Interfacial Ion‐Trapping Electrolyte‐Gated Transistors for High‐Fidelity Neuromorphic Computing. (14th March 2022)
- Record Type:
- Journal Article
- Title:
- Interfacial Ion‐Trapping Electrolyte‐Gated Transistors for High‐Fidelity Neuromorphic Computing. (14th March 2022)
- Main Title:
- Interfacial Ion‐Trapping Electrolyte‐Gated Transistors for High‐Fidelity Neuromorphic Computing
- Authors:
- Jin, Minho
Lee, Haeyeon
Im, Changik
Na, Hyun‐Jae
Lee, Jae Hak
Lee, Won Hyung
Han, Junghyup
Lee, Eungkyu
Park, Junwoo
Kim, Youn Sang - Abstract:
- Abstract: Li + electrolyte‐gated transistors (EGTs) have received much attention as artificial synapses for neuromorphic computing. EGTs, however, have been still challenging to achieve long‐term synaptic plasticity, which should be linearly and symmetrically controlled with the magnitude of electrical potential at the gate electrode. Herein, a fluoroalkylsilane (FAS) self‐assembled monolayer (SAM) is introduced as a channel‐electrolyte interlayer with the function of sequential ion‐trapping in Li + EGTs. It is demonstrated that the retention of Li + ions can be enhanced, resulting in stable non‐volatile channel conductance update with high fidelity, linearity, and symmetry in EGTs treated with FAS with 5 fluoroalkyl chains. Through investigating electrical analysis and chemical analysis, it is verified that fluoroalkyl chains enable the sequential ion‐trapping at the channel‐electrolyte interface by coulombic attraction between Li + ions and fluorocarbons. Simulations of artificial neural networks using 20 × 20 digits show FAS‐treated EGTs are suitable as artificial synapses with an accuracy of 89.71% by identical gate pulses and 91.97% by non‐identical gate pulses. A methodological approach is newly introduced for developing synaptic devices based on EGTs for neuromorphic computing with high fidelity. Abstract : The fluoroalkyl chains of the fluorinated self‐assembled monolayer can sequentially trap and de‐trap Li + ions by an electric field. Due to trapped Li + ions, theAbstract: Li + electrolyte‐gated transistors (EGTs) have received much attention as artificial synapses for neuromorphic computing. EGTs, however, have been still challenging to achieve long‐term synaptic plasticity, which should be linearly and symmetrically controlled with the magnitude of electrical potential at the gate electrode. Herein, a fluoroalkylsilane (FAS) self‐assembled monolayer (SAM) is introduced as a channel‐electrolyte interlayer with the function of sequential ion‐trapping in Li + EGTs. It is demonstrated that the retention of Li + ions can be enhanced, resulting in stable non‐volatile channel conductance update with high fidelity, linearity, and symmetry in EGTs treated with FAS with 5 fluoroalkyl chains. Through investigating electrical analysis and chemical analysis, it is verified that fluoroalkyl chains enable the sequential ion‐trapping at the channel‐electrolyte interface by coulombic attraction between Li + ions and fluorocarbons. Simulations of artificial neural networks using 20 × 20 digits show FAS‐treated EGTs are suitable as artificial synapses with an accuracy of 89.71% by identical gate pulses and 91.97% by non‐identical gate pulses. A methodological approach is newly introduced for developing synaptic devices based on EGTs for neuromorphic computing with high fidelity. Abstract : The fluoroalkyl chains of the fluorinated self‐assembled monolayer can sequentially trap and de‐trap Li + ions by an electric field. Due to trapped Li + ions, the non‐volatile channel current appears in the electrolyte‐gated transistor (EGT). The sequential ion‐trapping effect in EGT enables channel conductance update with high linearity and symmetry, confirming that EGTs with ion‐trapping interlayer are suitable for high‐fidelity neuromorphic computing. … (more)
- Is Part Of:
- Advanced functional materials. Volume 32:Number 24(2022)
- Journal:
- Advanced functional materials
- Issue:
- Volume 32:Number 24(2022)
- Issue Display:
- Volume 32, Issue 24 (2022)
- Year:
- 2022
- Volume:
- 32
- Issue:
- 24
- Issue Sort Value:
- 2022-0032-0024-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-03-14
- Subjects:
- artificial synapses -- coulombic attraction -- fluoroalkylsilane -- high linear conductance update -- non‐volatile conductance
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.202201048 ↗
- 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:
- 21833.xml