Characterization and modelling of trace compounds impacts on energetic fluids properties

IFP Energies nouvelles - Mobilité et Systèmes

Stage Chimie Hauts-de-Seine entre mars et avril 2023 6 mois


IFP Energies nouvelles (IFPEN) est un acteur majeur de la recherche et de la formation dans les domaines de l’énergie, du transport et de l’environnement. De la recherche à l’industrie, l’innovation technologique est au cœur de son action, articulée autour de quatre priorités stratégiques : Mobilité Durable, Energies Nouvelles, Climat / Environnement / Economie circulaire et Hydrocarbures Responsables.

Dans le cadre de la mission d’intérêt général confiée par les pouvoirs publics, IFPEN concentre ses efforts sur :

  • l’apport de solutions aux défis sociétaux de l’énergie et du climat, en favorisant la transition vers une mobilité durable et l’émergence d’un mix énergétique plus diversifié ;
  • la création de richesse et d’emplois, en soutenant l’activité économique française et européenne et la compétitivité des filières industrielles associées.

Characterization and modelling of trace compounds impacts on energetic fluids properties

With the announced drastic reduction of the share of fossil energy resources in the European energy mix, it is important to define real alternatives to petrochemicals. Biomass for example can provide a wide variety of families of high added value compounds.

Many fluids are used in the energy, transport, and environment sectors, for various applications ranging from renewable energy production to mobility. These fluids are often complex mixtures whose components are mainly made up of a hydrocarbon backbone. The complexity and chemistry of the components (hydrocarbons, alcohols, esters, etc.) of these fluids vary according to their origin and the targeted application: combustion, cooling, lubrication, or even electrical insulation. The chemical industry is focusing on new modelling techniques to predict the physicochemical behaviour of these fluids to improve for example the processes efficiency.

Computational methods are now involved in all activities of the chemical industry, including the design of new chemical products, the optimisation of manufacturing processes and even the evaluation of fluid properties. IFPEN contributes to these activities through the development of methods based on Machine Learning such as QSPR (Quantitative Structure Property Relationship) models and their inversion to identify the relevant chemical structures according to the targeted application.

This subject is well documented in the scientific literature, whether for the prediction of properties of pure molecules or fluid mixtures. These models rely on structural information of molecules and mixtures as well as on robust databases to deduce the desired properties. However, to date, it is known that the presence of trace compounds can have a strong impact on the properties without these models being able to take this into account.

The strategy proposed in this internship aims to make progress in this direction. It is based on three steps summarised below :

  • The first step will consist of an analysis of the scientific literature as well as the data available at IFPEN to identify the relevant trace compounds as well as the matrices of interest which could be treated within the framework of the internship.
  • Then, an experimental phase will be conducted. The objective will be to develop a test matrix that will make it possible to overcome certain shortcomings identified beforehand. It will also lead to develop a validation data set for future model developed.
  • The last step, depending on the progress of the selected candidate, will be to initiate the development of QSPR models to consider the trace species studied.

This work is part of a collaboration with the DLR (Deutsches Zentrum für Luft- und Raumfahrt) in Germany. The candidate may therefore be required to travel to one of their laboratories to both feed the database and of course to discuss the modelling approaches to be developed.

The internship thus offers the possibility of combining experimental and modelling work. It also enables to exchange with a research laboratory abroad. This is an excellent opportunity that could eventually lead to the start of a PhD at the end of the internship.

Requested profile and skills:

Master’s degree in chemical sciences/chemical engineering.

  • Interest in programming.

Duration and dates: 6 months between march and August 2023
Practical information: The internship will take place at IFP Energies nouvelles in Rueil-Malmaison (west of Paris). The intern will be granted with a financial compensation (unless granted otherwise).

Interested ? Send a letter of motivation and a CV !


(PDF - Max : 5 Mo)
(PDF - Max : 5 Mo)

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IFP Energies nouvelles - Mobilité et Systèmes
Mickael Matrat

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