Abstract

AbstractNucleation is one of the most common physical phenomena in physical, chemical, biological and materials sciences. Owing to the complex multiscale nature of various nucleation events and the difficulties in their direct experimental observation, development of effective computational methods and modeling approaches has become very important and is bringing new light to the study of this challenging subject. Our discussions in this manuscript provide a sampler of some newly developed numerical algorithms that are widely applicable to many nucleation and phase transformation problems. We first describe some recent progress on the design of efficient numerical methods for computing saddle points and minimum energy paths, and then illustrate their applications to the study of nucleation events associated with several different physical systems.

Highlights

  • The recent call of Materials Genome Initiative (MGI) exemplifies the use of computational modelling in new materials design.[1]

  • Nucleation of a new phase requires overcoming a minimum thermodynamic barrier, which leads to a saddle point configuration along the minimum energy path on the energy landscape

  • For complex and rough energy landscapes, we review some methods that can be used to compute either the transition tubes[28,29,30] or the mean free-energy path in the space of collective variables.[31,32]

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Summary

Introduction

The recent call of Materials Genome Initiative (MGI) exemplifies the use of computational modelling in new materials design.[1] One of the most effective ingredients to design materials with certain desired properties is through the control of their phase transformations and microstructure evolution. These processes often start with the nucleation of nanoscale new-phase particles, followed by growth and particle impingement or coarsening. Much computational effort has been called for to study the nucleation events in various applications.[2,3,4,5,6,7,8,9] Being a saddle point of the free energy, the critical nucleus satisfies the Euler–Lagrange equation of the energy

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