EEMizer: Automated modeling of fluorescence EEM data

For many years it has been known that PARAFAC offers a very attractive approach for modeling fluorescence excitation–emission matrices. Due to the uniqueness of the PARAFAC model and analogy between the structure of fluorescence data and the PARAFAC model, it is apparent that PARAFAC can resolve overlapping signals into pure spectra and relative concentrations under mild conditions. There are hundreds of applications exemplifying this, but still the use of PARAFAC has not spread from chemometrics to more main-stream analytical chemistry. Many reasons can be offered to explain this, but one seems to be that in practice it is difficult for chemometric novices to make use of PARAFAC. Selection of wavelengths, handling of scatter and of outliers are all issues that must be dealt with in order to build a good PARAFAC model. In this paper, a new algorithm called EEMizer is developed that aims to automate the use of PARAFAC. Through several examples it is shown how this algorithm can provide appealing PARAFAC models of data that would otherwise be hard to model.