Abstract Large-area monolayer WS 2 is a desirable material for applications in next-generation electronics and optoelectronics. However, the chemical vapour deposition (CVD) with rigid and inert substrates for large-area sample growth suffers from a non-uniform number of layers, small domain size and many defects, and is not compatible with the fabrication process of flexible devices. Here we report the self-limited catalytic surface growth of uniform monolayer WS 2 single crystals of millimetre size and large-area films by ambient-pressure CVD on Au. The weak interaction between the WS 2 and Au enables the intact transfer of the monolayers to arbitrary substrates using the electrochemical bubbling method without sacrificing Au. The WS 2 shows high crystal quality and optical and electrical properties comparable or superior to mechanically exfoliated samples. We also demonstrate the roll-to-roll/bubbling production of large-area flexible films of uniform monolayer, double-layer WS 2 and WS 2 /graphene heterostructures, and batch fabrication of large-area flexible monolayer WS 2 film transistor arrays.
Mechanosensitivity is one of the essential functionalities of biological ion channels. Synthesizing an artificial nanofluidic system to mimic such sensations will not only improve our understanding of these fluidic systems but also inspire applications. In contrast to the electrohydrodynamic ion transport in long nanoslits and nanotubes, coupling hydrodynamical and ion transport at the single-atom thickness remains challenging. Here, we report the pressure-modulated ion conduction in graphene nanopores featuring nonlinear electrohydrodynamic coupling. Increase of ionic conductance, ranging from a few percent to 204.5% induced by the pressure—an effect that was not predicted by the classical linear coupling of molecular streaming to voltage-driven ion transport—was observed experimentally. Computational and theoretical studies reveal that the pressure sensitivity of graphene nanopores arises from the transport of capacitively accumulated ions near the graphene surface. Our findings may help understand the electrohydrodynamic ion transport in nanopores and offer a new ion transport controlling methodology.
Hot-carrier transistors are a class of devices that leverage the excess kinetic energy of carriers. Unlike regular transistors, which rely on steady-state carrier transport, hot-carrier transistors modulate carriers to high-energy states, resulting in enhanced device speed and functionality. These characteristics are essential for applications that demand rapid switching and high-frequency operations, such as advanced telecommunications and cutting-edge computing technologies
Machine learning is the core of artificial intelligence. Using optical signals for training and converting them into electrical signals for inference, combines the strengths of both, and thus can greatly improve machine learning efficiency. Optoelectronic memories are the hardware foundation for this strategy. However, the existing optoelectronic memories cannot modulate a large number of non-volatile resistive states using ultra-short and ultra-dim light pulses, leading to low training accuracy, slow computing speed and high energy consumption. Here, we synthesized a van der Waals layered photoconductive material, (NH4)BiI3, with excellent photoconductivity and strong dielectric screening effect. We further employed it as the photosensitive control gate in a floating-gate transistor, replacing the commonly used metal control gate, to construct an optical floating gate transistor which achieves adjustable synaptic weights under ultra-dim light without gate voltage assistance. Moreover, it shows ultra-low training energy consumption to generate a non-volatile state and the largest resistive state numbers among the known non-volatile optoelectronic memories. These exceptional performances enable the construction of one-transistor-one-memory device arrays to achieve ~99% accuracy in Artificial Neural Networks. Moreover, the device arrays can match the performance of GPU in YOLOv8 while greatly reducing energy consumption. The authors synthesise a Bi-based halide and use it as a photosensitive control gate in a floating-gate transistor, enabling a non-volatile optoelectronic memory with ultra-low energy consumption and large resistive state numbers, for high-accuracy machine learning.
Significance Although graphene shows great promise as a generational flexible transparent electrode (FTE), its development has been severely limited by the intrinsic trade-off between electrical conductance and transparency with the performance metrics inferior to that of the state-of-the-art ITO electrodes. We report a straightforward approach to break previous limit in graphene FTEs and yield an unprecedented performance that rivals the best commercial ITO electrode. Using the tailored monolayer graphene FTE, we further demonstrate high-performance flexible green organic light-emitting diodes (OLEDs) with the efficiencies outperforming all comparable flexible OLEDs and surpassing that with rigid ITO anode. This simple strategy will boost the development of next-generation flexible optoelectronics beyond the dominant rigid platforms.
Ambient solution-processed conductive materials with a sufficient low work function are essential to facilitate electron injection in electronic and optoelectronic devices but are challenging. Here, we design an electrically conducting and ambient-stable polymer electrolyte with an ultralow work function down to 2.2 eV, which arises from heavy n-doping of dissolved salts to polymer matrix. Such materials can be solution processed into uniform and smooth films on various conductors including graphene, conductive metal oxides, conducting polymers and metals to substantially improve their electron injection, enabling high-performance blue light-emitting diodes and transparent light-emitting diodes. This work provides a universal strategy to design a wide range of stable charge injection materials with tunable work function. As an example, we also synthesize a high-work-function polymer electrolyte material for high-performance solar cells.
Natural few-layer graphene is unambiguously identified from the Chang'e-5 lunar soil samples, which serves as a new platform for investigating extraterrestrial bodies.
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