Inspection of the Defect State Using the Mobility Spectrum Analysis Method

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 th...

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Veröffentlicht in:Nanomaterials (Basel, Switzerland) Switzerland), 2022-08, Vol.12 (16), p.2773
Hauptverfasser: Ahn, Il-Ho, Kim, Deuk Young, Yang, Woochul
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Sprache:eng
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Zusammenfassung: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.
ISSN:2079-4991
2079-4991
DOI:10.3390/nano12162773