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Coulter counters electrically detect and size suspended particles from intermittent changes in impedance between electrodes. By combining the impedance-based sensing with microfabrication, Coulter counters can be distributed across a lab-on-a-chip platform for code-multiplexed monitoring of microfluidic manipulations. In this paper, we augment a code-multiplexed Coulter sensor network with a deep learning-based decoding algorithm for multiplexed detection of cancer cells sorted into different microfluidic channels.
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Multiplexed Paper Microfluidics for Titration and Detection of Ingredients in Beverages
Food safety and access to systematic approaches for ensuring detection of food hazards is an important issue in most developing countries. With the arrival of paper-based analytical devices (µPADs) as a promising, rapid, easy-to-use, and low-cost analytical tool, we demonstrated a simple microfluidic-based titration study for the analysis of packaged fruit juices. Similar, to the titration experiments using traditional glassware in chemistry laboratories, in this study the titration experiments were developed using paper microfluidics for the analysis of several analytes such as pH, vitamin C, sugars, and preservatives present in the packaged fruit juices. The allergen found commonly in dairy based mixtures and the non-pathogenic biochemical component responsible for food spoilage in cider based fruit juices were also determined. The results obtained using paper microfluidics were compared with those obtained using a conventional spectrophotometric technique. Finally, a paper microfluidics based multiplexed sensor was developed for the analysis of common nutritional ingredients, an allergen, and a non-pathogenic byproduct present in packaged fruit juices on a single platform. Overall, the results presented in this study reveal that the proposed paper microfluidic assisted colorimetric multiplexed sensor offers a quick and reliable tool for on-spot routine analysis for food safety applications.
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- Award ID(s):
- 1660233
- PAR ID:
- 10111677
- Date Published:
- Journal Name:
- Sensors
- Volume:
- 19
- Issue:
- 6
- ISSN:
- 1424-8220
- Page Range / eLocation ID:
- 1286
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/s19061286
