Green emitting Sr2ZnGe2O7:Mn2+ phosphor: A dual function material for w- LEDs and YOLOv8x based latent fingerprint detection

Abstract

Thermally robust, narrow-band green phosphors are vital for advancing white light emitting diodes (w-LEDs). In this study, we examined Sr₂ZnGe₂O₇:x% Mn²⁺ (SZGO:x% Mn²⁺) phosphors, with Mn²⁺ concentrations ranging from 0 to 6 mol %, synthesized via a solution combustion method using Camellia sinensis (C.S.) extract as the fuel. Upon monitoring the 539 nm emission, the excitation spectrum of the SZGO:4 %Mn²⁺ phosphors revealed two distinct ultraviolet (UV) excitation bands. When exposed to UV light, the phosphor produces a brilliant green emission at 539 nm, which corresponds to the characteristic Mn²⁺ transition (⁴T₁→⁶A₁). Moreover, the SZGO:4% Mn²⁺ phosphor achieved an internal quantum efficiency (I_QE) of 86.57 % and maintained a thermal stability of 90.73 % at 420 K. Thermometric analysis reveals that SZGO:4% Mn²⁺ phosphors achieve a maximum relative sensitivity (S_r) of 0.2112 % K⁻¹ at 300 K. Ultimately, a high-performance w-LED is assembled by coating commercial blue and red phosphors with the SZGO:4% Mn²⁺ phosphors on a 310 nm UV chip, yielding a correlated colour temperature (CCT) of 5391 K and an impressive colour rendering index (CRI) R_a of 93.7. In addition, the aging, thermal and continuous operation tests are conducted on w-LEDs to evaluate the stability of the devices. The results show that the phosphor can improve the operational stability of w-LEDs. These findings underscore the potential of SZGO:Mn²⁺ as an effective green component in w-LED lighting applications. Additionally, the outstanding luminescence properties of SZGO:4% Mn²⁺ phosphors are further leveraged for anti-counterfeiting (AC) purposes, enabling multi-level security features under UV-254 nm excitation. Its high-contrast fluorescence response also facilitated precise latent fingerprints (LFPs) detection and classification using You Only Look Once, version 8–Extra Large model (YOLOv8x), demonstrating significant promise for automated forensic analysis and secure authentication systems.