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<p>This review examines modeling methodologies for amorphous metal oxide thin-film transistors (a-MO TFTs). It covers underlying device physics, charge transport mechanisms including multiple trapping and release, surface potential, mobility, drain current, and capacitance models, alongside bias, temperature, and mechanical stress effects. Comparisons of compact models highlight trade-offs in accuracy, parameter extraction, and circuit-level validation. Future directions emphasize machine learning integration, unified multi-material frameworks, and strain-aware simulations.</p>

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Model representation in amorphous metal oxide thin-film transistors: a critical review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月30日

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  • Hassan Ul Huzaibi,
  • Su-Ting Han,
  • Meng Zhang

摘要

This review examines modeling methodologies for amorphous metal oxide thin-film transistors (a-MO TFTs). It covers underlying device physics, charge transport mechanisms including multiple trapping and release, surface potential, mobility, drain current, and capacitance models, alongside bias, temperature, and mechanical stress effects. Comparisons of compact models highlight trade-offs in accuracy, parameter extraction, and circuit-level validation. Future directions emphasize machine learning integration, unified multi-material frameworks, and strain-aware simulations.