Glycolysis of polyester waste (PET) : Inherited species catalytic activity

Status

Ongoing

Scientific disciplines

Physical Sciences and Physico-chemistry

Research direction

Process Design and Modeling

Affiliate site

Lyon

The PhD project is proposed in the context of PET waste chemical recycling into PET, via depolymerization. Chemical recycling is needed when plastic feedstocks cannot be mechanically processed, usually for non-transparent PET. The goal of the project is to understand and rationalize the catalytic mechanisms of inherited substances that act as catalysts during the recyling process, which are inherited catalysts from PET polycondensation and some additives. The project will combine analysis, acquisition of experimental data on  reactions kinetics and kinetic modeling, and will focus on the most abundant catalytic species, their activity and inhibition formalisms. The results should allow for a better understanding of the chemical reactivity involved and pave the way towards operating conditions optimization of depolymerization processes. Through this project the candidate will be trained in a variety of techniques and approaches for the fundamental and applied research in the field of reaction engineering, kinetic modeling, catalysis and plastics recycling.

Keywords: recycling, plastics, PET, glycolysis, catalysis, kinetics, modeling

  • Academic supervisor    Dr., HUDEBINE Damien, Reaction and Reactor Modeling Department, IFP Energies Nouvelles
  • Doctoral School    ED 206, chemistry, processes, environnement
  • IFPEN supervisor    Dr., MEKKI-BERRADA Adrien, Research Engineer, R065, adrien.mekki-berrada@ifpen.fr
  • PhD location    IFP Energies nouvelles, Lyon, France
  • Duration and start date    3 years, starting in fourth quarter 2023
  • Employer    IFP Energies Nouvelles, Solaize, FRANCE
  • Academic requirements    University Master degree in Chemical Engineering, Chemistry or Catalysis
  • Language requirements    Fluency in French or English
  • Other requirements    Programming skills (C/C++, Fortran, Python…)
     
Contact
Encadrant IFPEN :
MEKKI-BERRADA Adrien
PhD student of the thesis:
Promotion 2023-2026