On-site smartphone detection of ethanol content using paper-based colorimetric polydiacetylene sensor arrays.

[Display omitted] • A rapid and sensitive paper-based colorimetric sensing array for full-content ethanol detection is developed. • The sensing array is fabricated via inkjet-printing diacetylene monomers on A4 paper followed by photopolymerization. • The sensing array displays distinct color difference patterns for diverse ethanol contents. • The sensing array is applicable for discrimination and authentication of ethanol content in real samples. • A smartphone app is develped and integrared with the array that directly enables read-out of the ethanol content in real samples. The accelerated consumption of ethanol in pharmaceutical, food and fuel industries instinctively actuates the development of simple, portable, reliable and inexpensive sensing method for ethanol content monitoring. Herein, a paper-based polydiacetylene (PDA) sensor array is prepared from four diacetylene (DA) monomers modified with imidazole and its derivates. DA inks derived from the four monomers are directly coated on A4 paper via inkjet printing and converted to PDAs by UV irradiation with high stability and uniformity. The printed PDA sensors show solvent induced irreversible color transition upon exposure to organic solvents and water. The diverse colorimetric responses integrally provide unique color change patterns which are capable of distinguishing 11 distinct solvents including ethanol and water. The pattern-based sensing performance further promotes the fabrication of spot-matrix sensor array that could generate distinct color difference maps towards different ethanol contents with multiple sensing elements and a widely dynamic sensing range from 0 to 100%. Combined with RGB value radar map and principal component analysis (PCA), the sensor array also displays excellent ability of differentiating ethanol content from 5 to 100%. With this proposed method, commercial spirit samples with different ethanol contents or gasolines with different amounts of ethanol are readily distinguished and identified through naked eye and PCA score plot. Furthermore, to facilitate usability, a smartphone app is developed and integrated with the PDA sensor array, which directly enables read-out of the ethanol content in real liquor samples with high accuracy. Considering the simplicity, portability and reliability of the proposed sensing system, this study offers a promising method for point-of-use detection of ethanol content that may find broad applications in terms of quality control, food safety inspection and consumer protection. [ABSTRACT FROM AUTHOR]