CHARACTERIZATION OF INDUSTRIAL PLASTICS USING PYROLYSIS WITH ATMOSPHERIC PRESSURE GAS CHROMATOGRAPHY COUPLED TO HIGH-RESOLUTION MASS SPECTROMETRY
Posters | 2023 | Waters | ASMSInstrumentation
The transition to a circular plastics economy demands reliable methods to verify the composition and safety of recycled polymer materials.
Pyrolysis coupled with soft ionization and high-resolution mass spectrometry offers enhanced selectivity and sensitivity for comprehensive chemical profiling of industrial plastics.
This study aims to develop an analytical workflow to differentiate virgin and 100% recycled polyamide gears.
It combines pyrolysis atmospheric pressure gas chromatography with quadrupole time-of-flight mass spectrometry and multivariate statistical analysis to screen, identify, and validate chemical markers.
Samples of virgin and recycled gears were prepared in triplicate by loading 0.2 mg of material into stainless steel cups packed with quartz wool.
Pyrolysis was performed using an EGA/PY-3030D unit at 600 °C with an interface temperature of 320 °C.
GC separation used an Agilent 7890 with an Rtx-5MS column (30 m × 0.25 mm × 0.25 µm) under a 45 °C hold and ramp to 300 °C at 20 °C/min (37.25 min total).
Detection employed a Xevo G2-XS QTof with an APGC source in MSE mode, enabling concurrent acquisition of low- and high-energy spectra.
Data processing and screening were conducted with MassLynx 4.2, UNIFI, and EZInfo software.
Base peak intensity pyrograms revealed complex profiles for both gear types.
An in-house library of 24 pyrolyzate standards facilitated tentative identification of common and unique components across samples.
Principal component analysis clearly separated blanks, virgin, and recycled gear samples, indicating distinct chemical signatures.
OPLS-DA S-plots pinpointed significant markers, including a unique marker in recycled material identified as N-vinylcaprolactam.
The Discovery Tool in UNIFI utilized accurate precursor and fragment masses for structural elucidation, enabling the addition of confirmed markers to the screening library for future targeted analyses.
This workflow streamlines the characterization of complex polymer matrices, supporting quality control, regulatory compliance, and validation of recycling processes.
The creation of an expandable in-house database accelerates routine analysis and paves the way for targeted quantitation in industrial settings.
Integration of targeted quantification modules will enhance measurement accuracy for key markers.
Expanding the methodology to diverse polymer types and coupling with other soft-ionization sources can broaden the analytical scope.
Advanced data analytics and machine learning techniques promise to improve marker discovery and predictive modeling for material performance.
Pyrolysis-APGC-QTof HRMS combined with multivariate statistics provides a powerful platform for differentiating and characterizing virgin and recycled industrial plastics.
This approach fosters the development of robust screening libraries and supports the goals of a sustainable circular plastics economy.
GC/MSD, GC/MS/MS, GC/HRMS, Pyrolysis, GC/Q-TOF, GC/API/MS, LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
IndustriesEnergy & Chemicals
ManufacturerAgilent Technologies, Waters, Frontier Lab
Summary
Importance of the Topic
The transition to a circular plastics economy demands reliable methods to verify the composition and safety of recycled polymer materials.
Pyrolysis coupled with soft ionization and high-resolution mass spectrometry offers enhanced selectivity and sensitivity for comprehensive chemical profiling of industrial plastics.
Study Objectives and Overview
This study aims to develop an analytical workflow to differentiate virgin and 100% recycled polyamide gears.
It combines pyrolysis atmospheric pressure gas chromatography with quadrupole time-of-flight mass spectrometry and multivariate statistical analysis to screen, identify, and validate chemical markers.
Methodology and Instrumentation
Samples of virgin and recycled gears were prepared in triplicate by loading 0.2 mg of material into stainless steel cups packed with quartz wool.
Pyrolysis was performed using an EGA/PY-3030D unit at 600 °C with an interface temperature of 320 °C.
GC separation used an Agilent 7890 with an Rtx-5MS column (30 m × 0.25 mm × 0.25 µm) under a 45 °C hold and ramp to 300 °C at 20 °C/min (37.25 min total).
Detection employed a Xevo G2-XS QTof with an APGC source in MSE mode, enabling concurrent acquisition of low- and high-energy spectra.
Data processing and screening were conducted with MassLynx 4.2, UNIFI, and EZInfo software.
Main Results and Discussion
Base peak intensity pyrograms revealed complex profiles for both gear types.
An in-house library of 24 pyrolyzate standards facilitated tentative identification of common and unique components across samples.
Principal component analysis clearly separated blanks, virgin, and recycled gear samples, indicating distinct chemical signatures.
OPLS-DA S-plots pinpointed significant markers, including a unique marker in recycled material identified as N-vinylcaprolactam.
The Discovery Tool in UNIFI utilized accurate precursor and fragment masses for structural elucidation, enabling the addition of confirmed markers to the screening library for future targeted analyses.
Benefits and Practical Applications
This workflow streamlines the characterization of complex polymer matrices, supporting quality control, regulatory compliance, and validation of recycling processes.
The creation of an expandable in-house database accelerates routine analysis and paves the way for targeted quantitation in industrial settings.
Future Trends and Opportunities
Integration of targeted quantification modules will enhance measurement accuracy for key markers.
Expanding the methodology to diverse polymer types and coupling with other soft-ionization sources can broaden the analytical scope.
Advanced data analytics and machine learning techniques promise to improve marker discovery and predictive modeling for material performance.
Conclusion
Pyrolysis-APGC-QTof HRMS combined with multivariate statistics provides a powerful platform for differentiating and characterizing virgin and recycled industrial plastics.
This approach fosters the development of robust screening libraries and supports the goals of a sustainable circular plastics economy.
References
- European Commission. A European Strategy for Plastics in a Circular Economy. January 2018.
- Tsuge S., Ohtani H., Watanabe C. Pyrolysis-GC/MS Data Book of Synthetic Polymers. 2011.
- Plumb R. et al. UPLC/MSE; A New Approach for Generating Molecular Fragment Information for Biomarker Structure Elucidation. Rapid Commun. Mass Spectrom. 2006.
- Stevens D., Cabovska B., Bailey A. Detection and Identification of Extractable Compounds from Polymers. Waters Application Note 720004211. 2012.
- Riches E., Goshawk J., Da Costa, Jones G. Discrimination Between Commercial Lubricant Oils Using Mass Spectrometry and Multivariate Analysis. Waters Application Note 720006406. 2018.
- Schweighuber A. et al. Development of an LC-MS Method for Semiquantitative Determination of Polyamide 6 Contamination in Polyolefin Recyclates. Anal Bioanal Chem. 2021.
- Cabovska B. Screening Workflow for Extractable Testing Using the UNIFI Scientific Information System. Technical Note 720005688. 2016.
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