Rate Prediction for Homogeneous Nucleation of Methane Hydrate at Moderate Supersaturation Using Transition Interface Sampling

Arjun, Arjun; Bolhuis, Peter G.

doi:10.1021/acs.jpcb.0c04582

Cited by 29 publications

(42 citation statements)

References 71 publications

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“…This setup was also successfully applied in our previous work. 29 , 43 Here, we define the liquid stable state by MCG ≤ 10. We define the solid stable state by the presence of the largest cluster with an MCG of size ≥ 300.…”

Section: Methodsmentioning

confidence: 99%

Molecular Understanding of Homogeneous Nucleation of CO₂ Hydrates Using Transition Path Sampling

Arjun

Bolhuis

2020

J. Phys. Chem. B

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Carbon dioxide hydrate is a solid built from hydrogen-bond stabilized water cages that encapsulate individual CO 2 molecules. As potential candidates for reducing greenhouse gases, hydrates have attracted attention from both the industry and scientific community. Under high pressure and low temperature, hydrates are formed spontaneously from a mixture of CO 2 and water via nucleation and growth. Yet, for moderate undercooling, i.e., moderate supersaturation, studying hydrate formation with molecular simulations is very challenging due to the high nucleation barriers involved. We investigate the homogeneous nucleation mechanism of CO 2 hydrate as a function of temperature using transition path sampling (TPS), which generates ensembles of unbiased dynamical trajectories across the high barrier between the liquid and solid states. The resulting path ensembles reveal that at high driving force (low temperature), amorphous structures are predominantly formed, with 4 1 5 10 6 2 cages being the most abundant. With increasing temperature, the nucleation mechanism changes, and 5 12 6 2 becomes the most abundant cage type, giving rise to the crystalline sI structure. Reaction coordinate analysis can reveal the most important collective variable involved in the mechanism. With increasing temperature, we observe a shift from a single feature (size of the nucleus) to a 2-dimensional (size and cage type) variable as the salient ingredient of the reaction coordinate, and then back to only the nucleus size. This finding is in line with the underlying shift from an amorphous to a crystalline nucleation channel. Modeling such complex phase transformations using transition path sampling gives unbiased insight into the molecular mechanisms toward different polymorphs, and how these are determined by thermodynamics and kinetics. This study will be beneficial for researchers aiming to produce such hydrates with different polymorphic forms.

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Section: Methodsmentioning

confidence: 99%

Molecular Understanding of Homogeneous Nucleation of CO₂ Hydrates Using Transition Path Sampling

Arjun

Bolhuis

2020

J. Phys. Chem. B

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“…Some success has been achieved by using RETIS on the (shorter) innermost interfaces, while disabling replica exchange (allowing independent parallel simulations) on outer interfaces (see, e.g., ref. [117]).…”

Section: Software For Tps and Tismentioning

confidence: 99%

“…Several studies applied TPS to phase transitions, for example, solid polymorph transitons. [ 146–148 ] Nucleation processes tend to be very diffusive, [ 31,69,117,149–154 ] and can require quite long paths (>10 ns), especially for molecular systems such as water where path lengths can even run into the 100 s of ns. [ 117 ]…”

Section: Applicationsmentioning

confidence: 99%

“…[145] Several studies applied TPS to phase transitions, for example, solid polymorph transitons. [146][147][148] Nucleation processes tend to be very diffusive, [31,69,117,[149][150][151][152][153][154] and can require quite long paths (>10 ns), especially for molecular systems such as water where path lengths can even run into the 100 s of ns. [117] Transitions in small molecular systems have also been studied, for example, water cluster isomerization [155] and water evaporation, [156] diffusion of water, [157] water transport through pores, [158] polymer collapse collapse, [159,160] cavitation, [161] and coarse grained micelle fusion.…”

Section: Applicationsmentioning

confidence: 99%

“…[146][147][148] Nucleation processes tend to be very diffusive, [31,69,117,[149][150][151][152][153][154] and can require quite long paths (>10 ns), especially for molecular systems such as water where path lengths can even run into the 100 s of ns. [117] Transitions in small molecular systems have also been studied, for example, water cluster isomerization [155] and water evaporation, [156] diffusion of water, [157] water transport through pores, [158] polymer collapse collapse, [159,160] cavitation, [161] and coarse grained micelle fusion. [162] TPS also enables investigating of dynamical phase transitions in glassy systems, [56,[163][164][165][166][167][168] using the framework of large deviation theory.…”

Section: Applicationsmentioning

confidence: 99%

See 2 more Smart Citations

Transition Path Sampling as Markov Chain Monte Carlo of Trajectories: Recent Algorithms, Software, Applications, and Future Outlook

Bolhuis

Swenson

2021

Advcd Theory and Sims

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The development of enhanced sampling methods to investigate rare but important events has always been a focal point in the molecular simulation field. Such methods often rely on prior knowledge of the reaction coordinate. However, the search for this reaction coordinate is at the heart of the rare event problem. Transition path sampling (TPS) circumvents this problem by generating an ensemble of dynamical trajectories undergoing the activated event. The reaction coordinate is extracted from the resulting path ensemble using variants of machine learning, making it an output of the method instead of an input. Over the last 20 years, since its inception, many extensions of TPS have been developed. Perhaps surprisingly, large‐scale TPS simulations on complex molecular systems have become possible only recently. Other important developments include the transition interface sampling (TIS) methodology to compute rate constants, the application to multiple states, and adaptive path sampling. The development of OpenPathSampling and PyRETIS has enabled easy and flexible use and implementation of these and other novel path sampling algorithms. In this progress report, a brief overview of recent developments, novel algorithms, and software is given. In addition, several application areas are discussed, and a future outlook for the next decade is given.

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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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Rate Prediction for Homogeneous Nucleation of Methane Hydrate at Moderate Supersaturation Using Transition Interface Sampling

Cited by 29 publications

References 71 publications

Molecular Understanding of Homogeneous Nucleation of CO₂ Hydrates Using Transition Path Sampling

Molecular Understanding of Homogeneous Nucleation of CO₂ Hydrates Using Transition Path Sampling

Transition Path Sampling as Markov Chain Monte Carlo of Trajectories: Recent Algorithms, Software, Applications, and Future Outlook

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

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Rate Prediction for Homogeneous Nucleation of Methane Hydrate at Moderate Supersaturation Using Transition Interface Sampling

Cited by 29 publications

References 71 publications

Molecular Understanding of Homogeneous Nucleation of CO2 Hydrates Using Transition Path Sampling

Molecular Understanding of Homogeneous Nucleation of CO2 Hydrates Using Transition Path Sampling

Transition Path Sampling as Markov Chain Monte Carlo of Trajectories: Recent Algorithms, Software, Applications, and Future Outlook

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

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Molecular Understanding of Homogeneous Nucleation of CO₂ Hydrates Using Transition Path Sampling

Molecular Understanding of Homogeneous Nucleation of CO₂ Hydrates Using Transition Path Sampling