Surface chemical differentiation of fingermark samples by ToF-SIMS and multivariate statistical analysis

This study demonstrates the applicability of time-of-flight secondary ion mass spectrometry (ToF-SIMS) combined with multivariate statistical analysis (MVSA) for the chemical differentiation of fingermarks from eight donors. Multiple ToF-SIMS spectra were measured on a small area of each fingermark sample to assess whether chemical variability between the fingermark samples exceeded chemical variability within each individual one. Principal component analysis (PCA) enabled the separation of fingermark samples from different donors, while multivariate curve resolution (MCR) further resolved individual fingermark-associated MCR factors and revealed characteristic m/z signals contributing to fingermark sample discrimination. Some characteristic signals were confirmed as unique donor-associated signals within the examined dataset, whereas others still enabled donor differentiation because their relative intensities within the ToF-SIMS spectra differed across the spectral dataset obtained from different donors. This work demonstrates that combining ToF-SIMS and MVSA can provide a promising complementary methodology to conventional fingermark morphology analysis, particularly when only small areas of fingermark residue are available.