Literature DB >> 29907051

A structural coarse-grained model for clays using simple iterative Boltzmann inversion.

Karl Schaettle1, Luis Ruiz Pestana2, Teresa Head-Gordon1, Laura Nielsen Lammers3.   

Abstract

Cesium-137 is a major byproduct of nuclear energy generation and is environmentally threatening due to its long half-life and affinity for naturally occurring micaceous clays. Recent experimental observations of illite and phlogopite mica indicate that Cs+ is capable of exchanging with K+ bound in the anhydrous interlayers of layered silicates, forming sharp exchange fronts, leading to interstratification of Cs- and K-illite. We present here a coarse-grained (CG) model of the anhydrous illite interlayer developed using iterative Boltzmann inversion that qualitatively and quantitatively reproduces features of a previously proposed feedback mechanism of ion exchange. The CG model represents a 70-fold speedup over all-atom models of clay systems and predicts interlayer expansion for K-illite near ion exchange fronts. Contrary to the longstanding theory that ion exchange in a neighboring layer increases the binding of K in lattice counterion sites leading to interstratification, we find that the presence of neighboring exchanged layers leads to short-range structural relaxations that increase basal spacing and decrease cohesion of the neighboring K-illite layers. We also provide evidence that the formation of alternating Cs- and K-illite interlayers (i.e., ordered interstratification) is both thermodynamically and mechanically favorable compared to exchange in adjacent interlayers.

Entities:  

Year:  2018        PMID: 29907051     DOI: 10.1063/1.5011817

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  1 in total

1.  Ion exchange selectivity in clay is controlled by nanoscale chemical-mechanical coupling.

Authors:  Michael L Whittaker; Laura N Lammers; Sergio Carrero; Benjamin Gilbert; Jillian F Banfield
Journal:  Proc Natl Acad Sci U S A       Date:  2019-10-16       Impact factor: 11.205

  1 in total

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