State-of-the-art memristors are mostly formed by vertical metal–insulator–metal (MIM) structure, which rely on the formation of conductive filaments for resistive switching (RS). However, owing to the stochastic formation of filament, the set/reset voltage of vertical MIM memristors is difficult to control, which results in poor temporal and spatial switching uniformity. Here, a two-terminal lateral memristor based on electron-beam-irradiated rhenium disulfide (ReS2) is realized, which unveils a resistive switching mechanism based on Schottky barrier height (SBH) modulation. The devices exhibit a forming-free, stable gradual RS characteristic, and simultaneously achieve a small transition voltage variation during positive and negative sweeps (6.3%/5.3%). The RS is attributed to the motion of sulfur vacancies induced by voltage bias in the device, which modulates the ReS2/metal SBH. The gradual SBH modulation stabilizes the temporal variation in contrast to the abrupt RS in MIM-based memristors. Moreover, the emulation of long-term synaptic plasticity of biological synapses is demonstrated using the device, manifesting its potential as artificial synapse for energy-efficient neuromorphic computing applications.
requires increasing fabrication cost and is fast approaching the fundamental physical limits. At the same time, the shuttling of data between the memory unit and the processing unit is evaluated to consume most of the energy and time for a modern computer in which these two units are separated physically. [1,2] This is known as the memory wall, and thus novel technologies are required to overcome this barrier. Inspired by the information processing model of human brains, neuromorphic computing is proposed to address the issue of memory wall by computing within the memory to avoid data transfer between the memory unit and the processing unit. A neuromorphic computing system consists of electronic synapses and neurons. The electronic synapses are functional links, through which the information is transmitted from one neuron to another. To date, many emerging memory concepts are investigated to realize the electronic synapses, such as resistive random access memory (RRAM), phase change memory (PCM), and ferroelectric RAM (FeRAM). [3-6] In the past, the RRAM-based synaptic devices have been intensively studied and significant progress has been made. However, based on the mechanism of conductive filament formation/rupture (set/reset process) the filamentary RRAM suffers a significant drawback of high cycle-to-cycle and cell-to-cell variation. [7] Although some technologies are proposed to address this issue, extra delicate fabrication process is required and thus hinders the practical applications. [8-10] The phase change of PCM is realized by Joule heating and therefore the issues about heat dissipation and power consumption have to be addressed. To realize a resistive change via ferroelectric switching, ferroelectric field-effect transistor (FeFET) is proposed by replacing the oxide layer in an FET with ferroelectric materials. [11,12] The ferroelectric switching causes the hysteresis in a FeFET, thus exhibiting two resistive states. In addition, the ferroelectric tunneling junction and ferroelectric diode are also studied, in which the resistive change is achieved by the polarization-modulation Schottky-like barriers. [13-15] But these devices are mainly based on conventional ferroelectric materials such as BiFeO 3 , Pr (Zr, Ti)O 3 , BaTiO 3 , and poly(vinylidene fluoridetrifluoroethylene). Recently, 2D materials have attracted great attention due to their unique mechanical, electrical, optical, and thermal properties. However, 2D ferroelectric materials are rarely reported primarily because the increasing depolarization field with decreasing thickness poses fundamental Memristors with biological synaptic behaviors and functions have been intensively studied as an important component for neuromorphic computing system, which hold promise to address the power consumption issue in modern computers based on von Neumann architecture. However, the resistive switching mechanism that relies on the stochastic formation of conductive filaments leads to poor cycle-to-cycle (temporal) and cell-to-cell (spatial) variations for ...
Neuromorphic computing on the hardware level is promising for performing ever‐increasing data‐centric tasks owing to its superiority to conventional von Neumann architecture in terms of energy efficiency and learning ability. One key aspect to its implementation is the development of artificial synapses that can effectively emulate the multiple functionalities exhibited by their biological counterparts. Here, building on an inorganic ferroelectric gate stack integrated with a 2D layered semiconductor (WS2), a new type of ferroelectricity‐based synaptic transistor that differs from those relying on interface traps or floating gate configuration is reported. By virtue of a 6 nm thick ferroelectric hafnium zirconium oxide by atomic layer deposition and postannealing treatment, the device shows a channel resistance change ratio above 105 corresponding to opposite ferroelectric polarization direction. Furthermore, by applying electrical stimulus to the gate, it demonstrates good capability to mimic various synaptic behaviors including long‐term potentiation, long‐term depression, spike‐amplitude‐dependent plasticity, and spike‐rate‐dependent plasticity. Given the inherent compatibility of the ferroelectric gate stack with existing fabrication technology, and the reliability of ferroelectricity engineering, this work paves the way toward practical implementation of synaptic devices in neuromorphic circuits.
Water and sediment are two of the most essential elements in estuaries. Their product, suspended sediment concentration (SSC), is involved in hydrology, geomorphology and ecology. This study was focused on the spatial and temporal variations of SSC in the Yangtze Estuary under new situations after the closure of ~50,000 dams in the Yangtze basin, including the Three Gorges Dam (TGD) in 2003. It was found that the SSC first exhibited an increasing and then a decreasing trend longitudinally from Xuliujing Station to the outer estuary with the Turbidity Maximum Zone located in the mouth bar area. Vertically, the SSC in the bottom layers averaged 0.96 kg/m3, about 2.4 times larger than the surface layers (0.40 kg/m3). During spring tides, the SSCs were always higher than those in neap tides, which was fit for the cognition law. As for the seasonal variations in the North Branch and mouth bar area, the SSCs in the dry season were higher than those in the flood season, while in the upper reach of the South Branch and outer estuary, the seasonal variation of SSCs reversed. This phenomenon primarily reflected the competition of riverine sediment flux and local resuspended sediment flux by wind-induced waves. As for the interannual changes, the SSCs demonstrated overall fluctuant downward trends, determined by riverine sediment flux and influenced by waves. This study revealed the new situation of SSC and can be a reference for other related researches in the Yangtze Estuary.
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