FTIR spectroscopy method for identifying and quantifying PLA, PHA, and their blends
A rapid, accurate FTIR spectroscopy method to identify and quantify polylactic acid (PLA) and polyhydroxyalkanoate (PHA) biodegradable plastics and their blends. The approach supports mechanical recycling by enabling fast, non-destructive composition analysis of bio-based plastic waste streams, facilitating sorting and quality control for circular economy applications.
Overview
This research proposes developing a rapid, accurate analytical method using Fourier Transform Infrared (FTIR) spectroscopy to identify and quantify polylactic acid (PLA) and polyhydroxyalkanoate (PHA) biodegradable plastics, as well as their blends. As demand for bio-based and compostable plastics grows, effective mechanical recycling requires reliable ways to distinguish between polymer types and determine blend compositions. This method addresses a critical gap in plastics sorting and quality control, supporting circular economy goals for sustainable packaging and single-use plastics.
Technical specifications
- FTIR-based identification: Measures infrared absorption patterns unique to each polymer's chemical functional groups, enabling material identification
- PLA detection: Identifies lactic acid-based polymer signatures in the FTIR spectrum
- PHA detection: Identifies hydroxyalkanoate-based polymer signatures in the FTIR spectrum
- Blend quantification: Combines spectra of pure PLA and pure PHA, with relative peak intensities correlating to blend composition ratios
- Quantitative modeling: Develops predictive models linking spectral features to blend composition percentages
- Validation approach: Builds a reference library from pure commercial PLA and PHA samples, then tests against laboratory-produced blends and independent samples
Technology readiness level
This research is at an early stage (TRL 2-3). The hypothesis is supported by a 2020 published study characterizing FTIR spectra of PHA, PLA, and their blends, though quantitative correlation between blend composition and spectral peak intensity remains to be demonstrated. Future work includes building a spectral library, investigating how spectral features change with composition, developing a quantitative prediction model, and validating it with independent samples.
About South Dakota State University
South Dakota State University is a comprehensive public land‑grant research university serving a large statewide community. Industry engages through a university‑linked research and technology park that colocates tenant companies with faculty labs and pilot‑scale processing suites for de‑risking and demonstration. A statewide extension network and field sites provide real‑world environments for validation and market feedback, while shared‑use core facilities and tailored workforce pipelines connect talent and tools to corporate R&D. Research is supported by competitive federal funding from USDA and NSF, with additional awards from NIH and DOE, alongside state and industry partnerships. A dedicated technology transfer office manages IP and industry agreements, and incubator space at the research park supports startup formation and scale‑up.
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