Computational Study on PVC Degradation

IFP Energies Nouvelles Group; Rueil-Malmaison; On-site; EUR 10,000 - 13,000; Full time

Benefits offered by this job

Supervised by experienced team

Location in Rueil-Malmaison

Job summary

IFP Energies Nouvelles Group seeks an M2-level intern to study PVC degradation at 200 °C, focusing on solvent effects and dehydrochlorination mechanisms using molecular modelling.

The project includes literature surveys, reference data generation with DFT, training or validating ML potentials, and MD simulations to explore reaction pathways and kinetics. A final scientific report will summarize findings.

Qualifications

• M2 level in physical-chemistry or theoretical chemistry.
• Experience with DFT and MD is a plus.
• Proficiency in Python and Linux.

Responsibilities

• Conduct literature survey on PVC degradation and dehydrochlorination.
• Generate reference data (energies, barriers, structures) using DFT.
• Test and train ML potentials against the dataset.
• Run 200 °C MD simulations with MLP to study solvent effects.
• Analyze trajectories and extract observables; write a report.
• Validate simulations against experimental data.

Skills

Python

Linux

Data handling

Scientific communication

Analytical mindset

Autonomy

Education

Master 2 in Physical Chemistry

Tools

VASP

ORCA

Gaussian

LAMMPS

ASE

OpenMM

Job description

Computational Study on PVC Degradation

In the context of PVC recycling, we are looking for an M2-level intern to improve our understanding of the PVC degradation at 200 °C that is observed depending on the nature of the solvent used.

This study focusses on understanding the reaction mechanisms of the dehydrochlorination reaction as a function of the nature of the solvent and temperature using molecular modelling techniques.

Objectives / Tasks

• Literature survey on PVC degradation with a focus on the dehydrochloration reaction
• Generate reference data (energies, barriers, optimized structures, reaction profiles) based on DFT calculations
• Validate existing or train new machine-learned potentials (MLP) against the training set.
• Run molecular dynamics (NVT) simulations at 200 °C with the MLP to simulate PVC + dehydrochlorination reactions and assess solvent effects on kinetics and mechanisms.
• Analyse trajectories and extract observables: bond-breaking frequencies, reaction pathways, HCl production, formation of conjugated systems; write a scientific report.
• Validation of simulation results against experimental dosage experiments.

Profile & Required Skills

M2 Internship -Strong background in physical-chemistry, thermochemistry or theoretical chemistry.

• Familiarity with DFT codes (VASP, ORCA, Gaussian) or molecular dynamics simulators (LAMMPS, OpenMM, ASE) is a plus.
• Knowledge of molecular dynamics methods, interatomic potentials.
• Python skills, data handling, and comfort with Linux.
• Analytical mindset, rigor, autonomy, and good scientific communication skills.
• Technical English required; conversational French is a plus.

Practical details

• Duration: 6 months, start date: beginning of 2027.
• Location: IFPEN, Rueil-Malmaison (92)
• Supervision by an experienced team in polymer and computational chemistry.