Distinguishing Commercial Beers Using a Solution-Based Sensor Array Derived from Nanoscale Polydiacetylene Vesicles

Xiaomin Qian, Carina L. Gargalo, Krist V. Gernaey, Brigitte Städler*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Abstract

The fast and effective discrimination of different liquid mixtures such as beers is a long-standing challenge in the food and beverage industry. We report the fabrication of a solution-based sensor array derived from nanoscale polydiacetylene (PDA) vesicles to distinguish different ethanol containing aqueous solutions supplemented with different model flavor compounds relevant in beers. The sensitivity of the sensors was significantly affected by the head group modification of the diacetylenes and the composition of the sensors. Finally, a selected set of sensors was utilized as a sensor array to distinguish different commercial beers in combination with statistical data analysis. This approach represents an effort toward the employment of low-cost sensors with an easy read-out for the fast discrimination of different beverages.

Original languageEnglish
JournalACS Applied Nano Materials
Volume3
Issue4
Pages (from-to)3439−3448
Number of pages10
ISSN2574-0970
DOIs
Publication statusPublished - Apr 2020

Keywords

  • beer discrimination
  • diacetylene
  • hierarchical clustering analysis
  • nanoscale vesicles
  • polydiacetylene
  • principal component analysis
  • self-assembly
  • sensor array

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