Solute Precipitate Nucleation: A Review of Theory and Simulation Advances

Agarwal, Vishal; Peters, Baron

doi:10.1002/9781118755815.ch03

Cited by 77 publications

(142 citation statements)

References 300 publications

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“…(7), corresponding to the difference between the bulk solute chemical potentials in states of metastable supersaturation and solute-solvent coexistence. 1,4,55 It is, however, understood that usage of the bulk value ∆µ = ∆µ coex as the driving force to nucleation may be unsuitable for the description of the microscopic particle attachment process. 56 An alternative value ∆µ fit ( β, f ) can be obtained via a two parameter fit of Eq.…”

Section: E Choice Of ∆µmentioning

confidence: 99%

“…6(b), which is consistent with the intuition that diffusivity along the n coordinate is approximately constant close to the top of the free energy barrier. 1 We therefore use the data for ζ n (n 0 ) in the range n 0 ∈ [n * − 20, n * + 20] to estimate the statistical uncertainty in our measurement ζ n (n * ) of the diffusivity D n along the cluster size coordinate.…”

Section: Drift Velocities and Diffusivitiesmentioning

confidence: 99%

“…[1][2][3] To date, very few studies have computed quantitative absolute nucleation rates from such simulations. 4 A particularly challenging example where nucleation kinetics remain well beyond the reach of atomistic simulation is biomineralisation.…”

Section: Introductionmentioning

confidence: 99%

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Nucleation barrier reconstruction via the seeding method in a lattice model with competing nucleation pathways

Lifanov

Vorselaars

Quigley

2016

The Journal of Chemical Physics

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We study a three-species analogue of the Potts lattice gas model of nucleation from solution in a regime where partially disordered solute is a viable thermodynamic phase. Using a multicanonical sampling protocol, we compute phase diagrams for the system, from which we determine a parameter regime where the partially disordered phase is metastable almost everywhere in the temperature-fugacity plane. The resulting model shows non-trivial nucleation and growth behaviour, which we examine via multidimensional free energy calculations. We consider the applicability of the model in capturing the multi-stage nucleation mechanisms of polymorphic biominerals (e.g., CaCO 3 ). We then quantitatively explore the kinetics of nucleation in our model using the increasingly popular "seeding" method. We compare the resulting free energy barrier heights to those obtained via explicit free energy calculations over a wide range of temperatures and fugacities, carefully considering the propagation of statistical error. We find that the ability of the "seeding" method to reproduce accurate free energy barriers is dependent on the degree of supersaturation, and severely limited by the use of a nucleation driving force ∆µ computed for bulk phases. We discuss possible reasons for this in terms of underlying kinetic assumptions, and those of classical nucleation theory. C 2016 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license

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Section: E Choice Of ∆µmentioning

confidence: 99%

Section: Drift Velocities and Diffusivitiesmentioning

confidence: 99%

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Nucleation barrier reconstruction via the seeding method in a lattice model with competing nucleation pathways

Lifanov

Vorselaars

Quigley

2016

The Journal of Chemical Physics

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“…Homogeneous nucleation happens in a medium of solute and solvent, without the presence of any surfaces or impurities [33]. For example, bubbles can nucleate spontaneously inside a bulk liquid during boiling.…”

Section: Bubble Nucleationmentioning

confidence: 99%

“…2) CNT computes the nucleation rates based only on the nucleus size and ignoring the effect of local fluctuation and depletion of the solution concentration [33]. For instance, consumption of molecular concentration changes the free energy of nucleation and may effect the supersaturation limits that drives the bubble nucleation.…”

Section: Bubble Nucleationmentioning

confidence: 99%

Modeling of bubbles hydrodynamics and mass transfer in electrochemical gas-evolving systems

Taqieddin¹

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Molecular simulation approaches to study crystal nucleation from solutions: Theoretical considerations and computational challenges

Finney,

Salvalaglio

2023

WIREs Comput Mol Sci

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Nucleation is the initial step in the formation of crystalline materials from solutions. Various factors, such as environmental conditions, composition, and external fields, can influence its outcomes and rates. Indeed, controlling this rate‐determining step toward phase separation is critical, as it can significantly impact the resulting material's structure and properties. Atomistic simulations can be exploited to gain insight into nucleation mechanisms—an aspect difficult to ascertain in experiments—and estimate nucleation rates. However, the microscopic nature of simulations can influence the phase behavior of nucleating solutions when compared to macroscale counterparts. An additional challenge arises from the inadequate timescales accessible to standard molecular simulations to simulate nucleation directly; this is due to the inherent rareness of nucleation events, which may be apparent in silico at even high supersaturations. In recent decades, molecular simulation methods have emerged to circumvent length‐ and timescale limitations. However, it is not always clear which simulation method is most suitable to study crystal nucleation from solution. This review surveys recent advances in this field, shedding light on typical nucleation mechanisms and the appropriateness of various simulation techniques for their study. Our goal is to provide a deeper understanding of the complexities associated with modeling crystal nucleation from solution and identify areas for further research. This review targets researchers across various scientific domains, including materials science, chemistry, physics and engineering, and aims to foster collaborative efforts to develop new strategies to understand and control nucleation.This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Molecular and Statistical Mechanics > Free Energy Methods Theoretical and Physical Chemistry > Statistical Mechanics

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Solute Precipitate Nucleation: A Review of Theory and Simulation Advances

Cited by 77 publications

References 300 publications

Nucleation barrier reconstruction via the seeding method in a lattice model with competing nucleation pathways

Nucleation barrier reconstruction via the seeding method in a lattice model with competing nucleation pathways

Modeling of bubbles hydrodynamics and mass transfer in electrochemical gas-evolving systems

Molecular simulation approaches to study crystal nucleation from solutions: Theoretical considerations and computational challenges

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