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Plastics recycling is a major current issue, making it possible to reduce the ecological and environmental impacts linked to their production and consumption. This involves developing specific recycling processes depending on the plastics.
Catalytic processes have long been used regularly in academia and in various industries. One of the major objectives of catalysis today is to improve catalytic systems by combining the performance of homogeneous catalysis with the ease of implementation of heterogeneous catalysis.
Butadiene is a crucial chemical, notably for the manufacturing of elastomers and tires but currently is only produced from fossil sources. In the transition to the sustainable economy, the ethanol-to-butadiene reaction has emerged as a promising solution to secure its production but above all to limit its environmental footprint.
Process efficiency in the field of energy and biomass conversion is a contemporary and urgent societal issue. Heterogeneous catalysis is a key enabling technology towards this goal.
Greenhouse gas emissions are one of the main research areas at IFPEN. Through the solutions panel for reducing such emissions, Carbon Capture and Storage (CCS) represents between 15 to 30% of the total required work to achieve, following the different constructed models for climate prediction.
The transformation of lignocellulosic biomass must be considered to meet the challenges of the energy field. Detailed knowledge of the products generated is essential to develop efficient and innovative processes.
The overall aim of this project is to develop new techniques that lead to better performing heterogeneous catalyst products, which are applied in many gas-phase processes, such as production of fuels, chemical intermediates and biomass conversion.
Plastic recycling is one of the main challenges of the energy transition. Plastics are widely used in many fields (automotive, packaging, and housing) and generate a huge quantity of waste.
The development of specific liquid-liquid extraction operations is crucial for various bio-chemical processes, such as the production of biofuels. This technique is based on the differential solute affinity between two immiscible liquid phases.
Unlike conventional emulsions stabilized by surfactant molecules, Pickering emulsions are stabilized by nanoparticles. Because of their extreme stability to coalescence, they find numerous applications in several industries (agrifood, pharmaceuticals, chemical industry).
The advent of Machine Learning techniques (ML) is stimulating modern computational chemistry. This methodology may open avenues to address challenging questions in catalytic reactions involved in biomass derived molecules transformation.
In numerical simulation, the discretization of physical models made up of partial differential equations often gives rise to non-linear algebraic systems. The resolution of these systems is generally not easy, due to the large number of unknowns and especially their non-linear character.