Identification and absolute quantification of NIAS: towards a return to food contact for recycled plastics

Recycling plastics is one of the main ways of combating the impact of human activity on the environment. To improve the circularity of these materials, IFPEN is working on industrial solutions involving the design and development of new plastic transformation processes for recycling. The return of recycled plastics to food contact represents one of the most profitable economic sectors. However, regulations governing materials intended to come into contact with foodstuffs are very strict. To assess potential health risks, particular attention is paid to unexpected and potentially harmful substances that can migrate from packaging materials to food, known as NIAS (Non intentionally added Substances). The central idea of the thesis project is to develop analytical methods based on the coupling between liquid chromatography (LC) and high-resolution mass spectrometry (HRMS) for the identification and quantification of NIAS, drawing on high-volume data processing inspired by omics science methods, and more specifically on the construction of molecular networks. This approach is the first objective of this thesis and will make it possible to obtain previously unpublished data on chemically and/or mechanically recycled packaging in terms of NIAS, and to compare them with those previously identified in the literature for packaging made from virgin raw materials. To meet the challenge of NIAS quantification, this thesis topic aims to explore the potential of structural fingerprints calculated from MS2 data, in combination with other descriptors, in the implementation of a response factor prediction model for NIAS detected by LC-HRMS using machine learning methods.

Keywords: Recycled plastic, NIAS, Analyses, Liquid chromatography, High-resolution mass spectrometry, Molecular Networking, Data processing, Modelling, Quantification

• Academic supervisor    PhD. Véronique LACHET, IFPEN, ORCID : 0000-0002-1937-5975
• Doctoral School    ED388 - Ecole Doctorale de Chimie Physique et Chimie Analytique Paris 6
• IFPEN supervisor    PhD. Alexandra BERLIOZ-BARBIER, ORCID : 0000-0002-2587-2556
• PhD location    IFPEN Lyon, FRANCE  
• Duration and start date    3 years, starting in the fourth quarter 2025 (Novembre 3)
• Employer    IFPEN
• Academic requirements    University Master degree in analytical sciences    
• Language requirements    English level B2 (CEFR) 
• Other requirements    Complex data processing, modelling, molecular reconstruction, chemometrics/chemoinformatics, machine learning 

To apply, please send your cover letter and CV to the IFPEN supervisor indicated here below.