A detailed kinetic Monte Carlo study of growth from solution using MD-derived rate constants

Reilly, Anthony M.; Briesen, Heiko

doi:10.1016/j.jcrysgro.2012.05.041

Cited by 8 publications

(10 citation statements)

References 24 publications

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“…KMC is a general computational method used to describe the time evolution of a system. , The system size and time scale accessible in a KMC simulation can be substantially larger and longer than those in MD simulations. KMC has been successfully applied to chemical reactions, − polymer growth, charge transport, − predicting the kinetic factors for nucleation, , describing the growth of crystals, − and lateral growth of single-layer 2D materials. − Our KMC model reproduces key experimentally measured parameters of COF-5 growth, and provides new insights into the crystallization of COF-5. Importantly, the model simultaneously describes the nucleation and growth processes, with no predefined stages/pathways.…”

Section: Introductionmentioning

confidence: 96%

“…51,52 The system size and time scale accessible in a KMC simulation can be substantially larger and longer than those in MD simulations. KMC has been successfully applied to chemical reactions [51][52][53] , polymer growth 54 , charge transport [55][56][57] , predicting the kinetic factors for nucleation 58,59 , describing the growth of crystals [60][61][62][63][64] , and lateral 7 growth of single-layer 2D materials [65][66][67][68] . Our KMC model reproduces key experimentally measured parameters of COF-5 growth, and provides new insights into the crystallization of COF-5.…”

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confidence: 99%

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Nucleation and Growth of Covalent Organic Frameworks from Solution: The Example of COF-5

et al. 2017

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The preparation of two-dimensional covalent organic frameworks (2D COFs) with large crystalline domains and controlled morphology is necessary for realizing the full potential of their atomically precise structures and uniform, tailorable porosity. Currently 2D COF syntheses are developed empirically, and most materials are isolated as insoluble and unprocessable powders with typical crystalline domain sizes smaller than 50 nm. Little is known about their nucleation and growth processes, which involve a combination of covalent bond formation, degenerate bond exchange, and noncovalent stacking processes. A deeper understanding of the chemical processes that lead to COF polymerization and crystallization is key to achieving improved materials quality and control. Here, we report a kinetic Monte Carlo (KMC) model that describes the formation of a prototypical boronate-ester linked 2D COF known as COF-5 from its 2,3,6,7,10,11-hexahydroxytriphenylene and 1,4-phenylene bis(boronic acid) monomers in solution. The key rate parameters for the KMC model were derived from experimental measurements when possible and complemented with reaction pathway analyses, molecular dynamics simulations, and binding free-energy calculations. The essential features of experimentally measured COF-5 growth kinetics are reproduced well by the KMC simulations. In particular, the simulations successfully captured a nucleation process followed by a subsequent growth process. The nucleating species are found to be relatively small, multilayer structures that form through multiple pathways. During the growth of COF-5, extensions in the lateral (in-plane) and vertical (stacking) directions are both seen to be linear with respect to time and are dominated by monomer addition and oligomer association, respectively. Finally, we show that the experimental observations of increased average crystallite size with the addition of water are modeled accurately by the simulations. These results will inform the rational development of 2D COF polymerizations by controlling the rate of nucleation, thereby increasing their materials quality.

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Section: Introductionmentioning

confidence: 96%

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confidence: 99%

Nucleation and Growth of Covalent Organic Frameworks from Solution: The Example of COF-5

et al. 2017

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“…Understanding crystallization is of paramount interest in the field of material, pharmaceutical, and environmental sciences. , Over the years, computer simulations have emerged as effective tools in the study of crystal growth and predicting polymorphism. , Thus, molecular dynamics (MD) and Monte Carlo (MC) techniques are routinely employed to obtain crystallization atomic details that are often difficult to get from experiments. − …”

Section: Introductionmentioning

confidence: 99%

A Cannibalistic Approach to Grand Canonical Crystal Growth

Karmakar

Piaggi

Perego

et al. 2018

J. Chem. Theory Comput.

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Canonical molecular dynamics simulations of crystal growth from solution suffer from severe finite-size effects. As the crystal grows, the solute molecules are drawn from the solution to the crystal, leading to a continuous drop in the solution concentration. This is in contrast to experiments in which the crystal grows at an approximately constant supersaturation of a bulk solution. Recently, Perego et al. [ J. Chem. Phys. 2015, 142, 144113] showed that in a periodic setup in which the crystal is represented as a slab, the concentration in the vicinity of the two surfaces can be kept constant while the molecules are drawn from a part of the solution that acts as a molecular reservoir. This method is quite effective in studying crystallization under controlled supersaturation conditions. However, once the reservoir is depleted, the constant supersaturation conditions cannot be maintained. We propose a variant of this method to tackle this depletion problem by simultaneously dissolving one side of the crystal while letting the other side grow. A continuous supply of particles to the solution due to the crystal dissolution maintains a steady solution concentration and avoids reservoir depletion. In this way, a constant supersaturation condition can be maintained for as long as necessary. We have applied this method to study the growth and dissolution of urea crystal from water solution under constant supersaturation and undersaturation conditions, respectively. The computed growth and dissolution rates are in good agreement with those obtained in previous studies.

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“…Thus, the definition of a minimal set of distinct states and the estimation of corresponding transition rates are the main challenges for kMC simulations. Many kMC studies consider states on the basis of their nearest-neighbor coordination [33,34] or next-nearest-neighbor coordination [11,35]. Alternatively, the problem of state definition can be solved by identifying the most significant factors defining site reactivity with the help of electronic structure calculations and MD simulations for selected sites on the crystal surface [36].…”

Section: Introductionmentioning

confidence: 99%

“…Alternatively, the problem of state definition can be solved by identifying the most significant factors defining site reactivity with the help of electronic structure calculations and MD simulations for selected sites on the crystal surface [36]. Different approaches based on MD [11,20,[33][34][35], accelerated MD [31,37], ab initio MD [38] or even DFT techniques [39] have been reported to determine rate constants, though the last three imply significant computational effort making them less attractive for systems with a high number of potential transitions, as well as for systems consisting of complex molecules with a high internal degree of freedom [40]. Significant steps toward the multiscale modeling of crystallization have been presented in studies conducted by Piana and co-workers [11,33,35], who first combined MD and kMC approaches to investigate the growth of a urea crystal from solution.…”

Section: Introductionmentioning

confidence: 99%

In Silico Prediction of Growth and Dissolution Rates for Organic Molecular Crystals: A Multiscale Approach

2017

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Solution crystallization and dissolution are of fundamental importance to science and industry alike and are key processes in the production of many pharmaceutical products, special chemicals, and so forth. The ability to predict crystal growth and dissolution rates from theory and simulation alone would be of a great benefit to science and industry but is greatly hindered by the molecular nature of the phenomenon. To study crystal growth or dissolution one needs a multiscale simulation approach, in which molecular-level behavior is used to parametrize methods capable of simulating up to the microscale and beyond, where the theoretical results would be industrially relevant and easily comparable to experimental results. Here, we review the recent progress made by our group in the elaboration of such multiscale approach for the prediction of growth and dissolution rates for organic crystals on the basis of molecular structure only and highlight the challenges and future directions of methodic development.

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A detailed kinetic Monte Carlo study of growth from solution using MD-derived rate constants

Cited by 8 publications

References 24 publications

Nucleation and Growth of Covalent Organic Frameworks from Solution: The Example of COF-5

Nucleation and Growth of Covalent Organic Frameworks from Solution: The Example of COF-5

A Cannibalistic Approach to Grand Canonical Crystal Growth

In Silico Prediction of Growth and Dissolution Rates for Organic Molecular Crystals: A Multiscale Approach

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