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Abstract Nonlinear optical responses in two-dimensional (2D) materials can build free-space optical neuromorphic computing systems. Ensuring the high performance and the tunability of the system is essential to encode diverse functions. However, common strategies, including the integration of external electrode arrays or photonic structures with 2D materials, and barely patterned 2D materials, exhibit a contradiction between performance and tunability. Because the unique band dispersions of 2D materials can provide hidden paths to boost nonlinear responses independently, here we introduced a new free-space optical computing concept within a bare molybdenum disulfide array. This system can preserve high modulation performance with fast speed, low energy consumption, and high signal-to-noise ratio. Due to the freedom from the restrictions of fixed photonic structures, the tunability is also enhanced through the synergistic encodings of the 2D cells and the excitation pulses. The computing mechanism of transition from two-photon absorption to synergistic excited states absorption intrinsically improved the modulation capability of nonlinear optical responses, revealed from the relative transmittance modulated by a pump-probe-control strategy. Optical artificial neural network (ANN) and digital processing were demonstrated, revealing the feasibility of the free-space optical computing based on bare 2D materials toward neuromorphic applications.

Abstract Artificial visual system empowered by 2D materials-based hardware simulates the functionalities of the human visual system, leading the forefront of artificial intelligence vision. However, retina-mimicked hardware that has not yet fully emulated the neural circuits of visual pathways is restricted from realizing more complex and special functions. In this work, we proposed a human visual pathway-replicated hardware that consists of crossbar arrays with split floating gate 2D tungsten diselenide (WSe2) unit devices that simulate the retina and visual cortex, and related connective peripheral circuits that replicate connectomics between the retina and visual cortex. This hardware experimentally displays advanced multi-functions of red–green color-blindness processing, low-power shape recognition, and self-driven motion tracking, promoting the development of machine vision, driverless technology, brain–computer interfaces, and intelligent robotics.

Abstract Constructing crossmodal in-sensor processing system based on high-performance flexible devices is of great significance for the development of wearable human-machine interfaces. A bio-inspired crossmodal in-sensor computing system can perform real-time energy-efficient processing of multimodal signals, alleviating data conversion and transmission between different modules in conventional chips. Here, we report a bio-inspired crossmodal spiking sensory neuron (CSSN) based on a flexible VO2 memristor, and demonstrate a crossmodal in-sensor encoding and computing system for wearable human-machine interfaces. We demonstrate excellent performance in the VO2 memristor including endurance (>1012), uniformity (0.72% for cycle-to-cycle variations and 3.73% for device-to-device variations), speed (

Abstract Arsenic is an essential dopant in conventional silicon-based semiconductors and emerging phase-change memory (PCM), yet the detailed functional mechanism is still lacking in the latter. Here, we fabricate chalcogenide-based ovonic threshold switching (OTS) selectors, which are key units for suppressing sneak currents in 3D PCM arrays, with various As concentrations. We discovered that incorporation of As into GeS brings >100 °C increase in crystallization temperature, remarkably improving the switching repeatability and prolonging the device lifetime. These benefits arise from strengthened As-S bonds and sluggish atomic migration after As incorporation, which reduces the leakage current by more than an order of magnitude and significantly suppresses the operational voltage drift, ultimately enabling a back-end-of-line-compatible OTS selector with >12 MA/cm2 on-current, ~10 ns speed, and a lifetime approaching 1010 cycles after 450 °C annealing. These findings allow the precise performance control of GeSAs-based OTS materials for high-density 3D PCM applications.

Abstract As the prevailing non-volatile memory (NVM), flash memory offers mass data storage at high integration density and low cost. However, due to the ‘speed-retention-endurance’ dilemma, their typical speed is limited to ~microseconds to milliseconds for program and erase operations, restricting their application in scenarios with high-speed data throughput. Here, by adopting metallic 1T-LixMoS2 as edge contact, we show that ultrafast (10–100 ns) and robust (endurance>106 cycles, retention>10 years) memory operation can be simultaneously achieved in a two-dimensional van der Waals heterostructure flash memory with 2H-MoS2 as semiconductor channel. We attribute the superior performance to the gate tunable Schottky barrier at the edge contact, which can facilitate hot carrier injection to the semiconductor channel and subsequent tunneling when compared to a conventional top contact with high density of defects at the metal interface. Our results suggest that contact engineering can become a strategy to further improve the performance of 2D flash memory devices and meet the increasing demands of high speed and reliable data storage.

Abstract The exchange bias (EB) effect plays an undisputed role in the development of highly sensitive, robust, and high-density spintronic devices in magnetic data storage. However, the weak EB field, low blocking temperature, as well as the lack of modulation methods, seriously limit the application of EB in van der Waals (vdW) spintronic devices. Here, we utilized pressure engineering to tune the vdW spacing of the two-dimensional (2D) FePSe3/Fe3GeTe2 heterostructures. The EB field (H EB, from 29.2 mT to 111.2 mT) and blocking temperature (T b, from 20 K to 110 K) are significantly enhanced, and a highly sensitive and robust spin valve is demonstrated. Interestingly, this enhancement of the EB effect was extended to exposed Fe3GeTe2, due to the single-domain nature of Fe3GeTe2. Our findings provide opportunities for the producing, exploring, and tuning of magnetic vdW heterostructures with strong interlayer coupling, thereby enabling customized 2D spintronic devices in the future.

Understanding the mechanism of the formation and rupture of conductive filaments in HfO2-based memristors is essential to solve the problem of scalability of the devices. Here, Zhang et al. visualize this process by tracking atomic-scale evolution of conductive filaments during resistive switching cycles.

Hexagonal boron nitride (hBN) is a two-dimensional material with wide band gap and high thermal and chemical stability. Here the authors demonstrate the formation and trapping of hydrogen gas bubbles in hBN interlayers upon plasma treatment, promising for extracting and storing hydrogen.