, we have also successfully demonstrated a flexible Re-RAM crossbar array device with a metal-semiconductor-insulator-metal design for sneaky path mitigation, which can store information with long retention. Aggressive downscaling to ∼14 nm lateral dimension produced an ultra-small cell effectively having 76.5 nm² area for single bit storage. Furthermore, the devices also exhibited unique optical programmability among the low resistance states.

Optically tunable ultra-fast resistive switching in lead-free methyl-ammonium bismuth iodide perovskite films

Resistive RAMs (Re-RAMs) have come to the fore as a rising star among the next generation non-volatile memories with fast operational speed, excellent endurance and prolonged data retention capabilities. Re-RAMs are being profusely used as storage and processing modules in neuromorphic hardware and high frequency switches in radio-frequency (RF) circuits. Owing to its intrinsic hysteresis and abundance of charge migration pathways, lead halide perovskites have emerged as a promising switching medium in Re-RAMs besides their ubiquitous usage in optoelectronic devices. Here, we adopted a lead-free eco-friendly methyl-ammonium bismuth iodide (MA₃Bi₂I₉) perovskite (prepared by solvent-free engineering) as the switching medium sandwiched between copper (Cu) and indium doped tin oxide (ITO) electrodes. The devices exhibited a 10⁴ high ON/OFF ratio that provided a large window for the multi-bit data storage in a single cell with good accuracy. Robust endurance of 1730 cycles and good data retention ability of >3 × 10⁵ s were also observed. Careful switching speed measurements showed the devices can operate with an ultra-fast speed of 10 ns for writing and erasing respectively. The devices responded to light illumination and the prolonged retention of the opto-electrically tuned resistance states paved the way for image memorization.

A Monochloro Copper Phthalocyanine Memristor with High-Temperature Resilience for Electronic Synapse Applications

Memristors are considered to be one of the most promising device concepts for neuromorphic computing, in particular thanks to their highly tunable resistive states. To realize neuromorphic computing architectures, the assembly of large memristive crossbar arrays is necessary, but is often accompanied by severe heat dispassion. Organic materials can be tailored with on-demand electronic properties in the context of neuromorphic applications. However, such materials are more susceptible to heat, and detrimental effects such as thermally induced degradation directly lead to failure of device operation. Here, an organic memristive synapse formed of monochloro copper phthalocyanine, which remains operational and capable of memristive switching at temperatures as high as 300 °C in ambient air without any encapsulation, is demonstrated. The change in the electrical conductance is found to be a result of ion movement, closely resembling what takes place in biological neurons. Furthermore, the high viability of this approach is showcased by demonstrating flexible memristors with stable switching behaviors after repeated mechanical bending as well as organic synapses capable of emulating a trainable and reconfigurable memristor array for image information processing. The results set a precedent for thermally resilient organic synapses to impact organic neuromorphic devices in progressing their practicality.

Reliable organic memristors for neuromorphic computing by predefining a localized ion-migration path in crosslinkable polymer

In flexible neuromorphic systems for realizing artificial intelligence, organic memristors are essential building blocks as artificial synapses to perform information processing and memory. Despite much effort to implement artificial neural networks (ANNs) using organic memristors, the reliability of these devices is inherently hampered by global ion transportation and arbitrary growth of conductive filaments (CFs). As a result, the performance of ANNs is restricted. Herein, a novel concept for confining CF growth in organic memristors is demonstrated by exploiting the unique functionality of crosslinkable polymers. This can be achieved by predefining the localized ion-migration path (LIP) in crosslinkable polymers. In the proposed organic memristor, metal cations are locally transported along the LIP. Thus, CF growth is achieved only in a confined region. A flexible memristor with an LIP exhibits a vastly improved reliability and uniformity, and it is capable of operating with high mechanical and electrical endurance. Moreover, neuromorphic arrays based on the proposed memristor exhibit 96.3% learning accuracy, which is comparable to the ideal software baseline. The proposed concept of predefining the LIP in organic memristors is expected to provide novel platforms for the advance of flexible electronics and to realize a variety of practical neural networks for artificial intelligence applications.

Toward Controlling Filament Size and Location for Resistive Switches via Nanoparticle Exsolution at Oxide Interfaces

Memristive devices are among the most prominent candidates for future computer memory storage and neuromorphic computing. Though promising, the major hurdle for their industrial fabrication is their device-to-device and cycle-to-cycle variability. These occur due to the random nature of nanoionic conductive filaments, whose rupture and formation govern device operation. Changes in filament location, shape, and chemical composition cause cycle-to-cycle variability. This challenge is tackled by spatially confining conductive filaments with Ni nanoparticles. Ni nanoparticles are integrated on the bottom La_0.2 Sr_0.7 Ti_0.9 Ni_0.1 O_{3- δ} electrode by an exsolution method, in which, at high temperatures under reducing conditions, Ni cations migrate to the perovskite surface, generating metallic nanoparticles. This fabrication method offers fine control over particle size and density and ensures strong particle anchorage in the bottom electrode, preventing movement and agglomeration. In devices based on amorphous SrTiO₃ , it is demonstrated that as the exsolved Ni nanoparticle diameter increases up to ≈50 nm, the ratio between the ON and OFF resistance states increases from single units to 180 and the variability of the low resistance state reaches values below 5%. Exsolution is applied for the first time to engineer solid-solid interfaces extending its realm of application to electronic devices.

Anomalous Photoinduced Reconstructing and Dark Self-Healing Processes on Bi2O2S Nanoplates

We report an anomalous photoinduced reconstructing and dark self-healing process on Bi₂O₂S nanoplates by monitoring the time profile of open-circuit potential (OCP). When the light was switched on and off on the nanoplates, we observed pronounced and repeatable decrement-recovery cycles of the OCP signal, which are inexplicable by a rapid electron-hole separation-recombination process only as in a conventional semiconductor. It is proposed that upon irradiation, accumulation of photogenerated holes at the electrode surface caused oxidation of the S layers of Bi₂O₂S nanoplates into certain intermediates, which, when the light was turned off, were then reduced back to the original state by the electron back flow. Raman scattering spectroscopy provided te S-S vibrational signature of the intermediate, evidencing the hole oxidative dimerization of the S^2- species and the inverse reductive S-S dissociation process. The photophysics and photochemistry of semiconductor nanoplates reported here may inspire the development of energy devices, switches, and memristors.

Stimuli-Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives

Brain-inspired neuromorphic computing is intended to provide effective emulation of the functionality of the human brain via the integration of electronic components. Recent studies of synaptic plasticity, which represents one of the most significant neurochemical bases of learning and memory, have enhanced the general comprehension of how the brain functions and have thereby eased the development of artificial neuromorphic devices. An understanding of the synaptic plasticity induced by various types of stimuli is essential for neuromorphic system construction. The realization of multiple stimuli-enabled synapses will be important for future neuromorphic computing applications. In this Review, state-of-the-art synaptic devices with particular emphasis on their synaptic behaviors under excitation by a variety of external stimuli are summarized, including electric fields, light, magnetic fields, pressure, and temperature. The switching mechanisms of these synaptic devices are discussed in detail, including ion migration, electron/hole transfer, phase transition, redox-based resistive switching, and other mechanisms. This Review aims to provide a comprehensive understanding of the operating mechanisms of artificial synapses and thus provides the principles required for design of multifunctional neuromorphic systems with parallel processing capabilities.

Robust DNA-Bridged Memristor for Textile Chips

Electronic textiles may revolutionize many fields, such as communication, health care and artificial intelligence. To date, unfortunately, computing with them is not yet possible. Memristors are compatible with the interwoven structure and manufacturing process in textiles because of its two-terminal crossbar configuration. However, it remains a challenge to realize textile memristors owing to the difficulties in designing advanced memristive materials and achieving high-quality active layers on fiber electrodes. Herein we report a robust textile memristor based on an electrophoretic-deposited active layer of deoxyribonucleic acid (DNA) on fiber electrodes. The unique architecture and orientation of DNA molecules with the incorporation of Ag nanoparticles offer the best-in-class performances, e.g., both ultra-low operation voltage of 0.3 V and power consumption of 100 pW and high switching speed of 20 ns. Fundamental logic calculations such as implication and NAND are demonstrated as functions of textile chips, and it has been thus integrated with power-supplying and light emitting modules to demonstrate an all-fabric information processing system.

Multifunctional Polymer Memory via Bi-Interfacial Topography for Pressure Perception Recognition

Emerging memory devices, that can provide programmable information recording with tunable resistive switching under external stimuli, hold great potential for applications in data storage, logic circuits, and artificial synapses. Realization of multifunctional manipulation within individual memory devices is particularly important in the More-than-Moore era, yet remains a challenge. Here, both rewritable and nonerasable memory are demonstrated in a single stimuli-responsive polymer diode, based on a nanohole-nanowrinkle bi-interfacial structure. Such synergic nanostructure is constructed from interfacing a nanowrinkled bottom graphene electrode and top polymer matrix with nanoholes; and it can be easily prepared by spin coating, which is a low-cost and high-yield production method. Furthermore, the resulting device, with ternary and low-power operation under varied external stimuli, can enable both reversible and irreversible biomimetic pressure recognition memories using a device-to-system framework. This work offers both a general guideline to fabricate multifunctional memory devices via interfacial nanostructure engineering and a smart information storage basis for future artificial intelligence.

Self-Compliance and High Performance Pt/HfOx/Ti RRAM Achieved through Annealing

A self-compliance resistive random access memory (RRAM) achieved through thermal annealing of a Pt/HfO_x/Ti structure. The electrical characteristic measurements show that the forming voltage of the device annealing at 500 °C decreased, and the switching ratio and uniformity improved. Tests on the device’s cycling endurance and data retention characteristics found that the device had over 1000 erase/write endurance and over 10⁵ s of lifetime (85 °C). The switching mechanisms of the devices before and after annealing were also discussed.

Surface Functionalization of Single-Layered Ti3C2Tx MXene and Its Application in Multilevel Resistive Memory

MXenes are a new type of two-dimensional material, and they have attracted extensive attention because of their outstanding conductivity and rich surface functional groups that make surface engineering easy and possible for adapting to diverse applications. However, there are scarce studies on surface engineering of MXene. Herein, we demonstrate for the first time that octylphosphonic acid-modified Ti₃C₂T_x MXene can be used as an active layer for memory devices and exhibits stable ternary memory behavior. Low threshold voltage, steady retention time, clearly distinguishable resistance states, high ON/OFF rate, OFF/ON1/ON2 = 1:10^2.7:10^4.1, and considerable ternary yield (58%) were obtained. In the proof of the mechanism, in situ conductive atomic force microscopy was conducted and the electrode-area relationship was analyzed to demonstrate that charge trapping and filament conduction are more suitable in the nonvolatile information memory of Ti₃C₂T_x-OP MXene devices. In addition, a polyethylene-terephthalate-based flexible Ti₃C₂T_x-OP memory device can maintain its stable ternary memory performance after being bent 5000 times. This work provides an easy method for surface modification of MXene and broadens the field of MXene.

Hierarchical Hollow-Pore Nanostructure Bilayer Heterojunction Comprising Conjugated Polymers for High-Performance Flash Memory

We report the design and preparation of hierarchical hollow-pore nanostructure bilayer conjugated polymer films for high-performance resistive memory devices. By taking the merits of chemical and structural stabilities of a two-dimensional conjugated microporous polymer (2D CMP), a poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) film with a hollow surface was spin-coated onto 2D CMP nanofilm directly, constructing a bilayer heterojunction. A two-terminal diode with a configuration of indium tin oxide/2D CMP/hollow MEH-PPV/Al was fabricated by employing the prepared bilayer heterojunction. The device poses flash feature with a high on/off ratio (>10⁵) and a long retention time (>3.0 × 10⁴ s), which is higher than that of most of the reported conjugated polymers memories. Our work offers a general guideline to construct high on/off ratio polymer memories via hierarchical nanostructure engineering in memristive layer.

Memristive synapses with high reproducibility for flexible neuromorphic networks based on biological nanocomposites

Memristive synapses from biomaterials are promising for building flexible and implantable artificial neuromorphic systems due to their remarkable mechanical and biological properties. However, these biological devices have relatively poor memristive switching characteristics, and thus fail to meet the requirement of neuromorphic networks for high learning accuracy. Here, memristive synapses based on carrageenan nanocomposites that possess desirable characteristics are demonstrated. These devices show highly reproducible analog resistive switching behaviors with 250 conductance states, low write noise, good write linearity, high retention of more than 104 s and endurance for at least 106 pulses. The enhanced switching properties are attributed to controllable and confined conductive filament growth, owing to the synergistic effect of self-assembled silver nanocluster doping and nanocone-shaped electrode contact. Moreover, the devices exhibit excellent reliability after 1000 bending cycles. Simulations including the non-ideal factors prove that the synaptic device array can operate with an online learning accuracy of 94.3%. These findings enable broader applications of biomaterials in flexible memristive devices and neuromorphic systems.

Self-Assembled VO2 Mesh Film-Based Resistance Switches with High Transparency and Abrupt ON/OFF Ratio

Vanadium dioxide, a well-known phase transition material with abrupt resistance change during its transition temperature, is herein used to fabricate the transparent mesh film onto a glass slide through self-assembly mesh printing. A record high ON/OFF ratio up to 10⁴ is achieved together with high visible transmittance of 86% compared to the normal glass slide with visible transmittance at 88%. The high transparent properties make the resistive switches applicable for next-generation electronics, such as see-through computing device and beyond. A simple and scalable mesh printing approach-integrated phase change material may provide a promising way to fabricate transparent resistance switches for next-generation electronics.

Highly Robust Organometallic Small-Molecule-Based Nonvolatile Resistive Memory Controlled by a Redox-Gated Switching Mechanism

Although organic small-molecule-based memory devices (OSMDs) have been demonstrated to show great potential for the application in next-generation data-storage technology, progress toward their further development has been hugely hindered by the ambiguity of their electrical switching mechanism. Thus, purposely fabricating OSMDs with a definite switching behavior is very urgent. Here, we reported a redox-gated nonvolatile rewritable memory device using an organometallic small molecule as an active material. By introducing the redox-active ferrocene into an organic skeleton, the target small molecule exhibits reliable and robust FLASH-type bistable electrical characteristics with a clear redox-controlled switching mechanism, which leads to low operational voltages, good endurance, and long retention. Our study offers a proof-of-concept strategy to design controllable OSMDs with excellent performances.