Oxygen-Plasma-Treated Al/TaOX/Al Resistive Memory for Enhanced Synaptic Characteristics.

In this study, we investigate the impact of O2 plasma treatment on the performance of Al/TaOX/Al-based resistive random-access memory (RRAM) devices, focusing on applications in neuromorphic systems. Comparative analysis using scanning electron microscopy and X-ray photoelectron spectroscopy confirmed the differences in chemical composition between O2-plasma-treated and untreated RRAM cells. Direct-current measurements showed that O2-plasma-treated RRAM cells exhibited significant improvements over untreated RRAM cells, including higher on/off ratios, improved uniformity and distribution, longer retention times, and enhanced durability. The conduction mechanism is investigated by current-voltage (I-V) curve fitting. In addition, paired-pulse facilitation (PPF) is observed using partial short-term memory. Furthermore, 3- and 4-bit weight tuning with auto-pulse-tuning algorithms was achieved to improve the controllability of the synapse weight for the neuromorphic system, maintaining retention times exceeding 103 s in the multiple states. Neuromorphic simulation with an MNIST dataset is conducted to evaluate the synaptic device.

HfAlOx-based ferroelectric memristor for nociceptor and synapse functions.

Efficient data processing is heavily reliant on prioritizing specific stimuli and categorizing incoming information. Within human biological systems, dorsal root ganglions (particularly nociceptors situated in the skin) perform a pivotal role in detecting external stimuli. These neurons send warnings to our brain, priming it to anticipate potential harm and prevent injury. In this study, we explore the potential of using a ferroelectric memristor device structured as a metal-ferroelectric-insulator-semiconductor as an artificial nociceptor. The aim of this device is to electrically receive external damage and interpret signals of danger. The TiN/HfAlOx (HAO)/HfSiOx (HSO)/n+ Si configuration of this device replicates the key functions of a biological nociceptor. The emulation includes crucial aspects, such as threshold reactivity, relaxation, no adaptation, and sensitization phenomena known as "allodynia" and "hyperalgesia." Moreover, we propose establishing a connection between nociceptors and synapses by training the Hebbian learning rule. This involves exposing the device to injurious stimuli and using this experience to enhance its responsiveness, replicating synaptic plasticity.

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.

Realization of Multiple Synapse Plasticity by Coexistence of Volatile and Nonvolatile Characteristics of Interface Type Memristor.

Studies on neuromorphic computing systems are becoming increasingly important in the big-data-processing era as these systems are capable of energy-efficient parallel data processing and can overcome the present limitations owing to the von Neumann bottleneck. The Pt/WOx/ITO resistive random-access memory device can be used to implement versatile synapse functions because it possesses both volatile and nonvolatile characteristics. The gradual increase and decrease in the current of the Pt/WOx/ITO device with its uniform resistance state for endurance and retention enables additional synaptic applications that can be controlled using electric pulses. If the volatile and nonvolatile device properties are set through rehearsal and forgetting processes, the device can emulate various synaptic behaviors, such as potentiation and depression, paired-pulse facilitation, post-tetanic potentiation, image training, Hebbian learning rules, excitatory postsynaptic current, and Pavlov's test. Furthermore, reservoir computing can be implemented for applications such as pattern generation and recognition. This emphasizes the various applications of future neuromorphic devices, demonstrating the various favorable characteristics of pulse-enhanced Pt/WOx/ITO devices.

Improved Resistive Switching Characteristics and Synaptic Functions of InZnO/SiO2 Bilayer Device.

This paper investigates the bipolar resistive switching and synaptic characteristics of IZO single-layer and IZO/SiO2 bilayer two-terminal memory devices. The chemical properties and structure of the device with a SiO2 layer are confirmed by x-ray photoemission spectroscopy (XPS) and transmission electron microscopy (TEM) imaging. The device with the SiO2 layer showed better memory characteristics with a low current level, as well as better cell-to-cell and cycle-to-cycle uniformity. Moreover, the neuromorphic applications of the IZO/SiO2 bilayer device are demonstrated by pulse response. Paired pulse facilitation, excitatory postsynaptic current, and pulse-width-dependent conductance changes are conducted by the coexistence of short- and long-term memory characteristics. Moreover, Hebbian rules are emulated to mimic biological synapse function. The result of potentiation, depression, spike-rate-dependent plasticity, and spike-time-dependent plasticity prove their favorable abilities for future applications in neuromorphic computing architecture.

Effect of Pelvic Floor Muscle Training Using Pressure Biofeedback on Pelvic Floor Muscle Contraction and Trunk Muscle Activity in Sitting in Healthy Women.

Pelvic floor muscle training (PFMT) has been recommended as the first choice as one of the effective methods for preventing and improving urinary incontinence (UI). We aimed to determine whether pressure biofeedback unit training (PBUT) improves short term and retention performance of pelvic floor muscle contraction. The muscle activities of the external oblique (EO), transversus/internal oblique (TrA/IO), multifidus (MF) and the bladder base displacement were measured in the verbal feedback group (n = 10) and PBU group (n = 10) three times (baseline, post-training, and at the 1-week follow-up). Surface electromyographic activity was recorded from the EO, TrA/IO, and MF muscles. The bladder base displacement was measured using ultrasound. The results were analyzed using two way mixed ANOVA. The bladder base displacement may have elevated more in the PBU group than in the verbal feedback group due to decreased TrA/IO activity. These findings indicate that PBUT is a better method than verbal feedback training.