Baoshan Tang

Memristors offer a promising solution to address the performance and energy challenges faced by conventional von Neumann computer systems. Yet, stochastic ion migration in conductive filament often leads to an undesired performance tradeoff between memory window, retention, and endurance. Herein, a robust memristor based on oxygen‐rich SnO2 nanoflowers switching medium, enabled by seed‐mediated wet chemistry, to overcome the ion migration issue for enhanced analog in‐memory computing is reported. Notably, the interplay between the oxygen vacancy (Vo) and Ag ions (Ag⁺) in the Ag/SnO₂/p⁺⁺‐Si memristor can efficiently modulate the formation and abruption of conductive filaments, thereby resulting in a high on/off ratio (>106), long memory retention (10‐year extrapolation), and low switching variability (SV = 6.85%). Multiple synaptic functions, such as paired‐pulse facilitation, long‐term potentiation/depression, and spike‐time dependent plasticity, are demonstrated. Finally, facilitated by the symmetric analog weight updating and multiple conductance states, a high image recognition accuracy of ≥ 91.39% is achieved, substantiating its feasibility for analog in‐memory computing. This study highlights the significance of synergistically modulating conductive filaments in optimizing performance trade‐offs, balancing memory window, retention, and endurance, which demonstrates techniques for regulating ion migration, rendering them a promising approach for enabling cutting‐edge neuromorphic applications.

Realization of high-density and reliable resistive random access memories based on two-dimensional semiconductors is crucial toward their development in next-generation information storage and neuromorphic computing. Here, wafer-scale integration of solution-processed two-dimensional MoS₂ memristor arrays are reported. The MoS₂ memristors achieve excellent endurance, long memory retention, low device variations, and high analog on/off ratio with linear conductance update characteristics. The two-dimensional nanosheets appear to enable a unique way to modulate switching characteristics through the inter-flake sulfur vacancies diffusion, which can be controlled by the flake size distribution. Furthermore, the MNIST handwritten digits recognition shows that the MoS₂ memristors can operate with a high accuracy of >98.02%, which demonstrates its feasibility for future analog memory applications. Finally, a monolithic three-dimensional memory cube has been demonstrated by stacking the two-dimensional MoS₂ layers, paving the way for the implementation of two memristor into high-density neuromorphic computing system.

The performances of percolating thin-film photodetectors fabricated from liquid-exfoliated 2D materials such as MoS₂ and WS₂ are inferior compared to their single-crystalline counterparts due to the low-mobility arising from edge defects and inter-nanosheet resistance. Moreover, the mechanism controlling the photoresponse time is not well understood. In this study, we demonstrated better control of the photoresponse time via the size selection of the liquid-exfoliated nanosheets via cascade centrifugation. We discovered that a faster photoresponse was observed when using a large average nanosheet size, while a much slower response was observed when using small nanosheets, giving rise to the linear component of the photoresponse in addition to the exponential component. Furthermore, we discovered that mixing a controlled proportion of WS₂ and graphene nanosheets exactly at the percolation threshold results in a significantly increased photocurrent, up to 40 times higher compared to the pure WS₂ photodetector, due to good interfacial charge transfer between WS₂ and graphene, reaching a responsivity of 1.15 A W⁻¹ under blue light. Above the percolation threshold, the photocurrent vanishes due to increased dark current noise. This strategy of nanosheet size-selection and controlled mixing with graphene opens up the possibility for 2D material photodetectors fabricated via liquid-exfoliation to be more competitive with their single-crystalline counterparts. We believe that this approach can be applied to other emerging 2D materials, such as phosphorene, MXene, and graphitic carbon nitride.

3D monolithic integration of logic and memory has been the most sought after solution to surpass the Von Neumann bottleneck, for which a low-temperature processed material system becomes inevitable. Two-dimensional materials, with their excellent electrical properties and low thermal budget are potential candidates. Here, we demonstrate a low-temperature hybrid co-integration of one-transistor-one-resistor memory cell, comprising a surface functionalized 2D WSe₂p-FET, with a solution-processed WSe₂ Resistive Random Access Memory. The employed plasma oxidation technique results in a low Schottky barrier height of 25 meV with a mobility of 230 cm² V⁻¹ s⁻¹, leading to a 100x performance enhanced WSe₂p-FET, while the defective WSe₂ Resistive Random Access Memory exhibits a switching energy of 2.6 pJ per bit. Furthermore, guided by our device-circuit modelling, we propose vertically stacked channel FETs for high-density sub-0.01 μm² memory cells, offering a new beyond-Si solution to enable 3-D embedded memories for future computing systems.

The rational design of novel hierarchical MoS₂/CoS₂ heterogeneous nanotube arrays as self-supported and pH-universal electrocatalysts for efficient HER.