Litcius/Paper detail

Brain-inspired ferroelectric Si nanowire synaptic device

Moonsang Lee, W. Park, Hyungbin Son, Ji Min Seo, Oh‐Sung Kwon, Seroc Oh, Myung Gwan Hahm, U. J. Kim, Byungjin Cho

2021APL Materials28 citationsDOIOpen Access PDF

Abstract

We herein demonstrate a brain-inspired synaptic device using a poly(vinylidene fluoride) and trifluoroethylene (PVDF-TrFE)/silicon nanowire (Si NW) based ferroelectric field effect transistor (FeFET). The PVDF-TrFE/Si NW FeFET structure achieves reliable synaptic plasticity such as symmetrical potentiation and depression, thanks to the reversible dynamics of the PVDF-TrFE permanent dipole moment. The calculated asymmetric ratio of potentiation and depression is as low as 0.41 at the optimized bias condition, indicating a symmetrical synaptic plasticity behavior. Pattern recognition accuracy based on the actual synaptic plasticity data of the synaptic device can be estimated via the CrossSim simulation software. Our simulation result reveals a high pattern recognition accuracy of 85.1%, showing a potential feasibility for neuromorphic systems. Furthermore, the inverter-in-synapse transistor consisting of the Si NW FeFET synapse and resistor connected in series is able to provide energy-efficient logic circuits. A total noise margin [(NMH + NML)/VDD] of 41.6% is achieved, and the power consumption [Ps = VDD(ID,L + ID,H)/2] of the logic-in-synapse transistor is evaluated to be 0.6 µW per logic gate. This study would shed light on the way toward a brain-inspired neuromorphic computing system based on the FeFET synapse device.

Topics & Concepts

Neuromorphic engineeringMaterials scienceNanowireTransistorLong-term potentiationSynapseOptoelectronicsFerroelectricitySynaptic plasticityResistorElectrical engineeringComputer scienceNeuroscienceVoltageArtificial neural networkArtificial intelligenceEngineeringChemistryBiologyDielectricBiochemistryReceptorAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering