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Updated: Dec 26, 2025

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Automated rapid & intelligent microplastics mapping by FTIR microscopy: A Python-based workflow.

Gerrit Renner1,2, Torsten C Schmidt2, Jürgen Schram1

  • 1Instrumental Analytical and EnvironmentalChemistry, Faculty of Chemistry, Niederrhein University of Applied Sciences, Frankenring 20, D-47798, Krefeld, Germany.

Methodsx
|March 18, 2020
PubMed
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Analyzing environmental microplastics with FTIR microscopy is faster with a new intelligent algorithm. This method significantly reduces analysis time by intelligently selecting measurement spots on filters, improving efficiency for microplastic identification.

Area of Science:

  • Environmental Science
  • Analytical Chemistry
  • Materials Science

Background:

  • Microplastic analysis using FTIR microscopy is time-consuming due to large sample sizes and data volume.
  • Current methods involve analyzing entire filter areas, leading to extensive measurement and evaluation times exceeding 20 hours.

Purpose of the Study:

  • To develop a faster, automatable, and robust method for analyzing microplastic particles on filters using FTIR microscopy.
  • To reduce the overall analysis time for environmental microplastic samples without compromising data quality.

Main Methods:

  • Implementation of an intelligent algorithm for targeted spot analysis on FTIR filters.
  • Development of a system-independent Python workflow for automated data acquisition and processing.
  • Exclusion of non-evaluable areas, such as empty spaces and carbon black particles, from measurement.
Keywords:
ChemometricsFTIR microscopyMappingMicroplasitcsPython

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Related Experiment Videos

Last Updated: Dec 26, 2025

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Main Results:

  • Achieved a significant reduction in total analysis time from 50 hours to 7 hours.
  • Successfully reduced data volume by intelligently selecting measurement spots.
  • Demonstrated the method's effectiveness in speeding up FTIR microscopy area mapping without requiring an Focal Plane Array (FPA) detector.

Conclusions:

  • The intelligent FTIR microscopy area mapping approach offers a substantial improvement in analysis speed and efficiency for microplastic identification.
  • The Python-based, platform-independent workflow facilitates easy implementation across different FTIR systems.
  • This method provides a robust solution for the high-throughput analysis of environmental microplastics.