Short-term plasticity and long-term plasticity of bio-synapse are thought to underpin critical physiological functions in neural circuits. In this letter, we vividly emulated the short-term and ...long-term synaptic functions in a single Cu/a-Si/Pt memristor. By controlling the injection quantity of Cu cations into the a-Si layer, the device showed volatile and non-volatile resistive switching behaviors. Owing to the unique characteristics of Cu/a-Si/Pt device, the short-term synaptic functions, i.e., short-term potentiation, pair-pulse facilitation, and long-term functions, i.e., long-term potentiation/depression, spike-timing-dependent plasticity, were mimicked in the memristor successfully. Furthermore, the transition from short-term memory to long-term memory of the device was also observed under repeated stimuli. The experimental results confirm that the Cu/a-Si/Pt memristor with various synaptic behaviors has a potential application in the brain-inspired computing systems.
The electronic synapse, which can vividly emulate short-term and long-term plasticity, as well as voltage sensitivity, in the bio-synapse, is the vital device foundation for brain-inspired ...neuromorphic computing. In this letter, we propose a Ag/GeSe/TiN memristor as an electronic synapse for brain-inspired neuromorphic applications. Due to the electromigration and diffusion of Ag cation, the volatile and non-volatile switching behaviours are coexistent in this device. Various synaptic functions, including short-term plasticity, long-term plasticity, pair-pulse facilitation, and spike timing-dependent plasticity, have been successfully eliminated in Ag/GeSe/TiN devices. Furthermore, all the synaptic functions are induced by the spiking stimuli with amplitudes of several hundred millivolts. All the results demonstrate that the Ag/GeSe/TiN device has great potential for brain-inspired computing systems in the future.
•SnO2 samples with controllable oxygen vacancy concentration have been developed by organometallic chemistry-assisted strategy.•The SnO2 samples with high oxygen vacancy concentration exhibit ...excellent sensing performances for detection of acetone.•This work paves a new avenue for fabricating metal oxides with controllable oxygen vacancies for various applications.
Oxygen vacancies play a critical role in the sensing performances for metal oxides-based chemiresistor-type sensors. Developing facile and effective strategies for fabricating metal oxides with controllable oxygen vacancies is in great demand but remains paramount challenge. Herein, a novel organometallic chemistry-assisted method is reported to prepare SnO2 samples containing controllable surface oxygen vacancies. This new approach combines modification of SnO2 with dimethyltin dichloride, and subsequently thermal treatment in air atmosphere. Taking commercial SnO2 as an example, it is found that the optimized SnO2 sample possesses highest surface oxygen vacancy concentration of 37.13%. Owing to increased oxygen vacancy concentration, the resulting SnO2 sample (SnO2-Sn-0.5) presents excellent sensing performances for detection of acetone, including high response, fast response and recovery rate, good selectivity, compared with pristine SnO2 with low oxygen vacancy concentration (28.66%). This work paves a new avenue for fabricating metal oxides with controllable oxygen vacancies for various applications of sensing, energy storage, and so on.
A promising new bond coat using CuAlNiCrFe high-entropy alloy was proposed in this paper. The difference in pre-oxidation conditions between the traditional thermal-sprayed MCrAlY bond coat and ...CuAlNiCrFe high-entropy alloy bond coat deposited using high-speed laser cladding was investigated. The result confirmed that the CuAlNiCrFe high-entropy alloy bond coat deposited using high-speed laser cladding can complete the pre-oxidation faster and form a continuous α-Al2O3 thermally grown oxide (TGO), which shortens the initial oxidation stage, thereby avoiding the formation of other oxides and spinel structures. In the subsequent isothermal oxidation process, the block-like structure of the high-speed laser cladding layer and the sluggish diffusion effect of the high-entropy alloy work together to ensure the slow and continuous supply of aluminum element to TGO layer and obtain a low growth rate. Also, the diffusion between the bonding layer and the substrate is controlled at a low level, and the new CuAlNiCrFe bond coat exhibits excellent oxidation and diffusion resistance. With the consumption of aluminum, the phase structure of the high-entropy alloy bond coat changed from BCC to FCC, but it still maintained a stable simple solid solution structure.
•A high entropy alloys bond coat was prepared by ultra-high speed laser cladding.•The laser Cladded high-entropy alloys ensure the sluggish diffusion effect.•The CuAlNiCrFe bond coat shows great oxidation resistance in 1100 °C.•The phase structure of CuAlNiCrFe change to FCC single-phase solid solution.•A new thermal barrier coatings system with high entropy alloys was proposed.
Conductive‐bridge random access memory (CBRAM) is considered a strong contender of the next‐generation nonvolatile memory technology. Resistive switching (RS) behavior in CBRAM is decided by the ...formation/dissolution of nanoscale conductive filament (CF) inside RS layer based on the cation injection from active electrode and their electrochemical reactions. Remarkably, RS is actually a localized behavior, however, cation injects from the whole area of active electrode into RS layer supplying excessive cation beyond the requirement of CF formation, leading to deterioration of device uniformity and reliability. Here, an effective method is proposed to localize cation injection into RS layer through the nanohole of inserted ion barrier between active electrode and RS layer. Taking an impermeable monolayer graphene as ion barrier, conductive atomic force microscopy results directly confirm that CF formation is confined through the nanohole of graphene due to the localized cation injection. Compared with the typical Cu/HfO2/Pt CBRAM device, the novel Cu/nanohole‐graphene/HfO2/Pt device shows improvement of uniformity, endurance, and retention characteristics, because the cation injection is limited by the nanohole graphene. Scaling the nanohole of ion barrier down to several nanometers, the single‐CF‐based CBRAM device with high performance is expected to achieve by confining the cation injection at the atomic scale.
Excessive cation injection into a resistive switching layer beyond the requirement of conductive filament formation, leads to deterioration of conductive‐bridge random access memory (CBRAM) performance. The cation injection can be localized by inserting a nanohole graphene between the active electrode and resistive switching layer. The nanoscale localized cation injection, validated by conductive atomic force microscopy, gives rise to enhanced CBRAM performance.
The determination of the weights of decision makers (DMs) is an important problem in multi-attribute group decision making. Many approaches have been presented to determine DMs' weights. However, the ...computed weight vectors of DMs are usually assumed to be constant in existing studies, and this may cause irrationalities in the decision results. Therefore, this article proposes a novel method to determine DMs' weights based on variable weights theory in which the evaluation information is described as intuitionistic fuzzy sets (IFSs). First, DMs provide their assessment with IFSs, and the intuitionistic fuzzy weighted averaging (IFWA) operator is applied to obtain weighted decision matrix based on the prior given DMs' and attributes' weights. Second, the DMs' weights are obtained based on variable weights theory, and an alternative decision can be computed. Finally, the converted value of the achieved IFS of each alternative is calculated, and the best appropriate alternative is acquired. Two illustrative examples and the comparisons with exsiting approaches are also used to reflect the effectiveness of the proposed approach.
Alzheimer's disease (AD) is the most common neurodegenerative disease, with cognitive decline as the primary clinical feature. According to epidemiological statistics, 50 million people worldwide are ...currently affected by Alzheimer's disease. Although new drugs such as aducanumab have been approved for use in the treatment of AD, none of them have reversed the progression of AD. MicroRNAs (miRNAs) are small molecule RNAs that exert their biological functions by regulating the expression of intracellular proteins, and differential abundance and varieties are found between the central and peripheral tissues of AD patients and healthy controls. This article will summarise the changes of miRNAs in the AD process, and the potential role of diagnostic markers and therapeutic targets in AD will be explored.
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•MicroRNAs regulate gene expression post-transcriptionally responsible for regulating more than 70% of human genes.•In Alzheimer’s disease, microRNAs in serum, cerebrospinal fluid, and brain tissue have been studied.•MicroRNAs are involved in the pathological process of Alzheimer’s disease.•MicroRNAs are innovative treatment and diagnosis markers.
This article describes the development of a kind of full carbon-based humidity sensor fabricated on the paper substrate by handwriting. The electrodes were written by commercial pencils, and the ...sensitive layer was drawn with an oxidized multiwalled carbon nanotubes (o-MWCNTs) ink marker. The resultant devices exhibit good reproducibility and stability during the dynamic measurement. The response of the optimized paper-based sensor exhibits about five times higher than sensors fabricated on the ceramic substrate, which is owing to the hydrophilic property of the paper substrate. The structure of the sensitive layer formed by dispersing sensitive materials in the porous surface of paper substrates alleviates the inner stress in the process of bending. The response of printing paper-based sensors only shows the 6.7% decay even under an extremely high bending degree.
Neuromorphic machines are intriguing for building energy-efficient intelligent systems, where spiking neurons are pivotal components. Recently, memristive neurons with promising bio-plausibility have ...been developed, but with limited reliability, bulky capacitors or additional reset circuits. Here, we propose an anti-ferroelectric field-effect transistor neuron based on the inherent polarization and depolarization of Hf
Zr
O
anti-ferroelectric film to meet these challenges. The intrinsic accumulated polarization/spontaneous depolarization of Hf
Zr
O
films implements the integration/leaky behavior of neurons, avoiding external capacitors and reset circuits. Moreover, the anti-ferroelectric neuron exhibits low energy consumption (37 fJ/spike), high endurance (>10
), high uniformity and high stability. We further construct a two-layer fully ferroelectric spiking neural networks that combines anti-ferroelectric neurons and ferroelectric synapses, achieving 96.8% recognition accuracy on the Modified National Institute of Standards and Technology dataset. This work opens the way to emulate neurons with anti-ferroelectric materials and provides a promising approach to building high-efficient neuromorphic hardware.
Sustainability, as a trend of social development and the embodiment of corporate social responsibility, has begun to receive more attention. To achieve this goal, sustainable supplier selection (SSS) ...and order allocation (OA) are seen as the crucial activities in corporate management. In the process of SSS, the psychological behavior of decision-makers (DMs) could play a critical role in the evaluation results. Therefore, introducing it into the decision-making process may lead to decision in line with the actual situation. In the uncertain multi-criteria group decision-making (MCGDM) problem described by probability linguistic term sets (PLTS), the DMs can evaluate the criteria of each supplier based on his own preference and hesitation, which is useful to avoid the loss of information. For this reason, this study develops a novel multi-criteria group decision-making combined with fuzzy multi-objective optimization (MCGDM-FMOO) model for SSS/OA problems by considering the triple bottom line (TBL) in which includes economic, environmental and social factors. The proposed method includes four stages. (1) the best-worst method (BWM) and entropy weight method are utilized to assign the weights of criteria to obtain the comprehensive weight. According to the output weights, the an acronym for interactive and multi-criteria decision-making in Portugese (TODIM) approach is applied to rank the suppliers under PLTS environment; (2) a FMOO model that can effectively deal with uncertainties and dynamic nature of parameter is formulated for allocating optimal order quantities; (3) two novel approaches are utilized to solve the FMOO model in order to obtain the richer Pareto frontier; and (4) the final OA solution is achieved by technique for order preference by similarity to ideal solution (TOPSIS) method. Finally, the validity and practicability of proposed MCGDM-FMOO model are verified by an example and comparative analysis with other classical MCGDM methods.
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