Tunable Synaptic Plasticity in Crystallized Conjugated Polymer Nanowire Artificial Synapses
In biological synapses, short‐term plasticity is important for computation and signal transmission, whereas long‐term plasticity is essential for memory formation. Comparably, designing a strategy that can easily tune the synaptic plasticity of artificial synapses can benefit constructing an artificial neural system, where synapses with different short‐term plasticity (STP) and long‐term plasticity (LTP) are required. Herein, a strategy is designed that can easily tune the plasticity of crystallized conjugated polymer nanowire‐based synaptic transistors (STs) by low‐temperature solvent engineering. Essential synaptic functions are achieved, such as excitatory postsynaptic current (EPSC), paired‐pulse facilitation (PPF), spike‐frequency‐dependent plasticity (SFDP), spike‐duration‐dependent plasticity (SDDP) and spike‐number‐dependent plasticity (SNDP), and potentiation/depression. The balance between crystallinity and roughness is successfully adjusted by altering solvent compositions, and plasticity of the synaptic device is easily tuned between short term and long term. The evident transition from STP to LTP, good linearity and symmetry of potentiation and depression, and the broad dynamic working range of synaptic weight are achieved. This provides a facile way to tune synaptic plasticity at low temperatures and is applicable to future organic and flexible artificial nervous systems.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Tunable Synaptic Plasticity in Crystallized Conjugated Polymer Nanowire Artificial Synapses ; volume:2 ; number:3 ; year:2020 ; extent:6
Advanced intelligent systems ; 2, Heft 3 (2020) (gesamt 6)
- Urheber
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Han, Hong
Xu, Zhipeng
Guo, Kexin
Ni, Yao
Ma, Mingxue
Yu, Haiyang
Wei, Huanhuan
Gong, Jiangdong
Zhang, Shuo
Xu, Wentao
- DOI
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10.1002/aisy.201900176
- URN
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urn:nbn:de:101:1-2022062909174812101014
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:28 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Han, Hong
- Xu, Zhipeng
- Guo, Kexin
- Ni, Yao
- Ma, Mingxue
- Yu, Haiyang
- Wei, Huanhuan
- Gong, Jiangdong
- Zhang, Shuo
- Xu, Wentao
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