Unveiling excitation-independent visible photoluminescence of SnO2 nanodots for precise latent fingerprint identification powered by artificial intelligence

Abstract

The defect chemistry and defect-mediated photoluminescence (PL) of SnO₂ nanoparticles (NPs) is a topic of discussion nowadays, as the origin of the visible PL emissions of SnO₂ NPs are yet to be clearly understood. However, for successful applications of SnO₂ NPs, it is essential to understand the origin of visible PL emissions. Using complementary characterization techniques, we have shed light on the origin of visible PL emissions of crystalline SnO₂ nanodots (NDs), which have been synthesized using mechanical milling of larger SnO₂ NPs (average size ∼42 nm) for 10 h and 20 h. The PL emissions are found to be independent of the excitation wavelength. It is found that the visible emissions originate due to the presence of oxygen vacancies (V_O), tin interstitials (Sn_i) and tin vacancy (V_Sn) defect centers which can coexist in small SnO₂ particles. The coexistence of such defect centers is argued on the basis of theoretical reports and confirmed through Raman, electron paramagnetic resonance, and X-ray photoelectron spectroscopy analyses. As an important forensic application, detection of latent fingerprints (LFPs) using synthesized SnO₂ NDs has been demonstrated under ultraviolet light illumination. Furthermore, an artificial intelligence program has been used to match the LFPs on different substrates with the control LFP obtaining an outstanding matching score of 97.87%. These results ensure the effectiveness of SnO₂ NDs when integrated with digital processing algorithms, demonstrating their strong potential for practical applications in LFP recognition.