*Result*: Near-white light-emitting copper nanoclusters/starch composites for multiplexing imaging and multichannel enhancement of latent fingerprints.
*Further Information*
*• Easy synthesis of near-white light-emitting copper nanoclusters/starch composites. • Achievement of multiplexing imaging of developed fingerprints using optical filtering. • Multichannel image enhancement based on uneven distribution of signals and noises. • Quantitative and qualitative effect evaluation using Python and spectral analysis. Powdering latent fingerprints with photoluminescent materials is the most frequently used way to reveal the evidential value. Still, traditional and most emerging fingerprint powders possessing a single luminescence mode are insufficient to deal with the ones on surfaces with multicolor or intricate patterns. Inspired by violet-pump light emitting diode and wavelength division multiplexing technique, we present an intuitive notion and detailed implementation of multiplexing imaging and multichannel enhancement of latent fingerprints by near-white light-emitting copper nanoclusters (CuNCs)/starch composites. Through optimally combining blue- with orange-emitting CuNCs/starch composites, as well as cyan- with orange-emitting CuNCs/starch composites, two near-white light-emitting CuNCs/starch composites with fluorescence emissions across the visible wavelength region and color coordinates of (0.33, 0.28) and (0.33, 0.32) under excitation of 365 nm UV light have been acquired. All three levels of latent fingerprint morphological features can be developed precisely using them. In addition to the visual evaluation of developed fingerprint images, a quantitative and comprehensive analysis of the quality of fingerprint imaging and enhancement has been performed using Python, along with a qualitative commentary concerning fingerprint imaging and enhancement on problematic surfaces based on spectral analysis, proving that our strategy can widen the gap between fingerprint area and furrow-background areas, improve the signal-to-noise ratio, and thus enhance the fingerprint image quality. [ABSTRACT FROM AUTHOR]*