General information
Topics:
Chemical-engineering thermodynamics.
Title:
Innovative modeling methods to describe fluid properties: This work is devoted to the improvement of two types of thermo- dynamic models (equations of state) applicable to pure species and mixtures following innovative and unexplored methodologies:
(1) Development of a SAFT-type model* and the optimal way to parameterize it with emphasis on the association term**,
(2) A fully novel way to improve cubic equations of state – deriving from the Van der Waals theory – through the study of the temperature dependence of their attractive term.
This challenge is likely to highlight new horizons for thermodynamic modeling; it is ideal for students who are ready to commit themselves 100% and participate in an ambitious project.
Funding:
Scholarship from the GTT company.
Gross salary:
35 000 € / year (approximately).
Dates:
Start date: between October 2023 and December 2023 (depending on candidate preference). The duration of the doctoral thesis is 3 years.
Place:
Team ThermE (thermodynamics and energy), of the LRGP (Laboratory for Reactions and Chemical Engineering) – University of Lorraine, Nancy, France.
Ph.D. supervisors:
Jean-Noël Jaubert, full professor.
jean-noel.jaubert@univ-lorraine.fr
(+33)3.72.74.37.70
Romain Privat, associate professor.
romain.privat@univ-lorraine.fr
(+33)3.72.74.37.73
More about our research activities:
Ideal candidate’s skills
- Good knowledge in chemical engineering, thermodynamics and mathematics (numerical methods);
Problem-solving orientation; - High work capacity;
- Knowledge of a computer-programing language (ForTran ideally);
- Communication skills (in English or in French).
Note that the thesis work will be purely theoretical and numerical (no experimental work).
Application
To apply, send your CV, a motivation letter, a transcript of recent academic results (if possible, a letter of recommendation would be highly appreciated) to Jean-Noël Jaubert and Romain Privat.
Scientific content
Our team:
Our research group is specialized in the development and parameterization of equations of state. For many years, we are working conjointly on two EoS classes: the cubic models (issued from Van
der Waals’ seminal work) and the SAFT-type models (SAFT stands for “Statistical Associating Fluid Theory”).
Numerous successes were obtained in the past years by our team including the description of pure-component properties with an unprecedented accuracy and the development of efficient predictive methods making it possible to guesstimate phase behaviours and energetic properties of complex non-associating mixtures (i.e., mixtures that are free of hydrogen bonds). Among these, let us cite: the PPR78 and E-PPR78 models, the PR2SRK model, the I-PC-SAFT model, all available in commercial simulation software and regularly used by the scientific community.
Objectives of the thesis:
However, despite intensive efforts, progress remains to be made in fluid modeling. Regardless of the approach chosen (SAFT or cubic), equations of state are still struggling to simultaneously reproduce phase equilibria, volumetric and energetic properties of fluids, in particular when approaching the critical region.
While 99.99 % of current equations of state are classically derived from well founded SAFT or cubic theories, some unexplored or nearly-unexplored ways deserve interest and could have the potential to move the lines. In this thesis, two types of study are proposed:
- While SAFT-type models are currently plethoric and parameterized according to different or even contradictory methodologies, we propose here to first study the transferability of SAFT pa-
- rameters (i.e., the possibility of using similar parameters within the same family of compounds) and then to develop a method to predict association patterns and parameters. Ultimately, a new
- industrialized version of the PC-SAFT model will emerge from the study.
- A cubic type model involving a temperature dependent function in the volume polynomial of the attractive term. Note that this approach has never been explored before but following our
- preliminary calculations, it shows a strong potential.
*SAFT stands for Statistical Associating Fluid Theory.
**By association, it is meant mainly the hydrogen bonding.
