Characterizing And Classifying Water-Based Lubricants Using Direct Analysis In Real Time®-Time Of Flight Mass Spectrometry
Keywords
Classification; DART-MS; High resolution mass spectrometry; Lubricants
Abstract
Lubricant analysis is a relatively recent addition to the examination protocol in sexual assault cases by the forensic science community. Currently, lubricants cannot be unequivocally identified, although their presence can be determined based on the detection of a few chemical components, i.e. polydimethylsiloxane, polyethylene glycol, glycerol or nonoxynol-9. Confirmation of their presence typically requires that an authentic reference sample be submitted and compared to the unknown sample to determine if they potentially came from the same source. In this study, 33 individual personal water-based lubricants were characterized by direct analysis in real time-time of flight mass spectroscopy (DART-TOFMS). The resultant mass spectral data were evaluated using well-established multivariate statistical techniques, such as principal component and linear discriminant analysis. Statistical analysis revealed six different groupings within the data that could be correlated to sub-categories of water-based lubricants that contain additives in the form of anesthetics, sensation enhancers and flavorings. This variability in the personal lubricant sources can be utilized to aid in identifying the specific type of lubricant when only a questioned sample is available.
Publication Date
9-1-2016
Publication Title
Forensic Science International
Volume
266
Number of Pages
73-79
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.forsciint.2016.04.036
Copyright Status
Unknown
Socpus ID
84969787315 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84969787315
STARS Citation
Maric, Mark and Bridge, Candice, "Characterizing And Classifying Water-Based Lubricants Using Direct Analysis In Real Time®-Time Of Flight Mass Spectrometry" (2016). Scopus Export 2015-2019. 3562.
https://stars.library.ucf.edu/scopus2015/3562