Objective
The present RTN project aims to investigate and INtelligently DEsign NanoporouS media most adapted for the storage/separation of specific gas molecules. A number of applications use adsorption phenomena in nanoporous materials. The present Marie-Curie training project will form both ESR's and ER's in the dual fields of experiment and simulation with respect to given storage and separation applications inside nanoporous media. The RTN aims to design the zeolite and zeotype materials, to predict their adsorption properties in industrial applications with respect to specific molecules and to experimentally evaluate their performance by measurements of pure gas / mixture adsorption and diffusion.
Initial work will focus on the following gases:
-Carbon dioxide
- Methane
- Carbon monoxide
- Hydrogen
Whilst a large part of this project will be devoted to fundamental research, the role of the industrial partners and external consultants will be crucial in order to validate the choice of materials and to test under applied conditions. This work will combine modelling and experimental approaches by involving experts in the field of synthesis and experimental characterisation (adsorption, structure, diffusion), coupled with specialists in charge of the simulation of t he synthesis process as well as the various properties of the nanoporous materials investigated. The scientific originality of this project will be thus the development of a tool which is able to predict the structure and chemical composition of a given corresponding zeolite or zeotype. Building on this, specific synthesis routes will be developed to prepare such samples. The microscopic and macroscopic properties of these samples will be confronted with their performance in industrial tests. In this respect, this project is unique and ambitious.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural scienceschemical sciencesinorganic chemistryinorganic compounds
- agricultural sciencesagriculture, forestry, and fisheriesagriculturehorticulturefruit growing
- natural scienceschemical sciencesorganic chemistryaliphatic compounds
- social scienceseconomics and businessbusiness and managementemployment
- natural sciencesmathematicsapplied mathematicsmathematical model
Call for proposal
FP6-2002-MOBILITY-1
See other projects for this call
Funding Scheme
RTN - Marie Curie actions-Research Training NetworksCoordinator
PARIS
France