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The Recognition of Sweat Latent Fingerprints with Green-Emitting Carbon Dots.

Dan ZhaoWenting MaXincai Xiao
Published in: Nanomaterials (Basel, Switzerland) (2018)
The recognition of fingerprints has played an extremely important role in criminal investigations, due to its uniqueness. This paper reports on the recognition of sweat latent fingerprints using green-emitting, environment-friendly carbon dots prepared with DL-malic acid and ethylenediamine, and the exploration of impacting factors in the development process of fingerprints. The experiments showed that better fingerprint images could be obtained when the latent fingerprints are developed in green-emitting carbon dots with pH 9 for 30 min, at room temperature. The reported method was also effective for latent fingerprints on a variety of substrates, as well as for those water-immersed ones, where the developed fingerprint remained stable after long-term preservation. Furthermore, the fluorescent three-dimensional fingerprint image could provide direct and simple evidence on pressing habits. The objective of this paper was to present this method. The method may help to narrow the range of suspects during criminal investigations and in forensic science.
Keyphrases
  • quantum dots
  • room temperature
  • deep learning
  • fluorescent probe
  • energy transfer
  • living cells
  • quality control
  • light emitting
  • convolutional neural network
  • machine learning
  • adverse drug