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<p>This study presents a new approach for extracting small-signal parameters in enhancement-mode MgZnO/ZnO high electron mobility transistors (HEMTs), combining a traditional analytical method with advanced optimization algorithms. The extrinsic parameters encompass parasitic capacitances, inductances, and resistances, which are extracted under pinch-off conditions. In contrast, the intrinsic parameters of the small-signal equivalent circuit (SSEC), including gate forward and backward conductance, are determined with precision. Three advanced optimization techniques, quantum genetic algorithm (QGA), covariance matrix adaptation evolution strategy (CMA-ES), and iterative-focusing tree-structured Parzen estimator (IF-TPE), are utilized to minimize the discrepancy between modeled and measured <i>S</i>-parameters. The optimized SSEC models are validated by comparing them with TCAD simulations and existing experimental benchmarks, demonstrating that the QGA-based approach attains the lowest error rate of 1.1%. The MgZnO/ZnO HEMT structure exhibits a threshold voltage of 1.15&#xa0;V, a maximum extrinsic transconductance of 1520&#xa0;mS/mm, a saturation current of 1.6&#xa0;A/mm, a unity-gain cutoff frequency (<i>f</i><sub><i>T</i></sub>) of 540&#xa0;GHz, and a maximum oscillation frequency (<i>f</i><sub>max</sub>) of 770&#xa0;GHz, as demonstrated by DC and RF simulations. The results validate the appropriateness of the proposed device and modeling methodology for high-frequency, high-power microwave, and millimeter-wave applications.</p>

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Small-signal parameter extraction of enhancement-mode MgZnO/ZnO HEMT using advanced optimization algorithms for high-frequency microwave applications

  • 期刊论文

  • 发表日期：

    2026年6月25日

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  • K. Vinothkumar,
  • A. Kaleel Rahuman

摘要

This study presents a new approach for extracting small-signal parameters in enhancement-mode MgZnO/ZnO high electron mobility transistors (HEMTs), combining a traditional analytical method with advanced optimization algorithms. The extrinsic parameters encompass parasitic capacitances, inductances, and resistances, which are extracted under pinch-off conditions. In contrast, the intrinsic parameters of the small-signal equivalent circuit (SSEC), including gate forward and backward conductance, are determined with precision. Three advanced optimization techniques, quantum genetic algorithm (QGA), covariance matrix adaptation evolution strategy (CMA-ES), and iterative-focusing tree-structured Parzen estimator (IF-TPE), are utilized to minimize the discrepancy between modeled and measured S-parameters. The optimized SSEC models are validated by comparing them with TCAD simulations and existing experimental benchmarks, demonstrating that the QGA-based approach attains the lowest error rate of 1.1%. The MgZnO/ZnO HEMT structure exhibits a threshold voltage of 1.15 V, a maximum extrinsic transconductance of 1520 mS/mm, a saturation current of 1.6 A/mm, a unity-gain cutoff frequency (fT) of 540 GHz, and a maximum oscillation frequency (fmax) of 770 GHz, as demonstrated by DC and RF simulations. The results validate the appropriateness of the proposed device and modeling methodology for high-frequency, high-power microwave, and millimeter-wave applications.