Home Page of Jim Lutsko

Last updated: Jan. 9, 2016 Aider mieux vivre dans la rue

Research Interests
  • Protein nucleation and crystal growth
  • Nonlinear diffusion
  • Theory of Nucleation
  • Zeolites
  • Crystallization
  • Bubble Cavitation and Sonoluminescence
  • Reactive flows far from equilibrium
  • Structure of nonequilibrium fluids
  • Granular Fluids
  • Nonextensive statistical mechanics
  • Fuzzy rule induction
Publications PHYSF475 Nanophysique 2015-2016 Useful Links
American Physical Society
American Institute of Physics
Materials Research Society

Cirriculum Vitae
Cirriculum Vitae (en française)
Email: jlutsko AT ulb.ac.be
Center for Nonlinear Phenomena and Complex Systems
University Libre de Bruxelles
Campus Plaine, CP 231, 1050 Bruxelles, Belgium
Step Crowding Effects Dampen the Stochasticity of Crystal Growth Kinetics
Crystals grow by laying down new layers of material which can either correspond in size to the height of one unit cell (elementary steps) or multiple unit cells (macrosteps). Surprisingly, experiments have shown that macrosteps can grow under conditions of low supersaturation and high impurity density such that elementary step growth is completely arrested. We use atomistic simulations to show that this is due to two effects: the fact that the additional layers bias fluctuations in the position of the bottom layer towards growth and by a transition, as step height increases, from a 2D to a 3D nucleation mechanism.
This article was featured in Physics News and Commentary: see the Synopsis: Growing Crystals in Macrosteps
A macrostep bridging impurities on the crystal surface
Mesoscopic Impurities Expose a Nucleation-Limited Regime of Crystal Growth
Nanoscale self-assembly is naturally subject to impediments at the nanoscale. The recently developed ability to follow processes at the molecular level forces us to resolve older, coarse-grained concepts in terms of their molecular mechanisms. In this Letter, we highlight one such example. We present evidence based on experimental and simulation data that one of the cornerstones of crystal growth theory, the Cabrera-Vermilyea model of step advancement in the presence of impurities, is based on incomplete physics. We demonstrate that the piercing of an impurity fence by elementary steps is not solely determined by the Gibbs-Thomson effect, as assumed by Cabrera-Vermilyea. Our data show that for conditions leading up to growth cessation, step retardation is dominated by the formation of critically sized fluctuations. The growth recovery of steps is counter to what is typically assumed, not instantaneous. Our observations on mesoscopic impurities for lysozyme expose a nucleation-dominated regime of growth that has not been hitherto considered, where the system alternates between zero and near-pure velocity. The time spent by the system in arrest is the nucleation induction time required for the step to amass a supercritical fluctuation that pierces the impurity fence.
AFM images showing steps breaking through array of mesoscopic impurities.
Observing classical nucleation theory at work by monitoring phase transitions with molecular precision.
It is widely accepted that many phase transitions do not follow nucleation pathways as envisaged by the classical nucleation theory. Many substances can traverse intermediate states before arriving at the stable phase. The apparent ubiquity of multi-step nucleation has made the inverse question relevant: does multistep nucleation always dominate single-step pathways? Here we provide an explicit example of the classical nucleation mechanism for a system known to exhibit the characteristics of multi-step nucleation. Molecular resolution atomic force microscopy imaging of the two-dimensional nucleation of the protein glucose isomerase demonstrates that the interior of subcritical clusters is in the same state as the crystalline bulk phase. Our data show that despite having all the characteristics typically associated with rich phase behaviour, glucose isomerase 2D crystals are formed classically. These observations illustrate the resurfacing importance of the classical nucleation theory by re-validating some of the key assumptions that have been recently questioned... Read more ... The article is open source
AFM images showing crystallinity of sub-critical and super-critical clusters.
2-variable extension of classical nucleation theory.
A two-variable stochastic model for diffusion-limited nucleation is developed using a formalism derived from fluctuating hydrodynamics. The model is a direct generalization of the standard Classical Nucleation Theory. The nucleation rate and pathway are calculated in the weak-noise approximation and are shown to be in good agreement with direct numerical simulations for the weak-solution/strong-solution transition in globular proteins. We find that Classical Nucleation Theory underestimates the time needed for the formation of a critical cluster by two orders of magnitude and that this discrepancy is due to the more complex dynamics of the two variable model and not, as often is assumed, a result of errors in the estimation of the free energy barrier. Read more...
Free energy surfaces as functions of radius and density of a cluster. Left: sub-critical, Right: super-critical - the line shows the most likely nucleation pathway.
The physical basis of step pinning.
The growth of crystals from solution is a fundamental process of relevance to such diverse areas as X-ray-diffraction structural determination and the role of mineralization in living organisms. A key factor determining the dynamics of crystallization is the effect of impurities on step growth. For over fifty years, all discussions of impurity-step interaction have been framed in the context of the Cabrera--Vermilyea (CV) model for step blocking, which has nevertheless proven difficult to validate experimentally. Here we report on extensive computer simulations which clearly falsify the CV model, suggesting a more complex picture. While reducing to the CV result in certain limits, our approach is more widely applicable, encompassing non-trivial impurity-crystal interactions, mobile impurities and negative growth, among others. Read the paper... view movies
Left: Snapshot of kineic Monte Carlo simulation. Right: Step velocity shown as size of circles as a function of impurity size, L, and impurity spaceing, n_{c} shown for three different supersaturations. Blue indicates positive velocity, red is negative velocity and white is statistically zero. The CV prediction for zero velocity is everything below the broken line marked CV.