The transient temperature rise in the active region in AlGaN/GaN high electron mobility transistors （HEMTs） is measured using an electrical method. The original data are smoothed and denoised by a nonparametric fitt...The transient temperature rise in the active region in AlGaN/GaN high electron mobility transistors （HEMTs） is measured using an electrical method. The original data are smoothed and denoised by a nonparametric fitting algorithm, called locally weighted scatterplot smoothing （LOWESS）. The thermal time-constant spectrum is extracted to analyze the physical structure of the heat-conduction path in A1GaN/GaN HEMTs. The thermal time- constant spectra extracted using the LOWESS algorithm are richer and the RC network obtained is greater compared with those with the traditional denoising method （multi-exponential fitting）. Thus, the analysis of the heat-flow path is more precise. The results show that the LOWESS nonparametric fitting algorithm can remove noise from measured data better than other methods and can retain the subtle variation tendency of the original discrete data. The thermal time-constant spectra extracted using this method can describe the subtle temperature variations in the A1GaN/GaN HEMT active region. This will help researchers to precisely analyze the layer composition of the heat-flow path.展开更多
SiC MOSFET栅极氧化物附近存在的陷阱缺陷造成其在高温高压场景下出现许多可靠性问题。提出了完整的基于瞬态电流法的陷阱表征方案,结合贝叶斯迭代反卷积算法实现对陷阱位置、时间常数和激活能的表征。基于自建陷阱测试平台在栅极和漏...SiC MOSFET栅极氧化物附近存在的陷阱缺陷造成其在高温高压场景下出现许多可靠性问题。提出了完整的基于瞬态电流法的陷阱表征方案,结合贝叶斯迭代反卷积算法实现对陷阱位置、时间常数和激活能的表征。基于自建陷阱测试平台在栅极和漏极施加不同组合的电学偏置,表征了微秒量级的两个陷阱,其时间常数分别为2×10^(-5)s和2.5×10^(-4)s,并观察到SiC MOSFET中存在同时受栅源电压和漏源电压影响的陷阱,这种现象在沟槽型器件中尤其显著,根据此特性可以分析陷阱的位置。本研究丰富了陷阱表征的信息,为陷阱的定位和表征提供了新的思路。展开更多
文摘The transient temperature rise in the active region in AlGaN/GaN high electron mobility transistors （HEMTs） is measured using an electrical method. The original data are smoothed and denoised by a nonparametric fitting algorithm, called locally weighted scatterplot smoothing （LOWESS）. The thermal time-constant spectrum is extracted to analyze the physical structure of the heat-conduction path in A1GaN/GaN HEMTs. The thermal time- constant spectra extracted using the LOWESS algorithm are richer and the RC network obtained is greater compared with those with the traditional denoising method （multi-exponential fitting）. Thus, the analysis of the heat-flow path is more precise. The results show that the LOWESS nonparametric fitting algorithm can remove noise from measured data better than other methods and can retain the subtle variation tendency of the original discrete data. The thermal time-constant spectra extracted using this method can describe the subtle temperature variations in the A1GaN/GaN HEMT active region. This will help researchers to precisely analyze the layer composition of the heat-flow path.
