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Reconsidering Calcium Dehydration as the Rate-Determining Step in Calcium Mineral Growth

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Abstract

The dehydration of cations is generally accepted as the rate-limiting step in many processes. Molecular dynamics (MD) can be used to investigate the dynamics of water molecules around cations, and two different methods exist to obtain trajectory-based water dehydration frequencies. Here, these two different post-processing methods (direct method versus survival function) have been implemented to obtain calcium dehydration frequencies from a series of trajectories obtained using a range of accepted force fields. None of the method combinations reproduced the commonly accepted experimental water exchange frequency of 10-8.2 s-1. Instead, our results suggest much faster water dynamics, comparable with more accurate ab initio MD simulations and with experimental values obtained using neutron scattering techniques. We obtained the best agreement using the survival function method to characterize the water dynamics, and we show that different method combinations significantly affect the outcome. Our work strongly suggests that the fast water exchange kinetics around the calcium ions is not rate-limiting for reactions involving dissolved/solvated calcium. Our results further suggest that, for alkali and most of the earth alkali metals, mechanistic rate laws for growth, dissolution, and adsorption, which are based on the principle of rate-limiting cation dehydration, need careful reconsideration.

Original languageEnglish
Pages (from-to)26895-26903
Number of pages9
JournalJournal of Physical Chemistry C
Volume123
Issue number44
DOIs
Publication statusPublished - 16 Oct 2019

Funding

The research work of J.A.K. and M.W. is part of the Industrial Partnership Programme i32 Computational Sciences for Energy Research that is carried out under an agreement between Shell and the Netherlands Organisation for Scientific Research (NWO). This work was sponsored by NWO Exact and Natural Sciences for the use of supercomputer facilities. We are grateful to the UK Materials and Molecular Modelling Hub for additional computational resources, which is partially funded by EPSRC (EP/P020194/1). This research utilized Queen Mary’s Apocrita HPC facility, supported by QMUL Research-IT. http://doi.org/10.5281/zenodo.438045 . Finally, we acknowledge the support of the Supercomputing Wales project, which is part-funded by the European Regional Development Fund (ERDF) via the Welsh Government.

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