All‐Solid‐State Ion Synaptic Transistor for Wafer‐Scale Integration with Electrolyte of a Nanoscale Thickness. (30th March 2021)
- Record Type:
- Journal Article
- Title:
- All‐Solid‐State Ion Synaptic Transistor for Wafer‐Scale Integration with Electrolyte of a Nanoscale Thickness. (30th March 2021)
- Main Title:
- All‐Solid‐State Ion Synaptic Transistor for Wafer‐Scale Integration with Electrolyte of a Nanoscale Thickness
- Authors:
- Yu, Ji‐Man
Lee, Chungryeol
Kim, Da‐Jin
Park, Hongkeun
Han, Joon‐Kyu
Hur, Jae
Kim, Jin‐Ki
Kim, Myung‐Su
Seo, Myungsoo
Im, Sung Gap
Choi, Yang‐Kyu - Abstract:
- Abstract: Neuromorphic hardware computing is a promising alternative to von Neumann computing by virtue of its parallel computation and low power consumption. To implement neuromorphic hardware based on deep neural network (DNN), a number of synaptic devices should be interconnected with neuron devices. For ideal hardware DNN, not only scalability and low power consumption, but also a linear and symmetric conductance change with a large number of conductance levels is required. Here, an all‐solid‐state polymer electrolyte‐gated synaptic transistor (pEGST) is fabricated on an entire silicon wafer with CMOS microfabrication and initiated chemical vapor deposition process. The pEGST shows good linearity as well as symmetry in potentiation and depression, conductance levels up to 8, 192, and low switching energy smaller than 20 fJ pulse −1 . Selected 128 levels from 8, 192 are used to identify handwritten digits in the MNIST database with the aid of a multilayer perceptron, resulting in a recognition rate of 91.7%. Abstract : An all‐solid‐state polymer electrolyte‐gated synaptic transistor (pEGST) is fabricated on an entire silicon wafer with CMOS microfabrication and initiated chemical vapor deposition process. The pEGST shows good linearity as well as symmetry in potentiation and depression, conductance levels up to 8, 192, and low switching energy smaller than 20 fJ pulse −1 .
- Is Part Of:
- Advanced functional materials. Volume 31:Number 23(2021)
- Journal:
- Advanced functional materials
- Issue:
- Volume 31:Number 23(2021)
- Issue Display:
- Volume 31, Issue 23 (2021)
- Year:
- 2021
- Volume:
- 31
- Issue:
- 23
- Issue Sort Value:
- 2021-0031-0023-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-03-30
- Subjects:
- all solid state -- deep neural network -- electrolyte‐gated synaptic transistor -- initiated chemical vapor deposition -- polyethylene glycol di‐methacrylate -- synaptic devices
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.202010971 ↗
- 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:
- 16999.xml