Engineering study demonstrates rapid alcohol and water detection using machine-learning-optimized perovskite LEDs, highlighting a portable platform for field-deployable near-infrared screening.
Translating advanced luminescent materials into field-deployable screening tools remains a core challenge, demanding synergy between advanced optical materials and device engineering. Here, we demonstrate a portable dual-mode near-infrared semi-quantitative screening device. the luminescence performance of the core emitting materials, specifically lead-free Nd³⁺/Yb³⁺ co-doped Cs₂NaYCl₆ double perovskite phosphors, was first optimized through a machine-learning (ML) guided approach. Subsequently, these optimized phosphors were integrated to enable the device. Specifically, the Nd³⁺-doped emitter targets the 885 nm characteristic absorption band of alcohol while exhibiting anomalous thermal quenching, whereas the Nd³⁺/Yb³⁺ variant leverages 78.66% energy transfer efficiency to yield stable 985 nm emission (70% retention at 500 K) matching the characteristic absorption band of water. These optimized phosphor-converted LEDs were integrated into a compact detector featuring a coaxial dual-disc stepper mechanism and a customized three-stage circuit that amplifies faint optical signals into a five-level visual indicator. This configuration enables rapid screening of alcohol (30–60%) and water content (45–100%). Validated on commercial samples, this work establishes a holistic platform bridging high-precision instrumentation and real-world portability.
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Li et al. (2026) studied this question.
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