Issue 36, 2014

Designing mixed metal halide ammines for ammonia storage using density functional theory and genetic algorithms

Abstract

Metal halide ammines have great potential as a future, high-density energy carrier in vehicles. So far known materials, e.g. Mg(NH3)6Cl2 and Sr(NH3)8Cl2, are not suitable for automotive, fuel cell applications, because the release of ammonia is a multi-step reaction, requiring too much heat to be supplied, making the total efficiency lower. Here, we apply density functional theory (DFT) calculations to predict new mixed metal halide ammines with improved storage capacities and the ability to release the stored ammonia in one step, at temperatures suitable for system integration with polymer electrolyte membrane fuel cells (PEMFC). We use genetic algorithms (GAs) to search for materials containing up to three different metals (alkaline-earth, 3d and 4d) and two different halides (Cl, Br and I) – almost 27 000 combinations, and have identified novel mixtures, with significantly improved storage capacities. The size of the search space and the chosen fitness function make it possible to verify that the found candidates are the best possible candidates in the search space, proving that the GA implementation is ideal for this kind of computational materials design, requiring calculations on less than two percent of the candidates to identify the global optimum.

Graphical abstract: Designing mixed metal halide ammines for ammonia storage using density functional theory and genetic algorithms

Supplementary files

Article information

Article type
Paper
Submitted
16 Jul 2014
Accepted
05 Aug 2014
First published
05 Aug 2014
This article is Open Access
Creative Commons BY license

Phys. Chem. Chem. Phys., 2014,16, 19732-19740

Author version available

Designing mixed metal halide ammines for ammonia storage using density functional theory and genetic algorithms

P. B. Jensen, S. Lysgaard, U. J. Quaade and T. Vegge, Phys. Chem. Chem. Phys., 2014, 16, 19732 DOI: 10.1039/C4CP03133D

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