Uncovering Molecular Processes in Crystal Nucleation and Growth by Using Molecular Simulation

Anwar, Jamshed; Zahn, Dirk

doi:10.1002/anie.201000463

Cited by 244 publications

(226 citation statements)

References 122 publications

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“…Homogeneous nucleation of ice occurs on timescales that are generally not accessible by bruteforce simulation, and here we employed advanced Monte Carlo (MC) simulations in which we efficiently direct and enhance ice growth from supercooled water at 220 K for a periodic system comprising 2,880 TIP4P model water molecules (note that the melting temperature for this model is 232 K). An essential issue with such simulations is that one must ensure that the methodology does not favor a particular structure or phase (27), and to this end, we used the order parameters previously developed and verified by Brukhno et al (28).…”

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confidence: 99%

Structure of ice crystallized from supercooled water

Malkin

Murray

Brukhno

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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283

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The freezing of water to ice is fundamentally important to fields as diverse as cloud formation to cryopreservation. At ambient conditions, ice is considered to exist in two crystalline forms: stable hexagonal ice and metastable cubic ice. Using X-ray diffraction data and Monte Carlo simulations, we show that ice that crystallizes homogeneously from supercooled water is neither of these phases. The resulting ice is disordered in one dimension and therefore possesses neither cubic nor hexagonal symmetry and is instead composed of randomly stacked layers of cubic and hexagonal sequences. We refer to this ice as stacking-disordered ice I. Stacking disorder and stacking faults have been reported earlier for metastable ice I, but only for ice crystallizing in mesopores and in samples recrystallized from high-pressure ice phases rather than in water droplets. Review of the literature reveals that almost all ice that has been identified as cubic ice in previous diffraction studies and generated in a variety of ways was most likely stacking-disordered ice I with varying degrees of stacking disorder. These findings highlight the need to reevaluate the physical and thermodynamic properties of this metastable ice as a function of the nature and extent of stacking disorder using well-characterized samples.

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confidence: 99%

Structure of ice crystallized from supercooled water

Malkin

Murray

Brukhno

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

283

326

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“…Thereby, we implicitly assume thermodynamic control:the more stable ap articular surface,t he more it contributes to the crystal shape.Hence,kinetic aspects are,for the time being, ignored in this approximation, [14] and we will discuss cases where doing so is justified;nonetheless,westress that nucleation and growth of nanocrystals can be simulated nowadays,aswell. [15] Synthesis and utilization of nanocrystals are highly active fields of current research, but they require at horough understanding of the underlying crystal surfaces.I nt his Minireview,w espan the arc from surfaces to free nanocrystals,a nd onward to their chemical synthesis, using as examples lead selenide (PbSe), tin telluride (SnTe), and their direct chemical relatives.B esides experimental insights,w ehighlight the increasingly influential role playedb yquantum-chemical simulations of surfaces and nanocrystals.W hat can theory do today,or possibly tomorrow; where are its limits?Answering these questions, and skillfully linking them to experiments,c ould open up new atomistically (that is,c hemically) guided perspectives for nanosynthesis. Table 1provides an overview and thus also an outline for the following Sections.For reasons of brevity,wefocus on the IV-VI semiconductors.F or the backgrounds of the theoretical methods,w er efer the reader to excellent texts on ab initio surface chemistry [16] and the modeling of nanoparticles.…”

Section: Introductionmentioning

confidence: 99%

From Atomistic Surface Chemistry to Nanocrystals of Functional Chalcogenides

Deringer

Dronskowski

2015

Angew Chem Int Ed

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Synthesis and utilization of nanocrystals are highly active fields of current research, but they require a thorough understanding of the underlying crystal surfaces. In this Minireview, we span the arc from surfaces to free nanocrystals, and onward to their chemical synthesis, using as examples lead selenide (PbSe), tin telluride (SnTe), and their direct chemical relatives. Besides experimental insights, we highlight the increasingly influential role played by quantum‐chemical simulations of surfaces and nanocrystals. What can theory do today, or possibly tomorrow; where are its limits? Answering these questions, and skillfully linking them to experiments, could open up new atomistically (that is, chemically) guided perspectives for nanosynthesis.

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“…In this regard, molecular simulations play an important role and much work has been devoted to the study of homogeneous nucleation in simple model systems like Lennard-Jones particles or hard spheres (1)(2)(3). More recently, growing attention has been paid to the computer simulation of nucleation from solution of organic and inorganic materials (4)(5)(6)(7)(8)(9)(10)(11).…”

mentioning

confidence: 99%

Molecular-dynamics simulations of urea nucleation from aqueous solution

Salvalaglio

Perego

Giberti

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

161

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Despite its ubiquitous character and relevance in many branches of science and engineering, nucleation from solution remains elusive. In this framework, molecular simulations represent a powerful tool to provide insight into nucleation at the molecular scale. In this work, we combine theory and molecular simulations to describe urea nucleation from aqueous solution. Taking advantage of well-tempered metadynamics, we compute the freeenergy change associated to the phase transition. We find that such a free-energy profile is characterized by significant finite-size effects that can, however, be accounted for. The description of the nucleation process emerging from our analysis differs from classical nucleation theory. Nucleation of crystal-like clusters is in fact preceded by large concentration fluctuations, indicating a predominant two-step process, whereby embryonic crystal nuclei emerge from dense, disordered urea clusters. Furthermore, in the early stages of nucleation, two different polymorphs are seen to compete.T he nucleation of crystals from solution plays an important role in a variety of chemical and engineering processes. However, the very small scale that characterizes the early stages of nucleation makes its experimental study rather challenging. In this regard, molecular simulations play an important role and much work has been devoted to the study of homogeneous nucleation in simple model systems like Lennard-Jones particles or hard spheres (1-3). More recently, growing attention has been paid to the computer simulation of nucleation from solution of organic and inorganic materials (4-11).However, these simulations have to face an important challenge. Nucleation is a typical example of a rare event occurring on a timescale that is much longer than what atomistic simulations can typically afford. The problem is most easily understood if we focus on molecular dynamics (MD), which is the sampling method used here but it plagues other methods as well. In MD, the shortest timescale to be used for a correct integration of the equation of motion is dictated by the fastest atomic motions such as vibrations or rotations. Due to this constraint in the integration step, present MD simulations can reach timescales up to microseconds unless specific hardware, accessible only to few, is used. Even in this case the scale of the accessible times can be stretched only to the milliseconds range, a far cry from the much longer scale of nucleation phenomena.These timescale limitations affect molecular simulations in several other research fields, such as ligand protein binding, protein folding, or slow chemical reactions, to name just a few. To overcome this limit, many enhanced sampling methods have been proposed (12-21). Several of them are based on the application of a suitable external bias potential (12-14) that speeds up configurational sampling and permits free energies to be evaluated and transition rates to be computed (22)(23)(24). Here, we shall use well-tempered (WT) metadynamics to enhance the nucleation...

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Uncovering Molecular Processes in Crystal Nucleation and Growth by Using Molecular Simulation

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Cited by 244 publications

References 122 publications

Structure of ice crystallized from supercooled water

Structure of ice crystallized from supercooled water

From Atomistic Surface Chemistry to Nanocrystals of Functional Chalcogenides

Molecular-dynamics simulations of urea nucleation from aqueous solution

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