2008
DOI: 10.1007/s10812-009-9130-1
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Analytical relations for luminescence intensities accounting for reabsorption

Abstract: Mathematical relations defining distortions from true values of photoluminescence intensities that arise during measurements due to absorption at the luminescence frequencies are derived for various experimental designs. The adequacy of the derived relations is confirmed by special experiments. The relations allow one to define correctly the contours, widths, and maximum frequencies of luminescence bands of absorbing media and to deduce absorption coefficients of substances from luminescence measurements.Intro… Show more

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Cited by 9 publications
(15 citation statements)
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“…Such relations have been obtained recently for photoluminescence and photoluminescence excitation (PLE) spectra. In the first case, equations are used that determine the changes in the photoluminescence intensities as a result of re-absorption of photoluminescence in the analyte medium [5]. In the second case, the methods are based on the dependence of the photoluminescence intensity on the absorption coefficients of a multicomponent medium, [6,7].…”
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confidence: 99%
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“…Such relations have been obtained recently for photoluminescence and photoluminescence excitation (PLE) spectra. In the first case, equations are used that determine the changes in the photoluminescence intensities as a result of re-absorption of photoluminescence in the analyte medium [5]. In the second case, the methods are based on the dependence of the photoluminescence intensity on the absorption coefficients of a multicomponent medium, [6,7].…”
mentioning
confidence: 99%
“…In the second case, the methods are based on the dependence of the photoluminescence intensity on the absorption coefficients of a multicomponent medium, [6,7]. From the relations obtained in [5][6][7], equations are derived that make it possible to find the absorption coefficients of a medium from the measured intensity.The problem of finding the absorption coefficients according to the procedure outlined above is an inverse problem. In order to properly solve inverse problems with original data obtained experimentally with random errors,…”
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confidence: 99%
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