Application of Computational Intelligence to Investigation of Defect Centers in Semi-Insulating Materials by Photoinduced Transient Spectroscopy

Abstract

AbstractA computational intelligence algorithm has been applied to extracting trap parameters from the photocurrent relaxation waveforms recorded at the temperature range of 20-320 K for semi-insulating (SI) InP samples. Using the inverse Laplace transform procedure, the spectral surfaces, visualized in the three dimensional space as functions of temperature and emission rate, are calculated. The processes of thermal emission of charge carriers from defect centers manifest themselves as the sharp folds on the spectral surface. Using a set of Gaussian functions, the approximating surface is created and the ridgelines of the folds, giving the temperature dependences of the emission rate for the detected traps, are determined. The approximation is performed using the support vector machine (SVM) algorithm which allows for trading off between the model complexity and fitting accuracy. The new approach is exemplified by comparing the defect structure of SI InP wafers after annealing in iron phosphide and pure phosphorous atmospheres.