How can you identify microplastics from FTIR?
This page summarizes the recurring FTIR evidence reported for microplastics, including the most frequent peaks, supporting functional groups, and literature-backed interpretation patterns. It is a structured evidence page, not a claim of automatic single-spectrum certainty.
Backed by 51 cited sources
Quick answer
microplastics is usually reported with a recurring pattern of peaks and functional-group evidence. The most useful approach is to cross-check at least two characteristic peaks before treating it as a match, then verify whether the full spectrum still fits the same material family.
Peak interpretation
Possible materials / groups
| Grup funcțional | Dovezi |
|---|---|
| Alkyl C-H | 32 |
| Alkene (C=C) | 13 |
| Carbonyl (C=O) | 12 |
| Aromatic ring | 11 |
| Hydroxyl (O-H) | 11 |
| Methacrylate | 10 |
| Acetate | 10 |
| Carboxyl (COOH) | 7 |
Spectrum logic
The logic here is evidence aggregation: repeated literature mentions of microplastics, repeated peak positions, and repeated functional-group associations. A strong material hypothesis should still be supported by multiple peaks that agree with each other, not by one headline band alone.
Real-world usage
This page is designed for polymer identification, incoming-material QC, unknown plastic analysis, recycled-content review, and literature-backed interpretation of reference spectra.
Common mistakes
- Calling a material match too early because one famous peak is present.
- Ignoring sample prep, fillers, oxidation, water, or additives that can change the apparent pattern.
- Using literature evidence without checking whether your own sampling mode and spectrum quality are comparable.
Verification advice
Use DSC, GC-MS, or TGA to validate the material hypothesis when the peak pattern is ambiguous or mixed.
Literature behind this page
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Detection of Microplastic in Human Placenta and Meconium in a Clinical Setting DOI: 10.3390/pharmaceutics13070921 -
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Pyrolysis Process of Mixed Microplastics Using TG-FTIR and TED-GC-MS DOI: 10.3390/polym15010241 -
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A methodology for the fast identification and monitoring of microplastics in environmental samples using random decision forest classifiers DOI: 10.1039/c9ay00252a -
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Pan 等 - 2021 - Automated mu FTIR Imaging Demonstrates Taxon-Speci DOI: 10.1021/acs.est.1c03119 -
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An automated approach for microplastics analysis using focal plane array (FPA) FTIR microscopy and image analysis DOI: 10.1039/c6ay02476a -
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Hydrophobicitywater/airbased enrichment cell for microplastics analysis within environmental samples: A proof of concept DOI: 10.1016/j.mex.2019.11.006 -
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Effects and Impacts of Different Oxidative Digestion Treatments on Virgin and Aged Microplastic Particles DOI: 10.3390/polym14101958 -
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Weber 等 - 2022 - Investigating the dispersal of macroand micropla DOI: 10.1038/s41598-022-10294-w -
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Campanale 等 - 2023 - Fourier Transform Infrared Spectroscopy to Assess DOI: 10.3390/polym15040911 -
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Chai 等 - 2022 - Microplastic Contamination on the Beaches of South DOI: 10.3389/fmars.2022.863652
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