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Abstract <p>This study examines the impact of gate dielectric materials and gate-to-drain spacing (<i>L</i><sub>GD</sub>) on the performance of AlGaN/GaN HEMT biosensors for uric acid (UA) biomolecule detection using TCAD simulations. The commonly used gate dielectrics materials such as SiO<sub>2</sub>, HfO<sub>2</sub>, Al<sub>2</sub>O<sub>3</sub>, and Si<sub>3</sub>N<sub>4</sub> have been analyzed under UA concentrations of 55 to 460 µM. The SiO<sub>2</sub> exhibited highest drain current shift (Δ<i>I</i><sub>DS</sub> = 8&#xa0;mA/mm) and sensitivity (145.5 µA/µM), while Al<sub>2</sub>O<sub>3</sub> achieved the largest threshold voltage shift (Δ<i>V</i><sub>TH</sub> = 1.72&#xa0;V) and sensitivity (31.3 V/mM). Changes in <i>L</i><sub>GD</sub> showed a peak in both Δ<i>V</i><sub>TH</sub> and Δ<i>I</i><sub>DS</sub> at an optimal spacing, after which sensitivity decline can be attributed to the increased series resistance and weak electrostatic control. These findings highlight the importance of material selection and device geometry in enhancing GaN-based biosensor sensitivity.</p>

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Design Optimization of AlGaN/GaN HEMT Biosensors for Enhanced Biomolecule Sensitivity: Gate Dielectric and Spacing Effects

  • 期刊论文

  • 发表日期：

    2025年10月24日

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  • Sarita Singh,
  • Alokojjwal Das,
  • Sushanta Bordoloi,
  • Ashok Ray

摘要

Abstract

This study examines the impact of gate dielectric materials and gate-to-drain spacing (LGD) on the performance of AlGaN/GaN HEMT biosensors for uric acid (UA) biomolecule detection using TCAD simulations. The commonly used gate dielectrics materials such as SiO2, HfO2, Al2O3, and Si3N4 have been analyzed under UA concentrations of 55 to 460 µM. The SiO2 exhibited highest drain current shift (ΔIDS = 8 mA/mm) and sensitivity (145.5 µA/µM), while Al2O3 achieved the largest threshold voltage shift (ΔVTH = 1.72 V) and sensitivity (31.3 V/mM). Changes in LGD showed a peak in both ΔVTH and ΔIDS at an optimal spacing, after which sensitivity decline can be attributed to the increased series resistance and weak electrostatic control. These findings highlight the importance of material selection and device geometry in enhancing GaN-based biosensor sensitivity.