Clean Water and Sanitation (SDG 6), Climate Action (SDG 13)
Enhancing mineral carbonation through molecular simulations on diopside surfaces Jessica Jein White 1 , Yuan Mei 1 , Yanlu Xing 2 and Weihua Liu 2 1 CSIRO - Kensington, Australian Resources Research Centre (ARRC) 26 Dick Perry Ave, Kensington WA Australia 6151. 2 CSIRO Clayton Research Way, Clayton VIC Australia 3168. Corresponding author: jess.white@csiro.au The increasing carbon dioxide level in the atmosphere in the past century has caused dire effects on the environment. Mineral carbonation offers a promising approach to remove CO 2 from the atmosphere by reacting with rocks enriched with Ca 2+ , Mg 2+ , and Fe 2+ to form stable carbonate minerals. However, in nature these processes typically occur at extremely slow rates. Therefore, it is crucial to develop technologies that can rapidly accelerate these processes for effective CO 2 removal and storage. The slow dissolution of Mg 2+ and Ca 2+ from the silicate minerals has been pinpointed as one of the significant limiting reactions for carbon mineralisation. Recently, experimental and engineering studies have demonstrated the potential of using Ca 2+ and Mg 2+ -rich mafic-ultramafic rocks to store CO 2 . Yet, the reaction mechanisms during the mineral carbonation processes at various fluid compositions and temperature-pressure conditions are poorly understood. In this study, we applied a recently developed method called Machine Learning Molecular Dynamics (MLMD) to enable a much longer time scale to investigate the reaction mechanism but at reduced costs within the accuracy of AIMD. Molecular modelling will include looking at the mineral surface and seeing the optimal parameters (e.g temperature, water, etc) to dissociate these cations so they can be used for carbonation. This molecular study can help further enhance this reaction by pinpointing what is happening at an atomic level, and thus how to improve the reaction. Keywords: Density functional theory, machine learning, carbon mineralisation, climate action
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