Point-and-Shoot Strategy for Identification of Alcoholic Beverages.

Abstract

The lack of point-and-shoot detection methods of alcoholic beverages (ABs) available for ordinary people is a common cause of the overflow of various counterfeit ABs. Here, we, for the first time, provide a point-and-shoot identification for ABs via a smartphone. Using density functional theory, we find the binding ability of an ethylenediamine-functionalized polydiacetylene (P4) can reach a desirable trade-off among organic molecules in ABs. We therefore construct a versatile array consisting of P4 with different concentrations, which is able to generate unique color response patterns toward different ABs. The color response patterns are further analyzed by a custom-designed image processing algorithm based on machine learning. Finally, the identification of ABs can be achieved by capturing and analyzing the color pattern using an imaging recognition programmer on a smartphone, and the entire process is as fast as quick response (QR) code scanning. Our point-and-shoot strategy makes the identification of ABs accessible to every mobile phone user.