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Transferable Potentials For Perfluorinated Molecules
... Note that perfluorinated hydrocarbons were considered in detail in a previous publication. 16 We include a brief subsection summarizing our results for perfluorinated hydrocarbons. ...
... Recall that perfluorinated hydrocarbons were analyzed previously. 16 Perfluorinated hydrocarbons are known for their nonstick and flame retardant properties. They are peculiar in that they exhibit liquid instability with both hydrocarbons and hydrogen bonding compounds. ...
Vapor pressure and liquid density are used to characterize step potentials for fluorinated, chlorinated, brominated, and iodinated hydrocarbons, along with a variety other compounds, bringing the transferable database to 339 training compounds, 112 of which are added in this manuscript, and 25 “validation” compounds. The potentials were characterized by four-step potentials consistent with those of previous studies for the SPEADMD model. Vapor pressure deviations average near 10 % for most compounds in the training set and near 40 % for the validation set. Higher deviations appear in the validation set for compounds in which multiple functionalities are located in close proximity, indicating sensitivity to the transferability assumption in these cases. Deviations in liquid density approach 4 %, despite the large shifts in density caused by the relatively heavy halogenated atoms. The availability of transferable potentials for so many compounds sets the stage for systematic studies of phase behavior over a broad range of molecular types. In the context of this study, several key elements were identified for organizing the physical property database, simulation results, and analytical tools to infer optimal characterizations of the molecular interactions. The physical property database must be critically evaluated to eliminate extrapolations and ambiguous data. The directory structure must be flexible and extensible to accommodate continuous improvement as more data and more compounds are incorporated into the analysis. Finally, an efficient methodology must be implemented to permit optimal characterization of the molecular interactions in a reasonable time on a continuing basis. The methodology presented in this paper permits a fresh optimization of the entire database in roughly 12 h.
... We should also mention an alternative (but related) hybrid approach by Elliot and coworkers (53)(54)(55)(56)(57)(58)(59) in which the interaction between CG segments forming the molecules is described using a discretized number of square-well step potentials (typically four). A high-temperature thermodynamic perturbation theory (TPT) (of the type used to represent the monomer contribution in SAFT) is used to accurately correlate the average attractive contribution to the thermodynamic properties of the fluid from the average value and fluctuations of the number of pairs in each well, obtained from discontinuous molecular dynamics (DMD) simulations of a reference repulsive system. ...
A description of fluid systems with molecular-based algebraic equations of state (EoSs) and by direct molecular simulation is common practice in chemical engineering and the physical sciences, but the two approaches are rarely closely coupled. The key for an integrated representation is through a well-defined force field and Hamiltonian at the molecular level. In developing coarse-grained intermolecular potential functions for the fluid state, one typically starts with a detailed, bottom-up quantum-mechanical or atomic-level description and then integrates out the unwanted degrees of freedom using a variety of techniques; an iterative heuristic simulation procedure is then used to refine the parameters of the model. By contrast, with a top-down technique, one can use an accurate EoS to link the macroscopic properties of the fluid and the force field parameters. We discuss the latest developments in a top-down representation of fluids, with a particular focus on a group-contribution formulation of the statistical associating fluid theory (SAFT-γ). The accurate SAFT-γ EoS is used to estimate the parameters of the Mie force field, which can then be used with confidence in direct molecular simulations to obtain structural, interfacial, and dynamical properties that are otherwise inaccessible from the EoS. This is exemplified for several prototypical fluids and mixtures, including carbon dioxide, hydrocarbons, perfluorohydrocarbons, and aqueous surfactants. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering Volume 5 is June 07, 2014. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
Elliott and Gray developed mixing rules for the SPEADMD model by simulating many mixtures and examining the trends. The present work examines the accuracy of the methodology in correlating experimental data relative to a standard low-pressure database for testing VLE models developed by Danner and Gess. The database contains 104 binary systems categorized according to polarity and ideality. Six models are tested and compared for their characterization of these mixtures. In addition to the SPEADMD, Margules, NRTL, PR, and PRWS models, a new model is developed based on the SPEADMD model that corrects for deviations in the vapor pressure that derive from the application of transferable potentials. The new model is called the SPEADMDγ model. Results show that the SPEADMDγ model provides accuracy similar to the NRTL and PRWS models, even though it includes only one adjustable parameter per binary system while the NRTL model includes two and the PRWS models includes three. Deviations in correlated bubble point pressure are roughly 1-2% for these models. The SPEADMD models have the advantage that transferable potentials can be applied for solvation interactions that are remarkably similar to the Kamlet-Taft interaction parameters. Accurate vapor-liquid equilibria (VLE) estimation is important for many chemical processes, most notably distillation. Often experimental data do not exist for VLE in the temperature range of interest. Therefore models to predict VLE have become important. The most basic model for VLE is Raoult's Law, yiP = xiPi sat , where P is pressure, Pi sat , xi, and yi are the vapor pressure and liquid and vapor mole fractions component of i respectively. Raoult's Law assumes ideal mixing for all systems. However, most mixtures are non-ideal, thus more sophisticated methods are needed to explain mixture behavior. Two methods are commonly used for calculating VLE. The distinction between them is in the way the fugacity (φ) of the liquid is calculated. The fugacity of the vapor phase of the VLE is always calculated using an equation of state (EOS). The fugacity of the liquid phase can be calculated by using either the same EOS used for the gas or by the activity coefficient (γ) method.(1) The SPEADMD model is based on Step Potential Equilibria And Discontinuous Molecular Dynamics.(2) It provides a bridge between molecular simulation methodology and a conventional approach to engineering phase behavior models. By discretizing the intermolecular potential model into a series of steps, a combination of discontinuous molecular dynamics (DMD) simulation and thermodynamic perturbation theory (TPT) can be adapted to achieve a high degree of leverage from each simulation.(3) The SPEADMD model begins with molecular simulation of pure fluids and mixtures. Simulation of every pure fluid is necessary to characterize the TPT contributions. Owing to the adaptation of TPT for temperature effects, simulations of the reference fluid over the entire density range provide a complete EOS, customized for the particular molecular model at hand. In principle, treating mixtures requires
The present work examines the accuracy of the SPEADMD molecular simulation methodology in correlating experimental data relative to a standard low-pressure database for testing VLE models. The database contains 104 binary systems categorized according to polarity and ideality. Although the database is somewhat small, it covers a broad range of chemical functionality, including halocarbons and carboxylic acids as well as hydrocarbons and alcohols. Six models were tested and compared for their characterization of these mixtures. Four standard models were evaluated to establish a basis for comparison: the Margules, NRTL, PR, and PRWS models. The SPEADMD model was evaluated in three forms. In its elementary form, the SPEADMD model includes 10% deviations in vapor pressure because of the application of transferable potential functions in the molecular model. An alternative model is developed on the basis of SPEADMD combined with corrected vapor pressures and customized self-interaction parameter for pure compounds. This alternative is referred to as the SPEADCI model, in which CI stands for customized interactions. Results show that SPEADCI model provides accuracy similar to the NRTL and PRWS models, even though it includes only one adjustable parameter per binary system, whereas the NRTL model includes two and the PRWS models include three. Deviations in correlated bubble point pressure are roughly 1−2% for these models. The SPEADMD models have the advantage that transferable potentials can be applied for solvation interactions that are similar to the Kamlet-Taft interaction parameters.
Transferable step potentials are characterized for 39 carboxylic acids. The reference potential is treated with discontinuous molecular dynamics, including detailed molecular structure. Thermodynamic perturbation theory is used to interpret the simulation results and to provide an efficient basis for molecular modeling and characterization of the attractive forces. Four steps are used for representation of the attractive forces with only the first and last steps varied independently. The two middle steps are interpolated such that each site type is characterized by three parameters: the diameter, σ, the depth of the inner well, ε1, and the depth of the outer well, ε4. The depths of the attractive wells are optimized to fit experimental vapor pressure and liquid density data. Generally, the vapor pressure is correlated to an overall 43% average absolute deviation (% AAD) and the liquid density to 5% AAD. The deviations tend to be largest for the higher molecular weight acids. These deviations are larger than the errors previously encountered in characterizing organic compounds, but carboxylic acids present exceptional challenges owing to their peculiar dimerization behavior. Simultaneous correlation of vapor pressure, vapor compressibility factor, and phase equilibria of water + carboxylic acids place several constraints on the nature of the potential model, with the parameters of the present model representing a reasonable tradeoff. In other words, our model represents minimal deviations for vapor pressure, vapor compressibility factor, and phase equilibria of all acids simultaneously while varying the parameters σ, ε1, ε4, εCC(dimerizing site bonding energy), εAD(acceptor-donor bonding energy), and KHB(hydrogen bonding volume) for the acid O and OH site types. The present model is characterized by one acceptor and one dimerizing site on the carbonyl oxygen and one acceptor and one donor site on the hydroxyl oxygen. The acceptor and donor are capable of interacting with water while the dimerizing site is not. With this model, the saturated vapor compressibility factor of acids with seven or fewer carbons is near 0.5 while higher carbon ratios lead to a compressibility factor approaching 1.0. To compensate for the high vapor pressure deviations of the transferable potential model, a correction is introduced to customize the molecule-molecule self interaction energy. This adaptation results in deviations of 3.1% for vapor pressure of the pure acid database. To validate the behavior of the model for carboxylic acids in mixtures, 33 binary solutions were considered. Acids in this database ranged from formic to hexadecanoic. The average absolute deviation in bubble pressure for aqueous acid systems is 4.4%, 10.5% for acid + acid systems, and 4.7% for acid + n-alkane systems without a customized interaction correction. When applying the correction, deviations were 2.4% for aqueous systems, 2% for acid systems, and 2.8% for acid + n-alkane systems. © 2009 American Institute of Chemical Engineers AIChE J, 2010
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