상세 보기
Interfacial Ion-Trapping Electrolyte-Gated Transistors for High-Fidelity Neuromorphic Computing
- Jin, Minho;
- Lee, Haeyeon;
- Im, Changik;
- Na, Hyun-Jae;
- Lee, Jae Hak;
- ... Park, Junwoo;
- 외 4명
WEB OF SCIENCE
61SCOPUS
62초록
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 x 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.
키워드
- 제목
- Interfacial Ion-Trapping Electrolyte-Gated Transistors for High-Fidelity Neuromorphic Computing
- 저자
- Jin, Minho; Lee, Haeyeon; Im, Changik; Na, Hyun-Jae; Lee, Jae Hak; Lee, Won Hyung; Han, Junghyup; Lee, Eungkyu; Park, Junwoo; Kim, Youn Sang
- 발행일
- 2022-06
- 유형
- Article
- 권
- 32
- 호
- 24