Abstract
In this study, Ho³⁺-doped BaGd₂ZnO₅ (1–11 mol%) nanophosphors (BGZO:Ho3+ NPs) were synthesized through combustion synthesis, utilizing Spirulina leaf extract as a natural green fuel. Luminescence studies revealed that the BGZO:Ho³⁺ phosphors exhibit a strong green emission primarily resulting from the 5S2→5I8 transition of Ho³⁺ ions. The optimal doping concentration was found to be 7 mol % Ho³⁺, which yielded the highest luminescence efficiency. Furthermore, the CIE chromaticity coordinates for BGZO:7Ho³⁺ were accurately determined to be (0.2595, 0.7290), with a color purity (CP) of 99.98 %. These results indicate the potential of this material for producing high-quality green emissions suitable for solid-state lighting and display applications. Optimized BGZO:Ho3+ NPs were utilized for latent fingerprints (LFPs) development via the powder dusting method. Under 365 nm UV light, the NPs effectively revealed Level I-III fingerprints (FPs) details, including ridge patterns, minutiae, and sweat pore features, on various substrates such as glass, plastic, and metal. The high luminescence of BGZO:Ho3+ NPs under UV illumination offers a sensitive and non-destructive method for enhancing FPs visibility, making it a promising tool for forensic applications. In addition, this study focuses on FPs poroscopy, examining the detailed pore structure of LFPs for forensic identification. Using advanced imaging techniques, we analyzed sweat pore distribution, size, and shape across various substrates and conditions. A detailed poroscopic analysis of LFPs, focusing on key parameters such as pore interspacing (165–332 μm), pore size (4140–9956 μm2), shapes (elliptical, rhomboid, triangular, square and rectangular) and pore angle (167°–179°). Further, a mathematical model was developed using Python-based software to enable precise and accurate analysis of FPs, enhancing clarity and identification accuracy, supporting the uniqueness of FPs beyond ridge patterns. The results demonstrate the potential of poroscopy for enhancing FPs analysis by offering an additional layer of precise biometric data.
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