A Recoverable Synapse Device Using a Three‐Dimensional Silicon Transistor. (1st October 2018)
- Record Type:
- Journal Article
- Title:
- A Recoverable Synapse Device Using a Three‐Dimensional Silicon Transistor. (1st October 2018)
- Main Title:
- A Recoverable Synapse Device Using a Three‐Dimensional Silicon Transistor
- Authors:
- Hur, Jae
Jang, Byung Chul
Park, Jihun
Moon, Dong‐Il
Bae, Hagyoul
Park, Jun‐Young
Kim, Gun‐Hee
Jeon, Seung‐Bae
Seo, Myungsoo
Kim, Sungho
Choi, Sung‐Yool
Choi, Yang‐Kyu - Abstract:
- Abstract: To prepare for the upcoming big‐data era, numerous attempts are underway to develop a neuromorphic system which is capable of imitating a biologic neural network. Despite the significant improvements to software‐based artificial neural networks (ANNs) recently, they remain inefficient in terms of energy use. Alternatively, many researchers have been attracted to hardware‐based ANNs by fundamentally mimicking neural circuits and synapses. In this study, a two‐terminal silicon‐channel synapse (SINAPSE) with a poly‐Si/SiO2 /Si3 N4 gate stack over a silicon channel is introduced, and demonstrated the smallest size of a synapse device reported thus far, along with reliable, low‐power performance. A distinctive feature of SINAPSE is that it emulates synaptic recovery, a retrieval process for neurotransmitters which would be otherwise depleted. By applying an electrical recovery pulse to SINAPSE, synaptic recovery was for the first time successfully imitated. Experimental results demonstrate the potential of the curable SINAPSE as a fundamental unit in neuromorphic circuitry. Abstract : Two‐terminal silicon‐channel synapse device with a poly‐Si/SiO2 /Si3 N4 gate stack over a silicon channel, named as SINAPSE, dynamically and energy efficiently modulates the channel conductance. Based on the state‐of‐the‐art silicon technology, SINAPSE achieved the smallest synapse device feature size reported so far, and imitated the synaptic recovery behavior of an actual synapseAbstract: To prepare for the upcoming big‐data era, numerous attempts are underway to develop a neuromorphic system which is capable of imitating a biologic neural network. Despite the significant improvements to software‐based artificial neural networks (ANNs) recently, they remain inefficient in terms of energy use. Alternatively, many researchers have been attracted to hardware‐based ANNs by fundamentally mimicking neural circuits and synapses. In this study, a two‐terminal silicon‐channel synapse (SINAPSE) with a poly‐Si/SiO2 /Si3 N4 gate stack over a silicon channel is introduced, and demonstrated the smallest size of a synapse device reported thus far, along with reliable, low‐power performance. A distinctive feature of SINAPSE is that it emulates synaptic recovery, a retrieval process for neurotransmitters which would be otherwise depleted. By applying an electrical recovery pulse to SINAPSE, synaptic recovery was for the first time successfully imitated. Experimental results demonstrate the potential of the curable SINAPSE as a fundamental unit in neuromorphic circuitry. Abstract : Two‐terminal silicon‐channel synapse device with a poly‐Si/SiO2 /Si3 N4 gate stack over a silicon channel, named as SINAPSE, dynamically and energy efficiently modulates the channel conductance. Based on the state‐of‐the‐art silicon technology, SINAPSE achieved the smallest synapse device feature size reported so far, and imitated the synaptic recovery behavior of an actual synapse providing a significantly enhanced cyclic endurance characteristic. … (more)
- Is Part Of:
- Advanced functional materials. Volume 28:Number 47(2018)
- Journal:
- Advanced functional materials
- Issue:
- Volume 28:Number 47(2018)
- Issue Display:
- Volume 28, Issue 47 (2018)
- Year:
- 2018
- Volume:
- 28
- Issue:
- 47
- Issue Sort Value:
- 2018-0028-0047-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2018-10-01
- Subjects:
- artificial neural networks (ANN) -- fin field‐effect transistors (FinFET) -- neuromorphic systems -- silicon synapses (SINAPSE) -- synapse devices -- synaptic fatigue -- synaptic recovery
Materials -- Periodicals
Chemical vapor deposition -- Periodicals
620.11 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1616-3028 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/adfm.201804844 ↗
- Languages:
- English
- ISSNs:
- 1616-301X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.853900
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8608.xml