A Scalable Artificial Neuron Based on Ultrathin Two-Dimensional Titanium Oxide

Gate-Controlled Neuromorphic Functional Transition in an Electrochemical Graphene Transistor

Neuromorphic devices have attracted significant attention as potential building blocks for the next generation of computing technologies owing to their ability to emulate the functionalities of biological nervous systems. The essential components in artificial neural networks such as synapses and neurons are predominantly implemented by dedicated devices with specific functionalities. In this work, we present a gate-controlled transition of neuromorphic functions between artificial neurons and synapses in monolayer graphene transistors that can be employed as memtransistors or synaptic transistors as required. By harnessing the reliability of reversible electrochemical reactions between carbon atoms and hydrogen ions, we can effectively manipulate the electric conductivity of graphene transistors, resulting in a high on/off resistance ratio, a well-defined set/reset voltage, and a prolonged retention time. Overall, the on-demand switching of neuromorphic functions in a single graphene transistor provides a promising opportunity for developing adaptive neural networks for the upcoming era of artificial intelligence and machine learning.

Site-Specific Emulation of Neuronal Synaptic Behavior in Au Nanoparticle-Decorated Self-Organized TiOx Surface

Neuromorphic computing is a potential approach for imitating massive parallel processing capabilities of a bio-synapse. To date, memristors have emerged as the most appropriate device for designing artificial synapses for this purpose due to their excellent analog switching capacities with high endurance and retention. However, to build an operational neuromorphic platform capable of processing high-density information, memristive synapses with nanoscale footprint are important, albeit with device size scaled down, retaining analog plasticity and low power requirement often become a challenge. This paper demonstrates site-selective self-assembly of Au nanoparticles on a patterned TiOx layer formed as a result of ion-induced self-organization, resulting in site-specific resistive switching and emulation of bio-synaptic behavior (e.g., potentiation, depression, spike rate-dependent and spike timing-dependent plasticity, paired pulse facilitation, and post tetanic potentiation) at nanoscale. The use of local probe-based methods enables nanoscale probing on the anisotropic films. With the help of various microscopic and spectroscopic analytical tools, the observed results are attributed to defect migration and self-assembly of implanted Au atoms on self-organized TiOx surfaces. By leveraging the site-selective evolution of gold-nanostructures, the functionalized TiOx surface holds significant potential in a multitude of fields for developing cutting-edge neuromorphic computing platforms and Au-based biosensors with high-density integration.

Two-Dimensional Oxide Crystals for Device Applications: Challenges and Opportunities

Atomically thin two-dimensional (2D) oxide crystals have garnered considerable attention because of their remarkable physical properties and potential for versatile applications. In recent years, significant advancements have been made in the design, preparation, and application of ultrathin 2D oxides, providing many opportunities for new-generation advanced technologies. This review focuses on the controllable preparation of 2D oxide crystals and their applications in electronic and optoelectronic devices. Based on their bonding nature, the various types of 2D oxide crystals are first summarized, including both layered and nonlayered crystals, as well as their current top-down and bottom-up synthetic approaches. Subsequently, in terms of the unique physical and electrical properties of 2D oxides, recent advances in device applications are emphasized, including photodetectors, field-effect transistors, dielectric layers, magnetic and ferroelectric devices, memories, and gas sensors. Finally, conclusions and future prospects of 2D oxide crystals are presented. It is hoped that this review will provide comprehensive and insightful guidance for the development of 2D oxide crystals and their device applications.

Artificial Neuronal Devices Based on Emerging Materials: Neuronal Dynamics and Applications

Artificial neuronal devices are critical building blocks of neuromorphic computing systems and currently the subject of intense research motivated by application needs from new computing technology and more realistic brain emulation. Researchers have proposed a range of device concepts that can mimic neuronal dynamics and functions. Although the switching physics and device structures of these artificial neurons are largely different, their behaviors can be described by several neuron models in a more unified manner. In this paper, the reports of artificial neuronal devices based on emerging volatile switching materials are reviewed from the perspective of the demonstrated neuron models, with a focus on the neuronal functions implemented in these devices and the exploitation of these functions for computational and sensing applications. Furthermore, the neuroscience inspirations and engineering methods to enrich the neuronal dynamics that remain to be implemented in artificial neuronal devices and networks toward realizing the full functionalities of biological neurons are discussed.

Emerging 2D Metal Oxides: From Synthesis to Device Integration

2D metal oxides have aroused increasing attention in the field of electronics and optoelectronics due to their intriguing physical properties. In this review, an overview of recent advances on synthesis of 2D metal oxides and their electronic applications is presented. First, the tunable physical properties of 2D metal oxides that relate to the structure (various oxidation-state forms, polymorphism, etc.), crystallinity and defects (anisotropy, point defects, and grain boundary), and thickness (quantum confinement effect, interfacial effect, etc.) are discussed. Then, advanced synthesis methods for 2D metal oxides besides mechanical exfoliation are introduced and classified into solution process, vapor-phase deposition, and native oxidation on a metal source. Later, the various roles of 2D metal oxides in widespread applications, i.e., transistors, inverters, photodetectors, piezotronics, memristors, and potential applications (solar cell, spintronics, and superconducting devices) are discussed. Finally, an outlook of existing challenges and future opportunities in 2D metal oxides is proposed.

Controlled Growth of Wafer-Scale Transition Metal Dichalcogenides with a Vertical Composition Gradient for Artificial Synapses with High Linearity

Artificial synapses are promising for dealing with large amounts of data computing. Great progress has been made recently in terms of improving the on/off current ratio, the number of states, and the energy efficiency of synapse devices. However, the nonlinear weight update behavior of a synapse caused by the uncertain direction of the conductive filament leads to complex weight modulation, which degrades the delivery accuracy of information. Here we propose a strategy to improve the weight update behavior of synapses using chemical-vapor-deposition-grown transition metal dichalcogenides (TMDCs) with a vertical composition gradient, where the sulfur concentration decreases gradually along the thickness direction of TMDCs and thus forms a certain direction of the conduction filament for synapse devices. It is worth noting that the devices show an excellent linear conductance of potentiation and depression with a high linearity of 0.994 (surpassing most state-of-the-art synapses), have a large number of states, and are able to fabricate synapse arrays with wafer-scale. Furthermore, the devices based on the TMDCs with the vertical composition gradient exhibit an asymmetric feature of potentiation and depression behaviors with high linearity and follow the simulated linear Leaky ReLU function, resulting in a high recognition accuracy of 94.73%, which overcomes the unreliability issue in the Sigmoid function due to the vanishing gradient phenomenon. This study not only provides a universal method to grow TMDCs with a vertical composition gradient but also contributes to exploring highly linear synapses toward neuromorphic computing.

Materials nanoarchitectonics in a two-dimensional world within a nanoscale distance from the liquid phase

Promoted understanding of nanotechnology has enabled the construction of functional materials with nanoscale-regulated structures. Accordingly, materials science requires one-step further innovation by coupling nanotechnology with the other materials sciences. As a post-nanotechnology concept, nanoarchitectonics has recently been proposed. It is a methodology to architect functional material systems using atomic, molecular, and nanomaterial unit-components. One of the attractive methodologies would be to develop nanoarchitectonics in a defined dimensional environment with certain dynamism, such as liquid interfaces. However, nanoarchitectonics at liquid interfaces has not been fully explored because of difficulties in direct observations and evaluations with high-resolutions. This unsatisfied situation in the nanoscale understanding of liquid interfaces may keep liquid interfaces as unexplored and attractive frontiers in nanotechnology and nanoarchitectonics. Research efforts related to materials nanoarchitectonics on liquid interfaces have been continuously made. As exemplified in this review paper, a wide range of materials can be organized and functionalized on liquid interfaces, including organic molecules, inorganic nanomaterials, hybrids, organic semiconductor thin films, proteins, and stem cells. Two-dimensional nanocarbon sheets have been fabricated by molecular reactions at dynamically moving interfaces, and metal-organic frameworks and covalent organic frameworks have been fabricated by specific interactions and reactions at liquid interfaces. Therefore, functions such as sensors, devices, energy-related applications, and cell control are being explored. In fact, the potential for the nanoarchitectonics of functional materials in two-dimensional nanospaces at liquid surfaces is sufficiently high. On the basis of these backgrounds, this short review article describes recent approaches to materials nanoarchitectonics in a liquid-based two-dimensional world, i.e., interfacial regions within a nanoscale distance from the liquid phase.

Reliable Memristor Based on Ultrathin Native Silicon Oxide

Memristors based on two-dimensional (2D) materials can exhibit great scalability and ultralow power consumption, yet the structural and thickness inhomogeneity of ultrathin electrolytes lowers the production yield and reliability of devices. Here, we report that the self-limiting amorphous SiO_x (∼2.7 nm) provides a perfect atomically thin electrolyte with high uniformity, featuring a record high production yield. With the guidance of physical modeling, we reveal that the atomic thickness of SiO_x enables anomalous resistive switching with a transition to an analog quasi-reset mode, where the filament stability can be further enhanced using Ag-Au nanocomposite electrodes. Such a picojoule memristor shows record low switching variabilities (C2C and D2D variation down to 1.1 and 2.6%, respectively), good retention at a few microsiemens, and high conductance-updating linearity, constituting key metrics for analog neural networks. In addition, the stable high-resistance state is found to be an excellent source for true random numbers of Gaussian distribution. This work opens up opportunities in mass production of Si-compatible memristors for ultradense neuromorphic and security hardware.

Carrier Trapping in Wrinkled 2D Monolayer MoS2 for Ultrathin Memory

Atomically thin two-dimensional (2D) semiconductors are promising for next-generation memory to meet the scaling down of semiconductor industry. However, the controllability of carrier trapping status, which is the key figure of merit for memory devices, still halts the application of 2D semiconductor-based memory. Here, we introduce a scheme for 2D material based memory using wrinkles in monolayer 2D semiconductors as controllable carrier trapping centers. Memory devices based on wrinkled monolayer MoS₂ show multilevel storage capability, an on/off ratio of 10⁶, and a retention time of >10⁴ s, as well as tunable linear and exponential behaviors at the stimulation of different gate voltages. We also reveal an interesting wrinkle-based carrier trapping mechanism by using conductive atomic force microscopy. This work offers a configuration to control carriers in ultrathin memory devices and for in-memory calculations.