IFPEN’s fundamental research is structured around nine scientific challenges, which are organized to reflect the overall path followed by our R&I: ranging from the understanding of complex physical phenomena (experimentation, data acquisition) to the evaluation of a complete system (economic and environmental impacts), via the modeling and numerical representation (simulation) of these phenomena. 

As part of a multidisciplinary approach, this organizational structure framing fundamental research makes it possible to pool reasoning processes, identify emerging themes and mobilize scientific communities. It also makes it possible to create bridges between areas of expertise present within IFPEN’s research divisions, exploiting similarities in terms of scientific reasoning, pooling reflection processes and fostering the dissemination of knowledge acquired.

 Each challenge is tackled by a dedicated group, made up of researchers from the different research divisions, and led by a pair of experts.

«IFPEN's scientific challenges approach is both positive and constructive. The structuring of fundamental research around major scientific issues brings greater transparency vis-à-vis the outside», explains Grégoire Allaire, Chairman of IFPEN’s Scientific Board.

Having an organizational structure centered around nine scientific challenges ensures the coherence of all IFPEN’s fundamental research activities.

IFPEN's scientific challenges
IFPEN's nine scientific challenges

Each year, within the context of each main challenge, a number of scientific sub-challenges are identified and formalized, each sub-challenge expressing a scientific problem to be overcome for IFPEN, a problem translated into objectives to be met, for which a long-term research strategy is proposed.

In 2019:
46 sub-challenges examined, 44 sub-challenges formalized
10 new sub-challenges


Brochure: Fundamental research at IFPEN 
(PDF - 3.5 Mo)



  • Scientific challenge No. 1: material and fluid characterization for energy, on various scales
    The development of new analytical pre-treatment systems, based on centrifugal partition chromatography. By coupling these with high-performance analytical methods, it is now possible to characterize effluents more precisely. Moreover, this approach opens up new avenues for isolating and identifying enzymatic reaction inhibitors, these reactions being crucial to the biochemical conversion of biomass.
  • Scientific challenge No. 2: understanding chemical, catalytic and enzymatic reaction mechanisms on a molecular or adapted scal
    Culmination of three years’ research work within the Oxygen JIP.
  • Scientific challenge No.3: understanding the effect of confining fluids on their dynamics and their reactivity in porous media
    Molecular modeling adapted for the purposes of studying clay interface diffusion.
  • Scientific challenge No. 4: the optimum processing of large volumes of experimentation and simulation data
    Organization of the Scienc’Innov “DataScien2018” workshop, dedicated to data science in the energy field, bringing together 110 academic and industrial participants for three plenary sessions (Frameworks and platforms, Advances in algorithms and Industry) and two practical work sessions. 
  • Scientific challenge No. 5: the identification of descriptors for the design of materials, processes and simulators
    Culmination of the ANR Slimcat project.
  • Scientific challenge No. 6: the modeling of closely-coupled phenomena with a view to scale change
    Electrochemical modeling of the battery in usage conditions. Development of a thermal runaway model on the scale of a reference cell and calibrated on the basis of “safety data” provided by Ineris, to simulate the design of a battery pack that would limit the risks of runaway and make recommendations, within the framework of the H2020 Demobase project.
  • Scientific challenge No. 7: the control and optimization of complex systems
    Launch of the H2020 CEVolver project.
  • Scientific challenge No. 8: achieving the best numerical and IT performance of our computational codes
    Development of a new numerical resolution method to allow non-linear slope-dependent sediment flow, while respecting a maximum erosion rate constraint. It also combines sedimentation with surface water flow. This method makes it possible to better simulate the interaction of these natural phenomena.
  • Scientific challenge No. 9: assessing the economic and environmental impacts of innovations relating to the energy transition
    Within the framework of the Generate project, study of the criticality of energy transition materials and the geographic analysis of low-carbon innovations. Several raw materials markets (copper, lithium, etc.) haven been modeled in the TIMES family of energy forecasting models in order to evaluate the demand for materials in 2050 in a variety of climate scenarios.

Go to science@ifpen to find articles dedicated to our scientific challenges 
Scientific challenge 8 / Computational code performance:  issue 33 of Science@ifpen
Scientific challenge 7 / Control and optimization of complex systems: issue 30 of Science@ifpen
Scientific challenge 6 / Multiphysical and multiscale modeling: issue 26 of Science@ifpen
Special issue on scientific challenges: issue 20 of Science@ifpen



Hélène Olivier-Bourbigou

  • “Fundamental Research” program manager