TY - JOUR
T1 - Inspection of the Defect State Using the Mobility Spectrum Analysis Method
AU - Ahn, Il Ho
AU - Kim, Deuk Young
AU - Yang, Woochul
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/8
Y1 - 2022/8
N2 - 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 (Formula presented.) in which the ratio ((Formula presented.)) that is associated with the density of the minority carrier (Formula presented.), to the density of the majority carrier (Formula presented.), 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 (Formula presented.), 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 (Formula presented.) is also consistent with the temperature-dependent thermionic emission peak position. By having only (Formula presented.) 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.
AB - 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 (Formula presented.) in which the ratio ((Formula presented.)) that is associated with the density of the minority carrier (Formula presented.), to the density of the majority carrier (Formula presented.), 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 (Formula presented.), 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 (Formula presented.) is also consistent with the temperature-dependent thermionic emission peak position. By having only (Formula presented.) 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.
KW - deep level transient spectroscopy
KW - mobility spectrum analysis
KW - temperature-dependent minority carrier density
KW - thermally stimulated capacitance
UR - http://www.scopus.com/inward/record.url?scp=85137408384&partnerID=8YFLogxK
U2 - 10.3390/nano12162773
DO - 10.3390/nano12162773
M3 - Article
AN - SCOPUS:85137408384
SN - 2079-4991
VL - 12
JO - Nanomaterials
JF - Nanomaterials
IS - 16
M1 - 2773
ER -