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Abstract

Electrical properties of semiconductor materials depend on their defect structure. Point defects, impurities or admixture contained in a semiconductor material, strongly affect its properties and determine the performance parameters of devices made on its basis. The results of the currently used methods of examining the defect structure of semiconductor material are imprecise due to solution of ill-posed equations. These methods do not allow for determination of concentration of the defect centers examined. Improving the resolution of the obtained parameters of defect centers, determining their concentration and studying changes in the resistivity of semi-insulating materials can be carried out, among others, by modelling changes in the concentration of carriers in the conduction and valence bands. This method allows to determine how charge compensation in the material affects the changes in its resistivity. Calculations based on the Fermi-Dirac statistics can complement the experiment and serve as a prediction tool for identifying and characterizing defect centers. Using the material models (GaP, 4H–SiC) presented in the article, it is possible to calculate their resistivity for various concentrations of defect centers in the temperature range assumed by the experimenter. The models of semi-insulating materials presented in the article were built on the basis of results of testing parameters of defect centers with high-resolution photoinduced transient spectroscopy (HRPITS). The current research will allow the use of modelling to determine optimal parameters of semi-insulating semiconductor materials for use in photoconductive semiconductor switches (PCSS).
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Authors and Affiliations

Marek Suproniuk
1

  1. Military University of Technology, Faculty of Electronics, Institute of Electronic Systems, gen. S. Kaliskiego 2, Warsaw
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Abstract

This article discusses the performance of an algorithm for detection of defect centers in semiconductor materials. It is based on direct parameter approximation with nonlinear regression to determine the parameters of thermal emission rate in the photocurrent waveforms. The methodology of the proposed algorithm was presented and its application procedure was described and the results of its application can be seen in measured photocurrent waveforms of a silicon crystal examined with High-Resolution Photoinduced Transient Spectroscopy (HRPITS). The performance of the presented algorithm was verified using simulated photocurrent waveforms without and with noise at the level of 10 -2. This paper presents for the first time the application of the direct approximation method using modern regression and clustering algorithms for the study of defect centers in semiconductors.
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Authors and Affiliations

Witold Kaczmarek
1
Marek Suproniuk
1
Karol Piwowarski
1
Bogdan Perka
1
Piotr Paziewski
1

  1. Institute of Electronic Systems, Department of Electronics, Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warszawa, Poland

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