Resistive Switching Mechanism Research Articles

Transformation of MoSe2 to MoSe2-xOyvia controlled oxidation for high-performance resistive switching

The current study shows an improvised resistive switching in oxygenated MoSe2 (MoSe2-xOy) thin film. 2D nanosheets assembled nanoflower morphology of MoSe2 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 MoSe2 and MoOx in each samples was investigated with various spectroscopic techniques. The conversion to MoOx was maximum in 20 % O2 treated sample while other samples were converted partially. Au/MoSe2-xOy/Au structured devices were fabricated on SiO2/p-Si substrate and tested for resistive switching study. Among all four devices, 5 % O2 treated MoSe2-xOy 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 ION/IOFF 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 (MoSe2) and classic oxygen vacancy migrated switching of metal oxide (i.e. MoOx), were simultaneously important for achieving high performance memristive behavior in 5 % O2 treated MoSe2.

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.

HfO2-based resistive random access memory with an ultrahigh switching ratio

Resistive Random Access Memory (RRAM) is considered one of the most promising candidates for big data storage. By using atomic layer deposition and magnetron sputtering, HfO2 thin films were prepared on ITO first, which exhibited good resistive switching (RS) characteristics in the structure of Ag/HfO2/ITO. By analyzing the RS mechanism, it is found that both metal conductive filaments and oxygen vacancy conductive filaments coexisted and Sn ion in ITO can influence the retention of RRAM. Furthermore, a device in the structure of Ag/HfO2/Pt was proposed and prepared, which exhibited excellent RS characteristics, including an ultrahigh switching ratio averaging up to 108 and low operating voltage. It is concluded that the difference in the work function between the top and bottom electrodes contributes to improving the switching ratio, reducing the operating voltage. In addition, the Ag/HfO2/Pt device is similar to the Ag/HfO2-based threshold switching selector in the structure and in characteristics of high switching ratio, besides non-volatile memory. Hence, the device is functionally equivalent to the combination of an RRAM and a threshold switching selector. It is the potential way to replace the conventional 1S1R structure memory.

A Mechanism of Resistance Switching in CNT Based Memory Devices

Carbon nanotubes (CNTs) show promise for high energy efficiency electronic devices due to their high electrical conductivity. One possible application is in the fabrication of resistance-change computer memory, where the application of an external electrical bias can use a CNT layer as the switching element in a RAM cell. Memory cells of this type have been extensively demonstrated, where the electrical resistance of a switching layer of CNTs can be reversibly controlled by the application of external bias [1].To better understand these devices, we have developed a nanoscale model of their electrical switching. Towards this end, first-principles calculations of the electrical conductivity of CNT-CNT junctions were performed using the Density Functional Tight Binding (DFTB) in combination with the Non-Equilibrium Greens functions (NEGF) approach, enabling an improved understanding of the tunnelling of electrons across a range of CNT junctions [2]. These results demonstrate that the conductivity of CNT contacts depends on the overlap area between nanotubes and exponentially on the distances between the carbon atoms of the interacting CNTs. Secondly, we employed coarse-grained molecular dynamics [3,4] to produce nanoscale dense CNT film models like those used in the devices. We devise a set of metrics for characterising the structural properties of CNT films, and apply them to a set of model films designed to mimic those used in microelectronics devices. In order to understand how the geometrical properties of CNTs affect the film structure, we analyse films with different CNT chirality and length distributions. Unlike previous studies that focused on relatively low-density systems below ∼0.4 g/cm3, we also consider films with density of ∼0.6 g/cm3, as employed in experimentally fabricated CNT-based NRAM devices. By adding amorphous carbon to the film models, in varying amounts, we are then able to assess its effects. Finally, these two elements were combined to produce electrical simulations of the conductivity of the CNT films connected to TiN electrodes. These electrodes are shown to be partially oxidized during the device fabrication. The electrical conductivity in a device is characterized by formation of conduction paths formed by CNTs between the electrodes and connected via the CNT junctions. The conductivity is modulated by charging of CNTs and amorphous carbon present in the film.Using these simulations, we propose a resistance switching mechanism in TiN/CNT/TiN devices based on the physical movement of CNTs. During the initial operation of the device, oxygen is released from the oxidized bottom electrode and this readily reacts with individual CNTs to form charge trapping sites. Once these sites have become charged, they enable controllable movement of CNTs at the bottom electrode under the application of electric field. By reversibly connecting and disconnecting such CNTs from the bottom electrode, the electrical conductivity through the CNT film as a whole can be controlled.

Advances on MXene-Based Memristors for Neuromorphic Computing: A Review on Synthesis, Mechanisms, and Future Directions.

Neuromorphic computing seeks to replicate the capabilities of parallel processing, progressive learning, and inference while retaining low power consumption by drawing inspiration from the human brain. By further overcoming the constraints imposed by the traditional von Neumann architecture, this innovative approach has the potential to revolutionize modern computing systems. Memristors have emerged as a solution to implement neuromorphic computing in hardware, with research based on developing functional materials for resistive switching performance enhancement. Recently, two-dimensional MXenes, a family of transition metal carbides, nitrides, and carbonitrides, have begun to be integrated into these devices to achieve synaptic emulation. MXene-based memristors have already demonstrated diverse neuromorphic characteristics while enhancing the stability and reducing power consumption. The possibility of changing the physicochemical properties through modifications of the surface terminations, bandgap, interlayer spacing, and oxidation for each existing MXene makes them very promising. Here, recent advancements in MXene synthesis, device fabrication, and characterization of MXene-based neuromorphic artificial synapses are discussed. Then, we focus on understanding the resistive switching mechanisms and how they connect with theoretical and experimental data, along with the innovations made during the fabrication process. Additionally, we provide an in-depth review of the neuromorphic performance, making a connection with the resistive switching mechanism, along with a compendium of each relevant performance factor for nonvolatile and volatile applications. Finally, we state the remaining challenges in MXene-based devices for artificial synapses and the next steps that could be taken for future development.

Influence of stop and gate voltage on resistive switching of 1T1R HfO2-based memristors, a modeling and variability analysis

Memristive devices, particularly resistive random access memory (RRAM) cells based on hafnium oxide (HfO₂) dielectrics, exhibit promising characteristics for a wide range of applications. In spite of their potential, issues related to intrinsic variability and the need for precise simulation tools and modeling methods remain a medium-term hurdle. This study addresses these challenges by investigating the resistive switching (RS) behavior of different 1T1R HfO₂-based memristive devices under various experimental conditions. Through a comprehensive experimental analysis, we extract RS parameters using different numerical techniques to understand the cycle-to-cycle (C2C) and device-to-device (D2D) variability. Additionally, we employ advanced simulation methodologies, including circuit breaker-based 3D simulation, to shed light on our experimental findings and provide a theoretical framework to disentangle the switching phenomena. Our results offer valuable insights into the RS mechanisms and variability, contributing to the improvement of robust parameter extraction methods, which are essential for the industrial application of memristive devices.

Role of oxygen vacancy in controlling the resistive switching mechanism for the development of conducting filaments in response of homo and hetero electrodes: Using DFT approach

In the realm of progression of internet of things, artificial intelligence and cloud services, nonvolatile memory devices such as, resistive random access memory (RRAM) emulated the vision of building internet of everything. In this study, robustness of homo- (Ag–Ag, and Pt–Pt), and hetero- (Ag–Pt) top, and bottom electrodes material without and with incorporated oxygen vacancies (Vos) in Sr4Ti4O12 RS layer were investigated. Presence of conductivity in the absence of external electric field proves the presence of nonvolatile memory behavior. Observed RS behavior (in the range of a few Angstroms) may be used to resolve the scalability issue of the proposed RRAM device system. At the same time, oxygen vacancies (Vos) introduced additional functionalities like: additional reduction sites, and reduction of leakage current by quantizing the conduction within RS material. Diffusion barrier elucidated the diffusion mechanism of oxygen vacancies in the considered heterostructure to understand the energy state and the type of RS conduction mechanism. Potential energy line ups, formation energy and electronic properties identified the Vos as principal sites for reduction of Ag atoms by forming metal oxide (Ag-Vos) complex. It is predicted that ReSET, and hence high resistance state (HRS) is harder to achieve with homo-electrodes. The findings of this study provides the effective solution to scalability, stability, and low power consumption in the realm of Pt–Sr4Ti4O12–Ag (with 2Vos mediated in RS layer) based RRAM devices.

Exploring resistive switching properties and mechanisms in sol-gel derived Gd2Ti2O7 thin films for RRAM applications

This study focused on investigating the effects of film thicknesses and thermal treatments on the resistance-switching characteristics of Gd2Ti2O7-based RRAM devices for the first time. Gd2Ti2O7 thin films were successfully synthesized using a sol-gel deposition technique on ITO/glass substrates as the foundation for this research. The conduction mechanism of the filament was found to be primarily influenced by oxygen vacancies. The study found that annealing at 300 °C resulted in a slight increase in oxygen vacancies and switching cycles. However, annealing at 200 °C and 400 °C led to a significant decrease in oxygen vacancies, resulting in reduced switching cycles. To further enhance the device performance, a post-metal annealing process was applied at 300 °C to form an extra AlOx layer. This additional layer facilitated the coexistence of oxygen vacancies and aluminum ions, promoting the formation of conductive filaments and enhancing the resistive switching performance of the devices. As a result, the device subjected to 300 °C post-metal annealing demonstrated optimized resistive switching properties, including a maximum of 1248 switching cycles, a Ron/Roff ratio of 102, and VSet/VReset = −5.38 V/2.08 V. These findings highlight the promising potential of Gd2Ti2O7-based RRAM devices for practical applications in Resistive Random Access Memory (RRAM).

Optoelectronic Devices for In-Sensor Computing.

The demand for accurate perception of the physical world leads to a dramatic increase in sensory nodes. However, the transmission of massive and unstructured sensory data from sensors to computing units poses great challenges in terms of power-efficiency, transmission bandwidth, data storage, time latency, and security. To efficiently process massive sensory data, it is crucial to achieve data compression and structuring at the sensory terminals. In-sensor computing integrates perception, memory, and processing functions within sensors, enabling sensory terminals to perform data compression and data structuring. Here, vision sensors are adopted as an example and discuss the functions of electronic, optical, and optoelectronic hardware for visual processing. Particularly, hardware implementations of optoelectronic devices for in-sensor visual processing that can compress and structure multidimensional vision information are examined. The underlying resistive switching mechanisms of volatile/nonvolatile optoelectronic devices and their processing operations are explored. Finally, a perspective on the future development of optoelectronic devices for in-sensor computing is provided.

Resistive switching and synaptic characteristics of Hf-doped ZnO sandwiched between HfO2-based memristors for neuromorphic computing

With the rise of neuromorphic computing, memristors have attracted much attention as a device with potential synaptic properties. In this paper, we investigated the embedding of Hf-doped ZnO (Hf:ZnO) layers with different doping concentrations in HfO2-based memristors to design HfO2/(0 %-10 %)Hf:ZnO/HfO2 tri-layer structured memristors for resistive switching (RS) and synaptic characteristics. Utilizing first-principles calculations, we integrated assessments of both oxygen vacancy migration capability and material conductivity to evaluate the rationale behind our design. The experimental results show that the HfO2/(5 %)Hf:ZnO/HfO2 tri-layer structured memristor presents the best RS performance, with a storage window of 103. We analyze the impact of insertion layers with varying doping concentrations on the RS performance of the devices and elucidate the RS mechanism. In addition, we investigated the synaptic properties of HfO2/(5 %)Hf:ZnO/HfO2 tri-layer structured memristor, and effectively simulated synaptic plasticity akin to the synaptic behavior found in biological neurons. Finally, we also constructed a memristor-based Spiking Neural Network for recognizing the Mixed National Institute of Standards and Technology handwritten digit dataset, achieving a recognition accuracy of 82 %. This comprehensive study shows that the insertion of (5 %)Hf:ZnO into HfO2-based memristors holds significant promise for upcoming applications in the field of neuromorphic computing.

Metal-organic framework and MXene (ZIF-8:Ti3C2Tx) based organic and inorganic nanocomposite for bio-synaptic applications

Organic and inorganic hybrid materials have drawn more interest in the field of electronic devices. The metal-organic frameworks (MOFs) have emerged as one of the promising hybrid materials for electronic devices. However, their limited electrical conductivity hinders their electronic applications. To overcome these shortcomings, we synthesized MOF:MXene nanocomposite to enhance the stability and electrical conductivity of MOF. In particular, we synthesized and characterized zeolitic imidazolate framework-8 (ZIF-8):MXene (Ti3C2Tx) hybrid nanocomposite. From the application point of view, we demonstrated the analog memory effect and mimicked various synaptic learning functionalities using Ag/ZIF-8:Ti3C2Tx/FTO resistive switching (RS) device. The fabricated device exhibits a good analog-type bipolar RS effect. The device mimics various bio-synaptic properties such as potentiation, depression, excitatory-post synaptic current, and paired-pulse facilitation (PPF) index (%). The inherent non-ideal memristor property was dominated in the device, owing to the double-valued charge-flux relation. The conduction and possible RS mechanisms of the Ag/ZIF-8:Ti3C2Tx/FTO device were reported. These results suggested that the ZIF-8:Ti3C2Tx nanocomposite is a potential nanomaterial for brain-inspired computing applications.

Electrical switching properties of Ag2S/Cu3P under light and heat excitation

In this paper, we prepared and investigated the electrical switching behaviors of Cu3P/Ag2S heterojunction in the absence/presence of light/heat excitation. The structure exhibited bipolar memristor characteristics. The resistive switching mechanism is due to the formation of Ag conductive filaments and phase transition in Cu3P. We found that the resistance ratio (ROFF/RON) increased by a factor of 1.4/1.8 after light/heat excitation. The underlying mechanism was due to the photoelectric effect/Seebeck effect. Our results are helpful for the understanding of the resistive switching performance of Cu3P/Ag2S junctions, providing valuable insights into the factors influencing resistive switching performance and a clue for the enhancement of the memristor performance.

NbOx RRAM performance enhancement by surface modification with Au nanoparticles

Resistive random-access memory (RRAM) has been widely studied because of its high information storage density and easy integration, and it has potential to replace traditional memory storage means. However, it is prone to random formations and fracture of conductive filaments, which limits its commercial applications. In this study, magnetron sputtering was used to deposit NbOx films on different substrates modified with different concentrations of Au-nanoparticles (NPs). The as developed Pt-Aumin/NbOx/W tip device with the lowest concentration of Au-NPs modified bottom electrode exhibited the best performance; the Vset distribution of the device was more concentrated, Vreset decreased significantly, the distribution range was narrow, and the resistance distribution of high and low resistance states (HRS and LRS, respectively) was more stable. Modification of the bottom electrode with Au-NPs did not change the ohmic conduction behavior of NbOx RRAM in LRS; however, it changed the resistance switching mechanism from SCLC to P–F effect modified SCLC. The Au-NPs modified bottom electrode acted like a tip, enhancing the local electric field and promoting the formation of conductive filaments near the NPs. This work explains the internal mechanism for improving RRAM properties using a local electric field and provides theoretical guidance for enabling the rapid commercialization of RRAM.

Recent advancements in carbon-based materials for resistive switching applications

In the dynamic field of microelectronics, there is a notable trend towards leveraging carbon materials, favored for their ease of synthesis, biocompatibility, and abundance. This trend is particularly evident in the development of memristor devices, which benefit from the unique electronic properties of carbon, leading to enhanced device performance. The appeal of carbon materials lies in their ability to offer distinctive resistive switching (RS) mechanisms, sparking significant interest among researchers. This article aims to provide an insightful overview of the advancements in carbon-based memristive devices, focusing on the resistive switching mechanisms enabled by carbon materials. It delves into the various classes of carbon-based memristor devices, ranging from zero-dimensional (0D) to three-dimensional (3D) structures, each with its unique advantages and applications. Additionally, the discussion extends to innovative next-generation memristive devices, including those designed for health monitoring and skin-adhesive, self-powered applications. Moreover, the article touches upon the synthesis techniques and functionalization strategies that are crucial for optimizing the performance of carbon-based memristors. It also outlines the future opportunities in this rapidly advancing field, highlighting the potential for further research and development towards energy-efficient, compact, and bio-integrated memristive systems.

Modeling and simulation of electrochemical and surface diffusion effects in filamentary cation-based resistive memory devices

Cation-based (or electrochemical) resistive memory devices are gaining increasing interest in neuromorphic applications due to their capability to emulate the dynamic behavior of biological neurons and synapses. The utilization of such devices in neuromorphic systems necessitates a reliable physical model for the resistance switching mechanism, which is based on the formation and dissolution of a conductive filament in a thin dielectric layer, sandwiched between two metal electrodes. We propose a comprehensive model to simulate the evolution of the filament geometry under the effect of both surface diffusion caused by curvature gradient and electromechanical stress, and mass injection due to electrodeposition of cations. The model has been implemented in a C++ platform using a level-set approach based on a mixed finite element formulation, enriched by a mesh adaptation strategy to accurately and efficiently track the evolution of the filament shape. The numerical scheme is initially validated on various benchmark case studies. We then simulate the growth and self-dissolution of the filamentary geometry, incorporating an electrical model allowing a comparison with conventional cation-based memories. The simulations showcase filament formation under varying applied voltages and filament dissolution under different initial resistances.

Effect of Gamma Irradiation on the Structure, Morphology, and Memristive Properties of CVD Grown ReS2 Thin Film

AbstractIn this work, effect of gamma irradiation on chemical vapor deposition grown ReS2 thin films vis‐a‐vis change in its structure, morphology, chemical composition, and memristive behaviour is reported to assess its radiation hardness for space applications. High‐resolution transmission electron micrographs and selected area electron diffraction pattern infer polycrystalline to amorphous phase transition and increase in the number of grain boundaries (GBs) after exposure to 25 kGy of gamma radiation. X‐ray photoelectron spectroscopy and low‐temperature photoluminescence measurements reveal the formation of sulfur vacancies (SV) accompanied with partial oxidation of film. Memristors are then fabricated on the as‐grown film using different metal electrodes, which are Ag, Pt, and Ti in lateral geometry, and their resistive switching (RS) mechanism is studied along with the impact of gamma irradiation. RS is attributed to the formation of conducting filaments due to GB‐mediated migration of metal ions, SV, and oxygen ions from the partially oxidized film. Furthermore, irradiation is found to increase current in the high resistance state of the device, which subsequently reduces the memory window. This impact is observed to be consistent across all the devices which validates the effect of irradiation irrespective of the nature of the metal electrode used.

Performance improvement of bilayer memristor based on hafnium oxide by Ti/W synergy and its synaptic behavior

Bilayer and multi-layer structures can effectively improve the performance of memristors, but the oxide/metal interface during the resistance switching process affects its reliability and stability. In this work, the Pt/HfO2/HfOx/W and Pt/HfO2/HfOx/Ti/W memristors with a homogeneous bilayer structure are compared to systematically investigate the effect of interface engineering on bilayer hafnium oxide devices by inserting Ti buffer layer to construct Ti/W composite electrode. Compared with the stimulated oxidation of the W electrode, the device under the synergy of Ti/W composite electrode showed better switching uniformity (The resistance of the high-resistance state and reset voltage variation coefficient decreased from 83.1 % to 31.9 % and from 9.5 % to 5.6 %, respectively.) and robust endurance (>104 cycles). Meanwhile, some essential synaptic behaviors such as nonlinear transmission characteristics, paired-pulse facilitation, and spike-timing-dependent plasticity were mimicked by using different pulse stimuli. Subsequently, the resistance switching mechanism of the device under the Ti/W synergy was explored by combining the results of I–V curve fitting and material analysis. These results provided important experimental guidance and a theoretical basis for further optimization of electrode interfacial effect in the future.

Modified nonlinear ion drift model for TiO2 memristor: a temperature dependent study

The creation and optimisation of memristor models with different topologies and physical mechanisms have received increasing attention in recent years. Memristors, known for their unique resistive switching mechanism, have garnered significant interest as promising components for next-generation computing. However, to effectively design and test memristor-based circuits, it is crucial to have a mathematical representation of the experimentally determined current-voltage characteristics of memristors. This paper proposes a model and conducts an analysis that offers insights into memristor technology, beginning with its characteristics and extending to simulations involving various parameters. The proposed model and its dependency on temperature are implemented using MATLAB. The model captures changes in current characteristics concerning the fundamental voltage without using any window functions. Thus, it accurately represents the variation in memristance with temperature, contributing to a more precise and observed modelling approach.

Metal Penetration and Grain Boundary in MoS2 Memristors

Abstract2D semiconductors have demonstrated outstanding switching performance in resistive random‐access memory (RRAM). Despite the proposed resistive switching (RS) mechanism involving the penetration of electrode metal atoms, direct observation of metal penetration in these van‐der‐Waals stacked 2D semiconductors remains absent. This study utilizes 2D molybdenum disulfide (MoS2) as the switching material, employing gold and multilayer graphene as electrodes. Through analysis of the switching characteristics of these RRAM devices, the pivotal role of grain boundaries and metal atoms is identify in achieving RS. High‐resolution transmission electron microscopy and energy‐dispersive X‐ray spectroscopy provide direct evidence of metal penetration into multilayer MoS2. This study offers valuable insights into the RS mechanism in memristors based on multilayer MoS2, providing guidance for designing and optimizing 2D material memristive devices.

Resistance Switching and Carrier Transport Mechanisms of HfO2-Based Ferroelectric Diode

Resistance Switching and Carrier Transport Mechanisms of HfO₂-Based Ferroelectric Diode