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 journalJournal articleResearchpeer-review

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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
Issue number4
Pages (from-to)3439–3448
ISSN2574-0970
DOIs
Publication statusPublished - 2020

Bibliographical note

ASAP article. Hybrid Open access

Keywords

  • Diacetylene
  • Polydiacetylene
  • Self-assembly
  • Sensor array
  • Nanoscale vesicles
  • Beer discrimination
  • Principal component analysis
  • Hierarchical clustering analysis

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