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The resistive switching behavior is observed in the Cu/MoS2/Cu/ITO structures, which has been deposited by magnetron sputtering. With the increase in MoS2 thickness, the resistive switching behavior is gradually weakened. The optimal device with a MoS2 thickness of 120 nm has a lower Set voltage and Reset voltage, where Set voltage is 0.14–0.3 V and Reset voltage is −0.24 V to −0.08 V. The device also has a resistive switching ratio of up to 105 high resistance state/low resistance state, a data retention time over 104 s, and can endure more than 103 cycles. As the limiting current increases, the resistance switching (RS) characteristics of devices with MoS2 thickness of 200 nm at both positive and negative biases are improved. There is no RS behavior in ITO/MoS2/ITO devices fabricated by the same method, which indicates that sulfur vacancies have little effect on the RS characteristics of Cu/MoS2/Cu/ITO devices. Moreover, since the migration barrier and diffusion activation energy of Cu in MoS2 are lower than those of sulfur vacancy, combined with the data fitting structure, it is shown that the RS behavior is formed because Cu ions control the connectivity and fracture of conductive filaments through the diffusion and migration of MoS2 layer. [ABSTRACT FROM AUTHOR]

Fused deposition modeling (FDM) represents a state‐of‐the‐art 3D printing technology that holds great promise in the field of electrochemistry as a fast, in‐house, and digital fabrication method of sustainable sensors. Despite the progress in FDM, existing practical 3D printed sensors still require post‐printing treatment to improve their operational features, either through (electro)chemical surface activation or surface modification with external functional materials. Herein, a novel lab‐made conductive biofilament with integrated two different types of metallic nanoparticles (NPs) for the 3D printing of ready‐to‐use and multiplexed electrochemical sensors is introduced. The filament is composed of biodegradable polylactic acid as a base, polyethylene glycol dimethyl ether as a plasticizer, carbon black as a conductive filler, and nanopowder oxides of bismuth and copper as integrated functional precursor materials. The as‐printed sensors serve as multifunctional transducers for the direct and sensitive determinations of several analytes, by exploiting the different properties of the two co‐existing NPs. Particularly, heavy metals (such as lead, and cadmium) are voltammetrically quantified by amalgamation with BiNPs electrogenerated from Bi2O3, while biomarkers (such as glucose, and uric acid) are determined in enzymatic‐free modes. Determination of glucose takes advantage of the electrocatalytic properties of CuO, while uric acid is directly oxidized at the sensor. [ABSTRACT FROM AUTHOR]

Resistive random‐access memory (RRAM) stands out as a promising memory technology due to its ease of operation, high speed, affordability, exceptional stability, and potential to enable smaller memory devices with sizes under 10 nm. This has drawn significant attention, with atomic layer deposition (ALD) emerging as an ideal technology to tackle the challenges of nanoscale fabrication in the micro‐ and nanomanufacturing industry. ALD offers technological advantages such as functional multiple‐layer stacking, doping capabilities, and incorporating oxygen reservoirs or reactive layers. These factors contribute to achieving more intriguing, stable, and reliable nonvolatile resistance switching behaviors in RRAM. Specifically, ALD greatly benefits RRAM, that relies on the valence change mechanism, where high‐k transition metal oxides are commonly used as switching materials, and precise control over oxygen vacancies is achievable. This review provides a comprehensive overview of ALD films used in RRAM, delves into resistive switching properties and microscopic mechanisms in binary and ternary oxides and nitrides, and explores the impact of ALD‐prepared electrodes. Furthermore, the current status and future prospects of ALD‐based RRAM are highlighted, which is poised to catalyze further advancements in the fields of information storage and neural networks. [ABSTRACT FROM AUTHOR]

A comprehensive physical electro-thermal modeling approach is explored to investigate the intricate mechanisms underlying filament formation and the effect of surface perturbation in nanoscale Y2O3-based memristors. The approach integrates fundamental principles of solid-state physics, electrochemistry, and materials science to develop a detailed physical model that captures the key phenomena governing the operation of Y2O3 memristors. The simulation is carried out in a semiconductor physics-based tool, i.e., COMSOL Multiphysics with a defined MATLAB script, wherein simulation is based on the minimum free energy of the used materials at an applied input voltage. The fundamental processes in filament growth include ion migration, redox reactions, and vacancy dynamics within the Y2O3 lattice. Furthermore, the influence of surface perturbation on the overall device behavior, grain boundaries, and electrode interactions impact on memristor performance is also investigated. The surface perturbations significantly influenced the switching dynamics of the memristor, including variations in switching voltages, ON/OFF current ratio, filament radius, and filament temperature during the switching process. Therefore, the presented findings contribute to a deeper understanding of the physical mechanisms at play in Y2O3 memristors, offering valuable guidance for the design and engineering of these nanoscale devices for next-generation memory and neuromorphic computing applications. This physical modeling approach not only enhances our comprehension of memristor behavior but also paves the way for the development of more efficient and reliable memristor-based technologies. [ABSTRACT FROM AUTHOR]

Conductive‐bridge random access memory (CBRAM) emerges as a promising candidate for next‐generation memory and storage device. However, CBRAMs are prone to degenerate and fail during electrochemical metallization processes. To address this issue, herein we propose a self‐repairability strategy for CBRAMs. Amorphous NbSe2 was designed as the resistive switching layer, with Cu and Au as the top and bottom electrodes, respectively. The NbSe2 CBRAMs demonstrate exceptional cycle‐to‐cycle and device‐to‐device uniformity, with forming‐free and compliance current‐free resistive switching characteristics, low‐operation voltage, and competitive endurance and retention performance. Most importantly, the self‐repairable behavior is discovered for the first time in CBRAM. The device after failure can recover its performance to the initially normal state by operating with a slightly large reset voltage. The existence of Cu conductive filament and excellent controllability of Cu migration in the NbSe2 switching layer has been revealed by a designed broken‐down point approach, which is responsible for the self‐repairable behavior of NbSe2 CBRAMs. Our self‐repairable and high‐uniform amorphous NbSe2 CBRAM may open the door to the development of memory and storage devices in the future. [ABSTRACT FROM AUTHOR]

In this paper, the electrothermal coupling model of metal oxide resistive random access memory (RRAM) is analyzed by using a 2D axisymmetrical structure in COMSOL Multiphysics simulation software. The RRAM structure is a Ti/HfO2/ZrO2/Pt bilayer structure, and the SET and RESET processes of Ti/HfO2/ZrO2/Pt are verified and analyzed. It is found that the width and thickness of CF1 (the conductive filament of the HfO2 layer), CF2 (the conductive filament of the ZrO2 layer), and resistive dielectric layers affect the electrical performance of the device. Under the condition of the width ratio of conductive filament to transition layer (6:14) and the thickness ratio of HfO2 to ZrO2 (7.5:7.5), Ti/HfO2/ZrO2/Pt has stable high and low resistance states. On this basis, the comparison of three commonly used RRAM metal top electrode materials (Ti, Pt, and Al) shows that the resistance switching ratio of the Ti electrode is the highest at about 11.67. Finally, combining the optimal conductive filament size and the optimal top electrode material, the I-V hysteresis loop was obtained, and the switching ratio Roff/Ron = 10.46 was calculated. Therefore, in this paper, a perfect RRAM model is established, the resistance mechanism is explained and analyzed, and the optimal geometrical size and electrode material for the hysteresis characteristics of the Ti/HfO2/ZrO2/Pt structure are found. [ABSTRACT FROM AUTHOR]

Conventional computation techniques face challenges of deviations in Moore's law and the high‐power consumption of data‐centric computation tasks. Neuromorphic engineering attempts to overcome these issues by taking inspiration from neuron assemblies, ranging from distributed synaptic plasticity through orchestration of oscillator‐like action potential toward avalanche dynamics. Although solid networks of nanoparticles (NPs) are proven to replicate fingerprints of criticality and brain‐like dynamics, the aspect of dynamic spatial reconfigurations in the connectivity of networks remains unexplored. In this work, Ag/poly(ethylene glycol) (PEG) nanofluids are demonstrated as potential systems to mimic the spatio‐temporal reconfiguration of network connections. The nanofluids are prepared by directly loading Ag NPs from the gas aggregation cluster source into liquid PEG. The NPs exhibit a negative zeta potential in PEG; if the potential difference is applied between two electrodes submerged in this nanofluid, the NPs migrate toward the anode, accumulate in its vicinity, and form a conductive path. Spikes of electric current passing through the path are detected, accompanied by resistive switching phenomena, similar to the random switching dynamics in solid NPs networks. The unique behavior of Ag/PEG nanofluids makes them promising for the realization of spatio‐temporal reconfigurations in network topologies with the potential to transition to 3D. [ABSTRACT FROM AUTHOR]

Abstract Conductive‐bridge random access memory (CBRAM) emerges as a promising candidate for next‐generation memory and storage device. However, CBRAMs are prone to degenerate and fail during electrochemical metallization processes. To address this issue, herein we propose a self‐repairability strategy for CBRAMs. Amorphous NbSe2 was designed as the resistive switching layer, with Cu and Au as the top and bottom electrodes, respectively. The NbSe2 CBRAMs demonstrate exceptional cycle‐to‐cycle and device‐to‐device uniformity, with forming‐free and compliance current‐free resistive switching characteristics, low‐operation voltage, and competitive endurance and retention performance. Most importantly, the self‐repairable behavior is discovered for the first time in CBRAM. The device after failure can recover its performance to the initially normal state by operating with a slightly large reset voltage. The existence of Cu conductive filament and excellent controllability of Cu migration in the NbSe2 switching layer has been revealed by a designed broken‐down point approach, which is responsible for the self‐repairable behavior of NbSe2 CBRAMs. Our self‐repairable and high‐uniform amorphous NbSe2 CBRAM may open the door to the development of memory and storage devices in the future.

After investigating the behavior of ions during the growth of conductive filaments, we suggested a model for the growth process and electrical characteristics of the conductive filament under current-driven mode. In this model, the ionic displacement equation is derived by Arrhenius law, and a differential equation for the conductive filament growth has been established. We have also proved that the dielectric layer with the leakage current under current-driven mode can be equivalent to a parallel plate capacitor, which has a the equivalent dielectric constant. Consequently, the forming/set time of the device is gotten. At the same time, the kinetics process of ion motion is analyzed in detail, so that many microscopic parameters of the ion motion, such as the height of the potential barrier, the jump step, mobility and diffusion coefficient, can be obtained. Due to divalent and monovalent copper ions all participate in conduction, an equivalent copper ion Cuz+ is used for replacing both Cu+ and Cu2+, solving the computational complexity problem caused by multivalent metal ions. Finally, an equivalent circuit is proposed to calculate output voltage versus time characteristic. The calculation results of the model are consistent with experimental data. [ABSTRACT FROM AUTHOR]

Neuromorphic computing systems integrating both analog computing and data storage at the hardware level fundamentally overcome the von Neumann bottleneck. Organolead halide perovskite memristors are considered to be promising candidates to mimic biological synapses due to their highly tunable resistance states. Despite the considerable progress already made, the toxicity and instability of lead severely restrict potential applications. Herein, we successfully demonstrate all-inorganic and lead-free nanoscale Cs3Bi2X9 perovskites films. The Cs3Bi2I9-based memristors exhibited an excellent resistive switching (RS) performance, including ultralow power consumption, high environmental robustness, ultrafast switching speed, stable endurance and retention, large ON/OFF ratio, and multilevel capability. In particular, we propose an electrothermal simulation model and combine various experimental approaches to analyze the RS mechanism. More importantly, essential synaptic functions are emulated by Cs3Bi2I9-based memristors, including paired-pulse facilitation, long-term potentiation/depression, a learning–forgetting–relearning process, spike-voltage-dependent plasticity, spike-frequency-dependent plasticity, and so on. Basic photonic synaptic function plasticity was also investigated in the Cs3Bi2I9 memristors with tunable photophysical properties. Overall, this work is the original systematic study of memristors based on Cs3Bi2X9 perovskite systems and the comprehensive applications of Cs3Bi2I9 memristors in artificial neural networks, opening opportunities for ecofriendly, hardware-oriented neuromorphic computing architectures with perovskites as the functional material. [ABSTRACT FROM AUTHOR]

The performance stability of the resistive switching (RS) is vital for a resistive random-access memory device. Here, by inserting a thin HfAlO x layer between the InGaZnO (IGZO) layer and the bottom Pt electrode, the RS performance in amorphous IGZO memory device is significantly improved. Comparing with a typical metal-insulator-metal structure, the device with HfAlO x layer exhibits lower switching voltages, faster switching speeds, lower switching energy and lower power consumption. As well, the uniformity of switching voltage and resistance state is also improved. Furthermore, the device with HfAlO x layer exhibits long retention time (>104 s at 85 °C), high on/off ratio and more than 103 cycles of endurance at atmospheric environment. Those substantial improvements in IGZO memory device are attributed to the interface effects with a HfAlO x insertion layer. With such layer, the formation and rupture locations of Ag conductive filaments are better regulated and confined, thus an improved performance stability. [ABSTRACT FROM AUTHOR]

Neural networks implemented in memristor-based hardware can provide fast and efficient in-memory computation, but traditional learning methods such as error back-propagation are hardly feasible in it. Spiking neural networks (SNNs) are highly promising in this regard, as their weights can be changed locally in a self-organized manner without the demand for high-precision changes calculated with the use of information almost from the entire network. This problem is rather relevant for solving control tasks with neural-network reinforcement learning methods, as those are highly sensitive to any source of stochasticity in a model initialization, training, or decision-making procedure. This paper presents an online reinforcement learning algorithm in which the change of connection weights is carried out after processing each environment state during interaction-with-environment data generation. Another novel feature of the algorithm is that it is applied to SNNs with memristor-based STDP-like learning rules. The plasticity functions are obtained from real memristors based on poly-p-xylylene and CoFeB-LiNbO 3 nanocomposite, which were experimentally assembled and analyzed. The SNN is comprised of leaky integrate-and-fire neurons. Environmental states are encoded by the timings of input spikes, and the control action is decoded by the first spike. The proposed learning algorithm solves the Cart-Pole benchmark task successfully. This result could be the first step towards implementing a real-time agent learning procedure in a continuous-time environment that can be run on neuromorphic systems with memristive synapses. [ABSTRACT FROM AUTHOR]

Resistive random access memory (RRAM) has become one of the representatives of the next generation of nonvolatile memory because of its excellent performance, and the data reading function is caused by the growth and fracture of the conductive filament (CF) in the switch layer. Therefore, the study of the thermal properties of materials on the conductive mechanism is a step that cannot be ignored. In this paper, a numerical model of filament dissolution caused by the coupling effect of Joule heat and electric field in resistance elements is established. The influence of the thermal field on the electric field and ion mobility during device setup and reset is explained by solving partial differential equations. On this basis, the importance of electrode parameters for resistive switching behavior is emphasized. The results show that the best performance can be obtained at 298 K when TiN is selected as the top electrode material of the equipment. This work has deepened the understanding of RRAM resistance switch characteristics and has guiding significance for selecting memristor materials and promoting its industrialization process.

In this paper, the electrothermal coupling model of metal oxide resistive random access memory (RRAM) is analyzed by using a 2D axisymmetrical structure in COMSOL Multiphysics simulation software. The RRAM structure is a Ti/HfO2/ZrO2/Pt bilayer structure, and the SET and RESET processes of Ti/HfO2/ZrO2/Pt are verified and analyzed. It is found that the width and thickness of CF1 (the conductive filament of the HfO2 layer), CF2 (the conductive filament of the ZrO2 layer), and resistive dielectric layers affect the electrical performance of the device. Under the condition of the width ratio of conductive filament to transition layer (6:14) and the thickness ratio of HfO2 to ZrO2 (7.5:7.5), Ti/HfO2/ZrO2/Pt has stable high and low resistance states. On this basis, the comparison of three commonly used RRAM metal top electrode materials (Ti, Pt, and Al) shows that the resistance switching ratio of the Ti electrode is the highest at about 11.67. Finally, combining the optimal conductive filament size and the optimal top electrode material, the I-V hysteresis loop was obtained, and the switching ratio Roff/Ron = 10.46 was calculated. Therefore, in this paper, a perfect RRAM model is established, the resistance mechanism is explained and analyzed, and the optimal geometrical size and electrode material for the hysteresis characteristics of the Ti/HfO2/ZrO2/Pt structure are found.

A novel conductive filament based on graphite (Gr) dispersed in polylactic acid polymer matrix (PLA) is described to produce 3D-electrochemical devices (Gr/PLA). This conductive filament was used to additively manufacture electrochemical sensors using the 3D pen. Thermogravimetric analysis confirmed that Gr was successfully incorporated into PLA, achieving a composite material (40:60% w/w, Gr and PLA, respectively), while Raman and scanning electron microscopy revealed the presence of defects and a high porosity on the electrode surface, which contributes to improved electrochemical performance. The 3D-printed Gr/PLA electrode provided a more favorable charge transfer (335 Ω) than the conventional glassy carbon (1277 Ω) and 3D-printed Proto-pasta® (3750 Ω) electrodes. As a proof of concept, the ciprofloxacin antibiotic, a species of multiple interest, was selected as a model molecule. Thus, a square wave voltammetry (SWV) method was proposed in the potential range + 0.9 to + 1.3 V (vs Ag|AgCl|KCl(sat)), which provided a wide linear working range (2 to 32 µmol L−1), 1.79 µmol L−1 limit of detection (LOD), suitable precision (RSD < 7.9%), and recovery values from 94 to 109% when applied to pharmaceutical and milk samples. Additionally, the sensor is free from the interference of other antibiotics routinely employed in veterinary practices. This device is disposable, cost-effective, feasibly produced in financially limited laboratories, and consequently promising for evaluation of other antibiotic species in routine applications. [ABSTRACT FROM AUTHOR]

A new electrochemical device fabricated by the combination of 3D printing manufacturing and laser-generated graphene sensors is presented. Cell and electrodes were 3D printed by the fused deposition modeling (FDM) technique employing acrylonitrile butadiene styrene filament (insulating material that composes the cell) and conductive filament (lab-made filament based on graphite dispersed into polylactic acid matrix) to obtain reference and auxiliary electrodes. Infrared-laser engraved graphene, also reported as laser-induced graphene (LIG), was produced by laser conversion of a polyimide substrate, which was assembled in the 3D-printed electrochemical cell that enables the analysis of low volumes (50–2000 μL). XPS analysis revealed the formation of nitrogen-doped graphene multilayers that resulted in excellent electrochemical sensing properties toward the detection of atropine (ATR), a substance that was found in beverages to facilitate sexual assault and other criminal acts. Linear range between 5 and 35 μmol L−1, detection limit of 1 μmol L−1, and adequate precision (RSD = 4.7%, n = 10) were achieved using differential-pulse voltammetry. The method was successfully applied to beverage samples with recovery values ranging from 80 to 105%. Interference studies in the presence of species commonly found in beverages confirmed satisfactory selectivity for ATR sensing. The devices proposed are useful portable analytical tools for on-site applications in the forensic scenario. [ABSTRACT FROM AUTHOR]

Memristors are playing an increasingly important role in developing in-memory computing. Versatile memristors which offer both volatile and non-volatile performances can be employed as both memories and selectors, displaying unique advantages for developing novel electronic circuits. Herein, the remarkable multifunctional memristor with switchable operating modes between volatile and non-volatile by regulating compliance currents is implemented in Ag/CIPS/Au (CIPS: CuInP2S6) device. Diode-like volatile memristor performances with the rectification ratio of 103 and an endurance of 500 switching cycles were obtained. Meanwhile, significant non-volatile memory performances with on/off ratio of 103 and retention up to 104 s were also developed, which enables it to be utilized as selectors and memories simultaneously. Moreover, such versatile memristor can emulate the short-term plasticity (STP) and long-term plasticity (LTP) of artificial synapse, demonstrating its advantages in neuromorphic computing applications. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is used to detect brain activity by recording electrical signals across various points on the scalp. Recent technological advancement has allowed brain signals to be monitored continuously through the long-term usage of EEG wearables. However, current EEG electrodes are not able to cater to different anatomical features, lifestyles, and personal preferences, suggesting the need for customisable electrodes. Despite previous efforts to create customisable EEG electrodes through 3D printing, additional processing after printing is often needed to achieve the required electrical properties. Although fabricating EEG electrodes entirely through 3D printing with a conductive material would eliminate the need for further processing, fully 3D-printed EEG electrodes have not been seen in previous studies. In this study, we investigate the feasibility of using a low-cost setup and a conductive filament, Multi3D Electrifi, to 3D print EEG electrodes. Our results show that the contact impedance between the printed electrodes and an artificial phantom scalp is under 550 Ω , with phase change of smaller than −30 ∘ , for all design configurations for frequencies ranging from 20 Hz to 10 kHz. In addition, the difference in contact impedance between electrodes with different numbers of pins is under 200 Ω for all test frequencies. Through a preliminary functional test that monitored the alpha signals (7–13 Hz) of a participant in eye-open and eye-closed states, we show that alpha activity can be identified using the printed electrodes. This work demonstrates that fully 3D-printed electrodes have the capability of acquiring relatively high-quality EEG signals. [ABSTRACT FROM AUTHOR]

In this paper, an ultra-compact electrochemical metallization–based tunable filter with a simple metal–insulator–metal (MIM) waveguide system was proposed. The device comprises a MIM waveguide and a resonator with active electrodes. The formation and rupture of conductive filaments in the resonant cavity because of electrochemical metallization can change the resonant wavelength, which leads to the tunability of the transmission characteristics of the filter. The transmission characteristics of band-stop filter and band-pass filter are analyzed by finite element method (FEM) simulation. Numerical results demonstrate that the transmission line of the filter can be shifted by forming and rupture of the conductive filament, which is controlled by changing the applied electric field in the case of fixed structural parameters. The proposed compact tunable filter is a potential candidate for a low power consumption large-scale integrated photonic circuit for applications in optical communication, modulation, and computation. [ABSTRACT FROM AUTHOR]

The resistive switching layer of CeO2-x-TiO2 film was prepared on the FTO substrate by the sol-gel method and spin coating technique, and the Al/CeO2-x-TiO2/FTO resistive switching device was fabricated by depositing thin Al top electrode on the surface of the CeO2-x-TiO2 film. The crystal phase composition and crystal structure of CeO2-x-TiO2 thin films were characterized by XRD and XPS. The results show that the resistive switching layer is mainly composed of TiO2 and CeO2-x. Compared with Al/CeO2/FTO devices, the electrical performance of Al/CeO2-x-TiO2/FTO device is improved. I-V test shows that Al/CeO2-x-TiO2/FTO device has bipolar resistance variation characteristics without forming process. The resistive behavior with different CeO2-x-TiO2 thicknesses was carried out. The results show that the low resistance state of Al/CeO2-x-TiO2/FTO device shows ohmic conduction mechanism under different CeO2-x-TiO2 film thicknesses. As the thickness of CeO2-x-TiO2 increases, the essential change of resistance mechanism occurs in high resistance state. The resistance mechanism of the device changes from oxygen vacancy conductive filament mechanism to charge trapping/releasing mechanism by defect controlled. It was found that the AlOxlayer at the Al/CeO2-x-TiO2 interface is critical to the transformation of resistance mechanism, and the thickness of AlOx layer changes the device from "digital type" to "analog type".

The current work experimentally determined how the initial resistance and gauge factor in additively manufactured piezoresistive sensors are affected by the material, design, and process parameters. This was achieved through the tensile testing of sensors manufactured with different infill angles, layer heights, and sensor thicknesses using two conductive polymer composites. Linear regression models were then used to analyze which of the input parameters had significant effects on the sensor properties and which interaction effects existed. The findings demonstrated that the initial resistance in both materials was strongly dependent on the sensor geometry, decreasing as the cross-sectional area was increased. The resistance was also significantly influenced by the layer height and the infill angle, with the best variants achieving a resistance that was, on average, 22.3% to 66.5% lower than less-favorable combinations, depending on the material. The gauge factor was most significantly affected by the infill angle and, depending on the material, by the layer height. Of particular interest was the finding that increasing in the infill angle resulted in an increase in the sensitivity that outweighed the associated increase in the initial resistance, thereby improving the gauge factor by 30.7% to 114.6%, depending on the material. [ABSTRACT FROM AUTHOR]

Electrochemical metallization threshold switch (ECM TS) has received significant attention for various applications owing to its high ON/OFF ratio, fast switching characteristics, and simple active electrode/dielectric layer/inert electrode structures. However, the excess diffusion of active metal ions causes severe variation in threshold voltage and poor endurance. Furthermore, the small room for inert electrode metal is a problem to be solved for various applications of ECM TS. Here, a novel structure is proposed in which a two‐dimensional platinum diselenide (PtSe2) is inserted between the dielectric layer and inert electrode to engineer the conductive filament by controlling the active metal ion concentration. The low work function, superior inertness, layered structure, and smooth surface of PtSe2 insertion layer lead to thin and weak conductive filament with few active metal atoms and allow the use of various metals as inert electrode. Consequently, PtSe2‐inserted ECM TS shows high reliability in both threshold voltage distribution (σ/µ = ≈6.58%) and endurance (>106 cycles). Furthermore, PtSe2‐inserted ECM TS‐based 2 × 2 cross‐bar array is proposed as AND and OR logic circuits. This study is expected to pave the way for the development of ECM TS for next‐generation electronic applications. [ABSTRACT FROM AUTHOR]

Memristive devices that integrate storage and computing capabilities are highly promising candidates for artificial synapses in neuromorphic systems. However, achieving both cost-effectiveness and high-performance in memristors remains a substantial challenge. Ammonium polyphosphate (APP), an all-inorganic ionic polymer, has been utilized in the fabrication of memristive devices due to its distinctive poly-ionic properties and exceptional ion mobility. In this study, a two-terminal APP-based memristor with an Al/APP/ITO structure was fabricated. The experimental results revealed improved bipolar resistive switching behavior, characterized by lower operating voltages, enhanced endurance performance, and extended retention time. Detailed data fitting and chemical bonding analysis suggest that the physical mechanism underlying resistive switching involves a combination of interfacial Schottky barrier and conductive filaments. Furthermore, adjustable device conductance is achieved by applying consecutive positive and negative voltage sweeps. Various synaptic functions, including excitatory postsynaptic current, short-term paired-pulse facilitation, long-term potentiation /depression, and spike-timing-dependent plasticity, are effectively emulated. This study presents an effective approach to enhancing the memristive characteristics of APP-based devices and positions APP as a viable candidate for innovative neuromorphic architectures.

The linearity of conductance modulation of the artificial synapse severely restricts the recognition accuracy and the convergence rate in the learning of artificial neural networks. In this work, by alloy electrode engineering, a Ti–Ag device gained the forming-free property because Ag ions were promoted to migrate into the GeTeO _x layer to form a thicker conductive filament. This facilitated a uniform change in conductance with the pulse number, and the alloy synapse achieved a significant improvement in linearity (350%), which demonstrated its enhancement in recognition accuracy. To further validate its potential as a comprehensive artificial synapse, the multi-essential synaptic behaviors, including spike-timing-dependent plasticity, spike-rate-dependent plasticity, paired-pulse facilitation, post-tetanic potentiation, and excitatory post-synaptic current, were achieved successfully. This work proposes a promising approach to enhance the performance of conductive bridging random access memory synaptic devices, which benefits the hardware implementation of neuromorphic systems.

A filamentary-based organic memristor is a promising synaptic component for the development of neuromorphic systems for wearable electronics. In the organic memristors, metallic conductive filaments (CF) are formed via electrochemical metallization under electric stimuli, and it results in the resistive switching characteristics. To realize the bio-inspired computing systems utilizing the organic memristors, it is essential to effectively engineer the CF growth for emulating the complete synaptic functions in the device. Here, the fundamental principles underlying the operation of organic memristors and parameters related to CF growth are discussed. Additionally, recent studies that focused on controlling CF growth to replicate synaptic functions, including reproducible resistive switching, continuous conductance levels, and synaptic plasticity, are reviewed. Finally, upcoming research directions in the field of organic memristors for wearable smart computing systems are suggested.

Ultrathin (sub-2 nm) Al _2 O _3 /MgO memristors were recently developed using an in vacuo atomic layer deposition (ALD) process that minimizes unintended defects and prevents undesirable leakage current. These memristors provide a unique platform that allows oxygen vacancies (V _O ) to be inserted into the memristor with atomic precision and study how this affects the formation and rupture of conductive filaments (CFs) during memristive switching. Herein, we present a systematic study on three sets of ultrathin Al _2 O _3 /MgO memristors with V _O -doping via modular MgO atomic layer insertion into an otherwise pristine insulating Al _2 O _3 atomic layer stack (ALS) using an in vacuo ALD. At a fixed memristor thickness of 17 Al _2 O _3 /MgO atomic layers (∼1.9 nm), the properties of the memristors were found to be affected by the number and stacking pattern of the MgO atomic layers in the Al _2 O _3 /MgO ALS. Importantly, the trend of reduced low-state resistance and the increasing appearance of multi-step switches with an increasing number of MgO atomic layers suggests a direct correlation between the dimension and dynamic evolution of the conducting filaments and the V _O concentration and distribution. Understanding such a correlation is critical to an atomic-scale control of the switching behavior of ultrathin memristors.

Abstract Electrochemical metallization threshold switch (ECM TS) has received significant attention for various applications owing to its high ON/OFF ratio, fast switching characteristics, and simple active electrode/dielectric layer/inert electrode structures. However, the excess diffusion of active metal ions causes severe variation in threshold voltage and poor endurance. Furthermore, the small room for inert electrode metal is a problem to be solved for various applications of ECM TS. Here, a novel structure is proposed in which a two‐dimensional platinum diselenide (PtSe2) is inserted between the dielectric layer and inert electrode to engineer the conductive filament by controlling the active metal ion concentration. The low work function, superior inertness, layered structure, and smooth surface of PtSe2 insertion layer lead to thin and weak conductive filament with few active metal atoms and allow the use of various metals as inert electrode. Consequently, PtSe2‐inserted ECM TS shows high reliability in both threshold voltage distribution (σ/µ = ≈6.58%) and endurance (>106 cycles). Furthermore, PtSe2‐inserted ECM TS‐based 2 × 2 cross‐bar array is proposed as AND and OR logic circuits. This study is expected to pave the way for the development of ECM TS for next‐generation electronic applications.

The combination of CO2 laser ablation and electrochemical surface treatments is demonstrated to improve the electrochemical performance of carbon black/polylactic acid (CB/PLA) 3D-printed electrodes through the growth of flower-like Na2O nanostructures on their surface. Scanning electron microscopy images revealed that the combination of treatments ablated the electrode's polymeric layer, exposing a porous surface where Na2O flower-like nanostructures were formed. The electrochemical performance of the fabricated electrodes was measured by the reversibility of the ferri/ferrocyanide redox couple presenting a significantly improved performance compared with electrodes treated by only one of the steps. Electrodes treated by the combined method also showed a better electrochemical response for tyrosine oxidation. These electrodes were used as a non-enzymatic tyrosine sensor for quantification in human urine samples. Two fortified urine samples were analyzed, and the recovery values were 106 and 109%. The LOD and LOQ for tyrosine determination were 0.25 and 0.83 μmol L−1, respectively, demonstrating that the proposed devices are suitable sensors for analyses of biological samples, even at low analyte concentrations. [ABSTRACT FROM AUTHOR]

In this study, a flexible conductive filament was fabricated by mixing thermoplastic polyurethane (TPU), carbon nanotubes (CNTs), and Cu powder. A polymer extruder was used to disperse conductive materials in the TPU matrix. Because the dispersion of CNTs in polymers is difficult, the dispersion process was repeated several times for the homogeneity of the fabricated conductive filament. Cu powder with high electrical conductivity was additionally added to improve the electrical characteristics of the conductive polymer. As TPU generally has excellent ductility and durability, the fabricated filament can secure flexibility. The resistance was measured and compared according to the mixing ratio of CNT/Cu powder. Based on the obtained results, the resistance of the conductive filament decreased as the CNT and Cu powder contents were increased. The addition of metal powders, such as CNTs and Cu powder, however, reduced the ductility of TPU. Finally, the developed conductive filament was used to fabricate a simple closed photodiode circuit. [ABSTRACT FROM AUTHOR]

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Resistive random-access memory (RRAM) is a promising candidate for next-generation non-volatile memory. However, due to the random formation and rupture of conductive filaments, RRMS still has disadvantages, such as small storage windows and poor stability. Therefore, the performance of RRAM can be improved by optimizing the formation and rupture of conductive filaments. In this study, a hafnium oxide-/aluminum-doped zinc oxide/hafnium oxide (HfO2/Al-ZnO/HfO2) tri-layer structure device was prepared using the sol–gel method. The oxygen-rich vacancy Al-ZnO layer was inserted into the HfO2 layers. The device had excellent RS properties, such as an excellent switch ratio of 104, retention of 104 s, and multi-level storage capability of six resistance states (one low-resistance state and five high-resistance states) and four resistance states (three low-resistance states and one high-resistance state) which were obtained by controlling stop voltage and compliance current, respectively. Mechanism analysis revealed that the device is dominated by ohmic conduction and space-charge-limited current (SCLC). We believe that the oxygen-rich vacancy concentration of the Al-ZnO insertion layer can improve the formation and rupture behaviors of conductive filaments, thereby enhancing the resistive switching (RS) performance of the device. [ABSTRACT FROM AUTHOR]

In this study, a conductive thermoplastic elastomer (TPE) filament coated was developed with a graphene/polyvinyl alcohol composite solution by spray-coating it with an airbrush. The graphene/polyvinyl alcohol composite solution was prepared with three types of graphene content of 2 wt%, 8 wt%, and 16 wt%, and coated it 1, 5, 10, 15, 20, and 25 times. The prepared samples were analyzed by means of morphology, increase of diameter, pick-up rate, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), tensile strength, and conductivity. From the morphology and the increase of diameter and pick-up rate, it was confirmed that the diameter and weight increased as the graphene content and the number of coatings increased. In DSC, glass transition temperature and melting temperature were similar to those of TPE, but the enthalpy was increased as the number of coatings increased. For TGA, the residue increased as the graphene content and the number of coatings increased. For tensile strength, it was confirmed that the graphene content of 2 wt% composite solution had the best adhesion to the TPE filament surface resulting in a great tensile strength. The conductivity was the best when coated with a 16 wt% composite solution. Therefore, this study confirmed that the conductive filament, which is intended to be applied to wearable healthcare clothing in the future, needs to be coated with a 16 wt% graphene composite solution. [ABSTRACT FROM AUTHOR]

TiO 2 -based resistive random access memory (RRAM) devices has the potential to fabricating nonvolatile memory applications. However, the memories based on TiO 2 have severe problems like large resistive switching parameter fluctuations, poor cycling endurance and so on, which can be a limitation of the device in practical applications. Graphene oxide (GO) is a novel material that has attracted much attention and is often applied to enhance the performance of memories due to its own special properties. In this work, two types of bilayer structure based on TiO 2 for RRAM devices were fabricated. The significant improvement in uniformity of operating voltages and high HRS/LRS ratio of the TiO 2 -based RRAM were realized by inserting a two-dimensional GO film between TiO 2 and FTO. The presence of the GO film would prevent the ion exchange between the electrodes and the switching layer as well as its insulating properties. The conduction mechanisms of all the devices in low and high resistance states were dominant by the Ohmic conduction mechanism and the space charge limited conduction mechanism, respectively. This research manifests the promising potential of two-dimensional GO embedded layer for improving resistive switching performance of RRAMs. • Well and uniform TiO 2 and graphene oxide films were fabricated. • The bipolar resistive switching behavior was studied. • Improved performance of the TiO 2 -based RRAM by inserting graphene oxide film. • The mechanism of the inserting graphene on the switching performance was studied. • Conduction mechanism is ascribed to the SCLC and the Ohmic conduction. [ABSTRACT FROM AUTHOR]

2D materials have emerged as potential building blocks for electrochemical metallization (ECM) memristors with excellent performance. The evolution dynamics of conductive filaments (CFs) directly determine the resistance switching performance of the 2D material-based ECM memristors. However, achieving controllable CFs under the operation conditions remains challenging. Here, in situ transmission electron microscopy was employed to investigate the formation and evolution of CFs in Au/MoS 2 /Ag planar ECM memristors under electric fields, and various growth modes of CFs dependent on electric field strength were revealed. As the electric field intensity increased, the CFs exhibited diverse morphological variations, transitioning from a nanocluster-type to a continuous solid-type. Especially, the nanocluster-induced CF growth and nanobridge-assisted coalescence of nanoclusters under the electric field were observed, wherein bipolar electrochemical reactions were identified as playing a crucial role in the morphological evolution of nanoclusters and the formation of CFs. The results provide insights into the optimization of ECM planar memristors based on 2D materials.

Two-dimensional (2D) transition metal dichalcogenides (TMDCs) known for their exceptional electrical and optical properties have emerged as promising channel materials for next-generation electronics. However, as strong Fermi-level pinning (FLP) between the metal and the 2D TMDC material at the source/drain (S/D) contact decides the Schottky barrier height (SBH), the transistor polarity is fixed to a certain type, which remains a challenge for the 2D TMDC field-effect transistors (FETs). Here, a S/D contact structure with a quasi-zero-dimensional (quasi-0D) contact interface, in which the dimensionality reduction effect alleviates FLP, was developed to gain controllability over the polarity of the 2D TMDC FET. As a result, conventional metal contacts on the WSe 2 FET showed n-type characteristics due to strong FLP (pinning factor of 0.06) near the conduction band, and the proposed quasi-0D contact enabled by the Ag conductive filament on the WSe 2 FET exhibited p-type characteristics with a SBH very close to the Schottky-Mott rule (pinning factor of 0.95). Furthermore, modeling of Schottky barriers of conventional contacts, one-dimensional (1D) contacts, and quasi-0D contacts revealed that the SBH of the quasi-0D contact is relatively less subject to interface dipoles that induce FLP, owing to more rapid decaying of dipole energy. The proposed contact in this study provided a method that progressed beyond the alleviation of FLP to achieve controllable polarity. Moreover, reducing the contact dimensionality to quasi-0D will enable high compatibility with the further scaled-down nanoscale device contact structure.

Neuromorphic engineering is rapidly developing as an approach to mimicking processes in brains using artificial memristors, devices that change conductivity in response to the electrical field (resistive switching effect). Memristor-based neuromorphic systems can overcome the existing problems of slow and energy-inefficient computing that conventional processors face. In the Introduction, the basic principles of memristor operation and its applications are given. The history of switching in sandwich structures and granular metals is reviewed in the Historical Overview. Particular attention is paid to the fundamental articles from the pre-memristor era (the 1960s-70s), which demonstrated the first evidence of resistive switching and predicted the filamentary mechanism of switching. Multi-dimensionality in neuromorphic systems: Despite the powerful computational abilities of traditional memristor arrays, they cannot repeat many organizational characteristics of biological neural networks, i.e., their multi-dimensionality. This part reviews the unconventional nanowire- and nanoparticle-based neuromorphic systems that demonstrate incredible potential for use in reservoir computing due to the unique spiking change in conductance similar to firing in neurons. Liquid-based neuromorphic devices: The transition of neuromorphic systems from solid to liquid state broadens the possibilities for mimicking biological processes. In this section, ionic current memristors are reviewed and, the working principles of which bring us closer to the mechanisms of information transmittance in real synapses. Nanofluids: A novel direction in neuromorphic engineering linked to the application of nanofluids for the formation of reconfigurable nanoparticle networks with memristive properties is given in this section. The Conclusion t summarizes the bullet points of the Review and provides an outlook on the future of liquid-state neuromorphic systems., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

A novel antiferroelectric material, PbSnO 3 (PSO), was introduced into a resistive random access memory (RRAM) to reveal its resistive switching (RS) properties. It exhibits outstanding electrical performance with a large memory window (>10 4 ), narrow switching voltage distribution (±2 V), and low power consumption. Using high-resolution transmission electron microscopy, we observed the antiferroelectric properties and remanent polarization of the PSO thin films. The in-plane shear strains in the monoclinic PSO layer are attributed to oxygen octahedral tilts, resulting in misfit dislocations and grain boundaries at the PSO/SRO interface. Furthermore, the incoherent grain boundaries between the orthorhombic and monoclinic phases are assumed to be the primary paths of Ag + filaments. Therefore, the RS behavior is primarily dominated by antiferroelectric polarization and defect mechanisms for the PSO structures. The RS behavior of antiferroelectric heterostructures controlled by switching spontaneous polarization and strain, defects, and surface chemistry reactions can facilitate the development of new antiferroelectric device systems.

A theoretical model that describes the degradation of the resistive states of the memristor over time has been proposing. It has been showing that the current through the memristor cell is limiting by tunneling through the barrier at the nonstoichiometric oxide/metal interfaces. Degradation of the resistive state is generated by diffusive dissolution of the conductive channel. It leads to a change in the space charge region of the metal/dielectric interface. The impact of the filament cross-section, the width of the rupture region, and vacancy concentration in this area on the degradation of HRS and LRS states were investigated. The model explains various kinds of memristor degradation observed in the experimental works of different authors. The connection between the type of degradation and the filament parameters/environment of the dielectric has been demonstrating. [ABSTRACT FROM AUTHOR]

In this letter, we present a novel invisible bilayer ZnSnOy/ZnSnOx memristor for photo sensing. The device exhibits excellent photo sensing features such as a highly stable electrical set and optical reset endurances at least 2200 cycles for blue light and 1800 cycles for green and red light without any deterioration. Moreover, the device shows excellent retention (105 s) at 90 °C without disruption and high transmittance of about 85%. These outstanding device properties would allow us to create either an optical to an electronic memory device or an always-on continuous measurement optoelectronic sensor. [ABSTRACT FROM AUTHOR]

In this paper, the differential equations of the conductive filament growth are suggested on the basis of the jump conduction of ions in the dielectric film. We solved these equations by means of the average value method, obtaining the calculative formula of the forming and set time. Then, we proposed an algorithm of getting the jump rate, the jump distance, and the potential barrier. These parameters are linked with the forming and set time. As a result, the model of calculating microscopic parameters for the conductive filament growth is built. Besides calculating microscopic parameters, this model can also be used to compute the electrical parameters of ions and electrical characteristics of the conductive filament in the forming and set processes, such as the mobility of ions and the current in the process of the conductive filament growth. The calculated data of the model are consistent with the experimental results. [ABSTRACT FROM AUTHOR]

[Display omitted] • Hydrothermal synthesis of 2D nanosheets assembled MoSe 2 flowers. • Controlled oxidation of MoSe 2 to convert into MoSe 2-x O y. • Au/MoSe 2-x O y /Au exhibited filamentary type bipolar resistive switching. • Coexistence of MoSe 2 and MoO x (x < 3) enhanced memristive performance. • Valance change mechanism was dominant due to presence of MoOx in MoSe 2. The current study shows an improvised resistive switching in oxygenated MoSe 2 (MoSe 2-x O y) thin film. 2D nanosheets assembled nanoflower morphology of MoSe 2 was synthesized with hydrothermal route and then treated with thermal oxidation process at 300⁰C in presence of 0, 0.5, 5 and 20 % of oxygen. The coexistence of MoSe 2 and MoO x in each samples was investigated with various spectroscopic techniques. The conversion to MoO x was maximum in 20 % O 2 treated sample while other samples were converted partially. Au/MoSe 2-x O y /Au structured devices were fabricated on SiO 2 /p-Si substrate and tested for resistive switching study. Among all four devices, 5 % O 2 treated MoSe 2-x O y exhibited excellent filamentary type bipolar resistive switching with very low SET and RESET voltages of + 0.84 V and −0.79 V, respectively. The device showed I ON /I OFF ratio ∼50 (at read voltage: 0.5 V) with excellent retention (106 s) and endurance (100 cycles) characteristics with minimum cycle-to-cycle variation. The resistive switching mechanism was explained with valance change conducting filament formation/rupture model and the trap-controlled space charge limited current behavior. Rich transport properties of 2D-chalcogenide (MoSe 2) and classic oxygen vacancy migrated switching of metal oxide (i.e. MoO x), were simultaneously important for achieving high performance memristive behavior in 5 % O 2 treated MoSe 2. [ABSTRACT FROM AUTHOR]

Metal oxide-based memristors are promising candidates for breaking through the limitations in data storage density and transmission efficiency in traditional von Neumann systems, owing to their great potential in multi-state data storage and achievement of the in-memory neuromorphic computing paradigm. Currently, the resistive switching behavior of those is mainly ascribed to the formation and rupture of conductive filaments or paths formed by the migration of cations from electrodes or oxygen vacancies in oxides. However, due to the relatively low stability and endurance of the cations from electrodes, and the high mobility and weak immunity of oxygen vacancies, intermediate resistance states can be hardly retained for multilevel or synaptic resistive switching. Herein, we reviewed the memristors based on cationic interstitials which have been overlooked in achieving digital or analog resistive switching processes. Both theoretical calculations and experimental works have been surveyed, which may provide reference and inspiration for the rational design of multifunctional memristors, and will promote the increments in the memristor fabrications.

Electroencephalography (EEG) is used to detect brain activity by recording electrical signals across various points on the scalp. Recent technological advancement has allowed brain signals to be monitored continuously through the long-term usage of EEG wearables. However, current EEG electrodes are not able to cater to different anatomical features, lifestyles, and personal preferences, suggesting the need for customisable electrodes. Despite previous efforts to create customisable EEG electrodes through 3D printing, additional processing after printing is often needed to achieve the required electrical properties. Although fabricating EEG electrodes entirely through 3D printing with a conductive material would eliminate the need for further processing, fully 3D-printed EEG electrodes have not been seen in previous studies. In this study, we investigate the feasibility of using a low-cost setup and a conductive filament, Multi3D Electrifi, to 3D print EEG electrodes. Our results show that the contact impedance between the printed electrodes and an artificial phantom scalp is under 550 Ω, with phase change of smaller than −30∘, for all design configurations for frequencies ranging from 20 Hz to 10 kHz. In addition, the difference in contact impedance between electrodes with different numbers of pins is under 200 Ω for all test frequencies. Through a preliminary functional test that monitored the alpha signals (7–13 Hz) of a participant in eye-open and eye-closed states, we show that alpha activity can be identified using the printed electrodes. This work demonstrates that fully 3D-printed electrodes have the capability of acquiring relatively high-quality EEG signals.

Central and peripheral biological clocks are essential to regulate creatures' circadian rhythms, mimicking the biological clock controlled neural and/or immunological responses are research hotspots in the emerging neuromorphic or brain-like systems. However, the current neuromorphic devices still depend on programmable frequency dividing and doubling machine clocks, the high system cost is a challenge to conduct sophisticated brain-like neuromorphic computing. Herein, a dual biological-clocks (including ambient light and endocrine) controllable fibrous synapse crossbar array is proposed. It is demonstrated and confirmed in this work, the Ag conductive filaments, which are critical in the conventional MXene synapses, can be successfully switched by differently biased MoS 2 /MXene heterojunction. The current and power of the unit fibrous synapse in positive/negative switching processes can reach as low as 460 pA/-170 pA and 330 pW/121 pW, respectively. Then, four kinds of logical calculations to the input light signals are accomplished by using the as-prepared fibrous synapse based logical gate. Meanwhile, the light and serotonin combined modulation on the synaptic currents are manifested and applied to simulate the immune-neural responses (memory and the memory exhausted) of T cells in the skin clock. More interestingly, two biological immune compensation mechanisms controlled by the central clock and peripheral clock, namely balanced and reset immune compensation, are also accomplished. This work may pave a new way for promoting the development of dual biological-clock regulated computations in neuromorphic systems. [Display omitted] • A fibrous synapse array based on heterojunction-switched filament is proposed. • Low currents and power consumption of the unit device are demonstrated. • Four logical calculations to light signals are accomplished. • Simulations of skin T cell's immune responses in dual biological clocks. • The immune compensation mechanisms are successfully simulated for the first time. [ABSTRACT FROM AUTHOR]

The current work experimentally determined how the initial resistance and gauge factor in additively manufactured piezoresistive sensors are affected by the material, design, and process parameters. This was achieved through the tensile testing of sensors manufactured with different infill angles, layer heights, and sensor thicknesses using two conductive polymer composites. Linear regression models were then used to analyze which of the input parameters had significant effects on the sensor properties and which interaction effects existed. The findings demonstrated that the initial resistance in both materials was strongly dependent on the sensor geometry, decreasing as the cross-sectional area was increased. The resistance was also significantly influenced by the layer height and the infill angle, with the best variants achieving a resistance that was, on average, 22.3% to 66.5% lower than less-favorable combinations, depending on the material. The gauge factor was most significantly affected by the infill angle and, depending on the material, by the layer height. Of particular interest was the finding that increasing in the infill angle resulted in an increase in the sensitivity that outweighed the associated increase in the initial resistance, thereby improving the gauge factor by 30.7% to 114.6%, depending on the material.