A Unified Capacitive-Coupled Memristive Model for the Nonpinched Current-Voltage Hysteresis Loop

A study of the influence of the stability of the population's income and expenditure on the development of restaurant chains

This study examines the connection between the income of Chinese residents and the expansion of restaurant chains from 2005 to 2021. It employs multiple methodologies, such as an evaluation index system, the entropy value method, and the coupled coordination degree model. There are sixteen indicators divided into two groups: residents' income and expenditures, and restaurant chain expansion. The analysis reveals the following trends: instability from 2005 to 2009 as a result of the global financial crisis; regional disparities from 2010 to 2014; and coordinated development from 2015 to 2021 as a result of government policies that stimulate domestic demand. This research contributes to strategic planning and decision-making in the hotel, catering, and tourism industries by assessing the effect of Chinese residents' stable income and expenditures on restaurant chains.

Chirality-Induced Memristor of Chiral Nanostructured Half-Metallic Fe3O4 Films

Spintronic memristors, which combine the nonvolatile characteristics of memristors with the scalability of a spin-transfer torque device, are expected to play a crucial role in advancing quantitative information processing. This field commonly relies on magnetic tunnel junctions, domain wall motion, and spin waves. Here, the discovery of chirality-induced memristor behavior in chiral nanostructured Fe3O4 films (CNFFs) is reported. These CNFFs are grown on fluorine tin oxide (FTO) substrates using enantiomeric glutamic acid (Glu) as symmetry-breaking agents and consist of arrays of oriented twisted nanofibers. At 100 K, the L-CNFF exhibits memristor behavior as a pinched hysteresis loop in the I-V curve, while the D-CNFF exhibits semiconductor behavior with constant electrical resistance. The intrinsic spin polarization of half-metallic Fe3O4 and the chirality-induced spin selectivity (CISS) are speculated to contribute to the memristor in one handedness of the chiral structure. These findings present a novel spinristor that combines the functions of a memristor and a spin-filter based on chiral structures, which may promote the development of spintronic devices.

Hydrogel-Based Artificial Synapses for Sustainable Neuromorphic Electronics

Hydrogels find widespread applications in biomedicine because of their outstanding biocompatibility, biodegradability, and tunable material properties. Hydrogels can be chemically functionalized or reinforced to respond to physical or chemical stimulation, which opens up new possibilities in the emerging field of intelligent bioelectronics. Here, the state-of-the-art in functional hydrogel-based transistors and memristors is reviewed as potential artificial synapses. Within these systems, hydrogels can serve as semisolid dielectric electrolytes in transistors and as switching layers in memristors. These synaptic devices with volatile and non-volatile resistive switching show good adaptability to external stimuli for short-term and long-term synaptic memory effects, some of which are integrated into synaptic arrays as artificial neurons; although, there are discrepancies in switching performance and efficacy. By comparing different hydrogels and their respective properties, an outlook is provided on a new range of biocompatible, environment-friendly, and sustainable neuromorphic hardware. How potential energy-efficient information storage and processing can be achieved using artificial neural networks with brain-inspired architecture for neuromorphic computing is described. The development of hydrogel-based artificial synapses can significantly impact the fields of neuromorphic bionics, biometrics, and biosensing.

Capacitive and Inductive Characteristics of Volatile Perovskite Resistive Switching Devices with Analog Memory

With the increasing demands and complexity of the neuromorphic computing schemes utilizing highly efficient analog resistive switching devices, understanding the apparent capacitive and inductive effects in device operation is of paramount importance. Here, we present a systematic array of characterization methods that unravel two distinct voltage-dependent regimes demonstrating the complex interplay between the dynamic capacitive and inductive effects in volatile perovskite-based memristors: (1) a low voltage capacitance-dominant and (2) an inductance-dominant regime evidenced by the highly correlated hysteresis type with nonzero crossing, the impedance responses, and the transient current characteristics. These dynamic capacitance- and inductance-dominant regimes provide fundamental insight into the resistive switching of memristors governing the synaptic depression and potentiation functions, respectively. More importantly, the pulse width-dependent and long-term transient current measurements further demonstrate a dynamic transition from a fast capacitive to a slow inductive response, allowing for the tailored stimulus programming of memristor devices to mimic synaptic functionality.

Development of a novel self-healing Zn(II)-metallohydrogel with wide bandgap semiconducting properties for non-volatile memory device application

A rapid and effective strategy has been devised for the swift development of a Zn(II)-ion-based supramolecular metallohydrogel, termed Zn@PEH, using pentaethylenehexamine as a low molecular weight gelator. This process occurs in an aqueous medium at room temperature and atmospheric pressure. The mechanical strength of the synthesized Zn@PEH metallohydrogel has been assessed through rheological analysis, considering angular frequency and oscillator stress dependencies. Notably, the Zn@PEH metallohydrogel exhibits exceptional self-healing abilities and can bear substantial loads, which have been characterized through thixotropic analysis. Additionally, this metallohydrogel displays injectable properties. The structural arrangement resembling pebbles within the hierarchical network of the supramolecular Zn@PEH metallohydrogel has been explored using FESEM and TEM measurements. EDX elemental mapping has confirmed the primary chemical constituents of the metallohydrogel. The formation mechanism of the metallohydrogel has been analyzed via FT-IR spectroscopy. Furthermore, zinc(II) metallohydrogel (Zn@PEH)-based Schottky diode structure has been fabricated in a lateral metal-semiconductor-metal configuration and  it's charge transport behavior has also been studied. Notably, the zinc(II) metallohydrogel-based resistive random access memory (RRAM) device (Zn@PEH) demonstrates bipolar resistive switching behavior at room temperature. This RRAM device showcases remarkable switching endurance over 1000 consecutive cycles and a high ON/OFF ratio of approximately 270. Further, 2 × 2 crossbar array of the RRAM devices were designed to demonstrate OR and NOT logic circuit operations, which can be extended for performing higher order computing operations. These structures hold promise for applications in non-volatile memory design, neuromorphic and in-memory computing, flexible electronics, and optoelectronic devices due to their straightforward fabrication process, robust resistive switching behavior, and overall system stability.

Memristor-Based Bionic Tactile Devices: Opening the Door for Next-Generation Artificial Intelligence

Bioinspired tactile devices can effectively mimic and reproduce the functions of the human tactile system, presenting significant potential in the field of next-generation wearable electronics. In particular, memristor-based bionic tactile devices have attracted considerable attention due to their exceptional characteristics of high flexibility, low power consumption, and adaptability. These devices provide advanced wearability and high-precision tactile sensing capabilities, thus emerging as an important research area within bioinspired electronics. This paper delves into the integration of memristors with other sensing and controlling systems and offers a comprehensive analysis of the recent research advancements in memristor-based bionic tactile devices. These advancements incorporate artificial nociceptors and flexible electronic skin (e-skin) into the category of bio-inspired sensors equipped with capabilities for sensing, processing, and responding to stimuli, which are expected to catalyze revolutionary changes in human-computer interaction. Finally, this review discusses the challenges faced by memristor-based bionic tactile devices in terms of material selection, structural design, and sensor signal processing for the development of artificial intelligence. Additionally, it also outlines future research directions and application prospects of these devices, while proposing feasible solutions to address the identified challenges.

In-Memory Sensing and Computing for Cancer Diagnostics: A Perspective Paper

During the past two decades, a number of two-terminal switching devices have been demonstrated in the literature. They typically exhibit hysteric behavior in the current-to-voltage characteristics. These devices have often been also referred to as memristive devices. Their capacity to switch and exhibit electrical hysteresis has made them well-suited for applications such as data storage, in-memory computing, and in-sensor computing or in-memory sensing. The aim of this perspective paper is to is twofold. Firstly, it seeks to provide a comprehensive examination of the existing research findings in the field and engage in a critical discussion regarding the potential for the development of new non-Von-Neumann computing machines that can seamlessly integrate sensing and computing within memory units. Secondly, this paper aims to demonstrate the practical application of such an innovative approach in the realm of cancer medicine. Specifically, it explores the modern concept of employing multiple cancer markers simultaneously to enhance the efficiency of diagnostic processes in cancer medicine.

Piezo-Acoustic Resistive Switching Behaviors in High-Performance Organic-Inorganic Hybrid Perovskite Memristors

Memristors are regarded as promising candidates for breaking the problems including high off-chip memory access delays and the hash rate cost of frequent data moving induced by algorithms for data-intensive applications of existing computational systems. Recently, organic-inorganic halide perovskites (OIHPs) have been recognized as exceptionally favorable materials for memristors due to ease of preparation, excellent electrical conductivity, and structural flexibility. However, research on OIHP-based memristors focuses on modulating resistive switching (RS) performance through electric fields, resulting in difficulties in moving away from complex external circuits and wire connections. Here, a multilayer memristor has been constructed with eutectic gallium and indium (EGaIn)/ MAPbI3 /poly(3,4-ethylenedioxythiophene): poly(4-styrenesulphonate) (PEDOT: PSS)/indium tin oxide (ITO) structure, which exhibits reproducible and reliable bipolar RS with low SET/RESET voltages, stable endurance, ultrahigh average ON/OFF ratio, and excellent retention. Importantly, based on ion migration activated by sound-driven piezoelectric effects, the device exhibits a stable acoustic response with an average ON/OFF ratio greater than 103 , thus realizing non-contact, multi-signal, and far-field control in RS modulation. This study provides a single-structure multifunctional memristor as an integrated architecture for sensing, data storage, and computing.

Self-Organized Memristive Ensembles of Nanoparticles Below the Percolation Threshold: Switching Dynamics and Phase Field Description

Percolative memristive networks based on self-organized ensembles of silver and gold nanoparticles are synthesized and investigated. Using cyclic voltammetry, pulse and step voltage excitations, we study switching between memristive and capacitive states below the percolation threshold. The resulting systems demonstrate scale-free (self-similar) temporal dynamics, long-term correlations, and synaptic plasticity. The observed plasticity can be manipulated in a controlled manner. The simplified stochastic model of resistance dynamics in memristive networks is testified. A phase field model based on the Cahn-Hilliard and Ginzburg-Landau equations is proposed to describe the dynamics of a self-organized network during the dissolution of filaments.

Realization of Artificial Nerve Synapses Based on Biological Threshold Resistive Random Access Memory

A one-selector one resistor (1S1R) array formed of a selector and resistive random access memory (RRAM) is an important way to achieve high-density storage and neuromorphic computing. However, the low durability and poor consistency of the selector limit its practical application. The fabrication of a selector based on egg albumen (EA) is reported in this paper. The device exhibits excellent bidirectional threshold switching characteristics, including a low leakage current (10-7  A), a high ON/OFF current ratio (106 ), and good endurance (>700 days). It is used as a selector to form a 1S1R unit in combination with an EA-based RRAM to effectively solve the leakage current in a crossbar array. A feasible solution is provided for the realization of a protein-based 1S1R array to achieve high-density storage. The 1S1R unit shows characteristics similar to those of synapses in the human brain under impulse excitation and has great potential in simulating the human brain for neuromorphic calculations.).

A magnetic field controlled memristor towards the design of an implantable detector

Memristors, which combine the behaviors of memory and resistive switching (RS), have a wide application prospect in information processing and artificial neural networks. The RS memory behaviors of memristors are primarily determined by the functional layer materials, device structure, and working conditions. Herein, a CuMnO₂ nanomaterial with the manganese copper ore structure was prepared on a Ti substrate by hydrothermal method, and a memristor with the Ag/CuMnO₂/Ti sandwich structure was developed. The RS memory behavior of the as-prepared memristor can be regulated through a low magnetic field (MF), and thus the resistance value of device shows a multi-level resistance states. Compared with other regulation factors, the MF can remotely adjust and control the RS characteristics of memristor, which is a non-invasive and non-destructive regulatory means. The MF regulated memristor can not only be used for multi-level high-density information storage, but also it can protect the health of special populations by identifying the MF intensity of the surrounding environment. When the device is operated in an MF environment, the change of resistance value of the device in both high resistance state (HRS) and low resistance state (LRS) is mainly attributed to the influence of Loren magnetic force on conductive ions.

Evaluation of Cellulose–MXene Composite Hydrogel Based Bio-Resistive Random Access Memory Material as Mimics for Biological Synapses

We report a memory device based on organic-inorganic hybrid cellulose-Ti₃C₂T_X MXene composite hydrogel (CMCH) as a switching layer sandwiched between Ag top and FTO bottom electrodes. The device (Ag/CMCH/FTO) was fabricated by a simple, solution-processed route and exhibits reliable and reproducible bipolar resistive switching. Multilevel switching behavior was observed at low operating voltages (±0.5 to ±1 V). Furthermore, the capacitive-coupled memristive characteristics of the device were corroborated with electrochemical impedance spectroscopy and this affirmed the filamentary conduction switching mechanism (LRS-HRS). The synaptic functions of the CMCH-based memory device were evaluated, wherein potentiation/depression properties over 8 × 10³ electric pulses were observed. The device also exhibited spike time-dependent plasticity-based symmetric Hebbian learning rule of a biological synapse. This hybrid hydrogel is expected to be a potential switching material for low-cost, sustainable, and biocompatible memory storage devices and artificial synaptic applications.

Femtosecond Laser-Induced Nano-Joining of Volatile Tellurium Nanotube Memristor

Nanowire/nanotube memristor devices provide great potential for random-access high-density resistance storage. However, fabricating high-quality and stable memristors is still challenging. This paper reports multileveled resistance states of tellurium (Te) nanotube based on the clean-room free femtosecond laser nano-joining method. The temperature for the entire fabrication process was maintained below 190 °C. A femtosecond laser joining technique was used to form nanowire memristor units with enhanced properties. Femtosecond (fs) laser-irradiated silver-tellurium nanotube-silver structures resulted in plasmonic-enhanced optical joining with minimal local thermal effects. This produced a junction between the Te nanotube and the silver film substrate with enhanced electrical contacts. Noticeable changes in memristor behavior were observed after fs laser irradiation. Capacitor-coupled multilevel memristor behavior was observed. Compared to previous metal oxide nanowire-based memristors, the reported Te nanotube memristor system displayed a nearly two-order stronger current response. The research displays that the multileveled resistance state is rewritable with a negative bias.

In-Depth Physical Mechanism Analysis and Wearable Applications of HfOx-Based Flexible Memristors

Since memristors as an emerging nonlinear electronic component have been considered the most promising candidate for integrating nonvolatile memory and advanced computing technology, the in-depth reveal of the memristive mechanism and the realization of hardware fabrication have facilitated their wide applications in next-generation artificial intelligence. Flexible memristors have shown great promising prospects in wearable electronics and artificial electronic skin (e-skin), but in-depth research on the physical mechanism is still lacking. Here, a flexible memristive device with a Ag/HfO_x/Ti/PET crossbar structure was fabricated, and a remarkable analog switching characteristic similar to synaptic behavior was observed. Through detailed data fitting and in-depth physical mechanism analysis, it is confirmed that the analog switching characteristics of the device are mainly caused by carrier tunneling. Furthermore, the memristive properties of the Ag/HfO_x/Ag/PET device can be attributed to the conductive filaments formed by the redox reaction of the active metal Ag. Finally, the interfacial barrier is extracted by the Arrhenius diagram and the energy band diagram, which is drawn to clearly demonstrate the conduction mechanism of charge trapping in the device. Therefore, the HfO_x-based flexible memristor with analog switching behavior and stable memory performance lays the foundation for cutting-edge applications in wearable electronics and smart e-skin.

Threshold switching in nickel-doped zinc oxide based memristor for artificial sensory applications

Electronic devices featuring biomimetic behaviour as electronic synapses and neurons have motivated the emergence of a new era in information and humanoid robotics technologies. In the human body, a nociceptor is a unique sensory neuron receptor that is capable of detecting harmful signals, leading to the central nervous system initiating a motor response. Herein, a nickel-doped zinc oxide (NZO)/Au based memristor is fabricated for the first time and characterized for artificial nociceptor application. For this, the introduction of a nickel-doped zinc oxide (NZO) layer between P⁺⁺-Si and Au electrodes is used to eliminate the surface effects of the NZO layer, resulting in improved volatile threshold switching performance. Depending on the intensity, duration, and repetition rate of the external stimuli, this newly created memristor exhibits various critical nociceptive functions, including threshold, relaxation, allodynia, and hyperalgesia. The electron trapping/detrapping to/from the traps in the NZO layer is responsible for these nociceptive properties. This kind of NZO-based device produces a multifunctional nociceptor performance that is essential for applications in artificial intelligence systems, such as neural integrated devices with nanometer-sized features.

First Order Rate Law Analysis for Reset State in Vanadium Oxide Thin Film Resistive Random Access Memory Devices

In the reset state, the decay reaction mechanism and bipolar switching properties of vanadium oxide thin film RRAM devices for LRS/HRS are investigated and discussed here. To discover the properties of I-V switching curves, the first order rate law behaviors of the reset state between the resistant variety properties and the reaction time were observed. To verify the decay reaction mechanism in the reset state, vanadium oxide thin films from RRAM devices were measured by different constant voltage sampling and exhibited the same decay reaction rate constant. Finally, the electrical conduction transfer mechanism and metallic filament forming model described by I-V switching properties of the RRAM devices were proven and investigated.

Second-order associative memory circuit hardware implemented by the evolution from battery-like capacitance to resistive switching memory

Memristor-based Pavlov associative memory circuit presented today only realizes the simple condition reflex process. The secondary condition reflex endows the simple condition reflex process with more bionic, but it is only demonstrated in design and involves the large number of redundant circuits. A FeOx-based memristor exhibits an evolution process from battery-like capacitance (BLC) state to resistive switching (RS) memory as the I-V sweeping increase. The BLC is triggered by the active metal ion and hydroxide ion originated from water molecule splitting at different interfaces, while the RS memory behavior is dominated by the diffusion and migration of ion in the FeOx switching function layer. The evolution processes share the nearly same biophysical mechanism with the second-order conditioning. It enables a hardware-implemented second-order associative memory circuit to be feasible and simple. This work provides a novel path to realize the associative memory circuit with the second-order conditioning at hardware level.

Voltage-Controlled Conversion from CDS to MDS in an Azobenzene-Based Organic Memristor for Information Storage and Logic Operations

For organic memristors, non-zero-crossing current-voltage (I-V) curves are often observed, which can be attributed to capacitive effects. If the conversion between the capacitance-dominated state (CDS) and the memristance-dominated state (MDS) can be realized in a controllable manner, more device functions can be obtained. In this work, a two-terminal memristor using a common organic dye, azobenzene (AZB), as the active layer was prepared. It is found that as the applied voltage gradually increases, the device can transition from CDS to MDS. In the low voltage range (<1 V), the device is in CDS, and the capacitance is significantly increased by ∼10⁴ compared to the theoretical value. In the high voltage range (>1 V), the device is in MDS, achieving an HRS (high resistance state)/LRS (low resistance state) resistance ratio of ∼10⁴, and the logic operations are achieved. Through the analysis of the I-V curve, energy diagram of the materials, and computer simulation results, the mechanisms of CDS, MDS, and their conversion are proposed. This work provides an in-depth understanding of the working mechanism of organic memristors and demonstrates the potential of AZB-based organic memristors for information storage and logic display applications.

Applications of biomemristors in next generation wearable electronics

With the rapid development of mobile internet and artificial intelligence, wearable electronic devices have a great market prospect. In particular, information storage and processing of real-time collected data are an indispensable part of wearable electronic devices. Biomaterial-based memristive systems are suitable for storage and processing of the obtained information in wearable electronics due to the accompanying merits, i.e. sustainability, lightweight, degradability, low power consumption, flexibility and biocompatibility. So far, many biomaterial-based flexible and wearable memristive devices were prepared by spin coating or other technologies on a flexible substrate at room temperature. However, mechanical deformation caused by mechanical mismatch between devices and soft tissues leads to the instability of device performance. From the current research and practical application, the device will face great challenges when adapting to different working environments. In fact, some interesting studies have been performed to address the above issues while they were not intensively highlighted and overviewed. Herein, the progress in wearable biomemristive devices is reviewed, and the outlook and perspectives are provided in consideration of the existing challenges during the development of wearable biomemristive systems.

Natural-Casein-Based Biomemristor with Pinched Current-Voltage Characteristics

A biomaterials based memristor is of great interest for applications in the environment and human friendly electronic systems. Although a pinched current-voltage (I-V) characteristic is a signature of Chua's memristor model, biomemristors generally exhibit nonpinched I-V response. This work reports the discovery of the pinched I-V characteristics of a natural casein-based biomemristor. Water-soluble sodium caseinate (NaCas), synthesized using natural casein that was extracted from edible animal milk, was used for the fabrication of a Al/NaCas/ITO biomemristor device. In addition to pinched I-V characteristics, the Al/NaCas/ITO device shows improved performance with a sufficiently large resistance window (∼20 times), longer retention time (∼10⁵ s), and comparable cyclic endurance (>180 cycles), as compared with the reported biomemristors reported in the literature. A physical mechanism is proposed to explain the device characteristics.

ABO3 multiferroic perovskite materials for memristive memory and neuromorphic computing

The unique electron spin, transfer, polarization and magnetoelectric coupling characteristics of ABO₃ multiferroic perovskite materials make them promising candidates for application in multifunctional nanoelectronic devices. Reversible ferroelectric polarization, controllable defect concentration and domain wall movement originated from the ABO₃ multiferroic perovskite materials promotes its memristive effect, which further highlights data storage, information processing and neuromorphic computing in diverse artificial intelligence applications. In particular, ion doping, electrode selection, and interface modulation have been demonstrated in ABO₃-based memristive devices for ultrahigh data storage, ultrafast information processing, and efficient neuromorphic computing. These approaches presented today including controlling the dopant in the active layer, altering the oxygen vacancy distribution, modulating the diffusion depth of ions, and constructing the interface-dependent band structure were believed to be efficient methods for obtaining unique resistive switching (RS) behavior for various applications. In this review, internal physical dynamics, preparation technologies, and modulation methods are systemically examined as well as the progress, challenges, and possible solutions are proposed for next generation emerging ABO₃-based memristive application in artificial intelligence.

An ultrathin memristor based on a two-dimensional WS2/MoS2 heterojunction

Memristors are regarded as one of the key devices to break through the traditional Von Neumann computer architecture due to their capability of simulating the function of neural synapses. Among various memristive materials, two-dimensional (2D) materials are promising candidates to build advanced memristors with extremely high integration density and low power consumption. However, memristors based on 2D materials usually suffer from poor endurance and retention due to their vulnerability to material degradation during the formation/fusing processes of conductive filament channels within the switching media of 2D materials. Here, a new memristor architecture based on a WS2/MoS2 2D semiconducting heterojunction (metal/heterojunction/metal, MHM) is proposed, which is completely different from the conventional metal/insulator/metal (MIM) sandwich structure. Through the introduction of a type-II 2D heterojunction, a resistance switching mechanism based on band modulation rather than the conductive filaments can be realized to eliminate the material degradation during the set/reset processes. A prototype MHM memristor based on the WS2/MoS2 heterojunction is successfully developed with a large switching on/off ratio up to 104 and a clearly extended endurance over 120 switching cycles, showing the advantage of the 2D WS2/MoS2 heterojunction over the individual MoS2 or WS2 layers in memristive performance. The proposed method for the MHM-type 2D memristor has the potential to achieve a large-scale integrated memristor matrix with low power consumption and high integration density, which is promising for future artificial intelligence and brain-like computing systems.

Refining the Negative Differential Resistance Effect in a TiOx-Based Memristor

The N-type negative difference resistance (NDR) is characterized by the peak/valley voltage (V_p/V_v) and the corresponding current (I_p/I_v). The N-type NDR is observed in the resistive switching (RS) memory device of Ag|TiO₂|F-doped SnO₂ at room temperature. After the TiO₂ film is equipped with a nanoporous array, the ∼1.2 V gap voltage between V_p and V_v is effectively downscaled to ∼0.5 V, and the gap current of ∼7.23 mA between I_p and I_v is improved to ∼30 mA. It demonstrates that a lower power consumption and faster switching time of the NDR can be obtained in the memristor. Compensations and synergies among the nanoscale conduction filaments (OH^-, Ag⁺, and V_o) are responsible for the refining NDR behavior in our devices. This work provides an efficient method to construct a high-performance N-type NDR effect at room temperature and gives a new horizon on the coexistence of this type of NDR effect and RS memory behaviors.

Memristors With Controllable Data Volatility by Loading Metal Ion-Added Ionic Liquids

We demonstrate a new memristive device (IL-Memristor), in which an ionic liquid (IL) serve as a material to control the volatility of the resistance. ILs are ultra-low vapor pressure liquids consisting of cations and anions at room temperature, and their introduction into solid-state processes can provide new avenues in electronic device fabrication. Because the device resistance change in IL-Memristor is governed by a Cu filament formation/rupture in IL, we considered that the Cu filament stability affects the data retention characteristics. Therefore, we controlled the data retention time by clarifying the corrosion mechanism and performing the IL material design based on the results. It was found out that the corrosion of Cu filaments in the IL was ruled by the comproportionation reaction, and that the data retention characteristics of the devices varied depending on the valence of Cu ions added to the IL. Actually, IL-Memristors involving Cu(II) and Cu(I) show volatile and non-volatile nature with respect to the programmed resistance value, respectively. Our results showed that data volatility can be controlled through the metal ion species added to the IL. The present work indicates that IL-memristor is suitable for unique applications such as artificial neuron with tunable fading characteristics that is applicable to phenomena with a wide range of timescale.

A Battery-Like Self-Selecting Biomemristor from Earth-Abundant Natural Biomaterials

Using the earth-abundant natural biomaterials to manufacture functional electronic devices meets the sustainable requirement of green electronics, especially for the practical application of memristors in data storage and neuromorphic computing. However, the sneak currents flowing though the unselected cells in a large-scale cross-bar memristor array is one of the major problems which need to be tackled. The self-selecting memristors can solve the problem to develop compact and concise integrated circuits. Here, a sustainable natural biomaterial (anthocyanin, C₁₅H₁₁O₆) extracted from plant tissue is demonstrated for ions and electron transport. The capacitive-coupled memristive behavior of as-prepared bioelectronic device can be significantly modulated by diethylmethyl(2-methoxyethyl)ammoium bis(trifluoromethylsulfonyl)imide (DEME-TFSI) ionic liquid (IL). Furthermore, graphene was inserted into biomaterial matrix to manipulate the memristive effects by graphene protonation. This results in a battery-like self-selective memristive effect. This phenomenon is explained by a physical model and density functional theory (DFT) based first-principles calculations. Finally, the self-selective behavior was applied in 0T-1R array configuration, which indicates the battery-like self-selecting biomemristor has potential applications in the brain-inspired computing, data storage systems, and high-density device integration.

Analog and Digital Bipolar Resistive Switching in Co-Al-Layered Double Hydroxide Memristor

We demonstrate a nonvolatile memristor based on Co-Al-layered double hydroxide (Co-Al LDH). We also introduce a memristor that has a hexazinone-adsorbing Co-Al LDH composite active layer. Memristor characteristics could be modulated by adsorbing hexazinone with Co-Al LDHs in the active layer. While different, Co-Al LDH-based memory devices show gradual current changes, and the memory device with small molecules of adsorbed hexazinone undergo abrupt changes. Both devices demonstrate programmable memory peculiarities. In particular, both memristors show rewritable resistive switching with electrical bistability (>105 s). This research manifests the promising potential of 2D nanocomposite materials for adsorbing electroactive small molecules and rectifying resistive switching properties for memristors, paving a way for design of promising 2D nanocomposite memristors for advanced device applications.

Multilevel resistive switching memory behaviors arising from ion diffusion and photoelectron transfer in α-Fe2O3 nano-island arrays

Resistive switching (RS) memory behaviors are observed in an Ag|α-Fe₂O₃|Ti device after operating under an ultralow bias voltage of ±0.1 V. An SET voltage of ∼20 mV is obtained under illumination. Multilevel RS memory is realized under photoelectric signal control. The separation and fast transfer of hole-electron pairs are responsible for the enhanced RS memory under illumination.

Physical mechanism for the synapse behaviour of WTiOx-based memristors

Tungsten-based memristors possess many advantages as candidates for memristive devices, including gradual changes in resistance states and memorization and learning functions. However, most previous reports mainly focus on studying synaptic learning rules instead of analysing the internal mechanism that results in the exterior learning rules. Herein, we discuss stacked Au/WTiO_x/Au and Ti/WTiO_x/Au devices in which the function of the resistance switch is realized by the externally induced local migration of oxygen ions. The consecutively adjustable multilevel resistance of the Au/WTiO_x/Au device may be due to the variation in the barrier width and height in high oxygen vacancy concentrations. Additionally, the high and low resistance states of Ti/WTiO_x/Au devices are considered as a result of the connection and rupture of the conductive filaments at low concentrations of oxygen vacancies. The physical mechanism construction and state-full synapse development through the control of ion migration provide insight into the applications of oxide-based memristors in neuromorphic computation.