Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET

ML (Machine Learning)-based artificial neural network (ANN) model is proposed to estimate the LER (line edge roughness)-induced performance variation in Fin-shaped Field Effect Transistor (FinFET). For a given LER features such as rms amplitude(Δ), correlation length along x-direction (A_X), and correlation length along y-direction (A_Y), the metrics for device performance such as on-state drive current, off-state leakage current, threshold voltage, and subthreshold swing can be computing-efficiently estimated with the ANN model.

Abstract licence: CC BY-NC-ND

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