e-Science Technologies in the
Simulation of Complex Materials
S. A. French, D. S. Coombes, C. R. A. Catlow – RI
B. Butchart, W. Emmerich – UCL CS
H. Nowell, S. L. Price – UCL Chem
L. Blanshard, R. Tyer, K. Kleese - CLRC
e-Science refers to large scale science that will increasingly be carried out through
distributed global collaborations enabled by the Internet.
What is e-Science?
• will require access to very large data collections
• large scale computing resources
• high performance visualisation back to the individual user scientists
Besides information stored in Web pages, scientists will need easy access to
remote computing resources and to information stored in dedicated databases.
Combinatorial Computational Catalysis
Polymorphism
Polymorphism and Properties of
Parabanic Acid
Acid Sites in Zeolites
• Determine the extra-framework cation
position within the zeolite framework.
• Explore which proton sites are involved
in catalysis and then characterise the
active sites.
• Produce a database with structural
models and associated vibrational modes
for different Si/Al ratios.
The aim of this project is to apply e-Science and Grid technologies
H
O
to the area of polymorph prediction. A method of predicting which
N
crystal structure a given organic molecule will adopt is important in
O
a number of areas, as changes in polymorphic form can affect
properties such as the colour of pigments, detonation stability of
N
O
H
energetic materials and the properties of pharmaceutical drugs. As
an example, we apply the polymorph prediction methodology to find
Parabanic acid
possible polymorphs of parabanic acid.
Prediction of the possible polymorphism involves the three stages.
• Improve understanding of the role of
the Si/Al ratio in zeolite chemistry.
Optimised Molecular Structure
A combined Monte Carlo and energy minimisation approach has been developed to
model zeolitic materials with low and medium Si/Al ratios. Firstly Al is inserted into
a siliceous unit cell and then a charge compensating cation, such as Na, is added
between two of the oxygens coordinated to Al. The zeolite Mordenite, which has a 1
dimensional channel system, has been studied with a simulation cell containing two
unit cells, which means 296 atoms, with 96 Si centres (referred to as T sites).
-12085
Configurations
0
N~
MOLPAK
1500
 Generation of crystal packings into 29 packing types
• Optimisation of density of unit cell
100
5550
-12083
DMAREL
5530
full_TE
full_Vol
-12081
• Lattice energy optimisation
5510
5 per. Mov. Avg. (full_TE)
-12079
5490
-12077
5470
-12075
5450
-12073
5430
-12071
5410
-12069
5390
-12067
5370
-12065
5350
Cell Vol.
Total Energy (eV)
5 per. Mov. Avg. (full_Vol)
• Energetical data : Lattice energy

Crystal structures and properties stored in Database
At the end of this process, a large number of hypothetical structures are obtained.
Those within 2-6 kJ mol-1 of the global minimum could be considered as possible
polymorphs as they have reasonable mechanical properties and relative growth rates.
-70
90
100
110
120
130
140
150
160
-75
10000
configurations
N ~ 100
Restricted number of structures selected
It can be seen in both graphs that there are two distinct regions, -12079eV to
-12076eV and -12075eV to -12073eV. From the upper graph there is no obvious
correlation between total energy and cell volume. However, when 10,000 structures
are considered it is clear that the most stable structures correspond to cation
placements that do not cause the cell to expand. This requires that the cations sit in
the large channel, shown in the picture below left.
0
• Geometrical data : Unit cell volume, density
Morphology
-80
-12090
P1
TE
P-1
VOL
-85
200 per. Mov. Avg. (VOL)
Lattice energy (kJ/mol)
200 per. Mov. Avg. (TE)
5550
-12085
P21
P21/c
Cc
-90
C2
C2/c
P21212
P212121
-95
Pca21
Pna21
5500
Pbcn
-100
-12080
Pbca
TE
VOL
ExptMinOpt
-12075
5450
-105
-110
-115
Cell volume per molecule (cubic angstroms)
-12070
5400
-12065
5350
We have made extensive use of Condor pools (for example UCL – 950 nodes in
teaching pools). 48 cpu-years of previously unused compute resource have been
utilised in this study. We have run 50,000 calculations each with 488 particles per
simulation box, which means a grand total of 24,000,000 particles have been
included in our simulations to date.
Plot of lattice energy against cell volume per molecule for all the
minima found in the MOLPAK search
We next calculate the growth morphology (attachment energy of the observed faces)
of the observed and predicted polymorphs and use this as an aid in judging whether a
certain polymorph is likely to exist. From the attachment energy values we also
calculate the growth volume. This is the volume within the Wulff shape and is
calculated by numerical integration.
30000000
-45
-40
25000000
-30
-25
15000000
-20
10000000
-15
Volume
AE
-10
5000000
-5
Predicted morphology of the observed
polymorph of parabanic acid
ai
25
de
12
aq
17
de
10
bb
31
de
5
dd
11
de
2
az
17
ap
29
af
28
ai
28
az
32
fc
5
am
32
ex
pt
m
in
op
t
33
0
aq
29
0
am
When we have confirmed the lowest energy
positions of Al the cation is exchanged for a proton
and again energy minimised. This method along
with the exploitation of low specification
computational resources will allow us to construct
realistic models of low and medium Si/Al zeolites.
Such structures can be used for further simulations
and aid the interpretation of experimental data.
Relative Volume
20000000
AE/kJ mol-1 per molecule
-35
Growth volume and attachment energy
for polymorphs of parabanic acid
From this, we see that the observed polymorph grows relatively fast, although
other polymorphs are possible.