Results 11 to 20 of about 2,424,657 (202)
Nature Communications, 2022 Conventional filamentary memristors are limited in dynamics by the high electric-field dependence of the conductive filament. Here, Jeong et al. presents a method which creates a cluster-type memristor, enabling large conductance range and long data ...
Jaehyun Kang +10 more
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A triple-level cell charge trap flash memory device with CVD-grown MoS2
Results in Physics, 2022 This study investigates the triple-level cell (TLC) memory retention of a MoS2-channel based charge trap flash (CTF) device. A top-gated CTF device with a high-κ gate dielectric is found to have a high coupling ratio, which enhances the tunneling ...
Minkyung Kim +9 more
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Scientific Reports, 2021 Mid-infrared wavelengths are called the molecular fingerprint region because it contains the fundamental vibrational modes inherent to the substances of interest. Since the mid-infrared spectrum can provide non-destructive identification and quantitative
Hwa-Seub Lee +7 more
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IEEE Access, 2022 Neuromorphic hardware is a system with massive potential to enable efficient computing by mimicking the human brain. The novel system processes information using neuron spikes (Action Potentials) and the synaptic connections between neurons are trained ...
Suman Hu +11 more
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Novel nano-plasmonic sensing platform based on vertical conductive bridge
Scientific Reports, 2021 A novel nano-plasmonic sensing platform based on vertical conductive bridge was suggested as an alternative geometry for taking full advantages of unique properties of conductive junction while substantially alleviating burdens in lithographic process ...
Hyo-Seung Park +5 more
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Crystals, 2021 A synaptic device that contains weight information between two neurons is one of the essential components in a neuromorphic system, which needs highly linear and symmetric characteristics of weight update.
Minkyung Kim +10 more
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Neuromorphic Engineering: From Materials to Device Application
Advances in Materials, 2023 With the advent of the Internet of Things, an exponential growth in the amount of data has imposed critical requirements on the energy efficiency and processing speed for data-centric tasks, which calls for changes to information-processing paradigms to ...
J. J. Yang +3 more
semanticscholar +1 more source
Reservoir Computing with Charge‐Trap Memory Based on a MoS2 Channel for Neuromorphic Engineering
Advances in Materials, 2022 Novel memory devices are essential for developing low power, fast, and accurate in‐memory computing and neuromorphic engineering concepts that can compete with the conventional complementary metal−oxide−semiconductor (CMOS) digital processors.
M. Farronato +5 more
semanticscholar +1 more source
Visualizing a joint future of neuroscience and neuromorphic engineering.
Neuron, 2021 Recent research resolves the challenging problem of building biophysically plausible spiking neural models that are also capable of complex information processing. This advance creates new opportunities in neuroscience and neuromorphic engineering, which
Friedemann Zenke +3 more
semanticscholar +1 more source
Event-Based Feature Extraction Using Adaptive Selection Thresholds
Sensors, 2020 Unsupervised feature extraction algorithms form one of the most important building blocks in machine learning systems. These algorithms are often adapted to the event-based domain to perform online learning in neuromorphic hardware. However, not designed
Saeed Afshar +5 more
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