Programme

Rasmus Bro

How PARAFAC and PARAFAC2 have changed the analysis of fluorescence and chromatographic data

Multiway data are central in modern analytical chemistry, yet they are often “flattened” into matrices, losing structure and chemical interpretability. This talk highlights how PARAFAC and PARAFAC2 address two core application domains; each with its own data challenges and payoffs.

First, I will show how PARAFAC has transformed the analysis of fluorescence excitation–emission matrices (EEMs) by decomposing EEM datasets into chemically meaningful components that can be interpreted as underlying fluorophore “fingerprints” and sample-wise contributions.

Second, I will demonstrate why PARAFAC2 is often the enabling model for GC–MS data, where retention-time shifts and peak shape variability violate standard trilinear assumptions. Using real GC–MS examples, I will illustrate how PARAFAC2 handles time misalignment while still producing interpretable component profiles and improved quantitative/qualitative insight compared with unfolding-based workflows.

Birgit Götzinger

Natalie Gerhardt

Thomas Rose