Untargeted screening and identification of substances in plastic food contact materials using an Orbitrap Exploris GC 240 mass spectrometer

Significance of the Topic

Plastic food contact materials can release non-intentionally added substances (NIAS) formed during production, degradation, or recycling. Assessing these substances is crucial for consumer safety and regulatory compliance under EU regulation No 10/2022.

Objectives and Overview of the Study

This work aims to demonstrate an untargeted workflow combining gas chromatography with high-resolution accurate mass Orbitrap Exploris GC 240 mass spectrometry and Compound Discoverer software to screen and identify NIAS in a recycled low-density polyethylene (LDPE) film.

Methodology and Used Instrumentation

The analytical strategy consisted of:

• Sample Extraction: Acetone extraction of a 5×5 cm LDPE film at 40 °C for 1 h, followed by evaporation and reconstitution.
• GC–MS Analysis: TRACE 1610 GC with a TraceGOLD TG-5SilMS column coupled to an Orbitrap Exploris GC 240 mass spectrometer.
• Ionization Modes: Full-scan electron ionization (EI) at 70 eV and positive chemical ionization (PCI) with methane for molecular ion confirmation and MS/MS acquisition.
• Data Processing: Compound Discoverer workflows for deconvolution, NIST spectral matching, background removal, ChemSpider and mzCloud database searches, molecular formula prediction, and in silico fragmentation (FISh scoring).

Main Results and Discussion

After blank subtraction, 260 features were detected by EI, with 186 library matches at Total Score > 90% and ΔRI < 50 reducing confident identifications to 112 compounds. PCI data confirmed molecular ions and adduct patterns. The mzCloud search provided an 85.9% spectral match for methyl palmitate. In cases lacking library spectra, the FISh algorithm explained up to 77% of fragment ions from predicted structures, supporting robust identification.

Benefits and Practical Applications

The combined EI/PCI Orbitrap workflow and Compound Discoverer software accelerate NIAS screening with high selectivity, accurate mass assignments, and automated spectral deconvolution.

• The Mark Background Compounds node streamlines data review by removing blank signals.
• High-resolution data enable reliable molecular formula and fragment assignments beyond nominal mass libraries.
• In silico fragmentation via FISh adds confidence when standard spectra are unavailable.

Future Trends and Opportunities

Advances in spectral libraries (expanded mzCloud, mzVault) and machine-learning algorithms for fragment prediction will further improve untargeted workflows. Integration with retention index databases and higher-throughput GC systems can enhance screening of complex polymeric materials.

Conclusion

The presented Orbitrap GC–MS coupled with Compound Discoverer provides a comprehensive untargeted approach for identifying NIAS in plastic food contact materials. This method offers superior mass accuracy, selectivity, and software-driven data processing to support safety assessments and regulatory compliance.

References

1. Commission Regulation (EU) No 10/2022 of 14 January 2011 on plastic materials and articles intended to come into contact with food and its amendments.
2. International Life Science Institute (ILSI) Europe. Guidance on Best Practices for Risk Assessment of Non-Intentionally Added Substances (NIAS) in Food Contact Materials; ILSI Europe, Brussels, Belgium, 2015.
3. Miralles P.; Yusà V.; Pineda A.; Coscollà C. A Fast and Automated Strategy for Identification and Risk Assessment of Unknown Substances (IAS/NIAS) in Plastic Food Contact Materials by GC-Q-Orbitrap HRMS: Recycled LDPE as a Proof-of-Concept. Toxics 2021, 9(11), 283.