Affiliation:
1. Department of Chemical Engineering University College London London UK
2. Department of Materials, Design and Manufacturing Engineering The University of Liverpool Liverpool UK
Abstract
AbstractNucleation 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
Funder
Engineering and Physical Sciences Research Council
Subject
Materials Chemistry,Computational Mathematics,Physical and Theoretical Chemistry,Computer Science Applications,Biochemistry
Cited by
6 articles.
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