Monolayer molybdenum disulfide has been previously discovered to exhibit non-volatile resistive switching behavior in a vertical metal-insulator-metal structure, featuring ultra-thin sub-nanometer active layer thickness. However, the reliability of these nascent 2D-based memory devices was not previously investigated for practical applications. Here, we employ an electron irradiation treatment on monolayer MoS2 film to modify the defect properties. Raman, photoluminescence, and X-ray photoelectron spectroscopy measurements have been performed to confirm the increasing amount of sulfur vacancies introduced by the e-beam irradiation process. The statistical electrical studies reveal the reliability can be improved by up to 1.5× for yield and 11× for average DC cycling endurance in the devices with a moderate radiation dose compared to unirradiated devices. Based on our previously proposed virtual conductive-point model with the metal ion substitution into sulfur vacancy, Monte Carlo simulations have been performed to illustrate the irradiation effect on device reliability, elucidating a clustering failure mechanism. This work provides an approach by electron irradiation to enhance the reliability of 2D memory devices and inspires further research in defect engineering to precisely control the switching properties for a wide range of applications from memory computing to radio-frequency switches.

Abstract2D memristors have demonstrated attractive resistive switching characteristics recently but also suffer from the reliability issue, which limits practical applications. Previous efforts on 2D memristors have primarily focused on exploring new material systems, while damage from the metallization step remains a practical concern for the reliability of 2D memristors. Here, the impact of metallization conditions and the thickness of MoS2 films on the reliability and other device metrics of MoS2‐based memristors is carefully studied. The statistical electrical measurements show that the reliability can be improved to 92% for yield and improved by ≈16× for average DC cycling endurance in the devices by reducing the top electrode (TE) deposition rate and increasing the thickness of MoS2 films. Intriguing convergence of switching voltages and resistance ratio is revealed by the statistical analysis of experimental switching cycles. An “effective switching layer” model compatible with both monolayer and few‐layer MoS2, is proposed to understand the reliability improvement related to the optimization of fabrication configuration and the convergence of switching metrics. The Monte Carlo simulations help illustrate the underlying physics of endurance failure associated with cluster formation and provide additional insight into endurance improvement with device fabrication optimization.

in scaling-down, in-memory computing as an emerging alternative of traditional von Neumann architecture has attracted extensive research interest, which requires fast and scalable memory devices such as Resistive Random-Access Memory (RRAM), also known as memristors, Phase-Change Memory (PCM), and Magnetoresistive Random-Access Memory (MRAM). [2] Meanwhile, 2D materials have been widely studied, and several applications such as transistors, [3][4][5] flexible electronics, [6,7] photodetectors, [8,9] and more recently, memristors devices, [10][11][12][13][14][15] have been demonstrated. Due to the unique properties of 2D materials, memristors based on 2D materials have shown outstanding electrical properties, including high on-off ratio, low switching thresholds (≈100 mV), fast switching speed, ultra-low power consumption (fJ per switching), and THz operation. [14][15][16][17][18] The emerging applications of 2D materials demand new synthesis and integration processes. Furthermore, to achieve commercial applications, much effort has been devoted to the large-area synthesis [19][20][21] and patterning [22][23][24] of 2D materials to ensure the transition of these unique materials from the laboratory to industrial manufacturing. However, most reported studies rely on conventional CVD synthesis, [25] and MOCVD, [26,27] which are mostly relatively high-temperature processes. Due to the dissimilarity of synthesis equipment and complexity of synthesis procedures, a standard and simple process applicable for the industrial manufacturing of wafer-scale 2D materials remains a challenge. As an alternative to conventional CVD, studies have shown that sulfurization of thin metallic films can result in the large-scale synthesis of MoS 2 and WS 2 . One of the advantages of sulfurization processes, compared to the conventional CVD method, is large area coverage and uniformity of the as-grown film, due to simultaneously sulfurization over the entire substrate. Recent works have demonstrated synthesis of MoS 2 with vertically aligned layers, [28] sulfurization for horizontally layered MoS 2 with the high-temperature process (above 700 °C), [29,30] and relatively long sulfurization times (more than 1 h). [31] For this reason, one of the main challenges in sulfurization processes is to use temperatures below 700 °C while achieving horizontally layered films in short processing times. This work successfully demonstrates a simple method to synthesize MoS 2 and WS 2 films via one-step low-temperature sulfurization. The 2D materials have been of considerable interest as new materials for device applications. Non-volatile resistive switching applications of MoS 2 and WS 2 have been previously demonstrated; however, these applications are dramatically limited by high temperatures and extended times needed for the large-area synthesis of 2D materials on crystalline substrates. The experimental results demonstrate a one-step sulfurization method to synthesize MoS 2 and WS 2 at 550 °C in 15 min on sapphire wafers. Furthermore, a large area t...

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Resistive random-access memory (RRAM) devices have drawn increasing interest for the simplicity of its structure, low power consumption and applicability to neuromorphic computing. By combining analog computing and data storage at the device level, neuromorphic computing system has the potential to meet the demand of computing power in applications such as artificial intelligence (AI), machine learning (ML) and Internet of Things (IoT). Monolayer rhenium diselenide (ReSe2), as a two-dimensional (2D) material, has been reported to exhibit non-volatile resistive switching (NVRS) behavior in RRAM devices with sub-nanometer active layer thickness. In this paper, we demonstrate stable multiple-step RESET in ReSe2 RRAM devices by applying different levels of DC electrical bias. Pulse measurement has been conducted to study the neuromorphic characteristics. Under different height of stimuli, the ReSe2 RRAM devices have been found to switch to different resistance states, which shows the potentiation of synaptic applications. Long-term potentiation (LTP) and depression (LTD) have been demonstrated with the gradual resistance switching behaviors observed in long-term plasticity programming. A Verilog-A model is proposed based on the multiple-step resistive switching behavior. By implementing the LTP/LTD parameters, an artificial neural network (ANN) is constructed for the demonstration of handwriting classification using Modified National Institute of Standards and Technology (MNIST) dataset.