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Hidayatullah, Abdul Rosyid
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Utilization of Luminescent Carbon Nanodots from Soybean Husk Wastes for Fingerprint Identification using Tracker Software Spectrum Analysis Dwandaru, Wipsar Sunu Brams; Hidayatullah, Abdul Rosyid; Listari, Eka Sentia Ayu; SL, Deby Grace
POSITRON Vol 13, No 1 (2023): Vol. 13 No. 1 Edition
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Univetsitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/positron.v13i1.57863

Abstract

Visible fingerprints (FPs) play a crucial role in forensic identification, and luminescent carbon nanodots (C-Dots) have shown promise in enhancing their visibility. However, the optimal concentration of C-Dots for effective coating remains largely unexplored. This research aimed to determine the ideal C-Dots concentration for FPs identification. The fingerprint (FP) patterns of two subjects, L and P, were analyzed, revealing intensity peaks in 200 mm - 250 mm and 100 mm - 150 mm, respectively. The FP patterns were observed using a light microscope and Tracker software spectral analysis. The C-Dots samples were produced with variation in concentrations of (%W/V) 40%, 43.4%, and 47.6%. The spectrophotometer ultraviolet-visible (UV-Vis) test of the C-Dots showed absorption peaks at 270 nm and 330 nm wavelengths. The photoluminescence test indicated that the C-Dots have cyan luminescence. The X-ray diffraction (XRD) test showed that the C-Dots were amorphous. The spectrometer Fourier transform infrared (FTIR) test showed the presence of C = C functional groups. The scanning electron microscope (SEM) images with 5000x magnification showed the surface morphology of the C-Dots mimicking crumpled papers. Using Tracker software, FPs were successfully differentiated, with the clearest visual FPs observed when using a C-Dots concentration of 43.4%. Thus, the optimal concentration of C-Dots for FP identification was 43.4%.