A team of researchers from Nelson Mandela University, Gzeberha, South Africa, is working to improve fingerprint detection using carbon-coated nanoparticles.

Currently, fingerprints are dusted with a carbon-based powder that adheres to the moisture and grease left behind by the distinct patterns of ridges and valleys on a suspect’s fingertips.

Fingerprint ridge patterns of WLC-Mn-Fe2O3 nanocomposite powder obtained on aluminum foil at daylight. Source: Hybrid Advances (2023). DOI: 10.1016/j.hybadv.2023.100122

However, the new type of powder for dusting fingerprints reportedly enabled the researchers to better image the nanoscale details more clearly as it deepens the contrast between the fingerprint’s ridges and valleys.

The new powder is composed of manganese-doped iron oxide nanoparticles, which feature a high surface area and chemical reactivity that allows them to interact with the chemical compounds in fingerprint residues. Further, the nanoparticles are coated in an activated wool char, which is a chemically inert agricultural waste product that creates deeper contrast in fingerprints images, thereby making them easier to analyze.

To demonstrate the effectiveness of the new approach, the team created the iron oxide nanoparticles using an inexpensive, environmentally friendly "hydrothermal" method. The particles were then coated with the activated charred wool, which is safer to use than conventional carbon-based powders.

The team examined the powder's performance by dusting fingerprint residues on a non-porous aluminum surface and then using assorted types of electron microscopy and light spectroscopy to image them.

According to the researchers, the images produced revealed details down to a nanoscale resolution while also showing a starker contrast than other types of powder tested in previous studies.

The team suggests that the new material promises to help forensic investigators solve crimes more easily.

The technology is detailed in the article “Nanoarchitectonics of WLC-H₃PO₄–MnFe₂O₃ nanocomposite for latent fingerprint detection,” which appears in the journal Hybrid Advances.