Mingyu Zhuang, Zhiyuan Wang, Baochuan Liu, Jiawei Zhang, Qian Xin, Aimin Song
Neural-network-assisted EKV compact modeling for complementary oxide thin-film transistors
Appl. Phys. Lett. 129, 123504 (2026)
DOI: 10.1063/5.0349365
1. Shandong Technology Center of Nanodevices and Integration, Uni. Shandong (CN)
2. Department of Electrical and Electronic Engineering, Uni. Manchester (UK)
3. Southern University of Science and Technology, Shenzhen (CN)
ABSTRACT: This work reports a neural-network-assisted Enz–Krummenacher–Vittoz (EKV) compact-modeling framework for complementary oxidethin-film transistors (TFTs). The neural network is used as a bias-dependent effective-parameter generator for the equivalent mobility and onset voltage, while the drain current is calculated by the analytical EKV current core. This strategy represents defect-, contact-, and bias-dependent nonidealities of oxide TFTs through effective quantities without replacing the current equation with a black-box neural-networkpredictor. The model is validated using both n-type indium–gallium–zinc oxide TFTs and p-type tin monoxide (SnO) TFTs, achieving mean absolute percentage errors of 0.56% and 0.36%, respectively. The learned effective parameters further provide an EKV-constrained compact representation of bias-dependent transport capability and channel-onset behavior obtained from global fitting of the measuredoutput-characteristic dataset, rather than serving as directly extracted material parameters. The trained model is translated into aPSpice-compatible library and applied to complementary inverter simulation, showing good agreement with measured voltage-transfer characteristics and reproducing the main transient response characteristics. These results demonstrate an accurate, analytically structured, and Simulation Program with Integrated Circuit Emphasis-compatible compact-modeling strategy that links bias-dependent oxide-TFTtransport to circuit-level simulation.
FIG. (a) Equivalent parasitic‑capacitance and measurement‑loading network used in the transient simulation of the complementary SnO/IGZO inverter. (b) Simulated output waveforms for different values of the additional external capacitance.
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