An Organic Nanoparticle Transistor Behaving as a Biological Spiking Synapse
Органический транзистор на основе наночастиц, функционирующий как биологический спайковый синапс
2009-12-16
SCID: 54.1/pd69rtny
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NOMFETbiological spiking synapseneuromorphic computingorganic nanoparticle transistorsynaptic plasticity
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Abstract (AI)
Abstract Molecule‐based devices are envisioned to complement silicon devices by providing new functions or by implementing existing functions at a simpler process level and lower cost, by virtue of their self‐organization capabilities. Moreover, they are not bound to von Neuman architecture and this feature may open the way to other architectural paradigms. Neuromorphic electronics is one of them. Here, a device made of molecules and nanoparticles—a nanoparticle organic memory field‐effect transistor (NOMFET)—that exhibits the main behavior of a biological spiking synapse is demonstrated. Facilitating and depressing synaptic behaviors can be reproduced by the NOMFET and can be programmed. The synaptic plasticity for real‐time computing is evidenced and described by a simple model. These results open the way to rate‐coding utilization of the NOMFET in dynamical neuromorphic computing circuits.
Key Findings
1
A nanoparticle organic memory field-effect transistor (NOMFET) reproduces the main behavior of a biological spiking synapse.
2
Molecule- and nanoparticle-based devices may enable neuromorphic architectures beyond conventional von Neumann designs through self-organization and simpler processing.
3
The NOMFET demonstrates both facilitating and depressing synaptic behaviors, which can be programmed.
4
The device exhibits synaptic plasticity suitable for real-time computing, described using a simple model.
5
The results support using NOMFET devices for rate coding in dynamical neuromorphic computing circuits.
Research Object
nanoparticle organic memory field-effect transistor (NOMFET)
Research Subject
biological spiking synapse-like behavior, including programmable facilitating and depressing synaptic plasticity for real-time neuromorphic computing
Publication Details
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2009-12-16
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