Photoacoustic signal and noise analysis for Si thin plate: Signal correction in frequency domain

Abstract

Methods for photoacoustic signal measurement, rectification, and analysis for 85 μm thin Si samples in the 20-20 000 Hz modulation frequency range are presented. Methods for frequency-dependent amplitude and phase signal rectification in the presence of coherent and incoherent noise as well as distortion due to microphone characteristics are presented. Signal correction is accomplished using inverse system response functions deduced by comparing real to ideal signals for a sample with well-known bulk parameters and dimensions. The system response is a piece-wise construction, each component being due to a particular effect of the measurement system. Heat transfer and elastic effects are modeled using standard Rosencweig-Gersho and elastic-bending theories. Thermal diffusion, thermoelastic, and plasmaelastic signal components are calculated and compared to measurements. The differences between theory and experiment are used to detect and correct signal distortion and to determine detector and sound-card characteristics. Corrected signal analysis is found to faithfully reflect known sample parameters.

Electro-acustic influence of the measuring system on the photoacoustic signal amplitude and phase in frequency domain

“…For this kind of analysis, we performed the test using a thin Si plate sample, prepared from 3  5 cm, n-type, <100> oriented Si wafer, with the constant bulk values given in Table 1 as a PA signal generator. Because the Si plate is well-characterized (Markushev et al, 2015), we used it as a calibration sample to deduce the apparatus constants.…”

“…In general, the transfer function defined with equation 2explains the PA signal distortion originated from the instruments used to construct the apparatus. Although we find that two high-pass filters are appropriate, there is no reason why one or even more than two would not be appropriate for other apparatuses (Markushev et al, 2015). The signal S(j) detected by our microphone and sound-card in the low frequency range (f < 1 kHz) is the product of the photoacoustic signal generated by sample P(j) and H e total (j).…”

“…First, there is a big influence of noise that comes from different sources. Second, there is some influence of the instruments applied within the experimental system that distorts the signal, especially at the ends of the frequency interval (Markushev et al, 2015;Todorović et al, 2013).…”

The surface recombination velocity and bulk lifetime influences on photogenerated excess carrier density and temperature distributions in n-type silicon

“…The temperature changes can be detected measuring directly a sample surface temperature variations or perturbations of temperature-dependent thermodynamic parameters, such as pressure or density. These parameters changes are detected with various transducers, assuming that the transducer signal intensity is proportional to the amplitude of the measured parameter and depends of temperature propagation across the investigated sample and its environment [18][19][20]. There are several different experimental schemes that can be used to efficiently detect temperature changes in irradiated semiconductor samples having the form of circular or rectangular plates.…”

“…There are several different experimental schemes that can be used to efficiently detect temperature changes in irradiated semiconductor samples having the form of circular or rectangular plates. One of the most simple and popular among them is the so-called PA transmission detection configuration [20][21][22]. Such scheme assumes that the sample "front" surface is irradiated by the modulated optical beam, and the transducer detects the signal behind the "rear" one.…”