monte carlo calculations for alcohols

7/29/2019 Monte Carlo Calculations for Alcohols

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MONTE CARLO CALCULATIONS FOR

ALCOHOLS


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ABSTRACT

Trappe-UA force-field for hydrocarbons has been extended to primary, secondary

alcohols.

Coupled-decoupled configurational bias Monte-Carlo Simulations in the Gibbs ensemble

has been carried to calculate the 1 component vapor-liquid coexistence curves for

Alcohols.

Phase equilibria of the pure alcohols are accurately described by the Trappe-UA Force

fields.


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IMPORTANCE OF VLE

VLE gives the nature of intermolecular interactions present in

the liquid and vapor phases.

Useful in developing equations of state and corresponding state

theories Knowledge of critical points and VLE are key to achieving

fundamental understanding of these fluids.


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ALCOHOLS UNDER STUDY

Methanol

Ethanol

Propan-1-ol

Propan-2-ol

Butan-2-ol

Pentan-1-ol

Octan-1-ol


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ALCOHOLS

They are amphiphilic molecules composed of a f lexible, non-polar alkyl tail and a polar

hydroxyl head that is capable of acting as hydrogen donor and acceptor

Alcohols have desirable solvent characteristics due to their amphiphil ic nature.

They are readily available


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NEED FOR MOLECULAR SIMULATION

Knowledge of fluid phase diagrams and related thermo-physical properties is

essential in process design and process optimization.

Reliable Experimental data are only available for relatively low molecular

weight alcohols and only over a limited temperature range because of their

thermal instability above 600K. Molecular simulation is an alternative approach to obtain the thermo-physical

properties of alcohols

Accuracy of the prediction depends largely on the quality of the force-field

used and how well it describes the system.


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TRAPPE MODEL

Trappe Model was developed to

Reproduce Thermo-Physical Properties over a wide range of physical Conditions

Keep the models as transferable as possible by minimizing the number of (Pseudo)

atoms needed for any particular molecule and by using the same parameters for a

given (Pseudo) atom in all types of molecules


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TRAPPE MODEL

A Pseudo Atom mimics the interactions of its core electrons plus a share of the valence

electron that make its bonds to the neighboring atoms.

The Contribution of the valence electrons far outweighs the contribution of the core

electrons towards molecular polarizability.

Example: Pseudo atom for methyl group that is connected to another Carbon atom,

accounts for 3 C-H bonds and a share of the C-C bond. The same Pseudo atom can be

used for the methyl group in ethane, propane etc.

However the pseudo atom for the methyl group connected by a single bond to an Oxygen

atom is different due to the differences in the electronegativity between C and O atoms

which leads to intramolecular charge transfer and requires the use of a partial charge


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FORCE FIELD DEVELOPMENT

In Trappe-UA model, CHx groups are treated as pseudo atoms located at the sites of the

carbon atoms whereas all other atoms(e.g O and H) are modeled explicitly.

Non-bonded interactions are described by

Non-Bonded potentials of the above equation are used only for interactions of pseudo-

atoms belonging to different molecules or belonging to the same molecule but whose

interactions are not accounted for by any of the intramolecular, bonded potentials.


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FORCE-FIELD DEVELOPMENT

In TRAPPE-UA force-fields, all bond-lengths are fixed

A harmonic potential is used to control bond angle bending

Where , o and K are the measured bending angle, equilibrium bending angle and the

force constant

The Torsional potentials used to restrict the dihedral rotations is as shown above


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SIMULATION DETAILS

Combination of the Gibbs Ensemble Monte Carlo Method and the Configurational Bias

Monte Carlo method was employed to calculate the Vapor-Liquid Coexistence curves

Combined volume of the simulation boxes was adjusted to yield liquid-phase simulation

boxes with linear dimension of 30 A and larger vapor -phase simulation box containing

atleast 10 molecules

For the LJ part of the potential, a cut -off distance of 14 A was set and analytic tail

corrections were enforced.

An Ewald sum with thin-foil boundary conditions was used for the long-range electrostatic

interactions


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SIMULATION DETAILS

5 different Monte-Carlo moves were used to sample phase space in the Gibbs ensemble

simulations. The moves are

Translational

Rotational

Conformational

Volume Exchanges

Particle Swaps between boxes

Moves were selected randomly with fixed probabilities that were adjusted to yield about

one volume exchange or particle swap move per 10 MC Cycles and the remainder of the

moves were equally divided among the other moves


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SIMULATION DETAILS

Coupled decoupled Configurational Bias Monte-Carlo algorithm was used for

conformational and particle swap moves.

Computational efficiency was increased by utilizing a

Biased insertion

Additional center of mass based cut-off which avoids computing unnecessarydistances.

Coupled-decoupled CBMC particle swap proceeds as follows

(i) The hydroxyl O is inserted(using multiple insertions)

(ii) The Hydroxyl H and -carbons are added as a consequence

(iii) Then, the remainder of the alkyl tail is grown


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RESULTS

Methanol(Dashed lines and Squares), Ethanol(Solid lines and circles)

Pentan-1-ol(dotted lines and diamonds), octan-1-ol (dash-dotted lines and triangles up)


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RESULTS

Propan-1-ol(solid lines and circles), Propan-2-ol ( dashed lines and squares)

Butan-2-ol (dash-dotted lines and tr iangles down)


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RESULTS


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RESULTS

Experimental Saturated liquid densities are very well reproduced with average deviations

of about 1%.

However, larger deviations were observed for the saturated vapor densities and

pressures.

Vapor pressures are overestimated at higher reduced temperatures but underestimated at

lower reduced temperatures which is more pronounced for lower molecular weight

alcohols. TRAPPE force-field predicted high saturated vapor-pressures for unsaturated

alkanes too.


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CRITICAL CONSTANTS


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RESULTS

Agreement for the critical constants are satisfactory

Critical Temperatures of most alcohols are slightly underestimated with an average

deviation of about 1.5%

Critical densities are overestimated on average by about 3%

Critical Density disagreement can be due to

Law of rectilinear diameters has a negative slope, an underestimation of the

critical temperatures results in an overestimation of the critical densities

Vapor densities at elevated temperatures are too high, which results in a shift of

the mean saturated densities to higher values


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OUR GCN AND NPT RESULTS

T p rVap rLiq(K) (MPa) (kg/m3) (kg/m3)

470 1.64303 34.44982 591.996500 3.017061 70.74142 521.8192510 3.618617 91.18393 488.4794515 3.948885 106.3667 468.5673

470 1.626919 33.83991 591.4571500 3.02532 74.36615 515.2263510 3.616337 91.72798 485.3918515 3.923665 105.7948 472.4864


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CONCLUSION

The performance of the TRAPPE-UA Force field for the prediction of thermo-physical

properties is in general very satisfactory with mean errors of about

1% for the saturated liquid densities

1.5% for the critical temperature

3% for the critical density

As observed for alkanes, alkenes, this force field tends to over-predict the saturated

vapor densities.


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REFERENCES

Bin chen,Jeffrey J. Potoff, and J. Iija Siepmann. Monte Carlo Calculations for Alcohols.

Transferable Potentials for Phase equilibria. 5. United-Atom Description of Alcohols

Frenkel D and Smit B. Understanding Molecular Simulations.


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THANK YOU

monte carlo calculations for alcohols

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