Switching Mechanism Research Articles

Enhanced resistive switching behaviors of organic resistive random access memory devices by adding polyethyleneimine interlayer

Organic nonvolatile memory devices have garnered significant attention as next-generation electrical memory units owing to their potential for low-cost and straightforward fabrication through a solution process. In this study, we successfully fabricated fully solution-processed organic resistive random access memory (RRAM) devices using poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) as the resistive switching (RS) layer, with poly(3,4-ethylene-dioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) employed as the top electrode. Additionally, to enhance performance further, a polyethyleneimine (PEIE) interlayer was introduced between the bottom electrode and the P3HT:PCBM RS layer. The resulting organic RRAM devices with the PEIE interlayer exhibited bipolar resistive switching, with improved endurance increasing from 50 to 100 cycles, a retention time of 103 s, and a low SET voltage of 0.7 V. The organic RRAM devices featuring the PEIE interlayer demonstrated superior RS performance attributed to the higher Schottky barrier at the interface between the bottom electrode and the active switching layer, creating an asymmetric structure. I–V curve fitting confirmed that the potential switching mechanism involved Schottky emission in the high-resistance state and Ohmic conduction in the low-resistance state. Our findings suggest that organic RRAM devices with a PEIE interlayer hold promise for stable nonvolatile memory applications.

Development and optimization of large-scale integration of 2D material in memristors

Two-dimensional (2D) materials like transition metal dichalcogenides (TMD) have proved to be serious candidates to replace silicon in several technologies with enhanced performances. In this respect, the two remaining challenges are the wafer scale growth of TMDs and their integration into operational devices using clean room compatible processes. In this work, two different CMOS-compatible protocols are developed for the fabrication of MoS2-based memristors, and the resulting performances are compared. The quality of MoS2 at each stage of the process is characterized by Raman spectroscopy and x-ray photoemission spectroscopy. In the first protocol, the structure of MoS2 is preserved during transfer and patterning processes. However, a polymer layer with a minimum thickness of 3 nm remains at the surface of MoS2 limiting the electrical switching performances. In the second protocol, the contamination layer is completely removed resulting in improved electrical switching performances and reproducibility. Based on physico-chemical and electrical results, the switching mechanism is discussed in terms of conduction through grain boundaries.

Regional challenges concerning derivation of suspended particulate matter concentration and water turbidity from water reflectance. A case study in the western Black Sea

Assessment of water quality indicators, such as Suspended Particulate Matter (SPM) concentration and water turbidity (TUR) is essential for marine ecosystems health evaluations. This work focuses on the estimation of these two variables from water-leaving reflectance measurements, either derived from in-situ observations or satellite data, for the western Black Sea basin. The regional characteristics of the water optically active constituents can have important impact on the quality of such estimations if not properly accounted for. We test several existing inversion algorithms and quantify their accuracy. New, regionally adapted methods are then proposed, together with a new formulation for a multi-conditional switching mechanism. Calibration of these models is performed based on SPM and TUR in-situ measurements. It is shown that the improvements achieved through regional adaptation can be significant. Application of these algorithms to Sentinel-3 OLCI satellite data reveals the consistency of the proposed methodology. Also, it shows the degree of uncertainty if improper formulations are used, with major impact on the absolute values of retrieved SPM or TUR.

Using Coordination Chemistry to Control "Click" Reactions: The Selective Formation of Asymmetrically Ligated Polyoxometalates.

The Cu(I)-catalyzed azide-alkyne cycloaddition reaction between (NBu4)2[V6O13((OCH2)3CCH2N3)2] and 3-ethynylpyridine led to the formation of products capable of forming poorly soluble coordination compounds with transition metal ions such as Cu(I) and Zn(II). The formation of these poorly soluble phases is an important feature that was used to determine the course of reactions, allowing the selective preparation of symmetric bis-pyridyltriazolyl and asymmetric monopyridyltriazolyl derivatives with relatively high yields and high substrate conversions. The asymmetric compound (NBu4)2[V6O13((OCH2)3CCH2-N3C2H-C5H4N)((OCH2)3CCH2N3)] (V6asym) was utilized in the subsequent "click" postfunctionalization reaction with 1,4-diethynylbenzene, resulting in a covalently bound V6asym-V6asym dimer. This dimeric compound was subjected to scanning probe microscopy studies on gold surfaces, which revealed no electronic coupling between the hexavanadate cores within the dimer upon potential-induced switching. This observation indicates that such dimers and higher-order oligomers composed of polyoxometalate-ligand-polyoxometalate bridges can be exploited as active capacitor/memristor units, relevant to increase the data storage capacity of standard memory devices with innovative molecular switching mechanisms.

Recent Trends in Application of Memristor in Neuromorphic Computing: A Review

Abstract: Recently memristors have emerged as a form of nonvolatile memory that is based on the principle of ion transport in solid electrolytes under the impact of an external electric field. It is perceived as one of the key elements to building next-generation computing systems owing to its peculiar resistive switching characteristics. The switching mechanism in a memristor is mainly governed by filamentary conduction. Further, it can be employed as a memory as well as a logic element, which makes it an ideal candidate for building innovative computer architecture. Moreover, it is capable of mimicking the characteristics of biological synapses, which makes it an ideal candidate for developing a Neuromorphic system. In this review to begin with the switching mechanism of the memristor, primarily focusing on filamentary conduction, is discussed. Few SPICE models of memristor are reviewed, and their critical comparison is performed, which are widely used to build computing systems. An in-depth study on the various crossbar memory architecture augmented with memristors is reviewed. Finally, the application of memristors in neuromorphic computing and hardware implementation of Artificial Neural Networks (ANN) employing memristors is discussed.

Research on 5G Heterogeneous Network Switching Mechanism and Self-optimizing Network Switching Algorithm

Research on 5G Heterogeneous Network Switching Mechanism and Self-optimizing Network Switching Algorithm

Phase jumps in Josephson junctions with time-dependent spin–orbit coupling

Planar Josephson junctions (JJs), based on common superconductors and III–V semiconductors, are sought for Majorana states and fault-tolerant quantum computing. However, with gate-tunable spin–orbit coupling (SOC), we show that the range of potential applications of such JJs becomes much broader. The time-dependent SOC offers unexplored mechanisms for switching JJs, accompanied by the 2π-phase jumps and the voltage pulses corresponding to the single-flux-quantum transitions, key to high-speed and low-power superconducting electronics. In a constant applied magnetic field, with Rashba and Dresselhaus SOC, anharmonic current-phase relations, calculated microscopically in these JJs, yield a nonreciprocal transport and superconducting diode effect. Together with the time-dependent SOC, this allows us to identify a switching mechanism at no applied current bias, which supports fractional-flux-quantum superconducting circuits and neuromorphic computing.

Flexible IGZO TFT Technology for Shift Register Drivers

AbstractActive sensing matrices play a pivotal role in various electronic devices, including optical and X‐ray imaging arrays, electronic skins, and artificial tactile arrays, among others. These matrices function through a thin‐film active switching mechanism, allowing for the scanning of rows and columns by external circuitry to read the sensory signals of individual pixels. Recently, indium–gallium‐zinc oxide thin‐film transistors (IGZO TFTs) have emerged as highly promising technology in the realm of flexible electronics. They enable the large‐scale integration of functional circuits on flexible substrates. Shift registers are commonly employed as peripheral scanning circuits to sequentially address active‐matrix arrays. To enhance system compactness and minimize external electrical connections, it is imperative to seamlessly integrate shift registers within the active matrices. However, contemporary flexible IGZO‐based shift registers suffer from high operating voltages and low frequencies, which constrain their applicability in high‐performance flexible sensors and displays. In response to this challenge, a breakthrough is presented in the form of low‐voltage, high‐frequency bootstrap shift registers implemented with flexible IGZO technology. The approach involves utilizing SU‐8 buffered polyimide (PI) polymer foils as substrates. These foils boast an exceptional level of surface smoothness, significantly increasing the yield and performance of electronic components, including vias, IGZO TFTs, and capacitors used in the shift register circuitry. Additionally, HfO2/Al2O3/HfO2 sandwich structures are employed as high‐k dielectric layers to reduce the operational voltage. Thanks to the innovative circuit design and optimized fabrication methods, the 16‐stage shift register can operate at just 1.8 V with a frequency of 15 kHz. This breakthrough promises to have a profound impact on a wide range of applications for driving flexible active‐matrix electronic systems.

A versatile compact model of resistive random-access memory (RRAM)

We present a versatile compact model for resistive random-access memory (RRAM) that can model different types of RRAM devices such as oxide-RRAM (OxRAM) and conducting-bridge-RRAM (CBRAM). The model unifies the switching mechanisms of these RRAMs into a single framework. We showcase the model’s accuracy in reproducing published experimental device DC and transient characteristics of various RRAM structures. We also demonstrate the model’s efficacy in capturing RRAM variability and conducting 1T1R circuit simulations.

Implementation of photonic crystal based optical full adder using ring resonators

In this paper, the implementation of an all-optical full adder based on a two-dimensional photonic crystal is proposed. The proposed structure consists of hexagonal lattice of silicon rods embedded in air substrate. To design the proposed optical full adder, three nonlinear ring resonators, some linear waveguides, and some point defects are used. The switching mechanism of the ring resonators is based on nonlinear Kerr effect. The performance of the proposed structure has been analyzed and investigated by using plane wave expansion (PWE) and finite difference time domain (FDTD) methods. The minimum contrast ratio of the structure is 17.02 dB. The response time of the structure is 0.724 ps and can operate at a bit rate of 1.381 Tb/s. The proposed structure is simple, compact, and offers high contrast ratio, fast response time along with high bit rate and therefore can be a promising candidate for high speed data processing, computing, networking, and optical integrated circuits.

Propagating cortical waves coordinate sensory encoding and memory retrieval in the human brain.

Complex behavior entails a balance between taking in sensory information from the environment and utilizing previously learned internal information. Experiments in behaving mice have demonstrated that the brain continually alternates between outward and inward modes of cognition, switching its mode of operation every few seconds. Further, each state transition is marked by a stereotyped cascade of neuronal spiking that pervades most forebrain structures. Here we analyzed large fMRI datasets to demonstrate that a similar switching mechanism governs the operation of the human brain. We found that human brain activity was punctuated every several seconds by coherent, propagating waves emerging in the exteroceptive sensorimotor regions and terminating in the interoceptive default mode network. As in the mouse, the issuance of such events coincided with fluctuations in pupil size, indicating a tight relationship with arousal fluctuations, and this phenomenon occurred across behavioral states. Strikingly, concurrent measurement of human performance in a visual memory task indicated that each cycle of propagating fMRI waves sequentially promoted the encoding of semantic information and self-directed retrieval of memories. Together, these findings indicate that human cognitive performance is governed by autonomous switching between exteroceptive and interoceptive states. This apparently conserved feature of mammalian brain physiology bears directly on the integration of sensory and mnemonic information during everyday behavior.

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.

Magnetization reversal process in flat and patterned exchange-biased CoO/[Co/Pd] thin films

Nanostructured magnetic materials have gained great interest due to their possible technological applications in electronic and spintronic devices or in medicine as drug carriers. The key issue which decides on their potential industrial utilization is an exhibited type of a magnetization reversal process. Two main approaches used to describe the switching mechanism are the domain wall motion and coherent magnetization rotation, known as the Kondorsky and Stoner–Wohlfarth models, respectively. The reversal modes can be distinguished by angular measurements of hysteresis loops; however, in many experimental reports the dependencies do not precisely follow either of the models. This makes the question of how the magnetization reversal takes place and how to control or modify it one of the unclear and worth investigation issues in the research on magnetic materials. In this paper, we present our studies on the magnetization reversal in the exchange-biased CoO/[Co/Pd] thin films deposited on a flat substrate and on an array of anodized titanium oxide nanostructures. We studied the reversal mechanism using hysteresis loops and First-Order Reversal Curves. Interestingly, instead of the typical for the flat Co/Pd multilayers Kondorsky process, the system shows a crossover between the domain wall motion and the coherent rotation. A similar situation takes place for the pattern sample. Here, we connect this unusual behavior with the interface exchange interaction responsible for the exchange bias effect.

Partial melting nature of phase-change memory Ge-Sb-Te superlattice uncovered by large-scale machine learning interatomic potential molecular dynamics

[GeTe]m-[Sb2Te3]n superlattice (GST-SL) is a promising material candidate to solve the critical problem of high-power consumption for phase-change memory technology. However, the switching mechanism is still under strong debate during the last decade. A key controversial question is that whether melting in GST-SL is possible. In this work, a large-scale machine learning interatomic potential (MLIP) molecular dynamics (MD) simulation with a one-order-of-magnitude larger atom number than that of conventional density functional theory (DFT) MD captures a unique partial melting behavior in GST-SL, where a sparse-nucleation-and-growth governed melting behavior is triggered by the flipping of atoms into van der Waals (vdW) gaps and forming cation-in-vdW-gap (CiV) defect as starting point, and then is slowly developed via propagating liquid-crystalline interfaces. In great contrast, the traditional melting of rock salt (RS)-GST occurs very fast due to instant homogeneous nucleation from high-density intrinsic vacancies distributed randomly in its cubic lattice. Therefore, the melting regions in GST-SL can be spatially localized in form of partial melting and are readily controlled. Moreover, the atomic distribution after melting in GST-SL is more chemical ordering than that in RS-GST. By the large-scale MLIP-MD, the present study provides a critical atomic insight into GST-SL phase-change behaviors that conventional DFT-MDs hardly achieve. This partial-melting nature in GST-SL helps explain the long-term-confused working principle of GST-SL-based phase-change memory, which will accelerate its application in the big-data era.

Mechanism for Local-Atomic Structure Changes in Chalcogenide-based Threshold-Switching Devices.

Threshold-switching devices based on amorphous chalcogenides are considered for use as selector devices in 3D crossbar memories. However, the fundamental understanding of amorphous chalcogenide is hindered owing to the complexity of the local structures and difficulties in the trap analysis of multinary compounds. Furthermore, after threshold switching, the local structures gradually evolve to more stable energy states owing to the unstable homopolar bonds. Herein, based on trap analysis, DFT simulations, and operando XPS analysis, it is determined that the threshold switching mechanism is deeply related to the charged state of Se-Se homopolar defects. A threshold switching device is demonstrated with an excellent performance through the modification of the local structure via the addition of alloying elements and investigating the time-dependent trap evolution. The results concerning the trap dynamics of local atomic structures in threshold switching phenomena may be used to improve the design of amorphous chalcogenides.

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.

Compliance-free, analog RRAM devices based on SnOx

Brain-inspired resistive random-access memory (RRAM) technology is anticipated to outperform conventional flash memory technology due to its performance, high aerial density, low power consumption, and cost. For RRAM devices, metal oxides are exceedingly investigated as resistive switching (RS) materials. Among different oxides, tin oxide (SnOx) received minimal attention, although it possesses excellent electronic properties. Herein, we demonstrate compliance-free, analog resistive switching behavior with several stable states in Ti/Pt/SnOx/Pt RRAM devices. The compliance-free nature might be due to the high internal resistance of SnOx films. The resistance of the films was modulated by varying Ar/O2 ratio during the sputtering process. The I–V characteristics revealed a well-expressed high resistance state (HRS) and low resistance states (LRS) with bipolar memristive switching mechanism. By varying the pulse amplitude and width, different resistance states have been achieved, indicating the analog switching characteristics of the device. Furthermore, the devices show excellent retention for eleven states over 1000 s with an endurance of > 100 cycles.

Phenotypic switching mechanisms determine the structure of cell migration into extracellular matrix under the ‘go-or-grow’ hypothesis

A fundamental feature of collective cell migration is phenotypic heterogeneity which, for example, influences tumour progression and relapse. While current mathematical models often consider discrete phenotypic structuring of the cell population, in-line with the ‘go-or-grow’ hypothesis (Hatzikirou et al., 2012; Stepien et al., 2018), they regularly overlook the role that the environment may play in determining the cells’ phenotype during migration. Comparing a previously studied volume-filling model for a homogeneous population of generalist cells that can proliferate, move and degrade extracellular matrix (ECM) (Crossley et al., 2023) to a novel model for a heterogeneous population comprising two distinct sub-populations of specialist cells that can either move and degrade ECM or proliferate, this study explores how different hypothetical phenotypic switching mechanisms affect the speed and structure of the invading cell populations. Through a continuum model derived from its individual-based counterpart, insights into the influence of the ECM and the impact of phenotypic switching on migrating cell populations emerge. Notably, specialist cell populations that cannot switch phenotype show reduced invasiveness compared to generalist cell populations, while implementing different forms of switching significantly alters the structure of migrating cell fronts. This key result suggests that the structure of an invading cell population could be used to infer the underlying mechanisms governing phenotypic switching.

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.