Litcius/Paper detail

Compact model of retention characteristics of ferroelectric FinFET synapse with MFIS gate stack

Md. Aftab Baig, Hoang‐Hiep Le, Sourav De, Che-Wei Chang, Chia-Chi Hsieh, Xiao-Shan Huang, Yao‐Jen Lee, Darsen D. Lu

2021Semiconductor Science and Technology26 citationsDOI

Abstract

Abstract In this paper, multiple-fin n- and p-channel HfZrO 2 ferroelectric-FinFET devices are manufactured using a gate first process with post metalization annealing. The device transfer characteristics upon program and erase operations are measured and modeled. The drift in the transfer characteristics due to depolarization field and charge injection are captured using the shift in the threshold voltage along with time-dependent modeling of vertical field dependent mobility degradation parameters to develop a physical, computationally efficient, and accurate retention model for ferroelectric-FinFET devices. The modeled conductance is incorporated into deep neural network simulation platform CIMulator to analyze the role of conductance drift due to retention degradation, as well as the importance of the gap between high and low conductance states in improving the image recognition accuracy of neural networks.

Topics & Concepts

FerroelectricityConductanceMaterials scienceOptoelectronicsStack (abstract data type)DepolarizationThreshold voltageArtificial neural networkAnnealing (glass)VoltageField-effect transistorDegradation (telecommunications)Field effectElectronic engineeringComputer scienceTransistorElectrical engineeringCondensed matter physicsPhysicsEngineeringArtificial intelligenceDielectricEndocrinologyProgramming languageComposite materialMedicineAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesSemiconductor materials and devices