Multiscale modelling at ICIQ to improve hydrogen production

By February 7, 2018ICIQ

Researchers at the BIST Centre ICIQ are working towards understanding the hydrogen production from alcohol reforming by multiscale modelling.

Alcohols and sugars are among the main derivatives of non-edible biomass. The transformation of these molecules into hydrogen or other chemicals by reforming technologies could lead to a more sustainable future. However, hydrogen production from long-chain alcohols has a very complex reaction networks. Even a simple alcohol like ethylene glycol goes through 75 intermediates and 250 different possible reactions. Understanding this mechanism, as well as its behaviour under different operation conditions, is key to develop efficient catalytic processes to produce hydrogen from biomass.

The ICIQ research group lead by Prof. Núria López’s made a complete multiscale model on alcohols reforming that was recently published in Nature Communications. The models, based on DFT and microkinetics, were computed in MareNostrum at the Barcelona Supercomputing Centre. Researchers studied the decomposition reaction pathway of ethanol, glycerol, and ethylene glycol on four different metals: palladium, platinum, ruthenium, and earth abundant copper. ‘This means we computed more than 1000 different reactions, we considered almost 3000 elementary steps in this study,’ explains Dr. Qiang Li, one of the authors. ‘We also developed strategies to avoid the formation of catalyst poisons, thus improving the global efficiency of these important processes,’ adds Li.

Dr. Rodrigo García-Muelas highlights how this paper paves the way for new studies in the near future: ‘Not only have we published everything in an open access journal, we also made all of our calculations openly available in the ioChem-BD database,’ he says. ‘This will give researchers a nice starting point for the analysis of the reaction pathways of longer alcohols,’ he adds. With all the data in hand, chemists could develop fast screening tools and machine learning algorithms to predict the efficiency of new catalysts for hydrogen production. ‘We could discover new metals or alloys with higher activity and selectivity,’ explains García-Muelas. ‘Or we could use our models to scale-up the reforming processes, which could be very practical for the energy industry,’ points out Li.

More information can be found on the ICIQ website.

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