Structural analysis and Imaging

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.

Today, characterization of geological reservoirs, a long-standing theme in petroleum exploration, becomes a base of interest for a variety of applications, such as CO2 and hydrogen storage as well as geothermal energy. In recent years, the combined use of 3D microtomography (or micro-CT ) imaging and advanced simulation techniques has allowed the emergence of a digital approach to computing the petrophysical properties of reservoir rocks (Digital Rock Physics). This represents a real complement - and in some cases an alternative - to traditional laboratory measurements.

The design of high-quality porous materials is a major challenge for the energy efficiency of industrial processes in the fields of catalysis and biocatalysis and separation and purification operations. For such applications, these materials derive their properties of interest from their specific microstructure, incorporating a large quantity of empty spaces that are organized and connected on a nanometric scale. IFPEN and Saint Gobain Research Provence (SGRP) joined forces to acquire a tool that will ultimately facilitate the development of porous materials optimized for given usages.

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

Foam injection during oil production or ground remediation is aimed at overcoming problems of gravity segregation and viscous fingering a created by fluid injection. Improving this practice requires

Effectively detecting the presence of very low quantities of elements in industrial materials is a major challenge. One such example is heterogeneous catalysis where contamination and poisoning of

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