Abstract
The timely detection of aqueous analytes is critical to decision-makers in agriculture, industry, and munici-palities. However, nearly all water 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 water matrix 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 provid-ing spectrophotometric information on aqueous analytes across multiple locations over time. We show that by placing the nanotextured surface of the sensor system under or behind a water matrix, 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 commercial spectropho-tometers. A machine learning algorithm was used to lower the limit of detection of methylene blue from 5 µg/mL to 3 µg/mL and automate the classification of three distinct analyte types. These results demonstrate that using a mass-produced, textured surface as a sensor can offer benefits in water sensing capabilities, facilitating widely deployable aqueous analyte monitoring in a variety of applications.
Supplementary materials
Title
Supporting Information
Description
Biological sample preparation, microalgae microscopy, refractive index calculation, refractive index, calculated absorbance of dyes, Rhodomonas sp. microscopy images, diffraction sensor results of microalgae species, and measured UV-Vis spectra of nickel sulfate.
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