Enhanced Down-Conversion Emission, High-Level Security, and Advanced Latent Fingerprint Visualization in La<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub>:Er<sup>3+</sup> Nanophosphor through Surface Modification and Deep Learning Analysis
D.R. Lavanya, B.R. Radha Krushna, K. Manjunatha, Bing-Li Lyu, Hsin‐Hao Chiu, Wei-Che Lo, Ming-Kang Ho, Tsu-En Hsu, Sheng Yun Wu, S.C. Sharma, Balanehru Subramanian, J. Malleshappa, Chivukula Srikanth, H. Nagabhushana
Abstract
High Resolution Image Download MS PowerPoint Slide This study explores surface modifications on Er 3+ -activated La 2 Zr 2 O 7 nanophosphors (NPs) through solution combustion, revealing a narrower band gap (3.1 eV) in surface-modified NPs. Under UV excitation (378 nm), these nanophosphors emit green light at 550 nm, notably enhanced by oleic acid (OA) modification, offering the potential for white light-emitting diode applications. Due to enhanced energy transfer processes, OA-modified NPs show 98.6% color purity and improved quantum efficiency (68.7%). Additionally, OA-modified NPs exhibit promise for UV-based forensic applications. This research also showcases the YOLOv8 algorithm’s robustness (mAP@50 of 0.78 for bifurcation, 0.72 for ridge-end) in fingerprint detection, aiding forensics. The deep learning method supports feature-matching fingerprint detection and advanced identification techniques. These findings offer insights into nanophosphor modification’s optical impact and advanced fingerprint identification methods, contributing to lighting technology and forensic applications.