Memristor, based on the principle of biological synapse, is recognized as one of the key devices in confronting the bottleneck of classical von Neumann computers. However, conventional memristors are difficult to continuously adjust the conduction and dutifully mimic the biosynapse function. Here, TiO 2 films with self-assembled Ag nanoclusters implemented by gradient Ag dopant are employed to achieve enhanced memristor performance. The memristors exhibit gradual both potentiating and depressing conduction under positive and negative pulse trains, which can fully emulate excitation and inhibition of biosynapse. Moreover, comprehensive biosynaptic functions and plasticity, including the transition from short-term memory to long-term memory, long-term potentiation and depression, spike-timingdependent plasticity, and paired-pulse facilitation, are implemented with the fabricated memristors in this work. The applied pulses with a width of hundreds of nanoseconds timescale are beneficial to realize fast learning and computing. High-resolution transmission electron microscopy observations clearly demonstrate that Ag clusters redistribute to form Ag conductive filaments between Ag and Pt electrode under electrical field at ON-state device. The experimental data confirm that the oxides doped with Ag clusters have the potential for mimicking biosynaptic behavior, which is essential for the further creation of artificial neural systems.

Memristors with nonvolatile memory characteristics have been expected to open a new era for neuromorphic computing and digital logic. However, existing memristor devices based on oxygen vacancy or metal‐ion conductive filament mechanisms generally have large operating currents, which are difficult to meet low‐power consumption requirements. Therefore, it is very necessary to develop new materials to realize memristor devices that are different from the mechanisms of oxygen vacancy or metal‐ion conductive filaments to realize low‐power operation. Herein, high‐performance and low‐power consumption memristors based on 2D WS2 with 2H phase are demonstrated, which show fast ON (OFF) switching times of 13 ns (14 ns), low program current of 1 µA in the ON state, and SET (RESET) energy reaching the level of femtojoules. Moreover, the memristor can mimic basic biological synaptic functions. Importantly, it is proposed that the generation of sulfur and tungsten vacancies and electron hopping between vacancies are dominantly responsible for the resistance switching performance. Density functional theory calculations show that the defect states formed by sulfur and tungsten vacancies are at deep levels, which prevent charge leakage and facilitate the realization of low‐power consumption for neuromorphic computing application.

Resistive switching (RS) is a promising emerging storage technology that has received much attention due to its many advantages, such as economy, fast operating speed, long retention, high density, and low energy consumption. [1] RS effects are widely applied in the fields of nonvolatile RS random access memory (RRAM), artificial neural computing, and reconfigurable logic operations and so on. [2] RRAM memories based on electrochemical metallization (ECM) and valance change mechanism (VCM) are commonly used for the memristor application. [3] Compared with conventional computing based on the von Neumann architecture, memristor (i.e., RS device) computing is proving to be superior for brain-inspired computing, such as image processing and speech recognition, [2] where the diffusion of the metal ions such as Ag + , Cu + , or oxygen vacancies are used to mimic the diffusion of Ca + in the neural cell. [4] However, the switching voltages in the memristor devices (MDs) showWith the advent of the era of big data, resistive random access memory (RRAM) has become one of the most promising nanoscale memristor devices (MDs) for storing huge amounts of information. However, the switching voltage of the RRAM MDs shows a very broad distribution due to the random formation of the conductive filaments. Here, selfassembled lead sulfide (PbS) quantum dots (QDs) are used to improve the uniformity of switching parameters of RRAM, which is very simple comparing with other methods. The resistive switching (RS) properties of the MD with the self-assembled PbS QDs exhibit better performance than those of MDs with pure-Ga 2 O 3 and randomly distributed PbS QDs, such as a reduced threshold voltage, uniformly distributed SET and RESET voltages, robust retention, fast response time, and low power consumption. This enhanced performance may be attributed to the ordered arrangement of the PbS QDs in the self-assembled PbS QDs which can efficiently guide the growth direction for the conducting filaments. Moreover, biosynaptic functions and plasticity, are implemented successfully in the MD with the self-assembled PbS QDs. This work offers a new method of improving memristor performance, which can significantly expand existing applications and facilitate the development of artificial neural systems. Data Storage

Extensive efforts have been devoted to construct a fiber-shaped energystorage device to fulfill the increasing demand for power consumption of textile-based wearable electronics. Despite the myriad of available material selections and device architectures, it is still fundamentally challenging to develop eco-friendly fiber-shaped aqueous rechargeable batteries (FARBs) on a single-fiber architecture with high energy density and long-term stability. Here, we demonstrate flexible and high-voltage coaxialfiber aqueous rechargeable zinc-ion batteries (CARZIBs). By utilizing a novel spherical zinc hexacyanoferrate with prominent electrochemical performance as cathode material, the assembled CARZIB offers a large capacity of 100.2 mAh cm −3 and a high energy density of 195.39 mWh cm −3 , outperforming the state-of-the-art FARBs. Moreover, the resulting CARZIB delivers outstanding flexibility with the capacity retention of 93.2% after bending 3000 times. Last, high operating voltage and output current are achieved by the serial and parallel connection of CARZIBs woven into the flexible textile to power high-energy-consuming devices. Thus, this work provides proof-of-concept design for next-generation wearable energy-storage devices.

As the genomic basis for Down syndrome (DS), human trisomy 21 is the most common genetic cause of intellectual disability in children and young people. The genomic regions on human chromosome 21 (Hsa21) are syntenic to three regions in the mouse genome, located on mouse chromosome 10 (Mmu10), Mmu16 and Mmu17. Recently, we have developed three new mouse models using chromosome engineering carrying the genotypes of Dp(10)1Yey/+, Dp(16)1Yey/+, or Dp(17)1Yey/+, which harbor a duplication spanning the entire Hsa21 syntenic region on Mmu10, Mmu16, or Mmu17, respectively. In this study, we analyzed the hippocampal long-term potentiation (LTP) and cognitive behaviors of these models. Our results show that, while the genotype of Dp (17)1Yey/+ results in abnormal hippocampal LTP, the genotype of Dp(16)1Yey/+ leads to both abnormal hippocampal LTP and impaired learning/memory. Therefore, these mutant mice can serve as powerful tools for further understanding the mechanism underlying cognitively relevant phenotypes associated with DS, particularly the impacts of different syntenic regions on these phenotypes.