Threshold Switching Research Articles

Media impact research: a discrete SIR epidemic model with threshold switching and nonlinear infection forces.

The media's coverage has the potential to impact human behavior and aid in the control of emergent infectious diseases. We aim to quantify and evaluate the extent to which media coverage can influence infectious disease control through a mathematical model, thus proposing a switching epidemic model that considers the effect of media coverage. The threshold strategy incorporates media influence only when the number of infected cases surpasses a specific threshold; otherwise, it is disregarded. When conducting qualitative analysis of two subsystems, focusing on the existence and stability of equilibria. Using numerical methods, the codimension-2 bifurcation analysis is adopted here to investigate the various types of equilibria within the switching system that play a vital role in pest control. On the other hand, codimension-1 bifurcation analysis reveals the existence of periodic, chaotic solutions, period-doubling bifurcations, multiple attractors and other complexities within the proposed model, which could pose challenges in disease control. Additionally, the impact of key parameters on epidemic outbreaks is analyzed, such as the initial values of susceptible and infective individuals, and discuss the potential benefits of mass media coverage in preventing emerging infectious diseases. The modeling and analytical techniques developed for threshold control strategies can be applied to other disease control efforts.

Threshold switching in nickel-doped zinc oxide based memristor for artificial sensory applications.

Electronic devices featuring biomimetic behaviour as electronic synapses and neurons have motivated the emergence of a new era in information and humanoid robotics technologies. In the human body, a nociceptor is a unique sensory neuron receptor that is capable of detecting harmful signals, leading to the central nervous system initiating a motor response. Herein, a nickel-doped zinc oxide (NZO)/Au based memristor is fabricated for the first time and characterized for artificial nociceptor application. For this, the introduction of a nickel-doped zinc oxide (NZO) layer between P++-Si and Au electrodes is used to eliminate the surface effects of the NZO layer, resulting in improved volatile threshold switching performance. Depending on the intensity, duration, and repetition rate of the external stimuli, this newly created memristor exhibits various critical nociceptive functions, including threshold, relaxation, allodynia, and hyperalgesia. The electron trapping/detrapping to/from the traps in the NZO layer is responsible for these nociceptive properties. This kind of NZO-based device produces a multifunctional nociceptor performance that is essential for applications in artificial intelligence systems, such as neural integrated devices with nanometer-sized features.

Controllable On-Resistance and its Thermal-Induced Channel Expansive Model in Ovonic Threshold Switch Selector

Ovonic threshold switch (OTS) selector is a key enabler for developing high-density nonvolatile memory with crossbar arrays. In this work, we investigated the resistance characteristics of the OTS device at the ON state, which is pivotal in the integration of the OTS and the memory element. The results indicate that the ON-resistance is not a constant value in the OTS device and is uncorrelated with the device areas but dependent on the real-time power applied on the device that is at ON state. Then, we proposed a thermal-induced compact model to describe the ON-resistance in the OTS device, referring to the simulation of the expansive conductive channel in OTS. The proposed model matches well with the measured ON-resistances with different conditions in the study. Our results contribute to further understanding of the threshold switching mechanism and selecting appropriate operation conditions for the OTS selector integrated in the high-density memory array.

Elemental Redistribution During the Crystallization of Ge–Cu–Te Thin Films for Phase-Change Memory

Herein, a GeCu2Te2 alloy is proposed as a phase-change material for application in nonvolatile phase-change random access memory (PRAM). The crystallization kinetics and microchemical changes during phase transformation are investigated, and their correlation with the electrical behaviors of the GeCu2Te2 thin films are examined. The key findings are as follows: (ⅰ) the GeCu2Te2 alloy shows a higher crystallization temperature (∼185 °C) than the classic Ge2Sb2Te5 (GST) thin films, thus demonstrating superior thermal stability; (ⅱ) the crystallization kinetics demonstrate a decreasing in the Avrami exponent n from 4, which is related to the growth-dominated crystallization process evidenced by the micromorphology; (ⅲ) a massive redistribution of the chemical elements along the depth of the thin films during crystallization is considered to be driven by selective surface oxidation at amorphous state, and stress buildup during crystallization. In addition, the crystallization-induced stress is determined as ∼168 MPa by utilizing the wafer curvature and X-ray diffraction methods for the GeCu2Te2 thin films. Finally, the lower threshold switching voltage ∼1.72 V for amorphous GeCu2Te2 thin films is beneficial for reducing the SET operating power consumption. The authors believe that these results are valuable for the optimal phase change material design.

Resistive Switching Characteristics of HfO x -Based Memristor by Inserting GeTe Layer

In this study, by inserting a GeTe layer as the current suppression layer and the heating layer, we improved the forming yield (~91%), memory window (> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10^{{3}}$ </tex-math></inline-formula> ), and resistive switching uniformity of HfOx-based memristor. Two forming polarities including positive forming (PF) bias and negative forming (NF) bias were applied to study resistive switching characteristics. After the PF process, the device shows unstable and volatile behavior that is related to ovonic threshold switching (OTS) characteristic. Negative differential resistance (NDR) phenomenon was observed during the NF process. In addition, the device exhibits nonvolatile characteristic, multilevel resistive switching, and good endurance (> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10^{{5}}$ </tex-math></inline-formula> ) after the NF process. We also proposed a corresponding physical model to explain two resistive switching characteristics of the NF and PF processes.

Memristors based on NdNiO3 nanocrystals film as sensory neurons for neuromorphic computing.

By mimicking the behavior of the human brain, artificial neural systems offer the possibility to further improve computing efficiency and solve the von Neumann bottleneck. In particular, neural systems with perceptual capability expand the application field and lay a good foundation for the construction of perceptual storage and computational systems. However, research on neurons with perceptual functions is still relatively scarce, with most works focusing on optoelectronic synapses. The neuron is important for neuromorphic computing systems because neurons output excitatory or inhibitory stimuli to regulate the weight of synapses. Therefore, the construction of sensory neurons is crucial to expand the application range of brain-like neural computing. Here, an artificial sensory neuron is proposed, which is constructed using a photosensitive bipolar threshold switching memristor based on NdNiO3 (NNO) nanocrystals. These metallic phase nanocrystals can not only enhance the local electric field, but also act as a reservoir for defects (VoS) to guide the growth of conductive filaments and stabilize the performance of the device. They present stable bipolar threshold switching behavior with a low 120 nW set power, and the operating voltages decreased in light due to photocarrier action. A leaky integrate firing (LIF) neuron has been realized, which achieved key biological neuron functions, such as all-or-nothing spiking, threshold-driven firing, refractory period, and spiking frequency modulation. The LIF neurons receiving optical inputs have the properties of an artificial sensory neuron. It could regulate the spiking output frequency at different light densities, which could be used for a ship approaching a port. This work provides a promising hardware implementation towards constructing high-performance artificial intelligence to assist ships at night in a sensory system.

Chemical-vapor-deposited 2D VSe2 nanosheet with threshold switching behaviors for Boolean logic calculations and leaky integrate-and-fire functions

Reliable threshold switching behaviors can be observed in VSe2 nanosheets after an annealing method owing to the phase transition from the 1T to 2H. The VSe2 memristor can be employed to perform Boolean logic calculations and simulate LIF functions.

Effect of long chain fatty acids on the memory switching behavior of tetraindolyl derivatives.

Non-volatile memory devices using organic materials have attracted much attention due to their excellent scalability, fast switching speed, low power consumption, low cost etc. Here, we report both volatile as well as non-volatile resistive switching behavior of p-di[3,3'-bis(2-methylindolyl)methane]benzene (Indole2) and its mixture with stearic acid (SA). Previously, we have reported the bipolar resistive switching (BRS) behavior using 1,4-bis(di(1H-indol-3-yl)methyl)benzene (Indole1) molecules under ambient conditions [Langmuir 37 (2021) 4449-4459] and complementary resistive switching (CRS) behavior when the device was exposed to 353 K or higher temperature [Langmuir 38 (2022) 9229-9238]. However, the present study revealed that when the H of -NH group of Indole1 is replaced by -CH3, the resultant Indole2 molecule-based device showed volatile threshold switching behaviour. On the other hand, when Indole2 is mixed with SA at a particular mole fraction, dynamic evolution of an Au/Indole2-SA/ITO device from volatile to non-volatile switching occurred with very good device stability (>285 days), memory window (6.69 × 102), endurance (210 times), data retention (6.8 × 104 s) and device yield of the order of 78.5%. Trap controlled SCLC as well as electric field driven conduction was the key behind the observed switching behaviour of the devices. In the active layer, trap centers due to the SA network may be responsible for non-volatile characteristics of the device. Observed non-volatile switching may be a potential candidate for write once read many (WORM) memory applications in future.

A refresh operation method for solving thermal stability issues and improving endurance of ovonic threshold switching selectors

A refresh operation method for an OTS selector to ensure a long memory chip life.

A steep-switching impact ionization-based threshold switching field-effect transistor.

A steep switching device with a low subthreshold swing (SS) that overcomes the fundamental Boltzmann limit (kT/q) is required to efficiently process a continuously increasing amount of data. Recently, two-dimensional material-based impact ionization transistors with various structures have been reported with the advantages of a low critical electric field and a unique quantum confinement effect. However, most of them cannot retain steep switching at room temperature, and device performance degradation issues caused by impact ionization-induced hot carriers have not been structurally addressed. In this study, we presented an impact-ionization-based threshold switching field-effect transistor (I2S-FET) fabricated with a serial connection of a MoS2 FET and WSe2 impact ionization-based threshold switch (I2S). We obtained repetitive operation with low SS (32.8 mV dec-1) at room temperature, along with low dielectric injection efficiency (10-6), through a structural design with separation of the conducting region, which determines on-state carrier transport, and the steep-switching region where the transition from off- to on-state occurs via impact ionization. Furthermore, compared to previously reported threshold-switching devices, our device demonstrated hysteresis-free switching characteristics. This study provides a promising approach for developing next-generation energy-efficient electronic devices and ultralow-power applications.

Insight into the Charging and Relaxation Dynamics of Diffusive Memristors in Integration-and-fire Neuron Applications

Artificial neural networks (ANNs) have been studied to mimic biological neurons because of the limitations of conventional computing. Among various ANNs, the spike neural network (SNN) is advantageous owing to its energy efficiency. To demonstrate the effectiveness of the SNN, circuits of integrate-and-fire (IF), leaky IF (LIF), and Hodgkin-Huxley model have been studied using various methods. These circuits contain an external capacitor to mimic membrane behavior. In this study, it is expected that the LIF circuits can be simplified by adopting a diffusive memristor made of Pt/Ag-doped HfOSUBx/SUB/Pt. Volatile threshold switching was observed and modeled by performing electrical measurements. Their capacitive properties and relaxation behavior were interpreted by the internal capacitor and dissolution of the conducting filament. Pulse trains were adjusted to confirm the possibility of implementing an LIF neuron without an external capacitor.

Physical Origin of Negative Differential Resistance in V3 O5 and Its Application as a Solid-State Oscillator.

Oxides that exhibit an insulator-metal transition can be used to fabricate energy-efficient relaxation oscillators for use in hardware-based neural networks but there are very few oxides with transition temperatures above room temperature. Here the structural, electrical, and thermal properties of V3 O5 thin films and their application as the functional oxide in metal/oxide/metal relaxation oscillators are reported. The V3 O5 devices show electroforming-free volatile threshold switching and negative differential resistance (NDR) with stable (<3% variation) cycle-to-cycle operation. The physical mechanisms underpinning these characteristics are investigated using a combination of electrical measurements, in situ thermal imaging, and device modeling. This shows that conduction is confined to a narrow filamentary path due to self-confinement of the current distribution and that the NDR response is initiated at temperatures well below the insulator-metal transition temperature where it is dominated by the temperature-dependent conductivity of the insulating phase. Finally, the dynamics of individual and coupled V3 O5 -based relaxation oscillators is reported, showing that capacitively coupled devices exhibit rich non-linear dynamics, including frequency and phase synchronization. These results establish V3 O5 as a new functional material for volatile threshold switching and advance the development of robust solid-state neurons for neuromorphic computing.

Ovonic Threshold Switch Chalcogenides: Connecting the First-Principles Electronic Structure to Selector Device Parameters

Chalcogenides are attractive materials for microelectronics applications due to their ability to change physical, optical, and electrical properties under applied electric stimulus. One of the most recent interest in chalcogenides is their use to enable the development of a two-terminal selector device, which is a fast, volatile, resistance switching device. The electrical signature of Ovonic threshold switching (OTS) chalcogenide materials is well suited for such applications. While there are numerous known OTS materials, most of them contain toxic elements. There is hence a need to find environment-friendly OTS materials. For this to happen, we strive to predict electrical device parameters only from atomistic first-principles simulations of the chalcogenide materials, as this can be a faster and less expensive route to screen the performances of chalcogenide candidates. By mapping the experimentally measured set of electrical OTS materials into atomistic models and computing their electronic properties, we were able to identify correlations between computed properties such as the theoretical trap/mobility gaps, the local atomic coordination environments of the elements adopted in the material, and the experimentally measured first-fire/threshold/hold voltages, hold/leakage currents, or extracted trap density. These findings can guide in identifying OTS materials with predefined electronic properties, tailored to the requirements of specific microelectronics applications with only first-principles simulations.

Threshold switching behavior generated by the in situ filaments formation in carbon matrix enriched by ultra-small zirconium oxide nanoparticles

Threshold switching behavior generated by the in situ filaments formation in carbon matrix enriched by ultra-small zirconium oxide nanoparticles

Multifunctional Ag–In–Zn–S/Cs3Cu2Cl5‐Based Memristors with Coexistence of Non‐Volatile Memory and Volatile Threshold Switching Behaviors for Neuroinspired Computing

AbstractLead‐free all‐inorganic Cs3Cu2Cl5 perovskites, a member of the metal‐metal halide material family, have attracted pronounced attention owing to their low toxicity, facile fabrication strategies, considerable ambient stability, and intriguing photoelectric properties. However, the application of environmentally friendly copper‐based Cs3Cu2Cl5 in memristors has been rarely reported to the authors’ knowledge. Herein, multifunctional memristors with the coexistence of non‐volatile memory (MS) and volatile threshold switching (TS) behaviors are introduced based on an innovative Ag–In–Zn–S/Cs3Cu2Cl5 heterostructure. The inserted Ag–In–Zn–S quantum dots layer may provide an effective method for guiding the formation of the dominant metallic Ag filaments, resulting in considerably stable and controllable multiple switching behaviors. Additionally, the heterostructure memristor is capable of imitating some essential biological synaptic functions, including long‐term potentiation (LTP), long‐term depression (LTD), and the short‐term memory (STM) to long‐term memory (LTM) transition. Furthermore, the famous conditioning Pavlov's dog experiment corresponding to associative learning is electronically simulated by the studied device. Moreover, utilizing the devices’ LTP and LTD properties, relatively high recognition accuracies for small and large digits datasets are achieved through a three‐layer artificial neural network, revealing the feasibility of implementing neuromorphic computation using heterostructure memristors.

Emulating Nociceptive Receptor and LIF Neuron Behavior via ZrOx‐based Threshold Switching Memristor

AbstractFor the progress of artificial neural networks, the imitation of multiple biological functions is indispensable for processing more tasks in a complex working environment. Memristors, which possess these advantages such as uniformity, high switching speed, and smaller device scale, are the better candidates compared to conventional complementary metal–oxide–semiconductor (CMOS) technology in artificial neural networks. In this work, an Ag/ZrOx/Pt threshold switching memristor (TSM) is designed to overcome the drawback of the large variation in the non‐volatile filament type memristor. The cycle‐to‐cycle and device‐to‐device variations are 5.6% and 4.9%. This device has mimicked the “nociceptive threshold,” “relaxation,” “no adaptation,” and “sensitization” features for the nociceptor which can prevent the artificial intelligence system from dangers in the external environment. Additionally, with the change in the strength of the external stimulus, the artificial neuron is also built by emulating “all‐or‐nothing,” “threshold‐driven‐spiking,” and “strength‐modulated” characteristics. The proposed threshold‐switching memristor allows the simultaneous emulation of the biological nociceptor and leaky integrate‐and‐fire neuron for the first time, which represents an advance in the bioinspired technology adopted in future artificial neural networks and humanoid robots.

Programmable DNA biocomputing circuits for rapid and intelligent screening of SARS-CoV-2 variants

The frequent emergence of SARS-CoV-2 variants increased viral transmissibility and reduced protection afforded by vaccines. The rapid, multichannel, and intelligent screening of variants is critical to minimizing community transmissions. DNA molecular logic gates have attracted wide attention in recent years due to the powerful information processing capabilities and molecular data biocomputing functions. In this work, some molecular switches (MSs) were connected with each other to implement arbitrary binary functions by emulating the threshold switching of MOS transistors and the decision tree model. Using specific sequences of different SARS-CoV-2 variants as inputs, the MSs net was used to build several molecular biocomputing circuits, including NOT, AND, OR, INHIBIT, XOR, half adder, half subtractor, full adder, and full subtractor. Four fluorophores (FAM, Cy3, ROX, and Cy5) were employed in the logic systems to realize the multichannel monitoring of the logic operation results. The logic response is fast and can be finished with 10 min, which facilitates the rapid wide-population screening for SARS-CoV-2 variants. Importantly, the logic results can be directly observed by the naked eye under a portable UV lamp, thus providing a simple and intelligent method to enable high-frequency point-of-care diagnostics, particularly in low-resource communities.

Controlling Threshold and Resistive Switch Functionalities in Ag‐Incorporated Organometallic Halide Perovskites for Memristive Crossbar Array

AbstractHalide perovskites (HPs) can be the effective functional materials for the sneak‐path current issue in the memristive crossbar array. Herein, an efficient strategy is proposed to integrate the HPs‐based bidirectional threshold and bipolar resistive switches (TS and RS). The resistance change characteristics from volatile threshold to nonvolatile resistive switching are modulated by controlling Ag doping concentration in the MAPbI3. HPs provide the diffusive condition and the quantity of Ag regulates the radius of its network. A low amount of Ag contributes to weak network with a short lifetime. However, when the amount of Ag increases, the conductive filament becomes more robust, showing a long lifetime. A MAPbI3:Ag TS with a low Ag content is developed, showing a steep switching slope (1 mV per decade), fast switching speed (&lt; 80 ns), and low off‐current (10 nA). And, a MAPbI3:Ag RS with a high Ag content is developed, showing multilevel storage capability and long retention time (1400 s). Finally, these TS and RS coupled into the 1S‐1R integrated component, resulting the development of the maximum crossbar array size to 1.4 × 1012. This study offers an efficient methodology for tailoring the resistance change characteristics and a promising strategy for practical HPs‐based memristive crossbar application.

Exploration of threshold and resistive-switching behaviors in MXene/BaFe12O19 ferroelectric memristors

Ferroelectric memristors have great potentials to be the key computational element of the brain-inspired neuromorphic system due to their excellent endurance, multi-bit storage ability, ultrafast speed, and ultra-low energy consumption. In this work, novel barium ferrite (BFO: BaFe12O19)-based ferroelectric memristors have been fabricated. Meanwhile, two-dimensional MXene Ti3C2 was inserted onto the dielectric layer for performance enhancement. More importantly, under the regulation of compliance currents, the Cu/Ti3C2/BFO/Pt ferroelectric memristors can convert from stable threshold-switching (TS) to resistive-switching (RS) behavior. The coexistence of the TS and RS demonstrated in this work facilitates the simulation of biological synapses, i.e., short/long-term plasticity, paired-pulse facilitation, and spike-time-dependent plasticity. In addition, the one-bit adder circuit by fitting the non-volatile I-V curve (RS behavior) was demonstrated in the Cadence Virtuoso environment. The deep neural network based on our ferroelectric crossbar arrays has been architected for the image classification (on-chip: 85 %) of the CIFAR-10 dataset. The internal mechanisms are attributed to the combination of barrier variation induced by the ferroelectric polarization and motion of oxygen vacancies, which have been verified by the first-principles calculation of density functional theory. These results may provide possible suggestions for ferroelectric memristors-based neuro-inspired computing systems.

Sustainable Maintenance of Connected Dominating Set by Solar Energy Harvesting for IoT Networks

A new scheme, Sustainability in Dominating Set (SID), to construct and maintain a sustainable and adaptive node disjoint weighted connected dominating set (CDS) is presented for solar energy harvesting-enabled Internet of Things (IoT) networks. The primary contribution of this work is the design of an approximation algorithm for CDS construction and maintenance in energy harvesting-enabled IoT networks, which is triggered when energy of any CDS node falls below a threshold. This is a new CDS construction approach of approximation ratio <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\frac {\delta w(G) + 1}{2} + (1 + \ln 5) |O_{p}|$ </tex-math></inline-formula> , where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\delta w(G)$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$|O_{p}|$ </tex-math></inline-formula> are weighted average degree of the network and optimal number of Steiner nodes, respectively. The extensive simulation results show that per-slot-rotation-based SID (SIDS) improves residual energy (saves by 14.3%, 25.6%, 8.25% and 8%), message complexity (reduces by 88.5%, 34% and 72.75% and 83.25%), and average CDS size (reduces by 9.01%, 9.09%, 41.75%, and 54.5%) for two scenarios and cloud cover 0.25, 0.5 and 0.8, compared to LMW, Improved LMW (ILMW), DataCDS and UCDS, respectively. Merely based on threshold switching, SID enhances residual energy, message complexity, and CDS size by 3.08%, 51.88%, and 4% for all scenarios and cloud covers compared to SIDS, respectively.