Nucleation in Hard Spheres Systems

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Nucleation in Hard Spheres Systems

Sven Dorosz

University of Luxembourg, Group of Tanja Schilling - Softmatter Theory

February, 2012

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Softmatter

Liquids, colloids, polymers, foams, gels, granular materials, and a number of biological materials.

Illustration taken from SoftComp website

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Classical Nucleation Theory

∆G = 4πγR ² + 4π∆µρ

3 R ³ R ^∗ = 2γ

ρ|∆µ|

∆G _crit = 16πγ ³

3(ρ|∆µ|) ² I = κ exp

− 16πγ ³ 3k _B T (ρ|∆µ|) ²

source Hamed Maleki, PhD Thesis, University of Mainz, 2011

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Hard Spheres

V (r ) =

∞ if r < R 0 if r ≥ R collisions

are elastic ⇒ internal energy constant

F = −TS most simple model for a liquid

η = 1 6 πR ³ ρ The equation of state is given by

βP

ρ = (1 + η + η ² )

(1 − η) ³

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Phasediagram for Hard Spheres

Rintoul, Md. and Torquato, S., 1996, PRL 77, 20, 4198-4201.

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Comparison Experiment to Theory

Stefan Auer and Daan Frenkel, Nature 409, 1020-1023 (2001)

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Motivation Event driven molecular dynamics

time driven MD simulation vs. event driven MD simulation

V (r ) discontinuous ⇒ free flight between collisions NVE ensemble ⇒ T is trivial parameter ⇒ sets timescale

Alder, B. J., and Wainwright, T. E., 1957, J. chem. Phys., 27, 1208.

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Algorithm Event driven molecular dynamics

Diagram

⇒ Neighboring boxes

Find the first collision for each particle Insert into collision list - don’t execute yet Then execute earliest collision

Find next collision of the two particles ⇒ update the list Then execute earliest collision ...

Algorithm by setup serial execution

scales with N log N. N number of particles in system

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Local crystal symmetry

Hard spheres system. ρ = 1.03

Loading

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Local crystal symmetry

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Definition of the order parameter

Observables for the Local Bond Ordering:

In 3d:

¯

q 6m (i ) := 1 n(i )

n(i )

X

j=1

Y 6m (~ r ij ) , r ij < 1.4 where Y _6m ( ~ r _ij ) are the spherical harmonics (with l=6).

P. J. Steinhardt, D. R. Nelson, and M. Ronchetti. Phys. Rev. B, 28(2), 1983

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Distribution of the order parameter

scalar product q ~ ₆ (i ) · q ~ ₆ ^∗ (i)

source Hamed Maleki, PhD Thesis, University of Mainz, 2011

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Local crystal symmetry

scalar product q ~ ₆ (i ) · q ~ ₆ ^∗ (j) measures relative angle orientation

~

q ₆ (i ) · q ~ ₆ ^∗ (j ) < 0.7 q ~ ₆ (i ) · q ~ ₆ ^∗ (j ) > 0.7

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Detecting emerging crystallites

If particle i and n _b neighbouring particle j satisfy

~

q ₆ (i ) · q ~ ₆ ^∗ (j ) > 0.7

Crystalline particles (colorcoded ”green”), n _b > 10.

Low symmetry cluster (LSC)(colorcoded ”light brown”), n _b > 5.

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Motivation

How do the theoretical nucleation rates compare to the experiment?

(Brute force molecular dynamics simulation)

What are the structural properties of the emerging nuclei?

Can we identify characteristic preconditions near nucleation sites?

What are the properties of the growing nuclei?

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nucleation rates

⇒ MD and MC simulations produce rates match the experimental results

⇒ SPRES as the first full non equilibrium rare event sampling method

Schilling T.; Dorosz S.; Sch¨ope H. J.; et al. JPCM, 23, 19, 194120, 2011

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Precursor nucleation

⇒ Effective two step process. Precursor formation

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Radius of gyration

⇒ Small crystallites are far from being spherical

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SPRES

Going to lower densities ρ.

time

2 Bin 1 Bin 2 Bin 3

λ

τ τ 0

τ

J.T. Berryman and T. Schilling. Sampling rare events in nonequilibrium and nonstationary systems.

J Chem Phys, 133(24):244101, 2010.

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Motivation

Will the substrate induce different nucleation pathways?

Where does the nucleation happen?

What are the consequences of the mismatch between substrate and equilibrium crystal lattice constant?

What is the crystal structure of the nucleus?

How does the substrate change the nucleation rate?

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Setup of the system

Super-saturated fluid of hard spheres in contact with a triangular substrate.

1 1,1 1,2 1,3 1,4

lattice constant a [σ]

1,005 1,01 1,015 1,02

number density ρ instantaneous growth

nucleation

limit of stability

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Parameters

N = 220200 (216000 bulk + 4200 substrate) particles N/V = 1.005 (η = 0.526) − 1.02 (η = 0.534)

Corresponding chemical potentials −∆µ ≃ 0.50 − 0.54 k _B T

Rintoul, Md. and Torquato, S., 1996, PRL 77, 20, 4198-4201.

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Immediate wetting

a < a _sp

t = 6D t = 70D

S.D. and T. Schilling, 2012, J. Chem. Phys. 136, 044702.

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Vertical density profile

0 5 10 15

distance to the substrate z [σ]

0 0.002 0.004 0.006 0.008

density ρ( z)

t = 100 τ t = 50 τ t = 1 τ

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The first layer

at t > 150D

a = 1.01σ a = 1.1σ

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Defect density

1 2 3 4 5

layer n

0.1 0.2 0.3 0.4 0.5

defect density η

a=1.01σ a=1.05σ a=1.10σ

1 2 3 4 5

layer n

3400 3600 3800 4000 4200

# of particles in layer N(n)

⇒ Induced defects are compensated in the first 3 layers

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3 layer stacking

⇒ Domains of ABA and ABC structure

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5 layer stacking

⇒ Crystal grows in random hexagonal closed packing (RHCP)

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Nucleation at the wall

a > a _sp

t = 6D t = 80D

⇒ Droplet formation on the substrate

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Droplet characterization

0 100 τ 200 τ 300 τ 400 τ

time after critical nucleus is formed 100

1000 10000

# of solid particles in cluster

ρ=1.01 ρ=1.0175 ρ=1.02

100 1000

N 1

10

principal moment

R_⊥e

z

R_⊥e

z

R_||e

z

⇒ non-spherical droplets even up to 4000 particles.

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Nucleation rates

1.005 1.01 1.015 1.02 1.025

density ρ

0 5e-06 1e-05 1.5e-05 2e-05

nucleation rate * [ σ

5

/ 6D

l

]

^a=1.15σa=1.2σ

a=1.25σ a=1.3σ a=1.35σ a=1.4σ

a

⇒ Decreasing nucleation rate with increasing mismatch to the substrate

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Nucleation in Hard Spheres Systems