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.

This paper analyses the influence of the applied microwave power output on the intensification of drying in the context of process kinetics and product quality. The study involved testing samples of beech wood (Fagus sylvatica L.). Wood samples were dried in the microwave chamber at: 168 W, 210 W, 273 W, 336 W and 378 W power output level. For comparison, wood was dried convectively at 40 ◦C and 87% air relative humidity. The analysis of drying process kinetics involved nonlinear regression employing the Gompertz model. Dried samples were subjected to static bending tests in order to specify the influence of the applied microwave power on modulus of elasticity (MOE) and modulus of rapture (MOR). The obtained correlations of results were verified statistically. Analysis of drying kinetics, strength test results and Tukey’s test showed that the applied microwaves of a relatively low level significantly shortened the drying time, but did not cause a reduction in the final quality of dried wood, compared with conventional drying.