Inspection of the Defect State Using the Mobility Spectrum Analysis Method

Author:

Ahn Il-Ho,Kim Deuk Young,Yang WoochulORCID

Abstract

Mobility spectrum analysis (MSA) is a method that enables the carrier density (and mobility) separation of the majority and minority carriers in multicarrier semiconductors, respectively. In this paper, we use the p-GaAs layer in order to demonstrate that the MSA can perform unique facilities for the defect analysis by using its resolvable features for the carriers. Using two proven methods, we reveal that the defect state can be anticipated at the characteristic temperature Tdeep, in which the ratio (RNn/Nh) that is associated with the density of the minority carrier Nn, to the density of the majority carrier Nh, exceeds 50%. (1) Using a p-GaAs Schottky diode in a reverse bias regime, the position of the deep level transient spectroscopy (DLTS) peak is shown directly as the defect signal. (2) Furthermore, by examining the current–voltage–temperature (I–V–T) characteristics in the forward bias regime, this peak position has been indirectly revealed as the generation–recombination center. The DLTS signals are dominant around the Tdeep, according to the window rate, and it has been shown that the peak variation range is consistent with the temperature range of the temperature-dependent generation–recombination peak. The Tdeep is also consistent with the temperature-dependent thermionic emission peak position. By having only RNn/Nh through the MSA, it is possible to intuitively determine the existence and the peak position of the DLTS signal, and the majority carrier’s density enables a more accurate extraction of the deep trap density in the DLTS analysis.

Funder

National Research Foundation

Publisher

MDPI AG

Subject

General Materials Science,General Chemical Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Improvement of mobility spectrum algorithm based on Hall measurement;2023 3rd International Conference on Robotics, Automation and Intelligent Control (ICRAIC);2023-11-24

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