The use of an optimized DRIFTS-FTIR method for the forensic analysis and classification of silicone condom lubricants

Condom residues may be encountered in forensic investigations as traces left in sexual assault or rape cases. Considering casework samples analysis, where material from swabs will need to be extracted, Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) was reported as the most relevant method for trace evidence analysis. However, there has been no study to identify which specific parameters were the most suitable for the analysis of silicone-based lubricants, especially in terms of repeatability of the analyses. This study looked at the resolution and number of scans with the aim of optimizing these parameters for polydimethylsiloxane (PDMS) analysis and detection. Experimental parameters were refined while performing a full factorial experimental design (FFD) for the screening and extended to a face centered central composite design (FCCD) for the optimisation. Repeatability of the results was also investigated using principal component analysis (PCA) and hierarchical cluster analysis (HCA) in order to select the most relevant analytical parameters. The optimized DRIFTS parameters were then used to collect data from reference material and from traces after a transfer in a vaginal matrix has occurred. Discrimination models were built with DRIFTS data and compared to pre-existing models built with Attenuated Total Reflectance (ATR)-FTIR data. Condom traces were recovered from volunteers who had sexual intercourse using different types of silicone-lubricated condoms. The corresponding traces characteristics were investigated and analysed. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Automated summary

This study aimed to optimize the parameters for polydimethylsiloxane (PDMS) analysis and detection by looking at resolution and number of scans. Experimental parameters were refined through a full factorial experimental design (FFD) and extended to a face centered central composite design (FCCD) for optimization. Repeatability of the results was investigated using principal component analysis (PCA) and hierarchical cluster analysis (HCA) to select the most relevant analytical parameters.