Nanoarchitectonics of highly dispersed polythiophene on paper for accurate quantitative detection of metal ions

pi-Conjugated polymers such as polythiophene provide intramolecular wire effects upon analyte capture, which contribute to sensitive detection in chemical sensing. However, inherent aggregation-induced quenching causes difficulty in fluorescent chemical sensing in the solid state. Herein, we propose a solid-state fluorescent chemosensor array device made of a paper substrate (PCSAD) for the qualitative and quantitative detection of metal ions. A polythiophene derivative modified by dipicolylamine moieties (1poly), which shows optical changes upon the addition of target metal ions (i.e., Cu2+, Cd2+, Ni2+, Co2+, Pb2+, Zn2+, and Hg2+), was highly dispersed on the paper substrate using office apparatus. In this regard, morphological observation of the PCSAD after printing of 1poly suggested the contribution of the fiber structures of the paper substrate to the homogeneous dispersion of 1poly ink to suppress aggregation-induced quenching. The optical changes in the PCSAD upon the addition of metal ions was rapidly recorded using a smartphone, which was further applied to imaging analysis and pattern recognition techniques for high-throughput sensing. Indeed, the printed PCSAD embedded with 1poly achieved the accurate detection of metal ions at ppm levels contained in river water. The limit of detection of the PCSAD-based sensing system using a smartphone (48 ppb for Cu2+ ions) is comparable to that of a solution-based sensing system using a stationary spectrophotometer (16 ppb for Cu2+ ions). Therefore, the methodology based on a combination of a paper-based sensor array and a pi-conjugated polymer will be a promising approach for solid-state fluorescent chemosensors. Paper fibers allow the high dispersion of a fluorescent polythiophene chemosensor for the suppression of aggregation-induced quenching, which is applied to the solid-state fluorescent quantitative sensing of metal ions using imaging analysis and pattern recognition techniques.