Development and comparison of the techniques for solving the inverse problem in photoacoustic characterization of semiconductors

In this work, theoretically/mathematically simulated (TMS) model is presented for the photoacoustic (PA) frequency response of a semiconductor in a minimum volume PA cell. By analyzing of the TMS model, the influences of thermal diffusivity and linear coefficient of thermal expansion on silicon sample PA frequency response were investigated and two methods were developed for their estimation. The first one is a self consistent inverse procedure for solving the exponential problems of mathematical physics, based on regression. The second one, a well trained three-layer perceptron with back propagation, based upon theory of artificial neural networks, is developed and presented. These two inverse problem solving concepts are applied to thermo-elastic characterization of silicon, compared and discussed in the domain of semiconductor characterization.