Mono-and biexponential fits were performed utilizing EasyTau 2 software. For custom distribution analysis we used custom python scripts. There, numpy package was utilized for handling mathematics, Matplotlib package for visualization, numpy/scipy fitting procedures as wrapped in lmfit package for the reconvolution process itself (the one providing sophisticated wrapping classes for multiple model trials) and quadpy package for handling numerical integration where required Considering our assumption on particle formation, it was reasonable to attempt to fit decays to stretched exponentials of form [Equation ]. They are often utilized to describe exciton transport distributions in investigations of conjugated polymers and crystalline solids. And serve well to the purpose of complicated decay description in biological media. Our system, however, did not show any good chi-squared values even after we modified the model to accommodate several stretched exponentials and additional monoexponents.