u tenn, 4/28/2007 1 growth, structure and pattern formation for thin films lecture 1. growth of thin...
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![Page 1: U Tenn, 4/28/2007 1 Growth, Structure and Pattern Formation for Thin Films Lecture 1. Growth of Thin Films Russel Caflisch Mathematics Department Materials](https://reader037.vdocuments.net/reader037/viewer/2022110206/56649f445503460f94c65916/html5/thumbnails/1.jpg)
U Tenn, 4/28/20071
Growth, Structure and Pattern Formation for Thin Films
Lecture 1. Growth of Thin Films
Russel CaflischMathematics Department
Materials Science and Engineering DepartmentUCLA
www.math.ucla.edu/~material
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U Tenn, 4/28/20072
Outline
• Epitaxial Growth– molecular beam epitaxy (MBE)
– Step edges and islands
• Solid-on-Solid using kinetic Monte Carlo– Atomistic, stochastic
• Island dynamics model– Continuum in lateral directions/atomistic in growth
direction
– Level set implementation
– Kinetic step edge model
• Conclusions
![Page 3: U Tenn, 4/28/2007 1 Growth, Structure and Pattern Formation for Thin Films Lecture 1. Growth of Thin Films Russel Caflisch Mathematics Department Materials](https://reader037.vdocuments.net/reader037/viewer/2022110206/56649f445503460f94c65916/html5/thumbnails/3.jpg)
U Tenn, 4/28/20073
Outline
• Epitaxial Growth– molecular beam epitaxy (MBE)
– Step edges and islands
• Solid-on-Solid using kinetic Monte Carlo– Atomistic, stochastic
• Island dynamics model– Continuum in lateral directions/atomistic in growth
direction
– Level set implementation
– Kinetic step edge model
• Conclusions
![Page 4: U Tenn, 4/28/2007 1 Growth, Structure and Pattern Formation for Thin Films Lecture 1. Growth of Thin Films Russel Caflisch Mathematics Department Materials](https://reader037.vdocuments.net/reader037/viewer/2022110206/56649f445503460f94c65916/html5/thumbnails/4.jpg)
U Tenn, 4/28/20074
Effusion Cells
MBE ChamberSTM Chamber
Molecular Beam Epitaxy (MBE)Growth and Analysis Facility
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U Tenn, 4/28/20075
STM Image of InAs
20nmx20nm
250nmx250nm1.8 V, Filled States
HRL whole-wafer STMsurface quenched from 450°C, “low As”
Barvosa-Carter, Owen, Zinck (HRL Labs)
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U Tenn, 4/28/20076
AlSb Growth by MBE
Barvosa-Carter and Whitman, NRL
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U Tenn, 4/28/20077
Basic Processes in Epitaxial Growth
9750-00-444
(a) (a)
(h)
(f) (e) (b)
(c)
(i)
(g)
(d)
(a) deposition (f) edge diffusion(b) diffusion (g) diffusion down step(c) nucleation (h) nucleation on top of islands(d) attachment (i) dimer diffusion(e) detachment
![Page 8: U Tenn, 4/28/2007 1 Growth, Structure and Pattern Formation for Thin Films Lecture 1. Growth of Thin Films Russel Caflisch Mathematics Department Materials](https://reader037.vdocuments.net/reader037/viewer/2022110206/56649f445503460f94c65916/html5/thumbnails/8.jpg)
U Tenn, 4/28/20078
Outline
• Epitaxial Growth– molecular beam epitaxy (MBE)
– Step edges and islands
• Solid-on-Solid using kinetic Monte Carlo– Atomistic, stochastic
• Island dynamics model– Continuum in lateral directions/atomistic in growth
direction
– Level set implementation
– Kinetic step edge model
• Conclusions
![Page 9: U Tenn, 4/28/2007 1 Growth, Structure and Pattern Formation for Thin Films Lecture 1. Growth of Thin Films Russel Caflisch Mathematics Department Materials](https://reader037.vdocuments.net/reader037/viewer/2022110206/56649f445503460f94c65916/html5/thumbnails/9.jpg)
U Tenn, 4/28/20079
Solid-on-Solid Model
• Interacting particle system – Stack of particles above each lattice point
• Particles hop to neighboring points– random hopping times
– hopping rate D= D0exp(-E/T),
– E = energy barrier, depends on nearest neighbors
• Deposition of new particles– random position
– arrival frequency from deposition rate
• Simulation using kinetic Monte Carlo method– Gilmer & Weeks (1979), Smilauer & Vvedensky, …
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U Tenn, 4/28/200710
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U Tenn, 4/28/200711
Kinetic Monte Carlo • Random hopping from site A→ B
• hopping rate D0exp(-E/T),
– E = Eb = energy barrier between sites
– not δE = energy difference between sites
• Transition state theory
A
B
δEEb
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U Tenn, 4/28/200712
SOS Simulation for coverage=.2
Gyure and Ross, HRL
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U Tenn, 4/28/200713
SOS Simulation for coverage=10.2
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U Tenn, 4/28/200714
SOS Simulation for coverage=30.2
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U Tenn, 4/28/200715
Effusion Cells
MBE ChamberSTM Chamber
Molecular Beam Epitaxy (MBE)Growth and Analysis Facility
RHEED
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U Tenn, 4/28/200716
Validation of SOS Model:Comparison of Experiment and KMC Simulation
(Vvedensky & Smilauer)
Island size density Step Edge Density (RHEED)
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U Tenn, 4/28/200717
Difficulties with SOS/KMC
• Difficult to analyze• Computationally slow
– adatom hopping rate must be resolved
– difficult to include additional physics, e.g. strain
• Rates are empirical– idealized geometry of cubic SOS
– cf. “high resolution” KMC
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U Tenn, 4/28/200718
High Resolution KMC Simulations
High resolution KMC (left); STM images (right)Gyure, Barvosa-Carter (HRL), Grosse (UCLA,HRL)
•InAs
•zinc-blende lattice, dimers
•rates from ab initio computations
•computationally intensive
•many processes
•describes dynamical info (cf. STM)
•similar work
•Vvedensky (Imperial)
•Kratzer (FHI)
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U Tenn, 4/28/200719
Outline
• Epitaxial Growth– molecular beam epitaxy (MBE)
– Step edges and islands
• Solid-on-Solid using kinetic Monte Carlo– Atomistic, stochastic
• Island dynamics model– Continuum in lateral directions/atomistic in growth
direction
– Level set implementation
– Kinetic step edge model
• Conclusions
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U Tenn, 4/28/200720
Island Dynamics
F
D
v
F
dN/dt
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U Tenn, 4/28/200721
Island Dynamics• BCF Theory: Burton, Cabrera, Frank (1951)
• Epitaxial surface– adatom density ρ(x,t)
– Step edges = union of curves Γ(t)
– continuum in lateral direction, atomistic in growth direction
• Evolution of ρ and Γ– Adatom diffusion equation with equilibrium BC
ρt=DΔ ρ +F
ρ = ρeq on Γ(t)
– Step edge velocity: Γ(t) moves at normal velocity
v =D [∂ ρ/ ∂n]
v
ρ = ρeq
Γ
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U Tenn, 4/28/200722
Additions to BCF Theory• Nucleation and breakup of islands• Step stiffness/line tension• Strain effects (Lecture 2)• Numerical implementation: Level set method
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U Tenn, 4/28/200723
Nucleation (and Breakup)• Islands nucleate due to collisions between adatoms
– Rate = D σ1 ρ 2 – σ1 = capture number for nucleation
• accounts for correlation between random walkers: they have not collided earlier
• Modification in ρ eqtn– Nucleation is a loss term
ρt = DΔρ + F - dN/dtdN/dt = ∫ D σ1 ρ 2 dx
• Choice of nucleation time and position– Deterministic time, stochastic position– When N crosses an integer, nucleate a new island
• N(t) ≈ # islands at time t– Choose position at random with probability density proportional to
D σ1 ρ 2 – Alternatives to this choice of position were not successful– Ratsch et al. (2000)
• Similar method for adatom detachment and breakup of small islands
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U Tenn, 4/28/200724
Nucleation Rate:
Nucleation: Deterministic Time, Random Position
2),( tDdt
dNx
Random Seedingindependent of
Probabilistic Seedingweight by local 2
Deterministic Seedingseed at maximum 2
max
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U Tenn, 4/28/200725
C. Ratsch et al., Phys. Rev. B (2000)
Effect of Seeding Style on Scaled Island Size Distribution
Random Seeding Probabilistic Seeding Deterministic Seeding
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U Tenn, 4/28/200726
Line Tension/Step Stiffness
• Gibbs-Thomson terms: boundary condition for ρ and island velocity v
– Line tension and step stiffness satisfy
• Asymptotic analysis of detailed step edge model for |κ| <O( Pedge)<<1
– First derivation of Gibbs-Thomson from kinetics rather than energetics • Previous derivations use equilibrium or thermodynamic driving forces
– ρ* from kinetic steady state RC & Li (2003)
– Anisotropy of RC & Margetis (2007)
*D / n = D( ) -
D [ / n] - ssv
*( / )
ss
T D
= free energy per unit length
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U Tenn, 4/28/200727
Anisotropy of step stiffness
• θ = angle of step edge
• f+, f- are flux from upper, lower terrace
• θ-1 similar to results for Ising model, near-equilibrium by Einstein and Stasevich (2005)
1 1 2
1 2
for 1
(1) for 0E
E
c P
O P
( )c c f f
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U Tenn, 4/28/200728
Level Set Method• Level set equation for description and motion of
n(t) =boundary for islands of height n = { x : φ(x,t) = n }
φ t + v |grad φ| = 0
v = normal velocity of – Nucleation of new islands performed by “manual” raising of level set
function. Requires minimal size (4 atoms) for new islands
• Implementation– REC, Gyure, Merriman, Ratsch, Osher, Zinck (1999)– Chopp (2000)– Smereka (2000)
• Choice of grid– Numerical grid needed for diffusion and LS equations– Physical (atomistic) grid needed for nucleation and breakup– We use a single atomistic grid, which we consider to be a numerical grid
when needed
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U Tenn, 4/28/200729
The Levelset Method
Level Set Function Surface Morphology
t
=0
=0
=0
=0=1
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U Tenn, 4/28/200730
Simulated Growth by the Island Dynamics/Level Set Method
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U Tenn, 4/28/200731
LS = level set implementation of island dynamics
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U Tenn, 4/28/200732
Island size distributions
Experimental Data for Fe/Fe(001),Stroscio and Pierce, Phys. Rev. B 49 (1994)
Stochastic nucleation and breakup of islands
D = detachment rate
Petersen, Ratsch, REC, Zangwill (2001)
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U Tenn, 4/28/200733
Computational Speed: Level Set vs. KMC
• LS ≈ KMC for nucleation dominated growth– Diffusion computation on atomistic lattice is slow
• LS >> KMC for attachment/detachment dominated– Frequent attachment/detachment events represented by
single effective detachment
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U Tenn, 4/28/200734
Outline
• Epitaxial Growth– molecular beam epitaxy (MBE)
– Step edges and islands
• Solid-on-Solid using kinetic Monte Carlo– Atomistic, stochastic
• Island dynamics model– Continuum in lateral directions/atomistic in growth
direction
– Level set implementation
– Kinetic step edge model
• Conclusions
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U Tenn, 4/28/200735
Kinetic Theory for Step Edge Dynamics
• Theory for structure and evolution of a step edge– Mean-field assumption for edge atoms and kinks– Dynamics of corners are neglected
• Equilibrium solution (BCF)– Gibbs distribution e-E/kT for kinks and edge atoms– Detailed balance at edge between each process and the reverse process
• Kinetic steady state– Based on balance between unrelated processes
• Applications of detailed model– Estimate of roughness of step edge, which contributes to detachment rate– Starting point for kinetic derivation of Gibbs-Thomson
• References– REC, E, Gyure, Merriman & Ratsch (1999)– Similar model by Balykov & Voigt (2006), Filimonov & Hervieu (2004)
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U Tenn, 4/28/200736
Step Edge Model
•adatom density ρ•edge atom density φ•kink density (left, right) k•terraces (upper and lower)
• Evolution equations for φ, ρ, k
∂t ρ - DT ∆ ρ = F on terrace
∂t φ - DE ∂s2 φ = f+ + f- - f0 on edge
∂t k - ∂s (w ( kr - k ℓ))= 2 ( g - h ) on edge
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U Tenn, 4/28/200737
Equilibrium from Detailed Balance
edge atom ↔ terrace adatom:
DE φ = DT ρ
kink ↔ edge atom:
DK k = DE k φ
kink pair (“island”)
↔ edge atom pair:
DK (1/4) k2 = DE φ2
kink pair (“hole”) + edge atom
↔ straight step:
DS = DE (1/4) k2 φ
F
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U Tenn, 4/28/200738
Equilibrium from Detailed Balance
edge atom ↔ terrace adatom:
DE φ = DT ρ
kink ↔ edge atom:
DK k = DE k φ
kink pair (“island”)
↔ edge atom pair:
DK (1/4) k2 = DE φ2
kink pair (“hole”) + edge atom
↔ straight step:
DS = DE (1/4) k2 φ
KineticSteady State
f
f=
f= net flux to step edge
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U Tenn, 4/28/200739
Equilibrium Solution
•Solution for F=0 (no growth)•Derived from detailed balance•DT, DE, DK are diffusion coefficients (hopping rates) on Terrace, Edge, Kink in SOS model
Comparison of results from theory(-)
and KMC/SOS ()
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U Tenn, 4/28/200740
Kinetic Steady State vs. Equilibrium
•Solution for F>0•Derived from kinetic balance, not detailed balance•k >> keq
•Pedge=f/DE “edge Peclet #”
Comparison of scaled results from steady state (-), BCF(- - -), and KMC/SOS (∆) for L=25,50,100,with F=1, DT=1012
Kinetic steady state
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U Tenn, 4/28/200741
Hybrid and Accelerated Methods: Island Dynamics and KMC
• Schulze, Smereka, E (2003)• Russo, Sander, Smereka (2004)• Schulze (2004)• DeVita, Sander, Smereka (2006)• Sun, Engquist, REC, Ratsch (2007)
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U Tenn, 4/28/200742
Outline
• Epitaxial Growth– molecular beam epitaxy (MBE)
– Step edges and islands
• Solid-on-Solid using kinetic Monte Carlo– Atomistic, stochastic
• Island dynamics model– Continuum in lateral directions/atomistic in growth
direction
– Level set implementation
– Kinetic step edge model
• Conclusions
![Page 43: U Tenn, 4/28/2007 1 Growth, Structure and Pattern Formation for Thin Films Lecture 1. Growth of Thin Films Russel Caflisch Mathematics Department Materials](https://reader037.vdocuments.net/reader037/viewer/2022110206/56649f445503460f94c65916/html5/thumbnails/43.jpg)
U Tenn, 4/28/200743
Summary
• Island dynamics method for epitaxial growth– Coarse-graining of KMC
– Stochastic nucleation
• Kinetic model for step edge– kinetic steady state ≠ BCF equilibrium
– validated by comparison to SOS/KMC
• Next lectures– Inclusion of strain in epitaxial systems
– Strain leads to geometric structure (e.g. quantum dots) and alloy segregation