Chemical sciences

Semantic segmentation conducted on microscopy images is a processing operation carried out to quantify a material’s porosity and its heterogeneity. It is aimed at classifying every pixel within the image (on the basis of degree of heterogeneity and porosity). However, for some materials (such as aluminas employed for catalysis), it is very difficult or even impossible using a traditional image processing approach, since porosity differences are characterized by small contrasts and complex textural variations. One way of overcoming this obstacle is to tackle semantic segmentation via deep learning, using a convolutional neural network.

Numerical simulations are now widely employed in the industrial world to help design systems and predict complex phenomena. Reactive flow simulation, for example, is important for numerous applications, such as vehicle and aircraft propulsion and processes in the chemicals industry.

Zeolites are nanoporous solids widely used as acid catalysts for the conversion of hydrocarbon molecules. However, determining the rates of the elementary steps of reaction mechanisms...

Platinum nanoparticles supported on chlorinated γ-alumina are used in bifunctional heterogeneous catalysts, which are central to numerous industrial processes. An atomic-scale study...

The development of production processes for fuel and platform molecules from lignocellulosic biomass requires knowledge of the chemical composition, on a molecular scale, of the various liquid products generated...

Meeting environmental standards governing the sulfur content of oil-based fuels hinges around the optimization of hydrotreatment processes (HDT), involving, in particular, the development of more

IFPEN is actively involved in the development of innovative processes for the conversion of lignocellulosic biomass into bio-based fuels and molecules. However, in chemical terms, the products