2021
DOI: 10.1063/5.0069116
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Physical based compact model of Y-Flash memristor for neuromorphic computation

Abstract: Y-Flash memristors utilize the mature technology of single polysilicon floating gate non-volatile memories (NVM). It can be operated in a two-terminal configuration similar to the other emerging memristive devices, i.e., resistive random-access memory (RRAM), phase-change memory (PCM), etc. Fabricated in production complementary metal-oxide-semiconductor (CMOS) technology, Y-Flash memristors allow excellent reproducibility reflected in high neuromorphic products yields. Working in the subthreshold region, the … Show more

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Cited by 10 publications
(5 citation statements)
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“…Besides, strain effect promotes the trivial topology in VSi 2 P 4 and VA 2 Z 4 derived materials (VN 2 X 2 Y 2 ). [173][174][175] There exists an edge state connecting the valence and conduction bands under a compressive strain of 2.1 % [173] and a biaxial tensile strain. [174] Recent firstprinciples calculations reveal 2D MSi 2 Z 4 with 1T' structure as largebandgap and tunable quantum spin Hall insulator, which possesses a protected spinpolarized edge state and a large spinHall conductivity.…”
Section: Magnetic Propertiesmentioning
confidence: 99%
“…Besides, strain effect promotes the trivial topology in VSi 2 P 4 and VA 2 Z 4 derived materials (VN 2 X 2 Y 2 ). [173][174][175] There exists an edge state connecting the valence and conduction bands under a compressive strain of 2.1 % [173] and a biaxial tensile strain. [174] Recent firstprinciples calculations reveal 2D MSi 2 Z 4 with 1T' structure as largebandgap and tunable quantum spin Hall insulator, which possesses a protected spinpolarized edge state and a large spinHall conductivity.…”
Section: Magnetic Propertiesmentioning
confidence: 99%
“…As shown in Figure 4a, the BSIM4 models exhibited a precise fit with the measurement We extracted the Berkeley short-channel IGFET model (BSIM4) based on the measured transfer curve characteristics of the programmed and erased cells in order to perform SPICE simulations. To simulate on-chip learning, models need to be established for all program and erase operations [55]. However, since the proposed system is based on off-chip learning for hardware BNNs, models were extracted only for the two states.…”
Section: Resultsmentioning
confidence: 99%
“…When a writing gate voltage is applied, charges in the channel can cross over the tunneling layer through the Fowler-Nordheim (F-N) tunneling or channel hot electron injection mechanism and be stored in the floating gate layer. Thus, the threshold voltage of the device can be tuned by the Q FG when a write/erase operation is performed 48,133,134,[140][141][142][143][144][145][146][147][148] .…”
Section: Floating-gate Synapsesmentioning
confidence: 99%