(582e) Application of a Genetic Algorithm to Screen Metal-Organic Frameworks: Pre-Combustion CO2/H2 Separation

Metal-organic frameworks (MOFs) are novel porous materials consisting of organic and inorganic building blocks, whose combinatorial possibilities give rise to a practically unlimited number of possible structures. Due to the large number of possible MOFs, high-throughput computational screening has been used in the literature to identify high-performing MOFs for particular applications of interest, such as methane storage and delivery. Computational screening has also provided useful structure-property relationships that can guide experimental discovery efforts. However, current approaches are “brute-force”, where full molecular simulations are carried out to calculate the property of interest for a very large number of structures that have been generated or mined from the literature. This approach may not be suitable, however, for complex systems or for very time-consuming simulations because of the prohibitively large computational cost associated with such simulations.

In this work, we have developed a Genetic Algorithm (GA) to identify high-performing MOFs for pre-combustion CO₂/H₂ separation from a database of ~137,000 hypothetical MOFs [1]. Firstly, grand canonical Monte Carlo (GCMC) simulations were carried out to calculate CO₂/H₂ uptakes under selected operation conditions for a “genetically diverse” initial generation of 100 hypothetical MOFs. Secondly, genetic operations were carried out on the preceding generation of structures to create a new one, for which GCMC simulations were carried out as well. This procedure was continued until we reached 10 generations.

Our results demonstrate that the developed GA is a robust method that can find high-performing MOFs based on different performance metrics such as CO₂/H₂ selectivity and CO₂ working capacity in a much more computationally efficient fashion than the brute force method. One of the top MOFs identified by the GA was synthesized and activated, with the experimental CO₂ and H₂ adsorption values in good agreement with the molecular simulation results. Moreover, the predicted MOF has the highest CO₂ working capacity (~ 6 mol/kg) among reported MOFs and zeolites in the literature under the same operating conditions [2].

#: Authors contributing equally

References

[1] C. E. Wilmer, M. Leaf, C.Y. Lee, O.K. Farha, B.G. Hauser, J.T. Hupp, and R.Q. Snurr, “Large-scale screening of hypothetical metal-organic frameworks”, Nature Chemistry, 2012, 4, (2), 83 – 89.
[2] Z. R. Herm, J. A. Swisher, B. Smit, R. Krishna, and J. R. Long, “Metal-Organic Frameworks as Adsorbents for Hydrogen Purification and Precombustion Carbon Dioxide Capture”, J. Am. Chem. Soc., 2011, 133, (15), 5664 – 5667.