Cargando…

Statistical treatment of Photoluminescence Quantum Yield Measurements

The photoluminescence quantum yield (PLQY) is an important measure of luminescent materials. Referring to the number of emitted photons per absorbed photons, it is an essential parameter that allows for primary classification of materials and further is a quantity that is of utmost importance for ma...

Descripción completa

Detalles Bibliográficos
Autores principales: Fries, Felix, Reineke, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821858/
https://www.ncbi.nlm.nih.gov/pubmed/31666544
http://dx.doi.org/10.1038/s41598-019-51718-4
Descripción
Sumario:The photoluminescence quantum yield (PLQY) is an important measure of luminescent materials. Referring to the number of emitted photons per absorbed photons, it is an essential parameter that allows for primary classification of materials and further is a quantity that is of utmost importance for many detailed analyses of luminescent systems and processes. Determining the PLQY has been discussed in literature for many years and various methods are known. Absolute values can be measured directly using an appropriate setup. As this relies on the correct evaluation of photon-counts, it is a very sensitive method. Hence, systematic errors that can occur are discussed widely. However, of course those measurements also contain random uncertainties, which remain mainly unconsidered. The careful evaluation of both systematic and statistical errors of the PLQY is the only way to gain confidence in its absolute value. Here, we propose a way of evaluating the statistical uncertainty in absolute PLQY measurements. This relies on the combination of multiple measurements and the subsequent calculus of the weighted mean. The statistical uncertainty is then obtained as the standard deviation of the mean. This method not only quantifies the impact of statistical influences on the measurements, but also allows simple analysis of time-dependent systematic errors during the measurement and the identification of outliers.