Hyperspectral imaging system for rapid acrylamide detection in drinking water

Technology
Conceptual
University

An optical detection solution that uses hyperspectral imaging combined with machine learning to identify and quantify acrylamide in drinking water. Aims to deliver a limit of quantification below 0.5 ppb in under 15 minutes, enabling faster and more accessible water safety monitoring compared to conventional benchtop chemical methods.

Overview

This solution applies hyperspectral imaging to the detection of acrylamide in drinking water, addressing the need for faster, more accessible water safety monitoring. Acrylamide is a regulated contaminant of concern, and current detection typically relies on laboratory-based chemical analyses that are time-consuming and resource-intensive. By adapting hyperspectral imaging, which has already shown success in food product monitoring and underwater water quality assessment, the approach aims to achieve a limit of quantification below 0.5 ppb with a testing time of under 15 minutes.

The system is designed for practical deployment in water quality testing workflows, offering a rapid screening alternative that can complement or reduce dependence on traditional benchtop chemical methods. Potential applications include drinking water monitoring, environmental water quality assessment, and industrial process water screening.

Technical specifications

Core technology:

  • Hyperspectral imaging combined with machine learning-based correlation models
  • Custom underwater imaging tube with a transparent glass window to enable non-contact imaging of liquid samples
  • Mechanical housing designed to secure the hyperspectral camera and prevent direct contact with water

Key features:

  • Rapid detection capability targeting under 15 minutes per sample
  • Target limit of quantification below 0.5 ppb acrylamide in drinking water
  • Non-contact optical measurement using reflectance data
  • Machine learning algorithms that correlate hyperspectral reflectance with chemically validated ground truth concentrations
  • Adaptable design drawing on proven hyperspectral imaging performance in food and underwater environments

Validation approach:

  • Preparation of drinking water samples at varying acrylamide concentrations
  • Ground truth concentration determination using established benchtop chemical methods
  • Statistical and machine learning correlation models linking spectral data to chemical measurements
Technology readiness level

This technology is at an early-to-mid stage of development. Hyperspectral imaging has been validated in related contexts, including acrylamide detection in food products and water quality monitoring in lakes, but has not yet been applied to acrylamide detection in drinking water. Future work involves building a dedicated underwater hyperspectral imaging system, fabricating the mechanical tube housing, and generating calibration models through controlled experiments. Additional validation, optimization, and field testing will be required before commercial deployment.


About Iowa State University

Iowa State University is a large, comprehensive public land‑grant research university based in Ames, known for combining fundamental discovery with translational, industry‑relevant work. Companies collaborate through a research and technology park that co‑locates corporate R&D with faculty labs and startups, creating steady talent pipelines. Pilot‑scale facilities, field test sites, and a statewide extension network support prototyping, validation, and deployment with partners across the region. Research is supported by competitive federal funding, including awards from NSF, USDA, and DOE. A dedicated technology transfer office and affiliated research foundation streamline IP, licensing, and startup formation, with incubator space on site.

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