A new design of the universal Mössbauer spectrometer is presented. Hardware solution is based on commercial-available data acquisition devices working on the USB, PCI or PXI platform controlled by the main application running on the personal computer. Final application allows, in addition to Mössbauer spectra accumulation, the detailed analysis of the acquired detector signal in energy and time domains, and also to tune the velocity driving system separately. The experimental results show a high flexibility in various detectors and velocity transducers usage. It is easy to change the way of operation according to the different experimental requirements. This concept can be used with all common spectrometric benches with different velocity transducers, radioactive sources and gamma-ray detectors. This is a new approach in the Mössbauer spectrometer construction.
This work is focused on using the statistical methods and development of the filtration procedures for signal processing in Mössbauer spectroscopy. Statistical tools for noise filtering in the measured spectra are used in many scientific areas. The use of a pure statistical approach in accumulated Mössbauer spectra filtration is described. In Mössbauer spectroscopy, the noise can be considered as a Poisson statistical process with a Gaussian distribution for high numbers of observations. This noise is a superposition of the non-resonant photons counting with electronic noise (from γ -ray detection and discrimination units), and the velocity system quality that can be characterized by the velocity nonlinearities. The possibility of a noise-reducing process using a new design of statistical filter procedure is described. This mathematical procedure improves the signal-to-noise ratio and thus makes it easier to determine the hyperfine parameters of the given Mössbauer spectra. The filter procedure is based on a periodogram method that makes it possible to assign the statistically important components in the spectral domain. The significance level for these components is then feedback-controlled using the correlation coefficient test results. The estimation of the theoretical correlation coefficient level which corresponds to the spectrum resolution is performed. Correlation coefficient test is based on comparison of the theoretical and the experimental correlation coefficients given by the Spearman method. The correctness of this solution was analyzed by a series of statistical tests and confirmed by many spectra measured with increasing statistical quality for a given sample (absorber). The effect of this filter procedure depends on the signal-to-noise ratio and the applicability of this method has binding conditions.
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