2023
DOI: 10.1109/jeds.2023.3265392
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Lithium-ion-Based Resistive Devices of LiCoO2/LiPON/Cu With Ultrathin Interlayers of Titanium Oxide for Neuromorphic Computing

Abstract: Lithium (Li)-ion materials such as LiCoO2 and (Li3PO4)-N (LiPON) are used in Li-ion all-solid-state batteries, and are now expected to be used as ion-electron hybrid materials to create a new degree of freedom in future integrated circuits. We fabricated thin-film devices on the basis of LiCoO2/LiPON/Cu and ultrathin titanium oxide (TiOx) to demonstrate their new type of resistance change mechanism and characteristics. Multi-level resistance changes promising as synaptic plasticity were obtained, and the resis… Show more

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“…Further, increasing attraction has focused on applications for Li SSE films to electrochemical ion-insertion devices, such as electrochromic windows, thermal transistors, and electrochemical random-access memories (ECRAMs) . In a typical ECRAM, the electronic conductivity of a mixed ion-electron conductor channel in a transistor (or a mixed ion-electron conductor layer in a two-terminal device) can be changed in an analog manner, based on intercalation and deintercalation of Li ions through an SSE layer under voltage or current bias. These analog switching devices are expected to be used as artificial synaptic elements in future neuromorphic computing systems, which operate with high efficiency and low power consumption.…”
Section: Introductionmentioning
confidence: 99%
“…Further, increasing attraction has focused on applications for Li SSE films to electrochemical ion-insertion devices, such as electrochromic windows, thermal transistors, and electrochemical random-access memories (ECRAMs) . In a typical ECRAM, the electronic conductivity of a mixed ion-electron conductor channel in a transistor (or a mixed ion-electron conductor layer in a two-terminal device) can be changed in an analog manner, based on intercalation and deintercalation of Li ions through an SSE layer under voltage or current bias. These analog switching devices are expected to be used as artificial synaptic elements in future neuromorphic computing systems, which operate with high efficiency and low power consumption.…”
Section: Introductionmentioning
confidence: 99%