Latent fingermark detection using functionalised silicon oxide nanoparticles: Optimisation and comparison with cyanoacrylate fuming. (October 2020) - Lee, Po Lun Timothy; Kanodarwala, Fehmida K.; Lennard, Chris; Spindler, Xanthe; Spikmans, Val; Roux, Claude; Moret, Sébastien
Highlights: Further fingermark detection optimisation was completed on RuBpy-doped CES-SiO2 NPs. Streamlined treatment procedure was introduced with the use of a shaking incubator. Relatively, the SiO2 NPs were inferior to the benchmark cyanoacrylate fuming method. The SiO2 NPs were judged to be less donor dependent, but more substrate dependent. The above trait could be valuable for fingermark detection in casework scenarios. Abstract: Among the different types of nanoparticles (NPs) proposed for fingermark detection, silicon oxide nanoparticles (SiO2 NPs) are arguably the most promising due to their unique characteristics. In this study, carboxyl-functionalised SiO2 NPs doped with luminescent ruthenium complex—RuBpy-doped CES-SiO2 NPs—were further studied to investigate their effectiveness for latent fingermark detection. A modified version of the functionalised SiO2 NPs with a lower amount of surface functionalisation is proposed for improved fingermark detection effectiveness. A shaking incubator was also incorporated into the fingermark detection process to offer a more viable treatment approach in comparison to the previously published method. The shaking incubator offered a more robust application approach, as well as improved fingermark detection quality. To gain an insight into fingermark detection effectiveness relative to benchmark techniques, the performance of the optimised RuBpy-doped CES-SiO2 NPs was compared to that of a benchmark fingermark detection method—cyanoacrylate fuming (CAF) followed by luminescent dye staining. Relative fingermark detection effectiveness across the two techniques was evaluated via the treatment of 1724 fingermark specimens. It was concluded that, in general, the benchmark method provided superior detection results. It was evident that the SiO2 NPs are less affected by donor variability but are more dependent on substrate types. Such characteristics are encouraging as they could be favourable to practitioners in casework scenarios where the substrate is known but donor variability is obscure prior to fingermark processing. It should be noted that the overall effectiveness of the proposed NP-based technique will need to be improved before it could be considered for operational implementation.