Variable-Area Sensor Permits Near-Continuous Multipoint Measurements of Aqueous Biological and Chemical Analytes
The timely detection of aqueous analytes is critical to decision-makers in agriculture, industry, and municipalities. However, nearly all aqueous sensor systems rely on single-point measurements, often taken at an instantaneous point in time and in one location, which can limit their ability to detect analytes passing through the aqueous solution at other locations or times. In this work, we present the concept of employing a mass-manufactured nanotextured diffraction surface as a variable-area sensor system capable of providing spectrophotometric information about aqueous analytes across multiple locations over time. We show that by placing the nanotextured surface of the sensor system under or behind a water sample, the water can be scanned by simply changing the location or angle of the light source and detector. We demonstrate the detection and quantification of a variety of aqueous analytes, including visible and ultraviolet (UV)-absorbing dyes, dust particles, and microalgae species, at accuracies similar to those of commercial equipment. A machine-learning algorithm was used to lower the limit of detection of dye from 5 to 3 μg/mL as well as automate the classification of distinct analyte types. These results demonstrate that using a mass-manufactured, textured surface can offer benefits as aqueous sensors, facilitating widely deployable aqueous analyte monitoring in a variety of applications.
Authors
- Caitlin Howell (ORCID: https://orcid.org/0000-0002-9345-6642)
- Saman Zare (ORCID: https://orcid.org/0000-0002-1249-8462)
- Onur G. Apul (ORCID: https://orcid.org/0000-0002-2964-8279)
- Sheila Edalatpour (ORCID: https://orcid.org/0000-0002-5796-0630)
- Ariel Larrabee
- Lindsay Pierce
- Emma Perry (ORCID: https://orcid.org/0000-0001-9980-2182)
- Liza R. White (ORCID: https://orcid.org/0009-0008-7130-8789)
- Manoj Kamalanathan (ORCID: https://orcid.org/0000-0001-9617-1362)
- Manisha Choudhary (ORCID: https://orcid.org/0000-0003-1210-6593)
- Ramin Pouria (ORCID: https://orcid.org/0000-0003-4962-3471)
- Jordan N. Miner (ORCID: https://orcid.org/0000-0003-2998-3330)
- Anna Folley
- Lea Scrapchansky
- Wyatt Fessler
- Luke McKinney
Institutions
- Bigelow Laboratory for Ocean Sciences (US)
- University of Maine (US)
Publication Details
- Journal
- Industrial & Engineering Chemistry Research
- Published
- 2024-11-25
- DOI
- https://doi.org/10.1021/acs.iecr.4c02774
- Citations
- 1
- Primary Topic
- Water Quality Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.29