Chemistry with
Computers
Yingbin Ge
Iowa State University
Central Washington University
October 13, 2007
coupledcluster
CCSD(T)
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Perturbation
theory MP2
density
functional
theory (DFT)
Accuracy
Hartree
Fock (HF)
molecular
mechanics
Computer time
2
What has been done?
• Global optimization of
silicon nanoclusters.
Si14H20
• Chemical vapor deposition
of silicon carbide.
3
Global optimization
of silicon nanoclusters
•Why Si nanoclusters?
•Si nanoclusters exhibit bright roomtemperature photoluminescence which could
be used in light-emitting devices.
A. Meldrum group,
Adv. Mater.
17, 845 (2005)
•To
model the excitation and emission of
the Si nanoclusters, we need to know their
thermodynamically stable structures.
4
Global vs. local optimization
local
optimization
energy 
Energy
local minimum
local minimum
global minimum
conformations
5
Why is global optimization difficult?
#LM
Ar7
4
Ar9
21
Ar10 Ar11
64
152
Ar12 Ar13
464 1328
Tsai and Jordan, JPC 97, 11227 (1993)
1400
# of local minima
Ar8
8
1200
1000
y = 0.0034e
800
0.9827x
2
R = 0.997
600
400
200
0
6
8
10
# of Ar atoms
12
14
6
Global optimization strategies
• Exhaustive search: too many minima to
sample.
• Random sampling:”But there’s one I always
miss.”
• Genetic algorithm is based on “the fittest
survive” principle. It has been proven
efficient for the global optimization of
clusters and molecules.*
*Applications of evolutionary computation in chemistry,
Structure and Bonding, Vol. 110 (2004)
7
Genetic algorithm based
global optimization
Produce random structures as initial population.
Evaluate energy (fitness) for each individual.
Repeat following steps until convergence:
Perform competitive selection.
Apply genetic operators* to produce new clusters.
Lower energy clusters replace higher-energy ones.
*Genetic operators: crossover and mutation.
8
Biological crossover and mutation
Crossover
of 2 DNA
strings
Mutation:
1 missing
nucleotide
after crossover
normal
normal
missing nucleotide
after mutation
9
Crossover: silicon hydrides
crossover
local
opt.
10
Mutation methods
Hydrogen shift
Partial rotation
11
Mutation methods
SiH2  SiH3
a. initial geometry
b. after mutation
c. final structure
SiH2  SiH3
12
Diamond-lattice SixHy global minima
Si10H16
MP2 &
DFT
Si14H20
Si18H24
SixHy-2 global minima
Si10H14
Si14H1
8
Si18H22
13
MP2 & DFT
SixHy global minima
Si7H14
Si8H14
Si10H16
SixFy global minima
Si7F14
Si8F14
Si10H14
DFT
Si10F16
Si10F1414
Ligand effect
L= H
CH3
OH
F
L2Si=SiL2
L3Si-SiL
MP2 global
minimum
15
Ligand effect
• Si10(CH3)16 and Si10H16 adopt the same
diamond-lattice Si core.
• Si10(OH)16 and Si10F16 adopt same Si
core with a 4-membered Si ring.
• Ligand electronegativity affects the Si
core structures.
• -SiF3 and -Si(OH)3 are preferred at
expenses of forming small 4-membered
Si rings.
16
What did we learn?
• GA is efficient, scaling O(N4-5).
• Well H-passivated Si clusters
adopt diamond-lattice Si cores.
• Si core can be tuned with # ligands.
• Si core can be tuned with ligand
electronegativity. SixCly and SixBry?
• Further study the excitation and photonemitting mechanism of Si nanoclusters.
• Questions and comments?
17
Questions?
18
May 18, 2007
HomeStead Road, Sunnyvale, CA
http://www.opentravelinfo.com/north-america/gas-price-hike
19
•
Nuclear Energy
Additional energy source: less fight on oil.
• No SO2 less acid
rains.
• No CO2 less global
warming.
Let’s try to
keep New
York &
Shanghai
above sea.
20
http://globalwarming--awareness2007.com/globalwarming-awareness2007/
What about the safety?
Layer 1. Porous
carbon to
accommodate
fission products and
kernel swelling.
Layer 3. Silicon
carbide is impervious
to fission products
and serves as a
pressure vessel.
Layer 2. Pyrolytic
carbon to trap
fission products.
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UO kernel
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Layer 4. Pyrolytic
carbon to protect SiC.
http://www.iaea.org/inis/aws/htgr/fulltext/xa54410.08.pdf
21
Chemical vapor deposition
inlets
• CVD: gas phase
molecules break
down at high T;
fragments
deposit on a
substrate to
account for the
solid growth.
diamond growth
outlet
substrate
CH4
C
http://www.ieee-virtual-museum.org/collection/tech.php?taid=&id=2345958&lid=1
H2
22
Silicon carbide (SiC) coating process
Coater Wall
Uranium Particles
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Annealing Zone
Deposition Zone
precursors
23
Why silicon carbide?
•
•
•
•
•
•
High melting point: 2700 C.
Mohs’ hardness: 9.3/10.
Imperviousness to fission products.
Lower reactivity at high temperature.
Low cost.
SiC made by chemical vapor deposition is ideal
material for the protective layer of nuclear
energy pellets.
24
P: Defects in the SiC layer cause cracks on
the surfaces of nuclear energy pellets.
Q: How to reduce defects in SiC?
A: Understand the mechanism of the SiC
chemical vapor deposition. Propose ideal
production condition.
25
• Detailed Reaction Kinetics for
Modeling of Nuclear Fuel Pellet
Coating for High Temperature
Reactors.
• Drs. Gordon and Ge from the
chemistry department.
• Drs. Fox and Gao from the chemical
engineering department.
• Drs. Battaglia and Vedula from the
mechanical engineering department.
26
Chemical vapor deposition of SiC
Precursors: CH3SiCl3 (methyltrichlorosilane)
Temperature: 1000-2000 K
Pressure: ~1 atm
Complex gas-phase and surface chemistry
CH3SiCl3  SiC (solid) + 3HCl
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CH3SiCl3 decomposition pathways
G = H - TS in kcal/mol
at 0 K (left) and 1400 K (right)
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28
50 gas phase species
Cl, Cl2, H, H2, HCl, C2H, C2H2, C2H3, C2H3Cl,
C2H4, C2H5, C2H5Cl, C2H6(e), C2H6, 1CH2,
3CH , CH C, CH Cl, CH Cl , CH , CH CH(s),
2
2
2
2 2
3
3
CH3Cl, CH4, HCHC, Si2Cl4, Si2Cl5, Si2Cl6,
SiCl2, SiCl3, SiCl4, SiH2Cl, SiH2Cl2, SiH3Cl,
SiHCl, SiHCl2, SiHCl3, CH2SiCl2, CH2SiCl3,
CH2SiHCl, CH2SiHCl2, CH3SiCl, CH3SiCl2,
CH3SiCl2Cl, CH3SiCl3, CH3SiH2Cl, CH3SiHCl,
CH3SiHCl2, HCSiCl, 1CHSiCl3, 3CHSiCl3
29
41 reactions without a transition state
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To be continued …
30
73 reactions with a transition state
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Reduced mechanism
• Our collaborators, including the chemical
engineers and mechanical engineers, also
complained about the long lists.
• How to reduce it?
• Remove the species whose concentration is
very low at high temperatures.
• Keep important species such as 3CH2, CH3,
SiCl2, and SiCl3 as target molecules.
• Remove 1 species at a time and compare
the reduced and full mechanisms.
• Reduced to 28 species and 29 reactions. 32
[C2H3]
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Time (s)
33
[SiHCl]
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Time (s)
34
Surface reactions: deposition
• Surface reactions involve thousands of
atoms.
• Hybrid quantum mechanics/molecular
mechanics (QM/MM) method.
Accuracy
Quantum
mechanics
Molecular
mechanics
1 kcal/mol
10
kcal/mol
System
size
tens of
atoms
millions of
atoms
35
(bulk)-C3SiCl
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QM region
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a dna ™emiTkciuQ
rosserpmoced )WZL( FFIT
.erutcip siht ees ot dedeen era
QM + MM regions
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C
H
Si
Cl
36
1). Production of Si*.
H attacks
Cl
HCl
leaving
2). Si-C growth.
H3C attacks
Si*
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Forming
H3C-Si
bond
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MM
region
MM
region
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MM
region
MM
region37
What did we learn?
• A gas phase mechanism was proposed in the
silicon carbide chemical vapor deposition.
• The gas phase mechanism was reduced to
28 species and 29 reactions.
• How temperature and precursor
concentration affect gas phase chemistry.
• Surface chemistry under investigation.
• Questions and comments?
38
Research plan
• Atomic layer deposition of Al2O3, TiO2, and
SiO2.
• Global optimization of protein structures.
• Astrochemistry in ice.
• Chemical vapor deposition of diamond C,
pyrolytic C, and bulk Si.
• Fast global optimization of large silicon
clusters.
39
Atomic layer deposition
• ALD is based on sequential, self-limiting
surface chemical reactions.
• Precise atomic layer control: no defects!
A
repeat
B
http://www.colorado.edu/chemistry/GeorgeResearchGroup/intro/aldcartoon.GIF
40
Vanadium oxide (VxOy) catalyzed
oxidative dehydrogenation
• Experimental energy barrier: 20-30
kcal/mol.
• Theoretical energy barrier: 45-80 kcal/mol.
• What’s wrong? Vanadium oxide is supported
by the ALD produced Al2O3, SiO2, or TiO2
surfaces.
• How to model an ALD surface?
• How does the ALD surface help lower the
energy barrier of C3H8 + 1/2O2  C3H6 +
H2O?
41
Global optimization
of protein
structures:
important for
drug design
primary structure
secondary structure
tertiary structure
quaternary
structure
42
Global optimization methods
• Random sampling: 30 dihedral angles each
with 5 possible values.
530 (~1 billion trillion) conformations.
• Molecular dynamics: some proteins fold in
minutes; energy and force need to be
evaluated 1018 times (t=10-15s).
• Genetic algorithm + Tabu + In situ adaptive
tabulation.
43
• Genetic
algorithm.
dihedral angles
crossover
mutation
Tabu (taboo): to penalize the moves to
previously visited conformations.
• In situ adaptive tabulation. {1… N} -> E
•
a). Enew  Eold
b). Enew  wiEiold
c). compute Enew
2
1
44
Astrochemistry in ice
?
Callisto
Europa
Ganymede
45
Jupiter’s Magnetic Field
46
Potential energy surface of 1H2O2
CCSD(T)
(kcal/mol)
1
TS2
70.2
2
1
1
O+H2O
50.8
1
H + 2HOO
54.9
TS3
TS4
1
1
O-H2O
50.0
O2 + H2
29.7
1
TS1
19.2
1
H2O-O
15.7
2
OH + 2OH
16.1
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1
HOOH
-30.0
47
Probable Reaction Paths to HOOH
• 1O + H2O  1H2O-O  HOOH
• 1O2 + H2  1H2O-O  HOOH
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• 1O (3O) + H2O  2OH + 2OH  HOOH
48
Future work
• Study the reaction paths at higher level of
theories.
• Study the potential energy surfaces that
involves cations such as 2O+.
• Reaction rate constant calculations.
• Molecular dynamics calculations.
• Elucidation of H2O2 formation mechanism.
• Study of H2O2 reaction paths in a
biological environment.
49
Acknowledgements
Prof. John D. Head
at University of Hawaii
Prof. Mark S. Gordon
at Iowa State University
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Department of Energy
Grant# DE-FC07-05ID14661
50
Questions and comments are welcome.
51
Crossover and mutation:
Si only cluster
a
A
B
crossover
B
a
A
b
b
local
opt.
mutation
local
opt.
Deaven and Ho,
PRL 75, 288 (1995)
53
Reaction rate constant
kB  T G  / RT
k(T) 
e
h
G  -- Free energy barrier
(some times hard to obtain)
kB -- Boltzmann constant
T -- temperature
h -- Planck constant
R -- Gas constant
54
Free Energy Profile of CH4  H + CH3
R=3.6 Å
at 400 K
120
Relative G (kcal/mol)
100
GTS
80
60
R=3.0 Å
at 2000 K
40
20
R=3.4 Å
at 1200 K
400
T (K)
0
1200
2000
-20
1
1.5
2
2.5
3
R(H---CH3) (angstrom)
3.5
4
55
Molecular dynamics approximations
for A + B  A-B
Reaction probability
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Collision area
Relative velocity
Elec. degeneracy
k(T)  ge (T)(
: reduced mass.
: symmetry
factor.

8k B T

2
)1/ 2 (bmax
)(Preact )
2
k(T)  ge (T)()1/ 2 bmax

56
Predict k: from CH3 + H  H-CH3
to CX3 + Y  Y-CX3
prediction
experiment
-8
CH3+Cl
log(k)
-9
-10
CCl3+Cl
CH3+F
-11
CF3+F
-12
0
1
2
3
4
57
Predict k
• k1 (2CH3 + 2H  1CH4)
• k2 (3CH2 + 2H  2CH3) Free energy barrier is hard to get.
k2 (T)/k1(T)  [ge 2 (T)/ge1(T)](2 / 1)1/ 2 ( 2 /1)
k2 (T) /k1(T)
1 1 14 15 1/ 2
 ( / )( / ) (1/2)
3 4 15 16
 0.668
58
PES of SiCl3 + H2
Si: blue
G at 0 K
Cl: green
(kcal/mol)
H: light grey
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+
(75.9)
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+
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(69.7)
(64.6)
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(59.8)
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+
(47.7)
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+
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(34.2)
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(19.3)
+
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+
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+
a dna ™emiTkciuQ
rosserpmoced ) WZL( F FIT
.erutcip siht ees ot dedeen era
(16.9)
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(0.0)
(7.9)
59
+
+
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Predict k: from CH3 + CH3  CH3-CH3
to CX3 + CY3  CX3-CY3
prediction
experiment
-8
log(k)
-9
-10
CH3+SiH3
CH3+CCl3
-11
CCl3+CCl3
-12
0
1
2
3
4
60
Potential energy surface of 3H2O2
3
3
TS4 3TS5
69.9 69.2
TS2
70.9
CCSD(T)//CASSCF
(kcal/mol)
2
H + 2HOO
54.9
cis3
HOOH
20.8
3
3
O+H2O 3
H2O-O
0.0
-0.9
3
O-H2O
-1.2
TS1
17.6
trans2
2
OH
+
OH
3
3
HOOH OH-OH
16.1
16.2
13.6
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