Investigation of temperature-dependent performance degradation in AlGaN/InGaN/GaN HEMTs: Implications for device reliability and efficiency
This paper comprehensively analyzes the temperature-dependent performance of an AlGaN/InGaN/GaN high electron mobility transistor. Thermal simulations were conducted to evaluate the impact of both model temperature and lattice temperature on device performance. Simulated DC characteristics are valid...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-06-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0271310 |
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| Summary: | This paper comprehensively analyzes the temperature-dependent performance of an AlGaN/InGaN/GaN high electron mobility transistor. Thermal simulations were conducted to evaluate the impact of both model temperature and lattice temperature on device performance. Simulated DC characteristics are validated against experimental data using the 2D device simulation tool, TCAD Atlas. Key DC parameters such as transfer characteristics (Ids–Vgs), output characteristics (Ids–Vds), transconductance (gm), and threshold voltage (Vth) are analyzed over a temperature range of 260–360 K. In addition, radio-frequency analysis is conducted to evaluate important figures of merit, such as the current-gain cutoff frequency (fT), across the same temperature range. The results show that at elevated temperatures, saturation current and the linear region characteristics degrade due to reduced carrier mobility, observed consistently in both model and lattice-based studies. However, the effects of temperature variation on the lattice are more pronounced, primarily due to the additional impact of self-heating, which intensifies performance degradation. Nonetheless, both the threshold voltage and the density of two-dimensional electron gas (2DEG) sheets increase as temperature rises. These findings highlight the critical importance of temperature selection in the operation of GaN HEMTs, which significantly influences key performance metrics. |
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| ISSN: | 2158-3226 |