# A feasibility study on the application of MICRO XRF for latent fingermark detection on porous surfaces

## TL;DR

This study explores using MICRO XRF to detect latent fingermarks on paper without damaging them, showing promising results.

## Contribution

The study demonstrates the feasibility of using MICRO XRF for nondestructive latent fingermark detection on porous surfaces.

## Key findings

- MICRO XRF successfully captured elemental signals from natural and artificial fingermarks on paper.
- Chlorine and potassium provided the clearest images for natural fingermarks, while chlorine was effective for artificial ones.
- The method shows potential for nondestructive detection regardless of the background color of the surface.

## Abstract

In the context of criminal investigations, latent fingermarks play a pivotal role in obtaining clues related to suspects. Presently, various physical, chemical, and optical methods are employed for latent fingermark detection. However, it is observed that when utilizing physical and chemical techniques, latent fingermarks may sometimes suffer damage during the extraction process. Consequently, the importance of optical methods such as spectroscopy, ATR‐FTIR, and MICRO XRF, which are comparatively less destructive, has been on the rise these days. This study aimed to evaluate the applicability of MICRO XRF for detecting both natural and artificial latent fingermarks on porous paper surfaces. Natural latent fingermarks were deposited by five donors after handwashing, while artificial latent fingermarks were produced by printing an artificial fingermark solution. MICRO XRF successfully captured elemental signals, with chlorine and potassium providing the clearest images for natural fingermarks and chlorine for artificial fingermarks. These findings demonstrate the potential of MICRO XRF to image latent fingermarks nondestructively regardless of background color. This work lays the foundation for further research to refine artificial formulations, optimize acquisition parameters, making it a promising choice for prioritizing latent fingermark detection methods.