Y-Flash memristors utilize the mature technology of single polysilicon floating gate nonvolatile memories. It can be operated in a two-terminal configuration similar to the other emerging memristive devices, e.g., resistive random-access memory and phase-change memory. Fabricated in production complementary metal-oxide-semiconductor technology, Y-Flash memristors allow excellent reproducibility reflected in high neuromorphic products yields. Working in the subthreshold region, the device can be programmed to a large number of fine-tuned intermediate states in an analog fashion and allows low readout currents (1 nA ∼ 5 μA). However, currently, there are no accurate models to describe the dynamic switching in this type of memristive device and account for multiple operational configurations. In this paper, we provide a physical-based compact model that describes Y-Flash memristor performance in both DC and AC regimes and consistently describes the dynamic program and erase operations. The model is integrated into the commercial circuit design tools and is ready to be used in applications related to neuromorphic computation.
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27 December 2021
Research Article|
December 28 2021
Physical based compact model of Y-Flash memristor for neuromorphic computation
Special Collection:
Neuromorphic Computing: From Quantum Materials to Emergent Connectivity
Wei Wang
;
Wei Wang
a)
1
The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology
, Haifa 3200003, Israel
a)Authors to whom correspondence should be addressed: wei.wang@campus.technion.ac.il and shahar@ee.technion.ac.il
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Loai Danial;
Loai Danial
b)
1
The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology
, Haifa 3200003, Israel
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Eric Herbelin;
Eric Herbelin
1
The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology
, Haifa 3200003, Israel
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Barak Hoffer
;
Barak Hoffer
1
The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology
, Haifa 3200003, Israel
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Batel Oved;
Batel Oved
1
The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology
, Haifa 3200003, Israel
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Tzofnat Greenberg-Toledo;
Tzofnat Greenberg-Toledo
1
The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology
, Haifa 3200003, Israel
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Evgeny Pikhay;
Evgeny Pikhay
2
Tower Semiconductor
, Migdal HaEmek 2310502, Israel
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Yakov Roizin;
Yakov Roizin
2
Tower Semiconductor
, Migdal HaEmek 2310502, Israel
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Shahar Kvatinsky
Shahar Kvatinsky
a)
1
The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology
, Haifa 3200003, Israel
a)Authors to whom correspondence should be addressed: wei.wang@campus.technion.ac.il and shahar@ee.technion.ac.il
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a)Authors to whom correspondence should be addressed: wei.wang@campus.technion.ac.il and shahar@ee.technion.ac.il
b)
Current address: Intel Corporation, IDC, Haifa, Israel.
Note: This paper is part of the APL Special Collection on Neuromorphic Computing: From Quantum Materials to Emergent Connectivity.
Appl. Phys. Lett. 119, 263504 (2021)
Article history
Received:
August 29 2021
Accepted:
December 08 2021
Citation
Wei Wang, Loai Danial, Eric Herbelin, Barak Hoffer, Batel Oved, Tzofnat Greenberg-Toledo, Evgeny Pikhay, Yakov Roizin, Shahar Kvatinsky; Physical based compact model of Y-Flash memristor for neuromorphic computation. Appl. Phys. Lett. 27 December 2021; 119 (26): 263504. https://doi.org/10.1063/5.0069116
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