A simple, instrument-free, paper-based analytical device with dual-emission carbon dots (CDs) (blue CDs and red CDs) was developed for the semiquantitative, visual, and sensitive speciation analysis of lead ions in a real sample with a sensitive detection limit of 2.89 nM. When a paper strip was immersed into the sample solution, the blue fluorescence was quenched by Pb 2+ in solution, while the red fluorescence served as a background reference without color change, and significant color evolutions from blue to red were observed under the ultraviolet lamp, resulting in a semiquantitative visual detection. Furthermore, a smartphone was used in the visual detection of lead ions by identifying the RGB value of the fluorescent probe solution and corresponding paper strip. The application of smartphones and fluorescent paper strips has greatly shortened the detection time and reduced the cost of detection, providing a new strategy for the on-site and semiquantitative detection of heavy-metal ions in water samples.

Instrument-free, portable, and direct read-out minidevices have wider application prospects in various fields, especially for real-time/on-site sensing. Herein, combined with a paper strip, a smartphone sensing platform integrated with a UV lamp and dark cavity by 3D-printing technology has been developed for the rapid, sensitive, instrument-free, and visual quantitative analysis in real-time/on-site conditions. The platform proved the feasibility for visual quantitative detection of pesticide via a fluorescence "on−off−on" response with a single dualemissive ratiometric paper strip. Red-emitting CdTe quantum dots (rQDs) were embedded into the silica nanoparticles (SiO 2 NPs) as an internal reference, while blue-emitting carbon dots (bCDs) as a signal report unit were covalently linked to the outer surface of SiO 2 NPs. The blue fluorescence could be quenched by gold nanoparticles (Au NPs) and then recovered with pesticide. The red (R), green (G), and blue (B) channel values of the generated images were determined by a color recognizer application (APP) installed in the smartphone, and the R/B values could be used for pesticide quantification with a sensitive detection limit (LOD) of 59 nM. The smartphone sensing platform based on 3D printing might provide a general strategy for visual quantitative detection in a variety of fields including environments, diagnosis, and safety monitoring.