4.7 Article

The seven deadly sins: When computing crystal nucleation rates, the devil is in the details

期刊

JOURNAL OF CHEMICAL PHYSICS
卷 155, 期 4, 页码 -

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AMER INST PHYSICS
DOI: 10.1063/5.0055248

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资金

  1. EPSRC [EP/P020232/1, EP/R018820/1]
  2. EPSRC Centre for Doctoral Training in Modeling of Heterogeneous Systems (EPSRC) [EP/S022848/1]
  3. EPSRC [EP/R018820/1, EP/P020232/1] Funding Source: UKRI

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The formation of crystals is a challenging process to quantitatively model, with nucleation rate being a crucial parameter that is difficult to connect between atomistic simulations and experimental measurements. Understanding subtle details often overlooked when computing nucleation rates is essential to uncover the full impact of sources of uncertainty in simulations, which is key to shedding new light on the kinetics of crystal nucleation essential for practical applications.
The formation of crystals has proven to be one of the most challenging phase transformations to quantitatively model-let alone to actually understand-be it by means of the latest experimental technique or the full arsenal of enhanced sampling approaches at our disposal. One of the most crucial quantities involved with the crystallization process is the nucleation rate, a single elusive number that is supposed to quantify the average probability for a nucleus of critical size to occur within a certain volume and time span. A substantial amount of effort has been devoted to attempt a connection between the crystal nucleation rates computed by means of atomistic simulations and their experimentally measured counterparts. Sadly, this endeavor almost invariably fails to some extent, with the venerable classical nucleation theory typically blamed as the main culprit. Here, we review some of the recent advances in the field, focusing on a number of perhaps more subtle details that are sometimes overlooked when computing nucleation rates. We believe it is important for the community to be aware of the full impact of aspects, such as finite size effects and slow dynamics, that often introduce inconspicuous and yet non-negligible sources of uncertainty into our simulations. In fact, it is key to obtain robust and reproducible trends to be leveraged so as to shed new light on the kinetics of a process, that of crystal nucleation, which is involved into countless practical applications, from the formulation of pharmaceutical drugs to the manufacturing of nano-electronic devices.

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