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The quantum conductance (QC) behaviors in synaptic devices with stable and tunable conductance states are essential for high-density storage and brain-like neurocomputing (NC). In this work, inspired by the discontinuous transport of fluid in spider silk, a synaptic device composed of a silicon oxide nanowire network embedded with silicon quantum dots (Si-QDs@SiO) is designed. The tunable QC behaviors are achieved in both the SET and RESET processes, and the QC states exhibit stable retention time exceeding 10 s in the synaptic device and show stable reproducibility after an interval of two months. The synaptic plasticity, including long-term potentiation/depression and Pavlovian conditioning function, is simulated based on the tunable conductance. The mechanism of stable and tunable QC behaviors is analyzed and clarified by beading effect of spider silk in Si-QDs@SiO nanowires structure. The digit recognition capability of the device is evaluated by simulation using an artificial neural network consisting of the Si-QDs@SiO-based synaptic device. These results provide insights into the development of neurocomputing systems with high classification accuracy.
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http://dx.doi.org/10.1021/acsami.4c06328 | DOI Listing |
Basic Clin Pharmacol Toxicol
October 2025
Department of Medical Pharmacology, Faculty of Medicine, Eskisehir Osmangazi University, Eskisehir, Turkey.
Neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis and frontotemporal dementia represent a significant global health burden with limited therapeutic options. Current treatments are primarily symptomatic and fail to modify disease progression, emphasizing the urgent need for novel, mechanism-based interventions. Recent advances in molecular neuroscience have identified several non-classical pathogenic pathways, including neuroinflammation, mitochondrial dysfunction, impaired autophagy and proteostasis, synaptic degeneration and non-coding RNA dysregulation.
View Article and Find Full Text PDFACS Nano
September 2025
Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education, and School of Physics and Technology, Wuhan University, Wuhan 430072, China.
Ferroelectric tunnel junctions (FTJs) based on ferroelectric switching and quantum tunneling effects with thickness down to a few unit cells have been explored for applications of two-dimensional (2D) electronic devices in data storage and neural networks. As a key performance indicator, the enhanced tunneling electrosistance (TER) ratio provides a broader dynamic range for precise modulation of synaptic weights, improving the stability and accuracy of neural networks. Herein, we report an observation of pronounced enhancement in the TER ratio by over 4 orders of magnitude through the fabrication of large-scale heterostructures combining bismuth ferrite with two-dimensional Ruddlesden-Popper oxide BiFeO.
View Article and Find Full Text PDFACS Chem Neurosci
September 2025
Chemical and Biomolecular Engineering Dept, University of California, Los Angeles, Los Angeles, California 90095, United States.
Simulations in three dimensions and time provide guidance on implantable, electroenzymatic glutamate sensor design; relative placement in planar sensor arrays; feasibility of sensing synaptic release events; and interpretation of sensor data. Electroenzymatic sensors based on the immobilization of oxidases on microelectrodes have proven valuable for the monitoring of neurotransmitter signaling in deep brain structures; however, the complex extracellular milieu featuring slow diffusive mass transport makes rational sensor design and data interpretation challenging. Simulations show that miniaturization of the disk-shaped device size below a radius of ∼25 μm improves sensitivity, spatial resolution, and the accuracy of glutamate concentration measurements based on calibration factors determined .
View Article and Find Full Text PDFJ Colloid Interface Sci
September 2025
School of Electronic Information & Artificial Intelligence, Shaanxi University of Science and Technology, Xi'an 710021, China.
The integration of information memory and computing enabled by nonvolatile memristive device has been widely acknowledged as a critical solution to circumvent the von Neumann architecture limitations. Herein, the Au/NiO/CaBiTiO/FTO (CBTi/NiO) heterojunction based memristor with varying film thicknesses are demonstrated on FTO/glass substrates, and the CBTi/NiO-4 sample shows the optimal memristor characteristics with 5 × 10 stable switching cycles and 10-s resistance state retention. The electrical conduction in the low-resistance state is dominated by Ohmic behavior, while the high-resistance state exhibited characteristics consistent with the space-charge-limited conduction (SCLC) model.
View Article and Find Full Text PDFACS Appl Mater Interfaces
September 2025
Department of Material Sciences and Engineering, Seoul National University, Seoul 08826, Republic of Korea.
A nanometer-scale multilayer gate insulator (GI) engineering strategy is introduced to simultaneously enhance the on-current and bias stability of amorphous InGaZnO thin-film transistors (a-IGZO TFTs). Atomic layer deposition supercycle modifications employ alternating layers of AlO, TiO, and SiO to optimize the gate-oxide stack. Each GI material is strategically selected for complementary functionalities: AlO improves the interfacial quality at both the GI/semiconductor and GI/metal interfaces, thereby enhancing device stability and performance; TiO increases the overall dielectric constant; and SiO suppresses leakage current by serving as a high-energy barrier between AlO and TiO.
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