2019
DOI: 10.3390/electronics9010004
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Analysis of the Voltage-Dependent Plasticity in Organic Neuromorphic Devices

Abstract: The bias-dependent signal transmission of flexible synaptic transistors is investigated. The novel neuromorphic devices are fabricated on a thin and transparent plastic sheet, incorporating a high-performance organic semiconductor, dinaphtho[2,3-b:2′,3′-f]thieno[3,2-b]thiophene, into the active channel. Upon spike emulation at different synaptic voltages, the short-term plasticity feature of the devices is substantially modulated. By adopting an iterative model for the synaptic output currents, key physical pa… Show more

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Cited by 5 publications
(1 citation statement)
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“…Recently, a wide range of electronic memory devices were investigated as artificial synapses, including resistive random-access memories and various types of transistors. , Memories for neuromorphic applications may have different technical requirements compared to those relevant to traditional memories. For instance, the electrical accessibility to intermediate states (i.e., analog function) is desirable, while the nonvolatility of data retention is not strictly necessary for synaptic devices. , It seems that graphene-based flexible memories are well positioned to realize next-generation portable/wearable neuromorphic systems not only because of their excellent flexibility and performances (broadly reviewed up to this point) but also because of the possibility of fine optimization of the physical charge-conducting and storage sites (through hybridization, surface, and electrochemical routes) and a future potential for fully graphene intelligent circuits combining all of the neuronal, synaptic, and interface components made of high-performance graphene electronics.…”
Section: Emerging Neuromorphic Applicationsmentioning
confidence: 99%
“…Recently, a wide range of electronic memory devices were investigated as artificial synapses, including resistive random-access memories and various types of transistors. , Memories for neuromorphic applications may have different technical requirements compared to those relevant to traditional memories. For instance, the electrical accessibility to intermediate states (i.e., analog function) is desirable, while the nonvolatility of data retention is not strictly necessary for synaptic devices. , It seems that graphene-based flexible memories are well positioned to realize next-generation portable/wearable neuromorphic systems not only because of their excellent flexibility and performances (broadly reviewed up to this point) but also because of the possibility of fine optimization of the physical charge-conducting and storage sites (through hybridization, surface, and electrochemical routes) and a future potential for fully graphene intelligent circuits combining all of the neuronal, synaptic, and interface components made of high-performance graphene electronics.…”
Section: Emerging Neuromorphic Applicationsmentioning
confidence: 99%