Analysis of phthalate plasticizer migration from PVDC packaging materials to food simulants using molecular dynamics simulations and artificial neural network

Abstract

Based on the experimental data of gas chromatography-mass spectrometry, an improved artificial neural network was first established to predict the migration of 2-ethylhexyl phthalate (DEHP) plasticizer from poly(vinylidene chloride) (PVDC) into food simulants (ie., heptane, ethanol and water). The sensitivity analysis indicated that temperature acted as a crucial factor influencing the migration values of DEHP. Then, a combined experimental and molecular dynamic (MD) simulation was performed to understand the migration kinetics and the mechanism of DEHP. Hansen solubility parameters of three component (δd, δp, δh) were simplified into two-component solubility parameters (δvdW, δe), and the tuple was successfully applied to describe the interactions between PVDC and food simulants. The MD results showed that high interaction energy and fractional free volume in PVDC/DEHP/food simulant systems accelerated the migration of DEHP. These fundamental studies would provide significant insights into the migration of environmental contaminants.