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Regenerable Membrane Sensors for Ultrasensitive Nanoplastic Quantification Enabled by A Data-driven Raman Spectral

Ziyan Wu1, Sarah E Janssen2, Michael T Tate2

  • 1Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States.

Environmental Science & Technology
|July 29, 2025
PubMed
Summary
This summary is machine-generated.

A new algorithm, Pre_seg, combined with anodic aluminum oxide sensors, enables sensitive detection of nanoplastics (NPs) in water. This method improves accuracy and allows for quantification of NPs at low concentrations.

Keywords:
Raman microspectroscopydata processing algorithmfreshwatermembrane sensornanoplastics

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Area of Science:

  • Environmental Science
  • Analytical Chemistry
  • Materials Science

Background:

  • Nanoplastic (NP) detection in natural waters is challenging due to complex matrices and analytical limitations.
  • Existing methods struggle with sensitivity, accuracy, and single-particle analysis.

Purpose of the Study:

  • To develop an ultrasensitive, rapid, and quantitative method for single-particle nanoplastic detection.
  • To integrate a novel Raman spectral processing algorithm (Pre_seg) with regenerable anodic aluminum oxide (AAO) membrane sensors.

Main Methods:

  • Utilized AAO membranes as combined filtration substrates and Raman sensors to minimize sample loss.
  • Developed the Pre_seg algorithm with statistically determined thresholds for signal-to-noise ratios (SNRs) and full width at half maximums (fwhms).
  • Validated the method in diverse lake water matrices after oxidation digestion pretreatment.

Main Results:

  • Pre_seg achieved 93.5% prediction accuracy for nanoplastics and ≥90.4% rejection accuracy for non-NP particles.
  • Quantified mixed nanoplastics at concentrations as low as 0.5 μg L⁻¹.
  • Demonstrated robustness in eutrophic and oligotrophic lake water and confirmed sensor stability over multiple regeneration cycles.

Conclusions:

  • The Pre_seg algorithm and AAO sensor system offer a highly sensitive and accurate approach for nanoplastic detection.
  • This innovative method enables scalable, customizable, and environmentally relevant monitoring of nanoplastics in water systems.