The Seven Deadly Sins: when computing crystal nucleation rates, the devil is in the details

Abstract

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 endeavour 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.

arXiv comment15 pages (excluding references, 19 if included), 5 figures

References in corpus (44)

• Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method
• Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations
• From Metadynamics to Dynamics
• Elaborating Transition Interface Sampling Methods
• Direct Calculation of Ice Homogeneous Nucleation Rate for a Molecular Model of Water
• Crystal nucleation of hard spheres using molecular dynamics, umbrella sampling and forward flux sampling: A comparison of simulation techniques
• Computation of extreme heat waves in climate models using a large deviation algorithm
• Silicon liquid structure and crystal nucleation from ab-initio deep Metadynamics
• Rate of Homogeneous Crystal Nucleation in molten NaCl
• Ice is Born in Low-Mobility Regions of Supercooled Liquid Water
• Molecular Dynamics Simulations of Solutions at Constant Chemical Potential
• Systematic Improvement of Classical Nucleation Theory
• Understanding Homogeneous Nucleation in Solidification of Aluminum by Molecular Dynamics Simulations
• Microscopic Mechanism and Kinetics of Ice Formation at Complex Interfaces: Zooming in on Kaolinite
• Free energy landscapes for homogeneous nucleation of ice for a monatomic water model
• Numerical computation of rare events via large deviation theory
• Homogeneous nucleation of ice
• Phase diagram of supercooled water confined to hydrophilic nanopores
• A General Algorithm for Sampling Rare Events in Non-Equilibrium and Non-Stationary Systems
• Overcoming the time limitation in Molecular Dynamics simulation of crystal nucleation: a persistent-embryo approach
• Unravelling the Origins of Ice Nucleation on Organic Crystals
• Pathways to self-organization: crystallization via nucleation and growth
• Overcoming timescale and finite-size limitations to compute nucleation rates from small scale Well Tempered Metadynamics simulations
• Classical nucleation theory from a dynamical approach to nucleation
• Practical rare event sampling for extreme mesoscale weather
• Shape and area fluctuation effects on nucleation theory
• Molecular dynamics of open systems: construction of a mean-field particle reservoir
• Non-Stationary Forward Flux Sampling
• Systematically extending classical nucleation theory
• A Generalized Parallel Replica Dynamics
• How to Quantify and Avoid Finite Size Effects in Computational Studies of Crystal Nucleation: The Case of Heterogeneous Ice Nucleation
• The barrier to ice nucleation in monatomic water
• Reconsidering the structure of nucleation theories
• GCIceNet: A Graph Convolutional Network for Accurate Classification of Water Phases
• The Gibbs free energy of homogeneous nucleation: from atomistic nuclei to the planar limit
• Identification of a Multi-Dimensional Reaction Coordinate for Crystal Nucleation in ${\text{Ni}}_3\text{Al}$
• Classical nucleation theory of ice nucleation: second-order correction of thermodynamic parameters
• Crystal nucleation along an entropic pathway: Teaching liquids how to transition
• Role of pre-ordered liquid in the selection mechanism of crystal polymorphs during nucleation
• Communication: Truncated non-bonded potentials can yield unphysical behavior in molecular dynamics simulations of interfaces
• Nucleation rates from small scale atomistic simulations and transition state theory
• Caveats of mean first-passage time methods applied to the crystallization transition: effects of non-Markovianity
• How a Supercooled Liquid Borrows Structure from the Crystal
• On the reaction coordinate for seeded crystallisation

Cited by in corpus (8)

• Driving and characterizing nucleation of urea and glycine polymorphs in water
• Stochastic Resetting for Enhanced Sampling
• How to quantify and avoid finite size effects in computational studies of crystal nucleation: The case of homogeneous crystal nucleation
• Template induced precursor formation in heterogeneous nucleation -- Controlling polymorph selection and nucleation efficiency
• Controlling crystallization: What liquid structure and dynamics reveal about crystal nucleation mechanisms
• Nucleation rates from small scale atomistic simulations and transition state theory
• Interplay of structural and dynamical heterogeneity in the nucleation mechanism in Ni
• Stochastic transitions: Paths over higher energy barriers can dominate in the early stages