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An Optimised Genetic Algorithm to Computationally Predict a Metal-Organic Framework to Separate Helium from Methane


"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."

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Campus Ring 1
28725 Bremen
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 161 968,80
Administrative Contact
Ronald Kieschnick (Mr.)