Resistive Switching Behavior Research Articles

Coexistence of digital and analog resistive switching behaviors in nanocrystalline yttrium-iron-garnet thin films achieved by electrode engineering

Memristors with digital or analog resistive switching characteristics have the potential to acquire high-performance data storage or electronic synaptic device applications, respectively. It is considerably important to realize coexistence of digital and analog resistive switching characteristics for high-performance memristor applications. In this study, the nanocrystalline yttrium-iron-garnet Y3Fe5O12 (YIG) thin film was synthesized on Pt substrates by a facile solution-processed method, and it can be used as resistive switching layer for fabricating memory devices. The digital and analog resistive switching characteristics in YIG thin film devices were achieved by employing inert platinum and active silver electrodes, respectively. Oxygen vacancy-controlled conductive filaments (CFs) with Pt/YIG/Pt structure exhibited digital resistive switching behavior which can be modulated by changing voltage polarity. The resistive switching mode with positive Set/Reset in the Pt/YIG/Pt device acquired superior resistive switching properties. Ag/YIG/Pt device exhibited analog resistive switching characteristics based on the formation of Ag-based CFs. The conductance increase during Set operation and decrease during Reset process by adjusting current gradients and voltage windows, respectively. The present study exhibits an effective path to obtain the digital and analog resistive switching properties, which opens a door for understanding and optimizing resistive switching performance.

Nanoscale resistive switching behaviour and photoabsorption response from NiO nanoflakes

Nanoscale resistive switching behaviour and photoabsorption response from NiO nanoflakes

Data encryption/decryption and medical image reconstruction based on a sustainable biomemristor designed logic gate circuit

Memristors are considered one of the most promising new-generation memory technologies due to their high integration density, fast read/write speeds, and ultra-low power consumption. Natural biomaterials have attracted interest in integrated circuits and electronics because of their environmental friendliness, sustainability, low cost, and excellent biocompatibility. In this study, a sustainable biomemristor with Ag/mugwort:PVDF/ITO structure was prepared using spin-coating and magnetron sputtering methods, which exhibited excellent durability, significant resistance switching (RS) behavior and unidirectional conduction properties when three metals were used as top electrode. By studying the conductivity mechanism of the device, a charge conduction model was established by the combination of F-N tunneling, redox, and complexation reaction. Finally, the novel logic gate circuits were constructed using the as-prepared memristor, and further memristor based encryption circuit using 3-8 decoder was innovatively designed, which can realize uniform rule encryption and decryption of medical information for data and medical images. Therefore, this work realizes the integration of memristor with traditional electronic technology and expands the applications of sustainable biomemristors in digital circuits, data encryption, and medical image security.

Interface modeling analysis using density functional theory in highly reliable Pt/HfO2/TaOx/Ta self-rectifying memristor

The self-rectifying memristor (SRM) is a promising device prototype for high-density three-dimensional (3D) integration and high-efficiency in-memory computing (IMC) by virtue of its ability to effectively suppress sneak current, simple device structure, and low energy consumption. Theoretically understanding the intrinsic mechanisms of SRM is a matter of concern. Here, we fabricated a Ta/TaOx/HfO2/Pt-stacked SRM exhibiting >103 on/off ratio, rectification ratio, and nonlinearity. The SRM can be repeatedly programmed by more than 106 pulses and demonstrates robust retention and high scalability (∼59 Mbit). A reasonable interface model for this SRM is established based on first-principles calculations. Using self-energy corrected density function theory, we calculate the barrier heights at each interface. Detailed I–V curve fitting and energy band analysis are performed and computationally verified to explain the intrinsic reasons for resistive switching, self-rectifying, and nonlinear behaviors. The work may advance the development of SRM prototype to enable energy-efficient 3D IMC.

MemriSim: A theoretical framework for simulating electron transport in oxide memristors

We have developed a theoretical framework MemriSim for simulating the resistive switching behaviors of oxide memristors. MemriSim comprises two major parts, i) structural evolution of oxygen vacancies during conductive filament formation/rupture by kinetic Monte Carlo (kMC) algorithm, and ii) transport calculations based on the scenario of electron tunneling and thermionic emission with the kMC derived structures. As prototype probes, we have computed the current-voltage (I-V) curves of HfO2 and TaOx based memristors and compared the results with experimental measurements, which show perfect agreement. By tuning the physical parameters, MemriSim can describe resistive switching devices with different oxide layers and metal electrodes. In addition, the pulse transient current can also be simulated by considering the transient response of RLC circuit. The developed framework not only provides a general approach for understanding the fundamental mechanism of resistive switching in oxides, but also opens up new opportunities for designing and optimizing memristor-based architectures for nonvolatile memory, logic-in-memory and neuromorphic computing.Program summaryProgram Title: MemriSim.CPC Library link to program files: https://doi.org/10.17632/8gbbgf8z49.1Licensing provisions: GPLv2.Programming language: C++.Supplementary material: Supplementary material is available.Nature of problem: A general framework for simulating the resistive switching properties of oxide-based memristors; generate the structure of oxide layer during filament formation/rupture; calculate the I-V curves of memristive device; simulate the pulse transient current; predict the resistive switching performance of new devices.Solution method: The framework uses kMC algorithm for structural evolution, the electric field inside oxide layer is computed by the Poisson's equation, and the transport calculation is based on electron tunneling and thermionic emission.

Energy Efficient Memristor Based on Green-Synthesized 2D Carbonyl-Decorated Organic Polymer and Application in Image Denoising and Edge Detection: Toward Sustainable AI.

According to the United Nations, around 53 million metric tons of electronic waste is produced every year, worldwide, the big majority of which goes unprocessed. With the rapid advances in AI technologies and adoption of smart gadgets, the demand for powerful logic and memory chips is expected to boom. Therefore, the development of green electronics is crucial to minimizing the impact of the alarmingly increasing e-waste. Here, it is shown the application of a green synthesized, chemically stable, carbonyl-decorated 2D organic, and biocompatible polymer as an active layer in a memristor device, sandwiched between potentially fully recyclable electrodes. The 2D polymer's ultramicro channels, decorated with C═O and O─H groups, efficiently promote the formation of copper nanofilaments. As a result, the device shows excellent bipolar resistive switching behavior with the potential to mimic synaptic plasticity. A large resistive switching window (103), low SET/RESET voltage of ≈0.5/-1.5V), excellent device-to-device stability and synaptic features are demonstrated. Leveraging the device's synaptic characteristics, its applications in image denoising and edge detection is examined. The results show a reduction in power consumption by a factor of 103 compared to a traditional Tesla P40 graphics processing unit, indicating great promise for future sustainable AI-based applications.

Flexible memristors with low-operation voltage and high bending stability based on Cu2AgBiI6 perovskite

Cu2AgBiI6 films were prepared by a one-step spin coating method, and flexible memristors with an Ag/PMMA/Cu2AgBiI6/ITO structure were constructed. The devices showed a bipolar resistive switching behavior with low switching voltage, which is beneficial for reducing energy consumption. Furthermore, this study found that the device exhibits an endurance of about 900 cycles, a higher ON/OFF ratio of over 103, a long retention time (∼104 s), and high stabilities against mechanical stress. Remarkably, the present flexible memristor displayed extraordinary flexibility and stability, with no significant change for the resistive switching behavior even at various bending angles or after undergoing 900 bending cycles. This study establishes that the lead-free halide perovskite Cu2AgBiI6 can be used for the resistive random-access memory of flexible electronics.

Bipolar resistive switching behavior of PVA/g-C3N4 quantum dots hybrid thin films

Graphite-phase carbon nitride quantum dots (g-C3N4 QDs) have garnered widespread attention and considerable research interest as active media for resistive random-access memory (RRAM) devices owing to their exceptional physical properties. In this study, g-C3N4 QDs were synthesized via ultrasonic-assisted liquid-phase exfoliation. Subsequently, the obtained g-C3N4 QDs with uniform size were embedded into polyvinyl alcohol (PVA) for preparing PVA/g-C3N4 QDs hybrid, and the RRAM devices with Al/g-C3N4 QDs-PVA/ITO/PET structure were fabricated. The obtained memory devices exhibit bipolar resistive switching (BRS) behavior and are primarily influenced by the space charge limited conduction (SCLC) mechanism. The data retention time exceeds 104 s at a read voltage of 0.1 V, accompanied by an impressively low set voltage. In addition, the device exhibits a surprising temperature dependence of the resistive switching performance at different temperatures. The aforementioned properties demonstrate the significant potential of g-C3N4 QDs in RRAM for data storage applications.

Vacancy-driven resistive switching behavior based on wafer-scale MoSe2 artificial synapses

Recently, researches have revealed that synaptic transistors based on two-dimensional materials (2DMs) have substantial advantages and potential for modeling neural synapses. However, the mechanism of artificial synaptic device with 2DMs as conducting channels remains to be further clarified. Here, high-quality wafer-scale MoSe2 nanosheets were achieved by ALD-CVD process, where further 23 × 23 × 4 synaptic arrays were fabricated in situ. Notably, the outstanding MoSe2 synaptic device exhibits an on/off ratio of 3.6 × 107 with hysteresis ratio of 6.8k and simulates crucial biological synaptic behaviors such as paired pulse facilitation and excitatory postsynaptic currents. The mechanism of Se vacancy induction and horizontal diffusion driven is revealed based on high-resolution transmission electron microscopy characterization with first-principles calculations, which suggests a possible mechanistic explanation for the resistive switching behavior of 2DMs transistors. Artificial synaptic devices with 2DMs based on the working mechanism of vacancy diffusion are capable of satisfying the needs of complex neural network applications.

Speckle Pattern Analysis of PVK:rGO Composite Based Memristor Device

AbstractThe memristors are expected to be fundamental devices for neuromorphic systems and switching applications. The device made of a sandwiched layer of poly(N‐ vinylcarbazole) and reduced graphene composite between asymmetric electrodes (ITO/PVK:rGO/Al) exhibits bistable resistive switching behavior. The performance of the memristor can be optimized by controlling the doped graphene oxide. To assess the device performance when it switches between ON and OFF states, optical characterization approaches are highly promising due to their non‐destructive and remote nature. Here, speckle pattern (SP) analysis to this end is introduced. SPs include a huge amount of information about their generating mechanism, which is extracted through statistical elaboration. SPs of the PVK:rGO in different states in situ and examine the conduction mechanism is acquired. The variations in the statistical parameters are attributed to the resistance state of the PVK:rGO with regard to the physical switching mechanism. The resistance/conduction state, in turn, depends on the activity and properties of PVK:rGO memristors, as well as the additional non‐uniformities induced through the variations of density of carriers. The present optical methodology can be potentially served as a bench‐top device for characterization purposes of similar devices during their operating.

Improving the switching behavior of TaOx/HfO2-based non-volatile memristors by embedded Ti and Pt nano-islands

To investigate the effects of embedded metal nano-island (NI) arrays on reducing the variations of the device switching parameters, we fabricated Pt/HfO2/TiN, Pt/TaOx/HfO2/TiN devices, as well as devices with embedded NI arrays, including Pt/TaOx/HfO2/Pt NI/TiN and Pt/TaOx/HfO2/Ti NI/TiN devices. Compared to devices without nano-islands, the Pt/TaOx/HfO2/Pt NI/TiN devices with abrupt resistive switching behavior exhibit more stable resistance states (coefficient of variations (CVs) of RHRS and RLRS are 11.9 % and 13.0 %, respectively), and a large on/off ratio (>103), representing a high performance level among the HfO2-based non-volatile memristors reported to date, but the devices require a Forming process. The Pt/TaOx/HfO2/Ti NI/TiN devices with analog resistive switching behavior show low operating voltage (≤1 V), low resistance variations (CVs of RHRS, and RLRS are 15.8 %, and 17.6 %, respectively), but their on/off ratio (<10) is significantly reduced. The results indicate that embedding metal nano-island arrays decreases the fluctuations in device switching parameters, the different properties of nano-island materials significantly affect the abrupt/analog switching behavior, on/off ratio and the Forming of the non-volatile memristors. The methods employed in this study can be extended or evolved for other memristors to enhance their performance and applicability.

Antiferroelectric Heterostructures Memristors with Unique Resistive Switching Mechanisms and Properties.

A novel antiferroelectric material, PbSnO3 (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 (>104), 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.

Giant tunneling resistance and robust switching behavior in ferroelectric tunnel junctions of WS2/Ga2O3 heterostructures: The influence of metal–semiconductor contacts

The ferroelectric tunneling junctions (FTJs) are widely recognized as one of the non-volatile memories with significant potential. Ferroelectricity usually fades away as materials are thinned down below a critical value, and this problem is particularly acute in the case of shrinking device sizes, thus attracting attention to two-dimensional ferroelectric materials (2DFEMs). In this work, we designed 2D ferroelectric Ga2O3-based FTJs with out-of-plane polarization, and the influence of metal–semiconductor contact in the electrode region on the system is considered. Here, using density functional theory combined with the non-equilibrium Green's function approach to quantum transport calculations, we demonstrate robust ferroelectric polarization-controlled switching behavior between metallic and semiconducting states in Ga2O3/WS2 ferroelectric heterostructures. The potential barrier of the metal–semiconductor contact in the electrode region is lower than that of the intrinsic material, thereby resulting in an increased probability of electron tunneling. Our results reveal the crucial role of 2DFEMs in the construction of FTJs and highlight the significant impact of electrode contact types on performance. This provides a promising approach for developing high-density ferroelectric memories based on 2D ferroelectric semiconductor heterostructures.

Organic heterojunction memristors with enhanced tunable resistive states for artificial synapses

Tunable and uniform evolution of conductance is the key performance metric for neuromorphic computing leveraging memristors. Nonetheless, the stochastic conductance update associated with limited material composition and uncontrollable filament distribution has restricted the tunability that can be customized for targeted synaptic properties. Here, we introduce organic heterojunction memristors utilizing the C60/P3HT bilayer, demonstrating analog switching characteristics with multilevel conductance states. We demonstrate that both conventional bipolar and unipolar voltages can achieve synaptic plasticity modulation for potentiation and depression, offering enhanced tunability. Through in situ Raman spectroscopy and impedance spectroscopy, we directly observe the dynamic alterations within the active layers during switching processes. The reversible migration of ions diminishes the barrier within the polymer layer, leading to highly uniform resistive switching behavior. The C60 layer functions as a confined transport medium, mitigating critical current variability issues. Moreover, we introduce a shunt resistor approach, furnishing analog memristors with selectively adjustable uniformity, enhanced linearity, and expanded dynamic conductance range, providing a general solution adaptable to various memristive hardware architectures.

Enhancing phase and morphology control of vanadium oxide films for resistive memory applications: A water-assisted chemical approach

This study explores the influence of precursor solution composition and solvent selection on the synthesis of vanadium oxide (VO2) thin films tailored for resistive memory applications. The vanadium pentoxide and oxalic acid molar ratio and the dispersing medium (ethanol, water, and their mixture) were varied. Water content significantly influenced the VO2 phase, morphology, and film thickness. Ethanol yielded mixed vanadium oxide phases VO2 − Tetragonal, V2O5 − Orthorhombic, and Monoclinic) and a film with minor imperfections. Conversely, the active layer prepared using an aqueous medium showed a predominant VO2 − Monoclinic phase, albeit with a non-uniform film. An ethanol–water mixture produced the most uniform morphology and a mixture of vanadium oxide phases (VO2 − Tetragonal, V2O5- Orthorhombic). All devices displayed resistive switching behavior. VO2-containing devices exhibited a more pronounced transition from an ohmic conduction state to a space-charge-limited conduction mechanism. ON-state currents remained consistent, while OFF-state currents varied notably.

Ni3C nanosheets and PVA nanocomposite based memristor for low-cost and flexible non-volatile memory devices

Two-dimensional (2D) MXenes have gained extensive attention in the field of memristors due to their high ion mobility, chemical stability and tunable electrical and surface properties. Moreover, MXenes have tunable interlayer bonding which enables enhancement in memristor performance. In this work, we synthesize a novel nanocomposite of Ni3C nanosheets and polyvinyl alcohol (PVA) and fabricate a flexible memristor with Ag/Ni3C-PVA/ITO/PET configuration for non-volatile memory applications. Ni3C nanosheets were synthesized from Ni-MAX (Ni3AlC2) through a solvothermal etching and exfoliation process. The nanosheet like structure of Ni3C is confirmed through Scanning Electron Microscopy (SEM) and Transmission Electron microscopy (TEM). Characterization techniques like X-ray diffraction (XRD), Raman spectroscopy and Fourier Transform Infrared Spectroscopy (FTIR) reveal the crystalline phases, surface functional groups and chemical bonds present in Ni3C nanosheets and Ni3C-PVA nanocomposite. The memristor was fabricated through a facile low cost solution processed based fabrication technique. The Ag/Ni3C-PVA/ITO/PET memristor exhibits bipolar non-volatile switching characteristics. The device with optimised mass ratio of 4:3 (Ni3C: PVA) shows a decent off/on ratio of 2.09 × 102, long retention time of 104 s, and an endurance of 102 DC cycles. The SET voltage of the as-fabricated device is 2.8 V and the RESET voltage is −5.33 V. The flexible memristor exhibits outstanding mechanical robustness over 500 bending cycles. The high charge carrier mobility of Ni3C results in lower switching voltage and the dielectric property of PVA improves data retention and off/on ratio of the memristor. The resistive switching behaviour is explained through conductive metallic bridge mechanism. The conduction mechanism follows Ohmic conduction in ON state and trap controlled space charge limited current (TCSCLC) mechanism in OFF state. The results demonstrate that the nanocomposite with its superior resistive switching effects is suitable for cost-effective, high-performance, flexible non-volatile memory devices.

Understanding the Non-Volatile Resistive Switching Behavior of Lithium Titanium Oxide during Spinel to Rock Salt Conversion for Neuromorphic Computing

Lithium based synaptic device research has been a growing new field in the last few years for enabling robust neuromorphic hardware systems. It can realize parallel analogue computation which is beyond the conventional von Neumann computing architecture which is slow, energy inefficient and expensive to execute complex tasks. In this study, we showcase the remarkable potential of Lithium Titanium Oxide (Li4Ti5O12) spinel, both computationally through Density of States (DoS) analysis using Density Functional Theory (DFT), and experimentally via direct current (DC) polarization investigation of electrochemically lithiated Li4Ti5O12 thin film, examining diverse states of discharge (SoD) in both in-plane and out-of-plane configurations. The observed conductivity jump spans up to six orders of magnitude, transitioning from the Li4Ti5O12 spinel phase to the fully lithiated Li7Ti5O12 rock salt phase. Raman Spectroscopy validates the transformation from the Li4Ti5O12 spinel phase to the Li7Ti5O12 rock salt phase. Moreover, the onset of increase in conductivity during this transformation is corroborated by changes in the oxidation state of Titanium (Ti), as explained with the help of X-Ray Photoelectron Spectroscopy. To actualize these findings, we engineered a three-terminal artificial synaptic device integrating Lithium Phosphorous Oxynitride (LiPON) solid-state electrolyte as the lithium ion source and conductor, while employing Lithium Titanium Oxide (Li4Ti5O12) spinel as the channel material. In device testing, we maintained a source-drain voltage (VSD) of 0.5 V, while sweeping the gate voltage (VG) from -3 V to 3 V, resulting in switching spanning up to 4 orders of magnitude, consistently replicable across multiple cycles. Widening the gate voltage window from ±3 V to ±7V induced an increase in conductance. Furthermore, non-volatile testing affirmed the sustained retention of the conductance state across all tested gate voltage windows, showcasing the device's stability over time. These compelling results portray a promising trajectory for the development of a robust synaptic device architecture reliant on lithium-based all solid-state materials, catalyzing the evolution of high-precision analogue neuromorphic computing systems.

α-CsPbI3 Quantum Dots ReRAM with High Air Stability Working by Valance Change Filamentary Mechanism.

The current memory system is facing obstacles to improvement, and ReRAM is considered a powerful alternative. All-inorganic α-CsPbI3 perovskite-based ReRAM working by electrochemical mechanism is reported, but the electrochemically active electrode raised difficulty in long-term stable operation, and bulk α-CsPbI3 device can not show resistive switching behavior with an inert metal top electrode. Herein, by making the α-CsPbI3 into QDs and applying it to the device with inert Au as the top electrode, the devices working by valence change mechanism are successfully fabricated. The large surface-to-volume ratio made an abundant amount of iodine vacancies and facile migration of vacancies allowed the device to work by valence change mechanism. The devices show reliable electrical characteristics, 800 cycles endurance and retention for over 4 × 104 s, and air stability for 1 month. This work demonstrates that applying the QDs can improve the stability and enable a new type of working mechanism in ReRAM.

A Temperature Sensory Leaky Integrate-and-Fire Artificial Neuron Based on Chitosan/PNIPAM Bilayer Volatile Complementary Resistive Switching Memristor.

The presence of neurons is crucial in neuromorphic computing systems as they play a vital role in modulating the strength of synapses through the release of either excitatory or inhibitory stimuli. Hence, the development of sensory neurons plays a pivotal role in broadening the scope of brain-inspired neural computing. The present study introduces an artificial sensory neuron, which is constructed using a temperature-sensitive volatile complementary resistance switch memristor based on the functional layer of the chitosan/PNIPAM bilayer. The resistive switching behavior arises from the formation and ionization of oxygen vacancy filaments, whereby the threshold voltage and low resistive resistance of the device exhibit a temperature-dependent increase within the range of 290-410 K. A functional replication of a neuron with leaky integration and firing has been successfully developed, effectively simulating essential biological functions such as firing triggered by threshold, refractory period implementation, and modulation of spiking frequency. The artificial sensory neuron exhibits characteristics similar to those of leaky integrated firing neurons that receive temperature inputs. It has the potential to control the output frequency and amplitude under varying temperature conditions, making it suitable for temperature-sensing applications. This study presents a potential hardware implementation for developing efficient artificial intelligence systems that can support temperature detections.

Manganite memristive devices: recent progress and emerging opportunities

Manganite-based memristive devices have emerged as promising candidates for next-generation non-volatile memory and neuromorphic computing applications, owing to their unique resistive switching behavior and tunable electronic properties. This review explores recent innovations in manganite-based memristive devices, with a focus on materials engineering, device architectures, and fabrication techniques. We delve into the underlying mechanisms governing resistive switching in manganite thin films, elucidating the intricate interplay of oxygen vacancies, charge carriers, and structural modifications. This review underscores breakthroughs in harnessing manganite memristors for a range of applications, from high-density memory storage to neuromorphic computing platforms that mimic synaptic and neuronal functionalities. Additionally, we discuss the role of characterization techniques and the need for a unified benchmark for these devices. We provide insights into the challenges and opportunities associated with the co-integration of manganite-based memristive devices with more mature technologies, offering a roadmap for future research directions.