How to Identify Microplastics with FTIR Spectroscopy

Microplastic contamination is one of the defining environmental challenges of the decade. Particles under 5 mm are found in oceans, freshwater, soil, air, and increasingly in biological tissues. FTIR spectroscopy is the primary analytical technique for identifying the polymer composition of these particles — and it is the only method that provides both chemical identity and spatial distribution in a single measurement.

This guide walks through the complete microplastic identification workflow using FTIR, from sample collection to confident polymer assignment.

The identification workflow

Microplastic analysis follows a systematic pipeline: collect, isolate, measure, identify. Each step has failure modes that propagate downstream — contamination during collection produces false positives, incomplete isolation masks real particles, poor spectral quality prevents reliable identification.

Step 1: Sample collection and preparation

Water samples are typically collected by filtering a known volume through glass fiber or metal mesh filters (pore size 1–20 μm depending on the target size fraction). Stainless steel sieves and glass containers prevent plastic contamination from the collection equipment itself — this is critical, as common lab plastics (polypropylene centrifuge tubes, polyethylene wash bottles, nylon filters) are the same polymers you are trying to detect.

Sediment and soil samples require density separation. Sodium chloride (NaCl) or zinc chloride (ZnCl₂) solutions float plastic particles (density < 1.6 g/cm³) away from mineral grains (density > 2.5 g/cm³). ZnCl₂ recovers denser polymers like PET (1.38 g/cm³) that NaCl solution misses.

Biological tissue samples need enzymatic or chemical digestion (KOH, H₂O₂, or Fenton's reagent) to remove organic matrix material before analysis. The digestion protocol must not alter the polymer spectra — strong acids and high temperatures can degrade some plastics.

Contamination control is non-negotiable. Work in a laminar flow hood or clean bench. Wear cotton lab coats (not polyester). Use glass and metal labware exclusively. Run procedural blanks through every step to quantify background contamination.

Step 2: FTIR measurement

Two FTIR modes are used for microplastics, depending on particle size:

ATR-FTIR works well for particles larger than approximately 500 μm. Place individual particles on the ATR crystal using clean metal tweezers. The particle must make firm contact with the crystal surface — apply gentle pressure with the anvil. ATR is fast (under a minute per particle) and requires no additional preparation, making it ideal for screening large numbers of particles.

Micro-FTIR (FTIR microscopy) is necessary for particles below 500 μm. The infrared beam is focused through an optical microscope onto individual particles on a reflective substrate (gold-coated slides or aluminum oxide filters). Transmission mode works for thin particles; reflectance mode for thick or opaque ones. Micro-FTIR can analyze particles down to 10–20 μm, though spatial resolution is diffraction-limited at longer wavelengths.

For either mode:

• Run a clean background on the bare crystal (ATR) or substrate (micro-FTIR) before each particle or batch
• Use at least 32 scans per measurement to improve signal-to-noise
• Set resolution to 4 cm⁻¹ — sufficient for polymer identification without unnecessarily long acquisition times
• Scan the full mid-IR range (4000–400 cm⁻¹) to capture all diagnostic peaks

Step 3: Spectral interpretation and matching

Polymer identification relies on matching the measured spectrum against a reference library. Each polymer type has a characteristic pattern of absorption bands that acts as a molecular fingerprint. The key diagnostic peaks for the most common microplastic polymers are:

Polyethylene (PE)

The most abundant microplastic globally. PE spectra are dominated by C-H stretching and deformation modes:

• 2916 cm⁻¹ — asymmetric CH₂ stretch (strong)
• 2848 cm⁻¹ — symmetric CH₂ stretch (strong)
• 1472 cm⁻¹ — CH₂ scissoring deformation
• 1462 cm⁻¹ — CH₂ scissoring (doublet with 1472 in crystalline HDPE)
• 730/720 cm⁻¹ — CH₂ rocking doublet (crystallinity indicator)

The doublets at 1472/1462 and 730/720 cm⁻¹ distinguish high-density PE (HDPE, crystalline doublets resolved) from low-density PE (LDPE, single broad bands).

Polypropylene (PP)

The second most common microplastic. PP has a more complex C-H pattern than PE due to the methyl branch:

• 2950 cm⁻¹ — asymmetric CH₃ stretch
• 2916 cm⁻¹ — asymmetric CH₂ stretch
• 2848 cm⁻¹ — symmetric CH₂ stretch
• 1456 cm⁻¹ — CH₃ asymmetric deformation
• 1376 cm⁻¹ — CH₃ symmetric deformation (diagnostic — absent in PE)
• 997, 972 cm⁻¹ — helical chain vibrations (isotactic PP marker)

The methyl deformation at 1376 cm⁻¹ is the key distinguishing feature from PE.

Polystyrene (PS)

Aromatic C-H stretches and ring vibrations make PS immediately recognizable:

• 3026 cm⁻¹ — aromatic C-H stretch
• 2921 cm⁻¹ — aliphatic C-H stretch
• 1601, 1493, 1452 cm⁻¹ — aromatic C=C ring stretching
• 756, 698 cm⁻¹ — aromatic C-H out-of-plane bending (strong, diagnostic)

The strong pair at 756/698 cm⁻¹ is unmistakable for polystyrene. Expanded polystyrene (EPS) foam has the same spectral features as solid PS.

Polyethylene terephthalate (PET)

PET is common in fibers and bottle fragments. The ester carbonyl dominates:

• 1714 cm⁻¹ — C=O ester stretch (very strong, diagnostic)
• 1240 cm⁻¹ — C-O-C ester stretch (asymmetric)
• 1094 cm⁻¹ — C-O-C stretch (symmetric)
• 725 cm⁻¹ — aromatic C-H out-of-plane bend
• 871 cm⁻¹ — aromatic ring breathing

The intense carbonyl at 1714 cm⁻¹ combined with the ester C-O-C bands is definitive for PET.

Nylon (polyamide, PA)

Nylon fibers from textiles are a major source of microplastic fibers:

• 3296 cm⁻¹ — N-H stretch (broad)
• 1635 cm⁻¹ — C=O amide I stretch
• 1537 cm⁻¹ — N-H amide II deformation
• 1264 cm⁻¹ — C-N amide III stretch

The amide I/II pair at 1635/1537 cm⁻¹ is the diagnostic signature for polyamides. Different nylon types (PA6, PA66) show subtle differences in the fingerprint region below 1000 cm⁻¹.

Library matching in practice

Manual peak assignment works for clean spectra of pristine polymers, but environmental microplastics are rarely clean. Weathering, biofouling, and additive migration alter spectral features. Automated library searching provides more reliable identification:

1. Preprocess the spectrum — baseline correction (rubber band or concave rubber band) and normalization (min-max or vector normalization) remove artifacts and enable consistent matching
2. Search against a comprehensive polymer library — the library should include pristine polymers, weathered variants, and common additives. SpectralBench's reference library includes polymer reference spectra from published databases
3. Evaluate match quality — hit quality index (HQI) above 0.70 generally indicates a reliable identification. Scores between 0.60–0.70 may require manual verification. Below 0.60, the match is unreliable
4. Verify visually — always overlay the sample spectrum with the best-match reference spectrum using a spectral comparison tool to confirm that key diagnostic peaks align. Automated matching can be misled by heavily weathered or mixed spectra

Dealing with weathered and contaminated particles

Environmental microplastics rarely look like pristine polymer reference spectra. Common spectral alterations include:

Oxidation introduces carbonyl peaks near 1714 cm⁻¹ (the carbonyl index is used to quantify weathering degree in PE and PP). These peaks can complicate identification if the reference library only contains pristine spectra.

Biofouling adds protein (amide I at ~1650 cm⁻¹, amide II at ~1540 cm⁻¹) and lipid (C-H stretches, ester carbonyl) signatures that overlay the polymer spectrum. Enzymatic digestion or hydrogen peroxide treatment removes biofilms before measurement.

Inorganic contamination (mineral particles adhering to the plastic surface) introduces broad Si-O-Si absorption near 1000 cm⁻¹ or carbonate peaks near 1400 cm⁻¹ that can mask polymer features.

Additive migration — plasticizers, flame retardants, and stabilizers leach out over time, removing spectral features that were present in the original formulation and altering the match against pristine reference spectra.

For heavily weathered particles, focus on the most resistant spectral features: C-H stretches (2800–3000 cm⁻¹) and aromatic ring modes are relatively stable against environmental degradation. The fingerprint region (below 1000 cm⁻¹) is often the most affected by weathering.

Reporting and quantification

Microplastic studies should report:

• Polymer identity for each particle, with match quality scores
• Particle count and size distribution — binned by size class (e.g., 20–100 μm, 100–500 μm, 500–1000 μm, 1–5 mm)
• Morphology — fragment, fiber, film, pellet, or foam
• Color — visual classification before FTIR measurement
• Contamination controls — procedural blank results to demonstrate the reported particles are not laboratory artifacts

Standardized reporting enables comparison across studies and contributes to the growing understanding of microplastic distribution and fate in the environment.

Upload your microplastic spectra to SpectralBench's viewer for preprocessing and visualization, then run them against the reference library for automated polymer identification.