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Variable-Area Sensor Permits Near-Continuous Multipoint Measurements of Aqueous Biological and Chemical Analytes

  • Liza R. White
  • , Jordan N. Miner
  • , Luke D. McKinney
  • , Lindsay E. Pierce
  • , Anna Folley
  • , Ariel Larrabee
  • , Lea Scrapchansky
  • , Wyatt Fessler
  • , Manisha Choudhary
  • , Manoj Kamalanathan
  • , Ramin Pouria
  • , Saman Zare
  • , Emma Perry
  • , Sheila Edalatpour
  • , Onur G. Apul
  • , Caitlin Howell

Research output: Contribution to journalArticlepeer-review

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 languageEnglish (US)
Pages (from-to)382-391
Number of pages10
JournalIndustrial and Engineering Chemistry Research
Volume64
Issue number1
DOIs
StatePublished - Jan 8 2025

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Chemical Engineering
  • Industrial and Manufacturing Engineering

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