Prédiction de la conformité des matériaux d'emballage par intégration de méthodes de déformulation et de modélisation du coefficient de partage

Abstract : Plastic packagings are formulated with additives, which can migrate from materials into foodstuffs. According to European directive 2002/72/EC, the ability of plastic materials to be used in contact with food can be demonstrated using modelling tools. Their use is however limited due to availability of some data, like the formulation of materials and partition coefficients of substances between plastics and food. On the one hand this work aims to develop the ability of laboratories to identify and quantify the main substances in plastic materials, and on the other hand it aims to develop a new method to predict partition coefficients between polymers and food simulants. Four formulations of both HDPE and PS were chosen and used during the work. Standard extraction methods and quantification methods using HPLC-UV-ELSD and GC-FID were compared. A new deconvolution process applied on infrared spectra of extracts was developed to identify and quantify additives contained in HDPE. Activity coefficients in both phases were approximated through a generalized off-lattice Flory-Huggins formulation applied to plastic materials and to liquids simulating food products. Potential contact energies were calculated with an atomistic semi-empirical forcefield. The simulations demonstrated that plastic additives have a significant chemical affinity, related to the significant contribution of the positional entropy, for liquids consisting in small molecules. Finally, decision trees, which combine both experimental and modelling approaches to demonstrate the compliance of plastic materials, were discussed
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Guillaume Gillet. Prédiction de la conformité des matériaux d'emballage par intégration de méthodes de déformulation et de modélisation du coefficient de partage. Alimentation et Nutrition. Institut National Polytechnique de Lorraine, 2008. Français. ⟨NNT : 2008INPL081N⟩. ⟨tel-01753060⟩

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