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

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Distinguishing Commercial Beers Using a Solution-Based Sensor Array Derived from Nanoscale Polydiacetylene Vesicles. / Qian, Xiaomin; Gargalo, Carina L.; Gernaey, Krist V.; Städler, Brigitte.

In: ACS Applied Nano Materials, Vol. 3, No. 4, 04.2020, p. 3439−3448.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Bibtex

@article{74c56187f0c64759b0272f06edf88a58,

title = "Distinguishing Commercial Beers Using a Solution-Based Sensor Array Derived from Nanoscale Polydiacetylene Vesicles",

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.",

keywords = "beer discrimination, diacetylene, hierarchical clustering analysis, nanoscale vesicles, polydiacetylene, principal component analysis, self-assembly, sensor array",

author = "Xiaomin Qian and Gargalo, {Carina L.} and Gernaey, {Krist V.} and Brigitte St{\"a}dler",

year = "2020",

month = apr,

doi = "10.1021/acsanm.0c00187",

language = "English",

volume = "3",

pages = "3439−3448",

journal = "ACS Applied Nano Materials",

publisher = "ACS (American Chemical Society)",

number = "4",

}

RIS

TY - JOUR

T1 - Distinguishing Commercial Beers Using a Solution-Based Sensor Array Derived from Nanoscale Polydiacetylene Vesicles

AU - Qian, Xiaomin

AU - Gargalo, Carina L.

AU - Gernaey, Krist V.

AU - Städler, Brigitte

PY - 2020/4

Y1 - 2020/4

N2 - 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.

AB - 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.

KW - beer discrimination

KW - diacetylene

KW - hierarchical clustering analysis

KW - nanoscale vesicles

KW - polydiacetylene

KW - principal component analysis

KW - self-assembly

KW - sensor array

UR - http://www.scopus.com/inward/record.url?scp=85082737873&partnerID=8YFLogxK

U2 - 10.1021/acsanm.0c00187

DO - 10.1021/acsanm.0c00187

M3 - Journal article

AN - SCOPUS:85082737873

VL - 3

SP - 3439−3448

JO - ACS Applied Nano Materials

JF - ACS Applied Nano Materials

IS - 4

ER -