High-Speed and Low-Energy Resistive Switching with Two-Dimensional Cobalt Phosphorus Trisulfide for Efficient Neuromorphic Computing.

Two-dimensional (2D) materials hold significant potential for the development of neuromorphic computing architectures owing to their exceptional electrical tunability, mechanical flexibility, and compatibility with heterointegration. However, the practical implementation of 2D memristors in neuromorphic computing is often hindered by the challenges of simultaneously achieving low latency and low energy consumption. Here, we demonstrate memristors based on 2D cobalt phosphorus trisulfide (CoPS), which achieve impressive performance metrics including high switching speed (20 ns), low switching energy (1.

Impact of grain boundaries on the electronic properties and Schottky barrier height in MoS@Au heterojunctions.

Using density functional theory (DFT) calculations we thoroughly explored the influence of grain boundaries (GBs) in monolayer MoS composed of S-polar (S5|7), Mo-polar (Mo5|7), and (4|8) edge dislocation, as well as an edge dislocation-double S vacancy complex (S4|6), and a dislocation-double S interstitial complex (S6|8), respectively, on the electronic properties of MoS and the Schottky barrier height (SBH) in MoS@Au heterojunctions. Our findings demonstrate that GBs formed by edge dislocations can significantly reduce the SBH in defect-free MoS, with the strongest effect for zigzag (4|8) GBs (-20% reduction) and the weakest for armchair (5|7) GBs (-10% reduction). In addition, a larger tilt angle in the GBs leads to a more pronounced decrease in the SBH, suggesting that the modulation of SBH in the MoS@Au heterostructure and analogous systems can be accomplished by GB engineering.

Emerging 2D materials hardware for in-sensor computing.

The advent of the novel in-sensor/near-sensor computing paradigm significantly eliminates the need for frequent data transfer between sensory terminals and processing units by integrating sensing and computing functions into a single device. This approach surpasses the traditional configuration of separate sensing and processing units, thereby greatly simplifying system complexity. Two-dimensional materials (2DMs) show immense promise for implementing in-sensor computing systems owing to their exceptional material properties and the flexibility they offer in designing innovative device architectures with heterostructures.

Memristor Array Based on Wafer-Scale 2D HfS for Dual-Mode Physically Unclonable Functions.

Conventional Si-based physically unclonable functions (PUFs) take advantage of the unique variations in the fabrication processes. However, these PUFs are hindered by limited entropy sources and susceptibility to noise interference. Here we present a memristive device based on wafer-scale (2-in.

Compact Physical Implementation of Spiking Neural Network Using Ambipolar WSe n-Type/p-Type Ferroelectric Field-Effect Transistor.

Spiking neural networks (SNNs) are attracting increasing interests for their ability to emulate biological processes, offering energy-efficient computation and event-driven processing. Currently, no devices are known to combine both neuronal and synaptic functions. This study presents an experimental demonstration of an ambipolar WSe n-type/p-type ferroelectric field-effect transistor (n/p-FeFET) integrated with ferroelectric HfZrO (HZO) to achieve both volatile and nonvolatile properties in a single device.

Ferroelectric Aluminum Scandium Nitride Transistors with Intrinsic Switching Characteristics and Artificial Synaptic Functions for Neuromorphic Computing.

Aluminum Scandium Nitride (AlScN) has received attention for its exceptional ferroelectric properties, whereas the fundamental mechanism determining its dynamic response and reliability remains elusive. In this work, an unreported nucleation-based polarization switching mechanism in AlScN (AlScN) is unveiled, driven by its intrinsic ferroelectricity rooted in the ionic displacement. Fast polarization switching, characterized by a remarkably low characteristic time of 0.

An Atomically Resolved Schottky Barrier Height Approach for Bridging the Gap between Theory and Experiment at Metal-Semiconductor Heterojunctions.

We propose an atomically resolved approach to capture the spatial variations of the Schottky barrier height (SBH) at metal-semiconductor heterojunctions. This proposed scheme, based on atom-specific partial density of states (PDOS) calculations, further enables calculation of the effective SBH that aligns with conductance measurements. We apply this approach to study the variations of SBH at MoS@Au heterojunctions, in which MoS contains conducting and semiconducting grain boundaries (GBs).

Physical reservoirs based on MoS-HZO integrated ferroelectric field-effect transistors for reservoir computing systems.

Reservoir computing (RC), a variant of recurrent neural networks (RNNs), is well-known for its reduced energy consumption through exclusive focus on training the output weight and its superior performance in handling spatiotemporal information. Implementing these networks in hardware requires devices with superior fading memory behavior. Unlike filament-based two-terminal devices, those relying on ferroelectric switching demonstrate improved voltage reliability, while three-terminal transistors provide additional active control.

Recent Advances in In-Memory Computing: Exploring Memristor and Memtransistor Arrays with 2D Materials.

The conventional computing architecture faces substantial challenges, including high latency and energy consumption between memory and processing units. In response, in-memory computing has emerged as a promising alternative architecture, enabling computing operations within memory arrays to overcome these limitations. Memristive devices have gained significant attention as key components for in-memory computing due to their high-density arrays, rapid response times, and ability to emulate biological synapses.

Coupled Ferroelectric-Photonic Memory in a Retinomorphic Hardware for In-Sensor Computing.

The development of all-in-one devices for artificial visual systems offers an attractive solution in terms of energy efficiency and real-time processing speed. In recent years, the proliferation of smart sensors in the growth of Internet-of-Things (IoT) has led to the increasing importance of in-sensor computing technology, which places computational power at the edge of the data-flow architecture. In this study, a prototype visual sensor inspired by the human retina is proposed, which integrates ferroelectricity and photosensitivity in two-dimensional (2D) α-InSe material.

Sublimation-based wafer-scale monolayer WS formation self-limited thinning of few-layer WS.

Atomically-thin monolayer WS is a promising channel material for next-generation Moore's nanoelectronics owing to its high theoretical room temperature electron mobility and immunity to short channel effect. The high photoluminescence (PL) quantum yield of the monolayer WS also makes it highly promising for future high-performance optoelectronics. However, the difficulty in strictly growing monolayer WS, due to its non-self-limiting growth mechanism, may hinder its industrial development because of the uncontrollable growth kinetics in attaining the high uniformity in thickness and property on the wafer-scale.

Reliable Memristor Crossbar Array Based on 2D Layered Nickel Phosphorus Trisulfide for Energy-Efficient Neuromorphic Hardware.

Designing reliable and energy-efficient memristors for artificial synaptic arrays in neuromorphic computing beyond von Neumann architecture remains a challenge. Here, memristors based on emerging layered nickel phosphorus trisulfide (NiPS ) are reported that exhibit several favorable characteristics, including uniform bipolar nonvolatile switching with small operating voltage (<1 V), fast switching speed (< 20 ns), high On/Off ratio (>10 ), and the ability to achieve programmable multilevel resistance states. Through direct experimental evidence using transmission electron microscopy and energy dispersive X-ray spectroscopy, it is revealed that the resistive switching mechanism in the Ti/NiPS /Au device is related to the formation and dissolution of Ti conductive filaments.

Technology and Integration Roadmap for Optoelectronic Memristor.

Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and optoelectronic systems. These OMs possess a range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, and the ability to replicate crucial neurological functions such as vision and optical memory. By incorporating large-scale parallel synaptic structures, OMs are anticipated to greatly enhance high-performance and low-power in-memory computing, effectively overcoming the limitations of the von Neumann bottleneck.

Attack Resilient True Random Number Generators Using Ferroelectric-Enhanced Stochasticity in 2D Transistor.

By harnessing the physically unclonable properties, true random number generators (TRNGs) offer significant promises to alleviate security concerns by generating random bitstreams that are cryptographically secured. However, fundamental challenges remain as conventional hardware often requires complex circuitry design, showing a predictable pattern that is susceptible to machine learning attacks. Here, a low-power self-corrected TRNG is presented by exploiting the stochastic ferroelectric switching and charge trapping in molybdenum disulfide (MoS ) ferroelectric field-effect transistors (Fe-FET) based on hafnium oxide complex.

Van der Waals Layer Transfer of 2D Materials for Monolithic 3D Electronic System Integration: Review and Outlook.

Two-dimensional materials (2DMs) have attracted a great deal of interest due to their immense potential for scientific breakthroughs and technological innovations. While some 2D transition metal dichalcogenides (TMDC) such as MoS and WS are considered as the ultimate channel materials in unltrascaled transistors as replacements for Si, there has also been increasing interest in the monolithic 3D integration of 2DMs on the Si CMOS platform or in flexible electronics as back-end-of-line transistors, memory devices/selectors, and sensors, taking advantage of 2DM properties such as a high current driving capability with low leakage current, nonvolatile switching characteristics, a large surface-to-volume ratio, and a tunable bandgap. However, the realization of both of these scenarios critically depends on the development of manufacturing-viable high-yield 2DM layers transfer from the growth substrate to the Si, since the growth of high-quality 2DM layers often requires a high-temperature growth process on template substrates.

A MoS Hafnium Oxide Based Ferroelectric Encoder for Temporal-Efficient Spiking Neural Network.

Spiking neural network (SNN), where the information is evaluated recurrently through spikes, has manifested significant promises to minimize the energy expenditure in data-intensive machine learning and artificial intelligence. Among these applications, the artificial neural encoders are essential to convert the external stimuli to a spiking format that can be subsequently fed to the neural network. Here, a molybdenum disulfide (MoS ) hafnium oxide-based ferroelectric encoder is demonstrated for temporal-efficient information processing in SNN.

The effects of point defect type, location, and density on the Schottky barrier height of Au/MoS heterojunction: a first-principles study.

Using DFT calculations, we investigate the effects of the type, location, and density of point defects in monolayer MoS on electronic structures and Schottky barrier heights (SBH) of Au/MoS heterojunction. Three types of point defects in monolayer MoS, that is, S monovacancy, S divacancy and Mo (Mo substitution at S site) antisite defects, are considered. The following findings are revealed: (1) The SBH for the monolayer MoS with these defects is universally higher than that for its defect-free counterpart.

Interface-Modulated Resistive Switching in Mo-Irradiated ReS for Neuromorphic Computing.

Coupling charge impurity scattering effects and charge-carrier modulation by doping can offer intriguing opportunities for atomic-level control of resistive switching (RS). Nonetheless, such effects have remained unexplored for memristive applications based on 2D materials. Here a facile approach is reported to transform an RS-inactive rhenium disulfide (ReS ) into an effective switching material through interfacial modulation induced by molybdenum-irradiation (Mo-i) doping.

In-Memory Computing using Memristor Arrays with Ultrathin 2D PdSeO /PdSe Heterostructure.

In-memory computing based on memristor arrays holds promise to address the speed and energy issues of the classical von Neumann computing system. However, the stochasticity of ions' transport in conventional oxide-based memristors imposes severe intrinsic variability, which compromises learning accuracy and hinders the implementation of neural network hardware accelerators. Here, these challenges are addressed using a low-voltage memristor array based on an ultrathin PdSeO /PdSe heterostructure switching medium realized by a controllable ultraviolet (UV)-ozone treatment.

Wafer-Scale 2D Hafnium Diselenide Based Memristor Crossbar Array for Energy-Efficient Neural Network Hardware.

Memristor crossbar with programmable conductance could overcome the energy consumption and speed limitations of neural networks when executing core computing tasks in image processing. However, the implementation of crossbar array (CBA) based on ultrathin 2D materials is hindered by challenges associated with large-scale material synthesis and device integration. Here, a memristor CBA is demonstrated using wafer-scale (2-inch) polycrystalline hafnium diselenide (HfSe ) grown by molecular beam epitaxy, and a metal-assisted van der Waals transfer technique.

Gate-Defined Quantum Confinement in CVD 2D WS.

Temperature-dependent transport measurements are performed on the same set of chemical vapor deposition (CVD)-grown WS single- and bilayer devices before and after atomic layer deposition (ALD) of HfO . This isolates the influence of HfO deposition on low-temperature carrier transport and shows that carrier mobility is not charge impurity limited as commonly thought, but due to another important but commonly overlooked factor: interface roughness. This finding is corroborated by circular dichroic photoluminescence spectroscopy, X-ray photoemission spectroscopy, cross-sectional scanning transmission electron microscopy, carrier-transport modeling, and density functional modeling.

Suspended MoS Photodetector Using Patterned Sapphire Substrate.

The introduction of patterned sapphire substrates (PSS) has been regarded as an effective method to improve the photoelectric performance of 2D layered materials in recent years. Molybdenum disulfide (MoS ), an intriguing transition metal 2D materials with splendid photoresponse owing to a direct-indirect bandgap transition at monolayer, shows promising optoelectronics applications. Here, a large-scale, continuous multilayer MoS film is prepared on a SiO /Si substrate and transferred to flat sapphire substrate and PSS, respectively.

Self-Selective Multi-Terminal Memtransistor Crossbar Array for In-Memory Computing.

Two-terminal resistive switching devices are commonly plagued with longstanding scientific issues including interdevice variability and sneak current that lead to computational errors and high-power consumption. This necessitates the integration of a separate selector in a one-transistor-one-RRAM (1T-1R) configuration to mitigate crosstalk issue, which compromises circuit footprint. Here, we demonstrate a multi-terminal memtransistor crossbar array with increased parallelism in programming independent gate control, which allows computation at a dense cell size of 3-4.