Search Results (300)

Single memristive nanowire networks have emerged as a promising pathway for energy-efficient neuromorphic computing, owing to their intrinsic nonlinearity, high dimensionality, fading memory and volatile switching dynamics relevant to physical reservoir computing. While prior works focused on oxide- or silver-based network systems, these approaches face trade-offs between operating voltage, cost, stability, and scalability. This work presents a proof-of-concept demonstration of stochastic polyvinylpyrrolidone (PVP)-coated nickel nanowire networks as low-cost and scalable memristive platforms, exhibiting low-voltage resistive switching (1–2 V). The electrical characterization reveals predominantly volatile resistive switching combined with nonvolatile behavior, consistent with a filamentary conduction mechanism at nanowire junctions. The switching dynamics are governed by the polymer coating thickness, with an intermediate PVP concentration (Ni@PVP = 1:25) showing optimal performance, with a resistance ratio of ~200, stable retention over 1 h, and a reproducible endurance of over 45 cycles. These results establish Ni@PVP nanowire networks as promising memristive platforms for neuromorphic hardware applications and physical reservoir computing, with relevant properties such as fading memory and nonlinear dynamics. Full article

Here, the resistive switching characteristics in a Cu/a-SiC/P+-Si sandwiched structure are systematically investigated for multilevel nonvolatile memory applications. The formation of Cu conducting filaments is believed to be the switching mechanism through temperature-dependent testing. Four distinguished resistance states can be achieved in the Cu/a-SiC/P+-Si memory device through the modulation of suitable compliance current, which could be attributed to the formation of more conductive filaments when applying a higher compliance current during the Set process. In addition, these different resistance values can be easily distinguished and show reliable retention (~105 s), with the temperature even reaching 85 °C, which offers considerable potential for high-density RRAM applications. Full article

Memristors are valuable elements with very good memory and switching features. They have minimal power consumption, nano-scale sizes, and a possibility for integration with high-density Complementary Metal Oxide Semiconductor (CMOS) integrated circuits. They are applicable in neural networks, memory crossbars, and different electronic devices. This work considers some improved and existing models for memristors, functioning at high-frequency signals with a high speed and very good effectiveness. The main parasitic parameters—series resistance, capacitance, and small-signal direct current (DC) voltage and current shifting signals—are taken into account. An additional leakage conductance is analyzed as a parasitic component. The influence of the parasitic parameters on the normal functioning of memristor-based circuits is analyzed and evaluated at hard-switching and soft-switching modes. For investigations of the main characteristics of the considered models and their applicability in memory arrays, Linear Technology Simulation Program with Integrated Circuits Emphasis (LTSPICE) library models are generated and analyzed. The considered models operate at low-, middle- and high-frequency signals, clearly demonstrating the main properties of memristors. Their appropriate operation in passive memory arrays is analyzed and established. The proposed models have a 26% enhanced accuracy in fitting experimental i-v relations. They ensure good memory and switching properties for memory arrays. This work could be a suitable step towards the design and manufacturing of ultra-high-density memristor-based integrated chips. Full article

In the post-Moore’s Law era, conventional Von Neumann architectures face critical limitations, such as the “memory wall” and excessive power consumption, particularly when processing unstructured data. Neuromorphic computing, inspired by the human brain, offers a promising solution through parallel processing and adaptive learning. Among the candidates for artificial synapses, memristors based on two-dimensional MXenes (specifically Ti₃C₂T_x) have attracted significant attention due to their unique layered structure, high metallic conductivity, and tunable physicochemical properties. This review provides a comprehensive analysis of MXene-based memristors, from material synthesis to system-level applications. We examine how different synthesis strategies, including etching methods, directly influence device performance and elucidate the underlying resistive switching mechanisms driven by ion migration, valence change, and interfacial processes. Furthermore, the review demonstrates the efficacy of MXenes in emulating biological synaptic functions—such as spike-timing-dependent plasticity (STDP) and long-term potentiation/depression (LTP/LTD)—and their application in tasks like handwritten digit recognition. Finally, we highlight emerging frontiers in flexible electronics and in-sensor computing, offering insights into the future trajectory of integrated sensing, memory, and computation. Full article

In this study, ZnO thin films were prepared on the flexible stainless steel (FSS) substrates by the sol–gel method. ZnO nanorods were then hydrothermally grown in the presence of polyvinyl pyrrolidone (PVP) to obtain polymer/nanooxide composites. The microstructure and resistive switching properties of the composites were investigated. X-ray diffraction results confirmed that the PVP-doped ZnO nanorods retained the hexagonal wurtzite structure and had a preferred (002) orientation despite a slight decrease in crystallinity. Surface morphology analysis showed that the addition of PVP resulted in an increase in the nanorod density and a more regular hexagonal structure. Electrical measurements showed a significant improvement in the resistive switching behavior, with a high-resistance state to low-resistance state (HRS/LRS) ratio of 4.67 × 10³. In addition, radiation-tolerant cyclic tests demonstrated that the polymer–oxide hybrid structure effectively buffered irradiation-induced defects, stabilized conductive filament pathways, and preserved switching reliability. These results highlight the potential of PVP-doped ZnO nanorod composites as reliable, flexible, and radiation-tolerant RRAM devices for future aerospace and high-radiation electronics applications. Full article

This work focuses on developing resistive switching (RS) devices using thermally annealed (TA) SiO₂/Si multilayers (ML). Three SiO₂/Si bilayers were deposited with an additional 10 nm SiO₂ layer as a dielectric barrier layer on top of the ML. The SiO₂ layers were 6 nm thick, while the thickness of the Si layers varied from 2, 4, and 6 nm, and were labeled as ML-62, ML-64, and ML-66, respectively. X-ray photoelectron spectroscopy analysis revealed well-defined ML structures before TA. However, after TA, samples ML-64 and ML-62 showed discontinuities due to diffusion between neighboring Si layers, increasing the dimensions of the Si-rich regions. In fact, the concentration of elemental Si (Si⁰) within the intermediate Si layer increases as the Si layer becomes thinner. Consequently, the size of Si-nanocrystals, created after TA, increases from 6 to 8.5 nm for ML-66 to ML-62, as confirmed by Raman and transmission electron microscopy analysis. The composition discontinuities and loss of the ML structure resulted in erratic electrical behavior, with an electroforming (EF) voltage as high as −14 V in sample ML-62. For the ML-66, which retained the ML structure, the EF voltage was reduced to −4 V, showing SET/RESET values of around ±3 V and stable electrical behavior, with an ON/OFF ratio of up to seven orders of magnitude. This demonstrates the importance of the ML design in the operation of RS devices. Full article

Ba_0.6Sr_0.4TiO₃ (BST) thin films were deposited on ITO substrates via rf magnetron sputtering, followed by structural and morphological characterization using XRD and FE-SEM. Metal–insulator–metal (MIM) RRAM devices were fabricated by depositing Al top electrodes, and their electrical properties were examined through I–V measurements. The optimized BST films deposited at 40% oxygen concentration exhibited stable resistive switching, with an operating voltage of 3 V, an on/off ratio of 1, and a leakage current of 10⁻⁸ A. After rapid thermal annealing at 500 °C, the on/off ratio improved to 2 but leakage increased to 10⁻³ A. Incorporating an electron transport layer (ETL) effectively suppressed the leakage current to 10⁻⁵ A while maintaining the on/off ratio at 2. Moreover, a transition from bipolar to unipolar switching was observed at higher oxygen concentration (60%). These results highlight the role of ETLs in reducing leakage and stabilizing switching characteristics, providing guidance for the development of transparent, low-power, and high-reliability BST-based RRAM devices. This study aims to investigate the role of Ba_0.6Sr_0.4TiO₃ (BST) ferroelectric oxide as a functional switching layer in resistive random-access memory (RRAM) and to evaluate how interface engineering using an electron transport layer (ETL) can improve resistive switching stability, leakage suppression, and device reliability. Full article

Work investigates the doping of molybdenum oxide (MoO_x) with tungsten (W). The successful incorporation of W into the MoO_x lattice was confirmed through X-ray photoelectron spectroscopy (XPS) and energy-dispersive X-ray spectroscopy (EDS). Structural and optical analysis revealed the presence of oxygen vacancies within the W-MoO_x film, which are known to facilitate resistive switching (RS) in memristive devices. Based on this, a flexible memristor with the structure PET/ITO/W-MoO_x/polymethyl methacrylate (PMMA)/Al was fabricated. PMMA was strategically introduced between the W-MoO_x layer and the aluminum electrode to modulate interfacial properties that influence RS behavior. The W-MoO_x/PMMA-based memristor exhibited good resistive switching characteristics, with a memory window of approximately 12 and a retention time exceeding 2 × 10⁴ s, demonstrating a non-volatile memory behavior. In the high-resistance state (HRS), the conduction mechanism under higher applied voltages follows a space-charge-limited current (SCLC) model, indicating that the RS process is primarily governed by charge trapping and de-trapping at the interface. Overall, the consistent and robust switching performance of the W-MoO_x/PMMA heterostructure underlines its potential as a reliable functional layer for next-generation resistive random-access memory (ReRAM) devices. Full article

Thin films of nickel oxide (NiO) were deposited on a 5° miscut magnesium oxide (MgO)(100) substrate using electron-beam evaporation to pursue morphology-directed resistive switching. The atomic force microscope (AFM) confirmed a stepped surface with a terrace width of ~85 nm and a step height of ~7 nm. After deposition, the film resistance decreased from 200 MΩ to 25 MΩ by annealing under ambient air at 400 °C, attributed to the increase in the p-type conductivity through nickel vacancy formation. Top electrodes of Ag (500 nm width, 180 nm gap) were patterned parallel or perpendicular to the substrate steps using UV and electron-beam lithography. Devices aligned parallel to the step showed reproducible unipolar switching with 100% yield between forming voltages 20–70 V and HRS/LRS~10² at ±5 V. In contrast, devices formed perpendicular to the steps (8/8) subsequently failed catastrophically during electroforming, with scanning electron microscopy (SEM) showing breakdown holes on the order of ~100 nm at the step crossings. The anisotropic electrodynamic response is due to step-guided electric field distribution and directional nickel vacancy migration, illustrating how substrate morphology can deterministically influence filament nucleation. These results highlighted stepped MgO as a template to engineer the anisotropic charge transport of NiO, exhibiting a reliable ReRAM as well as directional electrocatalysis for energy applications. Full article

To meet the demand for energy-efficient and high-performance computing in resource-limited sensor edge applications, this paper presents a reconfigurable memristor-based computing-in-memory circuit for Content-Addressable Memory (CAM). The scheme exploits the analog multi-level resistance characteristics of memristors to enable parallel multi-bit processing, overcoming the constraints of traditional binary computing and significantly improving storage density and computational efficiency. Furthermore, by employing dynamic adjustment of the mapping between input signals and reference voltages, the circuit supports dynamic switching between exact and approximate CAM modes, substantially enhancing functional flexibility. Experimental results demonstrate that the 32 × 36 memristor array based on a TiN/TiOx/HfO₂/TiN structure exhibits eight stable and distinguishable resistance states with excellent retention characteristics. In large-scale array simulations, the minimum voltage separation between state-representing waveforms exceeds 6.5 mV, ensuring reliable discrimination by the readout circuit. This work provides an efficient and scalable hardware solution for intelligent edge computing in next-generation sensor networks, particularly suitable for real-time biometric recognition, distributed sensor data fusion, and lightweight artificial intelligence inference, effectively reducing system dependence on cloud communication and overall power consumption. Full article

In the pursuit of advanced non-volatile memory technologies, ferroelectric memristors have attracted great attention. However, traditional perovskite ferroelectric materials are hampered by environmental pollution, limited applicability, and the complexity and high cost of conventional vacuum deposition methods. This has spurred the exploration of alternative materials and fabrication strategies. Herein, a flexible Pt/Zr: HfO₂ (HZO)/graphene oxide (GO)/mica memristor is successfully fabricated using the total solution-processed method. The interfacial oxygen competition mechanism between the HZO layer and the GO bottom electrode facilitates the formation of the HZO ferroelectric phase. The as-prepared device exhibits a switching ratio of approximately 150 and can maintain eight distinct resistance levels, and it can also effectively simulate neural responses. By integrating the ferroelectric polarization principle and the piezoelectric effect of HZO, along with the influence of GO, the performance variations of the as-prepared device under mechanical and thermal influences are further explored. Notably, Morse code recognition is achieved by utilizing the device’s pressure properties and setting specific press rules. The as-prepared device can accurately convert and store information, opening new avenues for non-volatile memory applications in silent communication and promoting the development of wearable electronics. Full article

The random thermal switching of domain walls (DWs) in perpendicularly magnetized anisotropy nanowires (PMA) poses a significant challenge for the reliability of spintronic storage devices. In this work, we study the thermal nucleation and dynamics of DWs in PMA nanowires using micromagnetic simulations. The focus is on the effect of device temperature, with attention to uniaxial anisotropy energy (K_u), saturation magnetization (M_s), and nanowire geometry. The results show that larger K_u or M_s reduces DW thermal switching, thereby enhancing DW thermal stability and increasing the DW nucleation temperature (T_n). A wider or thicker nanowire also lowers the probability of thermally induced DW creation, further improving stability. In addition, DW velocity rises with temperature, showing a thermally assisted motion. These results provide useful guidance for designing PMA-based memory devices with improved resistance to thermal fluctuations. Full article

In this study, silicon carbide (SiC) thin films for resistive random-access memory (RRAM) devices were successfully prepared using the radio-frequency magnetron sputtering method at deposition powers of 50 and 75 W for 1 h. The aluminum (Al) top electrode of the RRAM devices was also fabricated using thermal evaporator deposition. Additionally, the electrical properties of the SiC thin film RRAM devices were determined using a B2902A mechanism. The current–voltage (I–V) curves of the as-deposited SiC thin films at 50 and 75 W power levels were measured and analyzed. Specifically, the set and reset voltages for the RRAM devices deposited at 50 and 75 W were approximately 1.2 and −1.5 V, respectively. For the annealed samples, the memory windows of the 75 W SiC thin film RRAM devices treated at 300 °C were found to be around 10⁵. Full article

Gallium oxide (Ga₂O₃)-based memristors are gaining traction as promising candidates for next-generation electronic devices toward in-memory computing, leveraging the unique properties of Ga₂O₃, such as its wide bandgap, high thermodynamic stability, and chemical stability. This review explores the evolution of memristor theory for Ga₂O₃-based materials, emphasising capacitive memristors and their ability to integrate resistive and capacitive switching mechanisms for multifunctional performance. We discussed the state-of-the-art fabrication methods, material engineering strategies, and the current challenges of Ga₂O₃-based memristors. The review also highlights the applications of these memristors in memory technologies, neuromorphic computing, and sensors, showcasing their potential to revolutionise emerging electronics. Special focus has been placed on the use of Ga₂O₃ in capacitive memristors, where their properties enable improved switching speed, endurance, and stability. In this paper we provide a comprehensive overview of the advancements in Ga₂O₃-based memristors and outline pathways for future research in this rapidly evolving field. Full article

Resistive switching (RS) phenomena are nowadays one of the most studied topics in the area of microelectronics. It can be observed in Metal–Insulator–Metal (MIM) structures that are the basis of resistive switching random-access memories (RRAMs). In the case of commercial use of RRAMs, it is beneficial that the applied materials would have to be compatible with Complementary Metal-Oxide-Semiconductor (CMOS) technology. Fabricating methods of these materials can determine their stoichiometry and structural composition, which can have a detrimental impact on the electrical performance of manufactured devices. In this study, we present the influence of the Ar/N₂ ratio during reactive magnetron sputtering of titanium nitride (TiN) electrodes on the resistive switching behavior of MIM devices. We used silicon oxide (SiOx) as a dielectric layer, which was characterized by the same properties in all fabricated MIM structures. The composition of TiN thin layers was controlled by tuning the Ar/N₂ ratio during the deposition process. The fabricated conductive materials were characterized in terms of chemical and structural properties employing X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) analysis. Structural characterization revealed that increasing the Ar content during the reactive sputtering process affects the crystallite size of the deposited TiN layer. The resulting crystallite sizes ranged from 8 Å to 757.4 Å. The I-V measurements of fabricated devices revealed that tuning the Ar/N₂ ratio during the deposition of TiN electrodes affects the RS behavior. Our work shows the importance of controlling the stoichiometry and structural parameters of electrodes on resistive switching phenomena. Full article