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- W4387302273 abstract "Nucleation is the initial step towards 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 towards phase separation can affect the resulting material structure and properties, which are crucial for a range of scientific fields. 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 affects the phase behaviour of nucleating solutions when compared to macroscale counterparts. An additional challenge is 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 obvious which simulation method is most suitable to study crystal nucleation from solution. This review surveys the recent advances in this field, shedding light on typical nucleation mechanisms and the appropriateness of various simulation techniques for their study. Herein, we aim to provide a deeper understanding of the complexities associated with modelling crystal nucleation from solution and identify areas for further research. Our review targets researchers across various scientific domains, including materials science, chemistry, physics and engineering, and will hopefully foster a collaborative effort to develop new strategies to comprehend and control nucleation." @default.
- W4387302273 created "2023-10-04" @default.
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- W4387302273 date "2023-10-03" @default.
- W4387302273 modified "2023-10-04" @default.
- W4387302273 title "Molecular simulation approaches to study crystal nucleation from solutions: theoretical considerations and computational challenges" @default.
- W4387302273 doi "https://doi.org/10.26434/chemrxiv-2023-rb79v-v2" @default.
- W4387302273 hasPublicationYear "2023" @default.
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