Kinetics of silica precipitation on quartz seeds at 200–300 °C

Alekseyev, V. A.; Medvedeva, L. S.; Starshinova, N. P.

doi:10.1134/s0016702909070076

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…quartz in water [3][4][5][6][7], amorphous silica in water and chloride solution [8] or in highly alkaline environment [9], silica nanoparticles [10] and silica glasses [11,12]. From their experimental data the authors measured a broad range of dissolution rate constant and/or activation energies (74.5 up to 108 kJ mol À1 ) depending on the respective material, environmental pH and temperature.…”

Section: Introductionmentioning

confidence: 99%

Dissolution of thin SiO2-coatings – Characterization and evaluation

Klause

Rothhaar

Bicker

et al. 2010

Journal of Non-Crystalline Solids

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Section: Introductionmentioning

confidence: 99%

Dissolution of thin SiO2-coatings – Characterization and evaluation

Klause

Rothhaar

Bicker

et al. 2010

Journal of Non-Crystalline Solids

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“…For example, dissolutionprecipitation processes of minerals play important roles in geoscientific and environmental phenomena in the earth's crust [2][3][4][5][26][27][28]. In laboratory experiments investigating solid-liquid interactions, it is often the case that only concentrations of intermediate products dissolved in liquid phase are quantitatively observable, and the observed time-series data are generally sparse and noisy [3][4][5]. Figure 1 shows the target dissolution-precipitation process governed by the surface heterogeneous reaction, in which the solid reactant r changes to a solid product p via an intermediate product i dissolved in a liquid phase:…”

Section: Estimation Algorithmmentioning

confidence: 99%

“…They are usually determined from observed time evolution of the amount of chemical species by laboratory experiments in various natural sciences [1,2]. In laboratory experiments, it is often the case that only a part of concentrations of chemical species among many species are quantitatively observable, and the observed time-series data are generally sparse and noisy [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Bayesian inversion analysis of nonlinear dynamics in surface heterogeneous reactions

et al. 2016

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It is essential to extract nonlinear dynamics from time-series data as an inverse problem in natural sciences. We propose a Bayesian statistical framework for extracting nonlinear dynamics of surface heterogeneous reactions from sparse and noisy observable data. Surface heterogeneous reactions are chemical reactions with conjugation of multiple phases, and they have the intrinsic nonlinearity of their dynamics caused by the effect of surface-area between different phases. We adapt a belief propagation method and an expectation-maximization (EM) algorithm to partial observation problem, in order to simultaneously estimate the time course of hidden variables and the kinetic parameters underlying dynamics. The proposed belief propagation method is performed by using sequential Monte Carlo algorithm in order to estimate nonlinear dynamical system. Using our proposed method, we show that the rate constants of dissolution and precipitation reactions, which are typical examples of surface heterogeneous reactions, as well as the temporal changes of solid reactants and products, were successfully estimated only from the observable temporal changes in the concentration of the dissolved intermediate product.

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Free-energy landscape and nucleation pathway of polymorphic minerals from solution in a Potts lattice-gas model

et al. 2015

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Metastable minerals commonly form during reactions between water and rock. The nucleation mechanism of polymorphic phases from solution are explored here using a two-dimensional Potts model. The model system is composed of a solvent and three polymorphic solid phases. The local state and position of the solid phase are updated by Metropolis dynamics. Below the critical temperature, a large cluster of the least stable solid phase initially forms in the solution before transitioning into more-stable phases following the Ostwald step rule. The free-energy landscape as a function of the modal abundance of each solid phase clearly reveals that before cluster formation, the least stable phase has an energetic advantage because of its low interfacial energy with the solution, and after cluster formation, phase transformation occurs along the valley of the free-energy landscape, which contains several minima for the regions of three phases. Our results indicate that the solid-solid and solid-liquid interfacial energy contribute to the formation of the complex free-energy landscape and nucleation pathways following the Ostwald step rule.

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Kinetics of silica precipitation on quartz seeds at 200–300 °C

Cited by 5 publications

References 13 publications

Dissolution of thin SiO2-coatings – Characterization and evaluation

Dissolution of thin SiO2-coatings – Characterization and evaluation

Bayesian inversion analysis of nonlinear dynamics in surface heterogeneous reactions

Free-energy landscape and nucleation pathway of polymorphic minerals from solution in a Potts lattice-gas model

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