Physical based compact model of Y-Flash memristor for neuromorphic computation

Wei Wang, Loai Danial, Eric Herbelin, Barak Hoffer, Batel Oved, Tzofnat Greenberg-Toledo, Evgeny Pikhay, Yakov Roizin, Shahar Kvatinsky

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number263504
JournalApplied Physics Letters
Volume119
Issue number26
DOIs
StatePublished - 27 Dec 2021
Externally publishedYes

Fingerprint

Dive into the research topics of 'Physical based compact model of Y-Flash memristor for neuromorphic computation'. Together they form a unique fingerprint.

Cite this