Organisation/Company CNRS Department Laboratoire Réactions et Génie des Procédés Research Field Engineering Chemistry Physics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 9 Jul 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Oct 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
This PhD will be carried out in the framework of a research program that is funded by the ANR and will take place in the Laboratory of Reactions and Process Engineering, LRGP (https://lrgp-nancy.cnrs.fr/?page_id=4673 ), located in the heart of Europe (Nancy, France). Nancy offers direct and easy access to numerous European destinations in France, Luxembourg, Germany, Switzerland and Belgium while its cost of living is significantly lower than that of many European cities and capitals (e.g., Paris, Strasbourg, city of Luxembourg, etc.).
The Laboratory of Research and Process Engineering (LRGP) leading autonomous research centre in Chemical and Process Engineering, both nationally and internationally. It hosts roughly 300 researchers working on the full spectrum of topics related to the modern challenges of chemical engineers, including energy and environment, process design and intensification techniques, biotechnology, kinetics and thermodynamics as well as product design. It is also part of the National Centre of Scientific Research, CNRS (https://www.cnrs.fr/en ) and of the University of Lorraine, UL (https://www.univ-lorraine.fr/en/univ-lorraine/ ), one of the largest French universities. The LRGP, in collaboration with the UL, also offer a dedicated administrative support for all incoming students and researchers.
The duration of the PhD is 36 months, subject to a monthly gross salary of ca. 2200 €. The recruited candidate will be able to participate, optionally, as assistant lecturer in lectures of the university as means to prepare an eventual pursue of an academic career in France or elsewhere.
Photoinduced Thermal Frontal Polymerization (PTFP) refers to the creation of polymers via the propagation of a localized polymerization reaction zone, called “front”, within the reaction mixture which is photochemically induced at the surface of the sample. Under irradiation, a given volume of polymerizable resin is photochemically cured, leading to the release of heat. This heat release increases locally the temperature at such a value that a thermal initiator can decompose and pursue the polymerization in depth. This leads to a propagating local reaction zone, leading ultimately to a fully cured polymer over a much greater depth than that accessible to the light. This provides a smart method to cure thick and filled polymers. This out-of-autoclave (OoA) process opens a sustainable route to the fabrication of glass-, carbon- or natural- fiber-reinforced polymers (composites) in a more efficient and cost-competitive manner. For example, it has been shown that the implementation of frontal polymerization for curing parts of an airplane could lead to an energy reduction of several orders of magnitude (i.e., up to ten orders of magnitude), with respect to the classical autoclave process, while also significantly reducing the process time and equipment cost. The produced composites have known an important growth over the last decades due to their low weight combined with their high mechanical properties that play a pivotal role in highly demanding markets such as aerospace, aeronautic, automotive and sport applications.
Within the framework of a project, that is financially supported by the National Agency for Research, a multidisciplinary approach is proposed to synthesize highly reactive initiating systems that will lead to stable propagation of the front in the presence of fiber charges and to develop theoretical mathematical models to predict the behavior of the PTFP and the properties of the synthesized resins and composites under various operating conditions. The present call for PhD applications concerns exactly this latter part, i.e., the mathematical modeling of the process. Accordingly, phenomenological and data-driven modeling techniques, ranging from stochastic Monte Carlo (MC) to Machine Learning (ML) methods, will be employed to provide the necessary understanding and predictive capacity tools that will drive the optimal synthesis of resins and composites with targeted end-use properties. Existing mathematical modeling frameworks of the polymerization front, as described in the relative literature, will be further extended and combined with state-of-the-art phenomenological and data-driven modeling tools for the prediction not only of the evolution of key process indexes (e.g., front velocity, temperature and monomer conversion) but also of the polymer properties under a wide range of process conditions. The adopted approach will evolve, depending on the specific modeling objectives of each phase of the project as well as on the available and/or generated knowledge and data on the modeled behavior. The modeling developments will be synchronized with the other two main pillars of the project, namely the study of the chemistry of the system and the characterization of the synthesized resins and composites.
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