Despite 55 years of efforts into short gate length transistors following the Moore's law, the gate length below 1 nm has not been realized. Here, we demonstrated a side-wall monolayer MoS 2 transistors with ultimate 0.34 nm gate length using the edge of graphene as gate electrode. Moreover, large area of chemical vapor deposition graphene and MoS 2 are used for 2-inch wafer production. These ultrashort devices show excellent ON/OFF current ratio of 2 × 10 5 . Simulation results indicate that the MoS 2 sidewall effective channel length approaches 0.34 nm in the ON state. This graphene edge gate combined with MoS 2 vertical channel structure provides an e cient gate control ability and enables the physical gate length scaling down to atomic level, which shows great potential to build next generation electronics.

We report an artificial eardrum using an acoustic sensor based on two-dimensional MXene (Ti 3 C 2 T x ), which mimics the function of a human eardrum for realizing voice detection and recognition. Using MXene with a large interlayer distance and micropyramid polydimethylsiloxane arrays can enable a two-stage amplification of pressure and acoustic sensing. The MXene artificial eardrum shows an extremely high sensitivity of 62 kPa −1 and a very low detection limit of 0.1 Pa. Notably, benefiting from the ultrasensitive MXene eardrum, the machine-learning algorithm for real-time voice classification can be realized with high accuracy. The 280 voice signals are successfully classified for seven categories, and a high accuracy of 96.4 and 95% can be achieved by the training dataset and the test dataset, respectively. The current results indicate that the MXene artificial intelligent eardrum shows great potential for applications in wearable acoustical health care devices.

Thermoacoustic (TA) effect has been discovered for more than 130 years. However, limited by the material characteristics, the performance of a TA sound source could not be compared with magnetoelectric and piezoelectric loudspeakers. Recently, graphene, a two-dimensional material with the lowest heat capacity per unit area, was discovered to have a good TA performance. Compared with a traditional sound source, graphene TA sound sources (GTASSs) have many advantages, such as small volume, no diaphragm vibration, wide frequency range, high transparency, good flexibility, and high sound pressure level (SPL). Therefore, graphene has a great potential as a next-generation sound source. Photoacoustic (PA) imaging can also be applied to the diagnosis and treatment of diseases using the photothermo-acoustic (PTA) effect. Therefore, in this review, we will introduce the history of TA devices. Then, the theory and simulation model of TA will be analyzed in detail. After that, we will talk about the graphene synthesis method. To improve the performance of GTASSs, many strategies such as lowering the thickness and using porous or suspended structures will be introduced. With a good PTA effect and large specific area, graphene PA imaging and drug delivery is a promising prospect in cancer treatment. Finally, the challenges and prospects of GTASSs will be discussed.

Two-dimensional (2D) heterostructures show great potential in achieving negative differential resistance (NDR) effects by Esaki diodes and or resonant tunneling diodes. However, most of the reported Esaki diode-based NDR devices realized by bulk 2D films lack sufficient gate tunability, and the tuning of NDR behavior from appearing to vanishing remains elusive. Here, a gate-tunable NDR device is reported based on a vertically stacked black phosphorus (BP) and molybdenum disulfide (MoS2) thin 2D heterojunction. At room temperature, a rectifying ratio of ∼6 orders of magnitude from a reverse rectifying diode to a forward rectifying diode by gate modulation is obtained. Through analyzing the temperature-dependent electrical properties, the tunneling mechanism at a certain gate voltage range is revealed. Moreover, the switchable and continuously gate-tunable NDR behavior is realized with a maximum peak-to-valley ratio of 1.23 at 77 K, as shown in the I DS mappings by sweeping V DS under different V GS. In addition, a compact model for gate-tunable NDR behavior in 2D heterostructures is proposed. To our best knowledge, this is the first demonstration of NDR behavior in BP-MoS2 heterostructures. Consequently, this work sheds light on the gate-tunable NDR devices and reconfigurable logic devices for realizing ternary and reconfigurable logic systems.

The channel/gate length of transistors is getting close to the physical limit. [1] To meet the requirements of chip performance, advanced design technologies are utilized to bring higher Transistors are getting close to their physical limitation, and complex chip design technologies have made the hotspot problem more serious. Graphene and hBN, as representative 2D semi-metal and dielectric materials, possess excellent thermal conductivities. Intrinsic 2D materials, 2D film materials, and 2D composite materials have been investigated, showing great potential for next-generation thermal-management materials. There are products that have already been commercialized based on graphene and hBN, but many companies seem to be sitting on the fence, and the obstacles toward implementation of these materials need to be specified. Here, high thermal conductivity 2D materials from theory and engineering to applications are reviewed, aiming to provide a comprehensive summary of the current state of the art of this field in order to give an overview and future prospects in application, manufacturing, and commercialization. From the theoretical perspective, the impact factors and development path of 2D materials for thermal dissipation and the engineering aspect of structural design are presented. The prospects and challenges are also tackled, expressing an objective view about future opportunities to build 2D-based heat-dissipation systems.

Biological synapses are the operational connection of the neurons for signal transmission in neuromorphic networks and hardware implementation combined with electrospun 1D nanofibers have realized its functionality for complicated computing tasks in basic three‐terminal field‐effect transistors with gate‐controlled channel conductance. However, it still lacks the fundamental understanding that how the technological parameters influence the signal intensity of the information processing in the neural systems for the nanofiber‐based synaptic transistors. Here, by tuning the electrospinning parameters and introducing the channel surface doping, an electrospun ZnO nanofiber‐based transistor with tunable plasticity is presented to emulate the changing synaptic functions. The underlying mechanism of influence of carrier concentration and mobility on the device's electrical and synaptic performance is revealed as well. Short‐term plasticity behaviors including paired‐pulse facilitation, spike duration‐dependent plasticity, and dynamic filtering are tuned in this fiber‐based device. Furthermore, Perovskite‐doped devices with ultralow energy consumption down to ≈0.2554 fJ and their handwritten recognition application show the great potential of synaptic transistors based on a 1D nanostructure active layer for building next‐generation neuromorphic networks.

Electrospun nanofibers have become the most promising building blocks for future high-performance electronic devices because of the advantages of larger specific surface area, higher porosity, more flexibility, and stronger mechanical strength over conventional film-based materials. Moreover, along with the properties of ease of fabrication and cost-effectiveness, a broad range of applications based on nanomaterials by electrospinning have sprung up. In this review, we aim to summarize basic principles, influence factors, and advanced methods of electrospinning to produce hundreds of nanofibers with different structures and arrangements. In addition, electrospun nanofiber based electronics composed of both two-terminal and three-terminal devices and their practical applications are discussed in the fields of sensing, storage, and computing, which give rise to the further integration to realize a comprehensive and brain-like system. Last but not least, the emulation of biological synapses through artificial synaptic transistors and additionally optoelectronics in recent years are included as an important step toward the construction of large-scale, multifunctional systems.

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