Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons

Hyejin Lee; Seong Won Cho; Seon Jeong Kim; Jaesang Lee; Keun Su Kim; Inho Kim; Jong Keuk Park; Joon Young Kwak; Jaewook Kim; Jongkil Park; Yeon Joo Jeong; Gyu Weon Hwang; Kyeong Seok Lee; Daniele Ielmini; Suyoun Lee

doi:10.1021/acs.nanolett.1c04125

Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons

Hyejin Lee, Seong Won Cho, Seon Jeong Kim, Jaesang Lee, Keun Su Kim, Inho Kim, Jong Keuk Park, Joon Young Kwak, Jaewook Kim, Jongkil Park, Yeon Joo Jeong, Gyu Weon Hwang, Kyeong Seok Lee, Daniele Ielmini, Suyoun Lee

Department of Physics

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

Inspired by information processing in biological systems, sensor-combined edge-computing systems attract attention requesting artificial sensory neurons as essential ingredients. Here, we introduce a simple and versatile structure of artificial sensory neurons based on a novel three-terminal Ovonic threshold switch (3T-OTS), which features an electrically controllable threshold voltage (V_th). Combined with a sensor driving an output voltage, this 3T-OTS generates spikes with a frequency depending on an external stimulus. As a proof of concept, we have built an artificial retinal ganglion cell (RGC) by combining a 3T-OTS and a photodiode. Furthermore, this artificial RGC is combined with the reservoir-computing technique to perform a classification of chest X-ray images for normal, viral pneumonia, and COVID-19 infections, releasing the recognition accuracy of about 86.5%. These results indicate that the 3T-OTS is highly promising for applications in neuromorphic sensory systems, providing a building block for energy-efficient in-sensor computing devices.

Original language	English
Pages (from-to)	733-739
Number of pages	7
Journal	Nano letters
Volume	22
Issue number	2
DOIs	https://doi.org/10.1021/acs.nanolett.1c04125
Publication status	Published - 2022 Jan 26

Bibliographical note

Funding Information:
This work was supported by the Korea Institute of Science and Technology (KIST) through 2E31040 and by the National Research Foundation program through NRF-2019M3F3A1A02072175, 2021M3F3A2A03017782, and 2021M3F3A2A01037814.

Publisher Copyright:
© 2022 American Chemical Society

All Science Journal Classification (ASJC) codes

Bioengineering
Chemistry(all)
Materials Science(all)
Condensed Matter Physics
Mechanical Engineering

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10.1021/acs.nanolett.1c04125

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Lee, H., Cho, S. W., Kim, S. J., Lee, J., Kim, K. S., Kim, I., Park, J. K., Kwak, J. Y., Kim, J., Park, J., Jeong, Y. J., Hwang, G. W., Lee, K. S., Ielmini, D., & Lee, S. (2022). Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons. Nano letters, 22(2), 733-739. https://doi.org/10.1021/acs.nanolett.1c04125

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abstract = "Inspired by information processing in biological systems, sensor-combined edge-computing systems attract attention requesting artificial sensory neurons as essential ingredients. Here, we introduce a simple and versatile structure of artificial sensory neurons based on a novel three-terminal Ovonic threshold switch (3T-OTS), which features an electrically controllable threshold voltage (Vth). Combined with a sensor driving an output voltage, this 3T-OTS generates spikes with a frequency depending on an external stimulus. As a proof of concept, we have built an artificial retinal ganglion cell (RGC) by combining a 3T-OTS and a photodiode. Furthermore, this artificial RGC is combined with the reservoir-computing technique to perform a classification of chest X-ray images for normal, viral pneumonia, and COVID-19 infections, releasing the recognition accuracy of about 86.5%. These results indicate that the 3T-OTS is highly promising for applications in neuromorphic sensory systems, providing a building block for energy-efficient in-sensor computing devices.",

author = "Hyejin Lee and Cho, {Seong Won} and Kim, {Seon Jeong} and Jaesang Lee and Kim, {Keun Su} and Inho Kim and Park, {Jong Keuk} and Kwak, {Joon Young} and Jaewook Kim and Jongkil Park and Jeong, {Yeon Joo} and Hwang, {Gyu Weon} and Lee, {Kyeong Seok} and Daniele Ielmini and Suyoun Lee",

note = "Funding Information: This work was supported by the Korea Institute of Science and Technology (KIST) through 2E31040 and by the National Research Foundation program through NRF-2019M3F3A1A02072175, 2021M3F3A2A03017782, and 2021M3F3A2A01037814. Publisher Copyright: {\textcopyright} 2022 American Chemical Society",

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AU - Lee, Hyejin

AU - Cho, Seong Won

AU - Kim, Seon Jeong

AU - Lee, Jaesang

AU - Kim, Keun Su

AU - Kim, Inho

AU - Park, Jong Keuk

AU - Kwak, Joon Young

AU - Kim, Jaewook

AU - Park, Jongkil

AU - Jeong, Yeon Joo

AU - Hwang, Gyu Weon

AU - Lee, Kyeong Seok

AU - Ielmini, Daniele

AU - Lee, Suyoun

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PY - 2022/1/26

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N2 - Inspired by information processing in biological systems, sensor-combined edge-computing systems attract attention requesting artificial sensory neurons as essential ingredients. Here, we introduce a simple and versatile structure of artificial sensory neurons based on a novel three-terminal Ovonic threshold switch (3T-OTS), which features an electrically controllable threshold voltage (Vth). Combined with a sensor driving an output voltage, this 3T-OTS generates spikes with a frequency depending on an external stimulus. As a proof of concept, we have built an artificial retinal ganglion cell (RGC) by combining a 3T-OTS and a photodiode. Furthermore, this artificial RGC is combined with the reservoir-computing technique to perform a classification of chest X-ray images for normal, viral pneumonia, and COVID-19 infections, releasing the recognition accuracy of about 86.5%. These results indicate that the 3T-OTS is highly promising for applications in neuromorphic sensory systems, providing a building block for energy-efficient in-sensor computing devices.

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Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons

Abstract

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