Back to papers
0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Sign in to save

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

MethodsX 2019 38 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 35 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Gerrit Renner, Gerrit Renner, Gerrit Renner, Torsten C. Schmidt Gerrit Renner, Gerrit Renner, Gerrit Renner, Gerrit Renner, Gerrit Renner, Torsten C. Schmidt Gerrit Renner, Torsten C. Schmidt Torsten C. Schmidt Torsten C. Schmidt Torsten C. Schmidt Jürgen Schram, Jürgen Schram, Torsten C. Schmidt Jürgen Schram, Gerrit Renner, Gerrit Renner, Jürgen Schram, Torsten C. Schmidt Jürgen Schram, Jürgen Schram, Torsten C. Schmidt Jürgen Schram, Jürgen Schram, Jürgen Schram, Torsten C. Schmidt Jürgen Schram, Jürgen Schram, Jürgen Schram, Torsten C. Schmidt Gerrit Renner, Gerrit Renner, Torsten C. Schmidt Torsten C. Schmidt Torsten C. Schmidt Torsten C. Schmidt Torsten C. Schmidt Jürgen Schram, Jürgen Schram, Jürgen Schram, Jürgen Schram, Torsten C. Schmidt Jürgen Schram, Jürgen Schram, Torsten C. Schmidt Gerrit Renner, Torsten C. Schmidt Torsten C. Schmidt Jürgen Schram, Jürgen Schram, Torsten C. Schmidt Gerrit Renner, Jürgen Schram, Jürgen Schram, Torsten C. Schmidt

Summary

An algorithm was developed for automated FTIR microscopy that skips empty areas and non-plastic particles on filters, dramatically reducing scan times while maintaining accuracy. Faster automated analysis makes it practical to screen more environmental microplastic samples, improving the quality of contamination assessments.

The analysis of environmental microplastic particles using FTIR microscopy is a challenging task, due to the very high number of individual particles within a single sample. Therefore, automatable, fast and robust approaches are highly requested. Micro particles were commonly enriched on filters, and sub- or the whole filter area was investigated, which took more than 20h and produced millions of data, which had to be evaluated. This paper presents a new approach of such filter area analysis using an intelligent algorithm to measure only those spots on a filter that would produce evaluable FTIR data. Empty spaces or IR absorbers like carbon black particles were not measured which successfully reduced the total analysis time from 50h to 7h. The presented method is based on system independent Python workflow and can easily be implemented on other FTIR systems. •••.

Read via DOI PubMed PMC Full Text Download PDF

Sign in to start a discussion.

Share this paper

Post Share Share Pin Email