2017/03/17 by Bingqing Cheng, Gareth A. Tribello, Michele Ceriotti
Earth and Planetary Sciences · Materials Science · Mathematics · Physics and Astronomy · #Computer science #Energy (signal processing) #Geometry #Gibbs free energy #Homogeneous #Limit (mathematics) #Material Dynamics and Properties #Mathematical analysis #Mathematics #Nucleation #Physics #Planar #Quantum mechanics #Statistical physics #Surface (topology) #Surface energy #Theoretical and Computational Physics #Thermodynamic integration #Thermodynamics #cond-mat.stat-mech #nanoparticles nucleation surface interactions
paper · pdf · doi:10.1063/1.4997180
arxiv created 2017/03/17 · openalex publication_date 2017/09/13 · arxiv updated 2017/10/11 · openalex created_date 2020/11/23 · openalex updated_date 2026/08/05
In this paper we discuss how the information contained in atomistic simulations of homogeneous nucleation should be used when fitting the parameters in macroscopic nucleation models. We show how the number of solid and liquid atoms in such simulations can be determined unambiguously by using a Gibbs dividing surface and how the free energy as a function of the number of solid atoms in the nucleus can thus be extracted. We then show that the parameters (the chemical potential, the interfacial free energy, and a Tolman correction) of a model based on classical nucleation theory can be fitted using the information contained in these free-energy profiles but that the parameters in such models are highly correlated. This correlation is unfortunate as it ensures that small errors in the computed free energy surface can give rise to large errors in the extrapolated properties of the fitted model. To resolve this problem we thus propose a method for fitting macroscopic nucleation models that uses simulations of planar interfaces and simulations of three-dimensional nuclei in tandem. We show that when the chemical potentials and the interface energy are pinned to their planar-interface values, more precise estimates for the Tolman length are obtained. Extrapolating the free energy profile obtained from small simulation boxes to larger nuclei is thus more reliable.