Enhancing simulation feasibility for multi-layer 2D MoS2 RRAM devices: reliability performance learnings from a passive network model.

While two-dimensional (2D) MoS2 has recently shown promise as a material for resistive random-access memory (RRAM) devices due to its demonstrated resistive switching (RS) characteristics, its practical application faces a significant challenge in industry regarding its limited yield and endurance. Our earlier work introduced an effective switching layer model to understand RS behavior in both mono- and multi-layered MoS2. However, functioning as a phenomenological percolation modeling tool, it lacks the capability to accurately simulate the intricate current-voltage (I-V) characteristics of the device, thereby hindering its practical applicability in 2D RRAM research. In contrast to the established conductive filament model for oxide-based RRAM, the RS mechanism in 2D RRAM remains elusive. This paper presents a novel simulator aimed at providing an intuitive, visual representation of the stochastic behaviors involved in the RS process of multi-layer 2D MoS2 RRAM devices. Building upon the previously proposed phenomenological simulator for 2D RRAM, users can now simulate both the I-V characteristics and the resistive switching behaviors of the RRAM devices. Through comparison with experimental data, it was observed that yield and endurance characteristics are linked to defect distributions in MoS2.

Programmable Retention Characteristics in MoS2-Based Atomristors for Neuromorphic and Reservoir Computing Systems.

In this study, we investigate the coexistence of short- and long-term memory effects owing to the programmable retention characteristics of a two-dimensional Au/MoS2/Au atomristor device and determine the impact of these effects on synaptic properties. This device is constructed using bilayer MoS2 in a crossbar structure. The presence of both short- and long-term memory characteristics is proposed by using a filament model within the bilayer transition-metal dichalcogenide. Short- and long-term properties are validated based on programmable multilevel retention tests. Moreover, we confirm various synaptic characteristics of the device, demonstrating its potential use as a synaptic device in a neuromorphic system. Excitatory postsynaptic current, paired-pulse facilitation, spike-rate-dependent plasticity, and spike-number-dependent plasticity synaptic applications are implemented by operating the device at a low-conductance level. Furthermore, long-term potentiation and depression exhibit symmetrical properties at high-conductance levels. Synaptic learning and forgetting characteristics are emulated using programmable retention properties and composite synaptic plasticity. The learning process of artificial neural networks is used to achieve high pattern recognition accuracy, thereby demonstrating the suitability of the use of the device in a neuromorphic system. Finally, the device is used as a physical reservoir with time-dependent inputs to realize reservoir computing by using short-term memory properties. Our study reveals that the proposed device can be applied in artificial intelligence-based computing applications by utilizing its programmable retention properties.

Editorial for the Special Issue on the Progress of Emerging Hardware Development for Post-Moore's Computing.

The potential of machine learning and novel computing architecture can be exploited in the immediate future if more efficient hardware is developed that meets the special requirements of bio-inspired computing or unconventional computing schemes [...].

Post-Moore Memory Technology: Sneak Path Current (SPC) Phenomena on RRAM Crossbar Array and Solutions.

The sneak path current (SPC) is the inevitable issue in crossbar memory array while implementing high-density storage configuration. The crosstalks are attracting much attention, and the read accuracy in the crossbar architecture is deteriorated by the SPC. In this work, the sneak path current problem is observed and investigated by the electrical experimental measurements in the crossbar array structure with the half-read scheme. The read margin of the selected cell is improved by the bilayer stacked structure, and the sneak path current is reduced ~20% in the bilayer structure. The voltage-read stress-induced read margin degradation has also been investigated, and less voltage stress degradation is showed in bilayer structure due to the intrinsic nonlinearity. The oxide-based bilayer stacked resistive random access memory (RRAM) is presented to offer immunity toward sneak path currents in high-density memory integrations when implementing the future high-density storage and in-memory computing applications.

[Characteristics of ANAMMOX Granular Sludge and Differences in Microbial Community Structure Under Different Culture Conditions].

Anaerobic ammonium oxidation (ANAMMOX) granular sludge was cultured during different operating conditions by an expanded granular sludge bed (EGSB) reactor and up-flow anaerobic sludge bed (UASB) reactors, and the characteristics of the granular sludge and microbial community were compared. The results showed that the flocculent ANAMMOX sludge can be granulated after being operated for 384 days by the EGSB and UASB reactors. The average particle size reached 1.17 mm and 1.21 mm, respectively. The particle size ratio of each range (<0.2, 0.2-1.5, 1.5-3, and>3 mm) was 6.06%, 60.05%, 25.25%, and 8.64% in the EGSB reactor, and 7.40%, 58.90%, 32.04%, and 1.66% in the UASB reactor, respectively. The results of scanning electron microscopy showed that the bacterial flora during different operating conditions were mainly Brevibacterium and Cocci aggregates. High-throughput sequencing results showed that the Shannon index of the EGSB reactor was 7.52, higher than the 7.18 of the UASB reactor on day 384; Proteobacteria was the main phylum of the sludge at each stage, and Planctomycetes increased from 3.30% to 12.30% in the EGSB reactor and 13.30% in the UASB reactor on day 384. The main ANAMMOX genera in the EGSB reactor were Candidatus Brocadia, accounting for 7.53%, followed by Candidatus Kuenenia accounting for 1.61%, whereas in the UASB reactor, Candidatus Kuenenia was the dominant anaerobic ammonia genus, accounting for 7.54%, followed by Candidatus Brocadia, which accounted for 3.69%. The proportion of dominant species was related to the change in environmental factors. The proportion of Candidatus Brocadia was positively correlated with the up-flow rate and nitrogen removal rate (NRR), but negatively correlated with hydraulic retention time (HRT). Candidatus Kuenenia was positively correlated with nitrogen removal efficiency (NRE), NRR, and HRT, but negatively correlated with the up-flow rate.

Neuronal dynamics in HfOx/AlOy-based homeothermic synaptic memristors with low-power and homogeneous resistive switching.

We studied the pseudo-homeothermic synaptic behaviors by integrating complimentary metal-oxide-semiconductor-compatible materials (hafnium oxide, aluminum oxide, and silicon substrate). A wide range of temperatures, from 25 °C up to 145 °C, in neuronal dynamics was achieved owing to the homeothermic properties and the possibility of spike-induced synaptic behaviors was demonstrated, both presenting critical milestones for the use of emerging memristor-type neuromorphic computing systems in the near future. Biological synaptic behaviors, such as long-term potentiation, long-term depression, and spike-timing-dependent plasticity, are developed systematically, and comprehensive neural network analysis is used for temperature changes and to conform spike-induced neuronal dynamics, providing a new research regime of neurocomputing for potentially harsh environments to overcome the self-heating issue in neuromorphic chips.

Dual Functions of V/SiOx/AlOy/p++Si Device as Selector and Memory.

This letter presents dual functions including selector and memory switching in a V/SiOx/AlOy/p++Si resistive memory device by simply controlling compliance current limit (CCL). Unidirectional threshold switching is observed after a positive forming with low CCL of 1 µA. The shifts to the V-electrode side of the oxygen form the VOx layer, where the threshold switching can be explained by the metal-insulation-transition phenomenon. For higher CCL (30 µA) applied to the device, a bipolar memory switching is obtained, which is attributed to formation and rupture of the conducting filament in SiOy layer. 1.5-nm-thick AlOy layer with high thermal conductivity plays an important role in lowering the off-current for memory and threshold switching. Through the temperature dependence, high-energy barrier (0.463 eV) in the LRS is confirmed, which can cause nonlinearity in a low-resistance state. The smaller the CCL, the higher the nonlinearity, which provides a larger array size in the cross-point array. The coexistence of memory and threshold switching in accordance with the CCL provides the flexibility to control the device for its intended use.

Graphite-based selectorless RRAM: improvable intrinsic nonlinearity for array applications.

Selectorless graphite-based resistive random-access memory (RRAM) has been demonstrated by utilizing the intrinsic nonlinear resistive switching (RS) characteristics, without an additional selector or transistor for low-power RRAM array application. The low effective dielectric constant value (k) layer of graphite or graphite oxide is utilized, which is beneficial in suppressing sneak-path currents in the crossbar RRAM array. The tail-bits with low nonlinearity can be manipulated by the positive voltage pulse, which in turn can alleviate variability and reliability issues. Our results provide additional insights for built-in nonlinearity in 1R-only selectorless RRAMs, which are applicable to the low-power memory array, ultrahigh density storage, and in-memory neuromorphic computational configurations.

Scaling Effect on Silicon Nitride Memristor with Highly Doped Si Substrate.

A feasible approach is reported to reduce the switching current and increase the nonlinearity in a complementary metal-oxide-semiconductor (CMOS)-compatible Ti/SiNx /p+ -Si memristor by simply reducing the cell size down to sub-100 nm. Even though the switching voltages gradually increase with decreasing device size, the reset current is reduced because of the reduced current overshoot effect. The scaled devices (sub-100 nm) exhibit gradual reset switching driven by the electric field, whereas that of the large devices (≥1 µm) is driven by Joule heating. For the scaled cell (60 nm), the current levels are tunable by adjusting the reset stop voltage for multilevel cells. It is revealed that the nonlinearity in the low-resistance state is attributed to Fowler-Nordheim tunneling dominating in the high-voltage regime (≥1 V) for the scaled cells. The experimental findings demonstrate that the scaled metal-nitride-silicon memristor device paves the way to realize CMOS-compatible high-density crosspoint array applications.

Analog Synaptic Behavior of a Silicon Nitride Memristor.

In this paper, we present a synapse function using analog resistive-switching behaviors in a SiNx-based memristor with a complementary metal-oxide-semiconductor compatibility and expandability to three-dimensional crossbar array architecture. A progressive conductance change is attainable as a result of the gradual growth and dissolution of the conducting path, and the series resistance of the AlOy layer in the Ni/SiNx/AlOy/TiN memristor device enhances analog switching performance by reducing current overshoot. A continuous and smooth gradual reset switching transition can be observed with a compliance current limit (>100 µA), and is highly suitable for demonstrating synaptic characteristics. Long-term potentiation and long-term depression are obtained by means of identical pulse responses. Moreover, symmetric and linear synaptic behaviors are significantly improved by optimizing pulse response conditions, which is verified by a neural network simulation. Finally, we display the spike-timing-dependent plasticity with the multipulse scheme. This work provides a possible way to mimic biological synapse function for energy-efficient neuromorphic systems by using a conventional passive SiNx layer as an active dielectric.

Self-Compliant Bipolar Resistive Switching in SiN-Based Resistive Switching Memory.

Here, we present evidence of self-compliant and self-rectifying bipolar resistive switching behavior in Ni/SiNx/n⁺ Si and Ni/SiNx/n++ Si resistive-switching random access memory devices. The Ni/SiNx/n++ Si device's Si bottom electrode had a higher dopant concentration (As ion > 1019 cm-3) than the Ni/SiNx/n⁺ Si device; both unipolar and bipolar resistive switching behaviors were observed for the higher dopant concentration device owing to a large current overshoot. Conversely, for the device with the lower dopant concentration (As ion < 1018 cm-3), self-rectification and self-compliance were achieved owing to the series resistance of the Si bottom electrode.

Ultralow power switching in a silicon-rich SiNy/SiNx double-layer resistive memory device.

Here we demonstrate low-power resistive switching in a Ni/SiNy/SiNx/p++-Si device by proposing a double-layered structure (SiNy/SiNx), where the two SiN layers have different trap densities. The LRS was measured to be as low as 1 nA at a voltage of 1 V, because the SiNx layer maintains insulating properties for the LRS. The single-layered device suffers from uncontrollability of the conducting path, accompanied by the inherent randomness of switching parameters, weak immunity to breakdown during the reset process, and a high operating current. On the other hand, for a double-layered device, the effective conducting path in each layer, which can determine the operating current, can be well controlled by the ICC during the initial forming and set processes. A one-step forming and progressive reset process is observed for a low-power mode, which differs from the high-power switching mode that shows a two-step forming and reset process. Moreover, nonlinear behavior in the LRS, whose origin can be attributed to the P-F conduction and F-N tunneling driven by abundant traps in the silicon-rich SiNx layer, would be beneficial for next-generation nonvolatile memory applications by using a conventional passive SiNx layer as an active dielectric.

Attaining resistive switching characteristics and selector properties by varying forming polarities in a single HfO2-based RRAM device with a vanadium electrode.

This study proposes a method for a HfO2-based device to exhibit both resistive switching (RS) characteristics as resistive random access memory (RRAM) and selector characteristics by introducing vanadium (V) as the top electrode. This simple V/HfO2/TiN structure can demonstrate these two different properties depending on forming polarities. The RS mechanism is activated by a positive forming bias. In contrast, the selector property is induced by a negative forming bias. The material analyses firstly confirm the existence of V in the top electrode. Then the electrical measurements for the same V/HfO2/TiN structures but with different forming polarities were carried out to further investigate their DC sweeping characteristics to act as either a selector or RRAM device. Furthermore, reliability tests for both selector and RRAM devices were also conducted to confirm their switching stabilities. Finally, current fitting methods and temperature influence experiments were performed to investigate the carrier transport mechanisms. Finally, physical models were proposed to illustrate the selector property and RS mechanism for selector and RRAM devices, respectively. This simple device structure with its easy operating method accomplishes a significant advancement of devices combining both selector properties and RRAM for remarkable real applications in the near future.

Demonstration of Synaptic Behaviors and Resistive Switching Characterizations by Proton Exchange Reactions in Silicon Oxide.

We realize a device with biological synaptic behaviors by integrating silicon oxide (SiO(x)) resistive switching memory with Si diodes. Minimal synaptic power consumption due to sneak-path current is achieved and the capability for spike-induced synaptic behaviors is demonstrated, representing critical milestones for the use of SiO2-based materials in future neuromorphic computing applications. Biological synaptic behaviors such as long-term potentiation (LTP), long-term depression (LTD) and spike-timing dependent plasticity (STDP) are demonstrated systematically using a comprehensive analysis of spike-induced waveforms, and represent interesting potential applications for SiO(x)-based resistive switching materials. The resistive switching SET transition is modeled as hydrogen (proton) release from (SiH)2 to generate the hydrogen bridge defect, and the RESET transition is modeled as an electrochemical reaction (proton capture) that re-forms (SiH)2. The experimental results suggest a simple, robust approach to realize programmable neuromorphic chips compatible with large-scale CMOS manufacturing technology.

A study of the interfacial resistive switching mechanism by proton exchange reactions on the SiO(x) layer.

In this work, we investigated SiO(x)-based interfacial resistive switching in planar metal-insulator-metal structures using physical/chemical/electrical analyses. This work helps clarify the interfacial reaction process and mechanism in SiO(x), and also shows the potential for high temperature operation in future nonvolatile memory applications.

"Cut-and-Paste" Manufacture of Multiparametric Epidermal Sensor Systems.

Multifunctional epidermal sensor systems (ESS) are manufactured with a highly cost and time effective, benchtop, and large-area "cut-and-paste" method. The ESS made out of thin and stretchable metal and conductive polymer ribbons can be noninvasively laminated onto the skin surface to sense electrophysiological signals, skin temperature, skin hydration, and respiratory rate.

Physical and chemical mechanisms in oxide-based resistance random access memory.

In this review, we provide an overview of our work in resistive switching mechanisms on oxide-based resistance random access memory (RRAM) devices. Based on the investigation of physical and chemical mechanisms, we focus on its materials, device structures, and treatment methods so as to provide an in-depth perspective of state-of-the-art oxide-based RRAM. The critical voltage and constant reaction energy properties were found, which can be used to prospectively modulate voltage and operation time to control RRAM device working performance and forecast material composition. The quantized switching phenomena in RRAM devices were demonstrated at ultra-cryogenic temperature (4K), which is attributed to the atomic-level reaction in metallic filament. In the aspect of chemical mechanisms, we use the Coulomb Faraday theorem to investigate the chemical reaction equations of RRAM for the first time. We can clearly observe that the first-order reaction series is the basis for chemical reaction during reset process in the study. Furthermore, the activation energy of chemical reactions can be extracted by changing temperature during the reset process, from which the oxygen ion reaction process can be found in the RRAM device. As for its materials, silicon oxide is compatible to semiconductor fabrication lines. It is especially promising for the silicon oxide-doped metal technology to be introduced into the industry. Based on that, double-ended graphene oxide-doped silicon oxide based via-structure RRAM with filament self-aligning formation, and self-current limiting operation ability is demonstrated. The outstanding device characteristics are attributed to the oxidation and reduction of graphene oxide flakes formed during the sputter process. Besides, we have also adopted a new concept of supercritical CO2 fluid treatment to efficiently reduce the operation current of RRAM devices for portable electronic applications.

Integrated one diode-one resistor architecture in nanopillar SiOx resistive switching memory by nanosphere lithography.

We report on a highly compact, one diode-one resistor (1D-1R) nanopillar device architecture for SiOx-based ReRAM fabricated using nanosphere lithography (NSL). The intrinsic SiOx-based resistive switching element and Si diode are self-aligned on an epitaxial silicon wafer using NSL and a deep-Si-etch process without conventional photolithography. AC-pulse response in 50 ns regime, multibit operation, and good reliability are demonstrated. The NSL process provides a fast and economical approach to large-scale patterning of high-density 1D-1R ReRAM with good potential for use in future applications.