Dye-Doped Cellulose Nanocrystals as Novel Dusting Powders for Visualizing Latent Fingerprints

Abstract

Powder-dusting method based on the visual contrast between background surface and powder-covered ridges of fingerprint, is widely used to develop the invisible latent fingerprints (LFPs) left at crime scenes. Recently, the development of nano-sized powders with excellent optical performances have been extensively explored. In this work, we looked for environmentally friendly and low-toxicity cellulose nanocrystals as the novel support. Using dye-doped cellulose nanocrystals as novel dusting powders, two dyes (phenylfluorone, and curcumin) were adsorbed on the cellulose nanocrystals by a simple batch adsorption method. The dye-doped cellulose nanocrystals (such as phenylfluorone-doped cellulose nanocrystals (PDCN) and curcumin-doped cellulose nanocrystals (CDCN)) containing 2% of the loaded mass of both dyes with bright green fluorescence have been developed to visualize the LFPs on the surfaces of various substrates (such as glass slide, printing paper, orange plastic card, tile, stainless steel, compact disc, red plastic packing, copper foil and aluminum foil). The images of the LFPs can been exhibited by both the dye-doped cellulose nanocrystals with the sufficient affinity with the ridges of LFPs. High-quality ridge details with features at second and third level can be detected based on CDCN, whereas PDCN only displays the secondary-level features of ridge details. For a comparison, the CDCN illustrates higher sensitivity, higher selectivity, and better contrast, especially for detecting fresh and non-fresh LFPs on porous and non-porous substrates, and has the potential to use practically in forensic science.

Supplementary files

Article information

Article type
Paper
Submitted
17 May 2024
Accepted
01 Aug 2024
First published
06 Aug 2024

Anal. Methods, 2024, Accepted Manuscript

Dye-Doped Cellulose Nanocrystals as Novel Dusting Powders for Visualizing Latent Fingerprints

X. Yao, G. Li, J. Wang, C. Tang, D. Li , N. You, Z. Li, S. Zhang and W. Mao, Anal. Methods, 2024, Accepted Manuscript , DOI: 10.1039/D4AY00923A

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