GA MOF
An Optimised Genetic Algorithm to Computationally Predict a Metal-Organic Framework to Separate Helium from Methane
| Coordinatore | JACOBS UNIVERSITY BREMEN GGMBH
Organization address
address: Campus Ring 1 contact info |
| Nazionalità Coordinatore | Germany [DE] |
| Totale costo | 161˙968 € |
| EC contributo | 161˙968 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2012-IIF |
| Funding Scheme | MC-IIF |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-03-01 - 2015-02-28 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
JACOBS UNIVERSITY BREMEN GGMBH
Organization address
address: Campus Ring 1 contact info |
DE (BREMEN) | coordinator | 161˙968.80 |
Mappa
Word cloud
Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.
Obiettivo del progetto (Objective)
'Metal-Organic Frameworks (MOFs) are a class of inorganic-organic crystalline material with extremely high porosity, making them ideal substrates for the separation of gas mixtures by selective adsorption. The most significant barrier to the bottom-up design of a MOF for a given application is the combinatorial explosion of possible MOFs as the sheer number of chemical environments it is possible to create makes it highly unlikely that any naïve approach will locate a suitable one in any reasonable timeframe. The overall aim of this project is to develop a method to efficiently search the space of possible metal-organic framework structures and to use this to design a framework structure with user specified properties. To this end, we propose an optimised genetic algorithm for the guided computational design of a metal-organic framework to separate helium from methane.'
Altri progetti dello stesso programma (FP7-PEOPLE)
INTERACTIONS (2013)
"Investigation of the interaction between external stimulation and ongoing brain activity in cortical networks: analysis, modeling and empirical corroboration"
Read More