Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 382-391 |
| Number of pages | 10 |
| Journal | Industrial and Engineering Chemistry Research |
| Volume | 64 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 8 2025 |
All Science Journal Classification (ASJC) codes
- General Chemistry
- General Chemical Engineering
- Industrial and Manufacturing Engineering
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