Jason Thompson, Casey Kelly, Benjamin Lynch, Christopher J. Cramer and Donald G. Truhlar
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Transcript of Jason Thompson, Casey Kelly, Benjamin Lynch, Christopher J. Cramer and Donald G. Truhlar
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Development of Methods for Predicting Solvation and Separation of Energetic
Materials in Supercritical Fluids
Jason Thompson, Casey Kelly, Benjamin Lynch,
Christopher J. Cramer and Donald G. Truhlar
Department of Chemistry and Supercomputing Institute
University of Minnesota
Minneapolis, MN 55455
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Methods for the demilitarization of excess stockpiles
containing high-energy materials
• burning
• detonation
• recycling explosive materials by extraction using
supercritical CO2 along with cosolvents
• Environmentally problematic• Expensive
To develop a predictive model for solubilities of high-energy materials
in supercritical CO2: cosolvent mixtures.
What cosolvent? What conditions?
The goal of this work
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What Do We Usually Predict with Our Continuum Solvation Models?
solvent A
solvent B
GSo(A B)
gas-phase
pure solution of solute
GSo(self )
gas-phase
liquid solution
GSo
Absolute free energy of solvation
Solvation energy
Free energy of self-solvation
Vapor pressure
Transfer free energy of solvation
Partition coefficient
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GSo (self)
GSo (aqliq)
GSo (aq)
A(liq)A(aq)
A(g)
GSo (aq):
equilibrium standard-state aqueous free energy of solvation
can be calculated or obtained from expt.
equilibrium standard-state free energy of self-solvation
can be calculated or obtained from expt.
defines pure-solute vapor pressure of A
GSo (self ):
GSo (aq liq) RT ln
SA
MAl
solubility of A
molarity of A
Similar relationships exist for other liquid solvents or when A is a solid.
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The SM5.43R Solvation Model1,2
• Bulk-electrostatic contribution to free energy of solvation
– Solute-solvent polarization energy
– Electronic distortion energy of solute and solvent cost
• Generalized Born approximation
– Solute is collection of atom-centered spheres with empirical Coulomb radii and atom-centered point charges
• Need accurate charges
• Need dielectric constant of solvent
GSo GEP GCDS
1Thompson, J. D.; Cramer, C. J.; Truhlar, D. G. J. Phys. Chem. A 2004, 108, 6532.
2Thompson, J. D.; Cramer, C. J.; Truhlar, D. G. Theor. Chem. Acc. 2004, in press.
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• Non-bulk-electrostatic contribution to free energy of solvation
– Cavitation, dispersion, solvent structure, and other effects
• Model: proportional to solvent-accessible surface areas of atoms in solute
– Constants of proportionality are surface tension coefficients
• Need index of refraction, Abraham and parameters, and macroscopic surface tension of solvent
The SM5.43R Solvation Model1,2
GSo GEP GCDS
1Thompson, J. D.; Cramer, C. J.; Truhlar, D. G. J. Phys. Chem. A 2004, 108, 6532.
2Thompson, J. D.; Cramer, C. J.; Truhlar, D. G. Theor. Chem. Acc. 2004, in press.
H bond acidity, basicity
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• CM3 charge model
– Maps lower level charges to improved charges as trained on dipole moments
– Uses a larger training set than previous charge models
– Is less sensitive to basis set size than previous charge models
– Uses redistributed Löwdin population analysis (RLPA)4 charges when diffuse functions are used
– Is available for many combinations of hybrid-density functional theory and basis set
• How accurate is CM3 for high-energy materials?
1Winget, P.; Thompson, J. D.; Xidos, J. D. Cramer, C. J.; Truhlar, D. G. J. Phys. Chem. A 2002, 106, 10707.
2Thompson, J. D.; Cramer, C. J.; Truhlar, D. G. J. Comput. Chem. 2003, 24, 1291.
3Kelly, C. P.; Cramer, C. J.; Truhlar, D. G. Theor. Chem. Acc. 2004, in press.
4Thompson, J. D.; Xidos, J. D.; Sonbuchner, T. M.; Cramer, C. J.; Truhlar, D. G. PhysChemComm 2002, 5, 117.
SM5.43R Uses CM31-3 charges
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Accurate, Density, and CM3 Dipole Moments
N NO
OH
HN N
H
H
O
ON N
HH
O
ON N
H
H
O
O
3.943.593.84
4.313.93 4.19
2.972.71 2.89
3.283.07 3.27
nitramide
MUE (density) = 0.30 debyes MUE (CM3) = 0.08 debyes
Accurate: mPW0/MG3S density dipole
MUE mean unsigned error:
Cs C2v Cs C2v
from mPW0/MIDI!
Approximate dipoles
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Accurate, Density, and CM3 Dipole Moments
4.814.21 4.67
5.044.43 4.87
3.432.99 3.33
3.693.38 3.77
dimethylnitramine
MUE (density) = 0.49 debyes MUE (CM3) = 0.12 debyes
Accurate: mPW0/MG3S density dipole
N NO
OMe
MeN N
Me
Me
O
ON N
MeMe
O
ON N
Me
Me
O
O
MUE mean unsigned error:
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Accurate, Density, and CM3 Dipole Moments
5.975.22 6.20
7.196.227.34
: RDX
MUE (density) = 0.86 debyes MUE (CM3) = 0.19 debyes
Accurate: mPW0/MG3S density dipole
N N
N
NO2
O2N NO2
MUE mean unsigned error;
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Accurate, Density, and CM3 Dipole Moments
1.561.321.80
0.310.42 0.79
: HNIW; CL-20
MUE (density) = 0.32 debyes MUE (CM3) = 0.29 debyes
Accurate: mPW1PW91/MG3S density dipole
2.561.95 2.41
N N
N N
NNNO2O2N
NO2
NO2O2N
O2N
MUE mean unsigned error:
[hexa-nitrohexaaza-iso-wurtzitane]
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CM3 Delivers Consistent Partial Atomic Charges
Conformer CM3 ChElPG CM3 ChElPG-HNIW -12.6 -13.4 -12.4 -19.1-HNIW -13.2 -13.6 -13.0 -19.2-HNIW -13.7 -13.9 -13.7 -19.6
mPW1PW91/MIDI! HF/MIDI!
Polarization energies (in nitromethane) calculated using different charge schemes by wave function (kcal/mole):
MUD (CM3) = 0.1MUD (ChElPG) = 5.7
All 14 nitramines(0.2)(2.8)
MUD (Löwdin) = 5.9 (2.9)
MUD mean unsigned deviation:
GP 1
2
1
qk q k k k
k , k
electrostatic fitting
population analysis
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The new CDS Term for SM5.43R
• Parameters in surface tension coefficients optimized using a large training set of solvation data
– 2237 experimental free energies of solvation in water and 90 organic solvents, partition coefficients between water and 12 organic solvents, and free energies of self-solvation
• Parameters are universal
– Parameters optimized for specific wave functions are similar to one another
• 2–8 times more accurate than the polarizable-continuum models (PCMs) in Gaussian 03, such as IEF-PCM
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Mean-Unsigned Errors (MUEs) of Free Energies of Solvation
B3LYP/6-31G(d)IEF-PCMGaussian03
MPW0/6-31+G(d)SM5.43RHONDOPLUSGAMESSPLUSSMXGAUSS
mean unsigned error: 257 neutrals in water 1.24 0.54 621 neutrals in 16 organic solvents 3.96 0.511359 neutrals in 74 other org. solvents not available 0.53 16 self-solvation energies 3.93 0.56 74 other self-solvation energies not available 0.55
better density functionalbetter basisuniversal in solventsbroader range of software packages
smaller errors, and yet…
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SM5.43R for Supercritical CO2
with and without cosolvents
• Need to develop solvent descriptors as a function of T and P
– Dielectric constant, index of refraction, Abraham’s hydrogen bond parameters, macroscopic surface tension, possibly others
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1.00
1.10
1.20
1.30
1.40
1.50
1.60
0 10 20 30 40
dielectric constant fromexperimentdielectric constant fromClausius-Mossotti eq.
Dielectric Constant Predictions
Dielectric constant as a function of pressure at 323 K
Pressure (MPa)
1 MPa = 10 atm
Die
lect
ric
cons
tant
,
Similar accuracy at other temperatures
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SM5.43R for Supercritical CO2
with and without Cosolvents
• Develop solvent descriptors as a function of T and P
– Dielectric constant, index of refraction, Abraham’s hydrogen bond parameters, macroscopic surface tension, possibly others
• Need training set of solvation data
– Mostly solubility data
• Relate free energies of solvation to solubility?1
1Thompson, J. D.; Cramer, C. J.; Truhlar, D. G. J. Chem. Phys. 2003, 119, 1661.
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Test Relationship
• Use a test set of 75 liquid solutes and 15 solid solutes
– Compounds composed of H, C, N, O, F, and Cl• Each solute has a known experimental aqueous free energy of solvation, pure
vapor pressure, and aqueous solubility
• Predict using experimental quantities
• Predict using experimental vapor pressures and calculated aqueous free energies of solvation
• Predict using calculated vapor pressures and aqueous free energies of solvation
solubility of A SA PA
Po
exp
GSo(aq)
RT
log Slog S
log S
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Mean-Unsigned Errors of the Logarithm of Solubility
calculated from experimental values, from theoretical free energies and experimental vapor pressures, and from theoretical values
Solute class No.data
Expt1.GS
o (aq) and PCalc. GS
o (aq)
Exptl. PCalc.
GSo (aq) and P
nitro compounds 5 0.04 0.25 0.35
all H, C, N, Ocompounds
60 0.15 0.32 0.35
all liquid solutes 75 0.15 0.32 0.34
solid solutes 15 (7) 0.42 0.47 (0.66)
requires “solvent” descriptors for solutes;we have the required solvent descriptors for only 7
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Other Progress
• Optimized electronic structure computer programs for hybrid density functional methods– Up to 4 times faster
• Assembling training set of solubility data in supercritical CO2
• New theoretical models to estimate solvent descriptors for free energy of self-solvation calculations
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Acknowledgments
Department of Defense Multidisciplinary University Research Initiative (MURI)
Minnesota Supercomputing Institute (MSI)
Casey P. Kelly (grad. student)
Dr. Benjamin J. Lynch (postdoctoral associate)
Jason D. Thompson (graduate student; Ph. D. completed summer ’04)
Christopher J. Cramer (co-PI)