Applications and integration with experimental data

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Applications and integration with experimental
data
Checking your results Validating your
results Structure determination from powder
data calculations on crystal surfaces
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Polymorph predictionchecking your results
Why are most predicted structures not found
experimentally, even if they have a low
energy? 1. Experimentalists should try harder
-) The more time one spends crystallizing, the
more polymorphs one will find
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Polymorph predictionchecking your results
Why are most predicted structures not found
experimentally, even if they have a low
energy? 2. The energy function is wrong. Check
with experimentally known structures, or
other experimental data.
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Polymorph predictionchecking your results
Why are most predicted structures not found
experimentally, even if they have a low
energy? 3. The structure is not a true minimum,
but is on a saddle point, due to symmetry
constraints. example
Possible solution optimize again, after
removing (some) symmetry constraints, e.g. in P1.
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Polymorph predictionchecking your results
Why are most predicted structures not found
experimentally, even if they have a low
energy? 4. The structure is in a very unstable
local minimum. Example two packings which only
differ in a methyl rotamer. Solution do a very
short MD simulation on the structure, and
optimize again. Combination with (2) run MD on
the P1 structure.
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Polymorph predictionchecking your results
Why are most predicted structures not found
experimentally, even if they have a low
energy? 5. Kinetic factors (over-) rule
thermodynamic factors. Solution Lengthy MD
runs? Isotropy? .
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Polymorph predictionvalidating your results
Is the model in line with experimental data?
Powder diffraction is the XRPD reproduced?
Are structural features from ssNMR, IR, AFM,
reproduced? - number of independent molecules
- H-bond scheme - surface features - optical
properties
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Structure solution from X-ray powder data
A company produces a compound, and does quality
control via the XRPD pattern. One day, something
bad appears to have happened.
? yesterdays pattern
todays pattern ?
Are they still making the same polymorph? What
is/are the crystal structure(s)?
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Structure solution from X-ray powder data
Input An indexable powder pattern Knowledge
of (the major part of ) the cell contents. Step
1 indexing the powder pattern. Let the computer
guess cell parameters that correspond to the
diffraction angles. Result cell parameters Z
possible space groups. example a9.0 b12.0
c15.0 ??90º ?112º ? V1502 monoclinic. If
MV380 ? Zcell volume / molecular volume ?
4. P21/c?
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Structure solution from X-ray powder data
example a9.0 b12.0 c15.0 ??90º
?112º monoclinic, Z? 4. Guess P21/c. Why?
CSD statistics and symmetry restrictions
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Structure solution from X-ray powder data
Step 2, option 1 do a polymorph prediction run
in P21/c.
What will be the most likely conformer(s)? ? CSD
search on similar structures. Where will the
chloride ion be? major part of the structure
defined as fragment which must be present
Cl- present no water/other polar solvent
present Result molecular conformation
and position of the Cl-. Probably.
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Structure solution from X-ray powder data
Step 2, option 1 do a polymorph prediction run
in P21/c with the complex of the two ions as a
single particle during MD. Finally, compare the
XRPDs with experiment.
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Structure solution from X-ray powder data
Step 2, option2 Determine all parameters that
influence the powder pattern, but do not depend
on the structure zero-point error, overall
temperature factor, peak shape, etc. Result An
ideal powder pattern If we put in the correct
atomic coordinates, we should get a close match
between calculated and observed diffraction
patterns. Step 3 MC search. Create trial
structures by varying molecular position and
orientation conformation (via rotatable
torsions) keeping
the unit cell fixed. For each trial structure,
compare calculated and observed powder pattern.
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Simulation of surfacesSimulation of epitaxial
growth
Expitaxial growth of anthraquinone on
NaCl. Observation well oriented stripe-pattern
on 100
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
Approach 1 assume structure and morphology are
not changed compared to single crystal structure.
Which anthraquinone surface has the highest
affinity for NaCl 1 0 0?
Likely candidates 1 0 0 1 0 -2 0 0 2
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
Approach 1 static energy calculations
?
build a representative part of the 100, 10-2,
and 002 surfaces. calculate E(?) for each
surface
1 0 0 1 0 -2 0 0 2
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Building a representative surface model
1 0 0 0 0 2 1 0-2
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Building a representative surface model
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translate dy
translate dz
rotate d?
optimize
Print E, ?
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Minimum energy as a function of ? and hkl
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These results depend on cut-off radius
(11-17Å) anthraquinone system size (6x4x2
10x1x1 molecules)
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
Conclusions from static approach growth
occurs in single rows single rows give the
lowest interaction energy the 45º
orientation has by far the lowest interaction
energy, which explains the two (45º and 135º)
observed orientations of the needles on the
surface the 10-2 surface fits best to NaCl
d(OO) d(NaNa) within 0.2. Will single
molecules from the vapor attach to the surface
in this way?
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
Approach 2 Molecular Dynamics 100x100x12Å NaCl
surface (3240 NaCl) 12 anthraquinone. All atoms
free to move, except NaCl on sides and
bottom swimming pool-like system.
a) T300K b) T600K c) T450K
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
T450K, 100ps (2 days CPU) top view
Conclusion initially too much potential
energy, and too little interaction with NaCl
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
T450K, 100ps (2 days CPU) side view
Conclusion some molecules do attach to the
surface!
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
T450K, 100ps (2 days CPU) side view, detail
Conclusion carbonyls attach to the Na really
well.
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
To get a more useful simulation start from
last frame of MD run 1 bring the evaporated
molecules closer, but not too close, to the
surface. do another MD run...
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
Another 100 ps of MD top view
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
Another 100 ps of MD close up
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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100
Maybe 200 ps is a bit short. Lets go for 1250 ps

• Note
• Row of 3
• reorients
• is immobile
• Number 4 gets
• almost attached
• Molecules that lie
• flat are mobile

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Simulation of surfacesepitaxial growth of
anthraquinone on NaCl 100

• Results from MD
• Growth in rows as proposed from the static
  energy calculations
• is indeed well possible.
• 1 ns simulation is still very short.
• The MD T is not directly comparable to the real
  T.
• Mobility depends on the orientation of the
  molecules.
• Some orientations are very common we could use
  the energies
• as parameters in other calculations.

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Molecular Modeling of Crystal Structures
Energy function is essential to obtain a reliable
result. Visual interpretation of results (MD
movies, charge distributions, the shape of a
cavity,) can be essential to understand your
system. 30/10/2002 from MM to QM, and how to
visualize your results.