Three-Dimensional Integrated Synaptic Devices Based on a Silver-Cluster Conduction Mechanism with High Thermostability
- Authors
- Li, Mingjun; Li, Ming; An, Jun Seop; An, Haoqun; Kim, Dae Hun; Lee, Yong Hun; Park, Kwan Kyu; Kim, Tae Whan
- Issue Date
- Aug-2024
- Publisher
- American Chemical Society
- Keywords
- Ag cluster-type filaments; high thermal stability; molybdenum disulfide quantum dots; neuromorphic computing; synaptic devices; three-dimensional stacked
- Citation
- ACS Applied Materials & Interfaces, v.16, no.32, pp 42380 - 42391
- Pages
- 12
- Indexed
- SCIE
SCOPUS
- Journal Title
- ACS Applied Materials & Interfaces
- Volume
- 16
- Number
- 32
- Start Page
- 42380
- End Page
- 42391
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/195037
- DOI
- 10.1021/acsami.4c04957
- ISSN
- 1944-8244
1944-8252
- Abstract
- During the operation of synaptic devices based on traditional conductive filament (CF) models, the formation and dissolution of CFs are usually uncertain. Moreover, when the device is operated for a long time, the CFs may dissolve due to both the Joule heat generated by the device itself and the thermal coupling between the devices. These problems seriously reduce the reliability and stability of the synaptic device. Here, an artificial synapse device based on polyimide-molybdenum disulfide quantum dot (MoS2 QD) nanocomposites is presented. Research has shown that MoS2 QDs doped into the active layer can effectively induce the reduction of Ag ions into Ag atoms, leading to the formation of Ag clusters and thereby achieving control over the growth of the CFs. Therefore, the device is capable of stably realizing various basic synaptic functions. Moreover, the long-term potentiation/long-term depression (LTP/LTD) of this device shows good linearity. In addition, due to the change in the shape of the CFs, the highly integrated devices with a three-dimensional (3D) stacked structure can operate normally even in a high-temperature environment of 110 °C. Finally, the synaptic characteristics of the devices on learning and inference tests show that their recognition rates are approximately 90.75% (room temperature) and 90.63% (110 °C).
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Collections - 서울 공과대학 > 서울 기계공학부 > 1. Journal Articles
- 서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles

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