A generalization of the recent version of the statistical associating fluid theory for variable range Mie potentials [Lafitte et al., J. Chem. Phys. 139, 154504 (2013)] is formulated within the framework of a group contribution approach (SAFT-γ Mie). Molecules are represented as comprising distinct functional (chemical) groups based on a fused heteronuclear molecular model, where the interactions between segments are described with the Mie (generalized Lennard-Jonesium) potential of variable attractive and repulsive range. A key feature of the new theory is the accurate description of the monomeric group-group interactions by application of a high-temperature perturbation expansion up to third order. The capabilities of the SAFT-γ Mie approach are exemplified by studying the thermodynamic properties of two chemical families, the n-alkanes and the n-alkyl esters, by developing parameters for the methyl, methylene, and carboxylate functional groups (CH3, CH2, and COO). The approach is shown to describe accurately the fluid-phase behavior of the compounds considered with absolute average deviations of 1.20% and 0.42% for the vapor pressure and saturated liquid density, respectively, which represents a clear improvement over other existing SAFT-based group contribution approaches. The use of Mie potentials to describe the group-group interaction is shown to allow accurate simultaneous descriptions of the fluid-phase behavior and second-order thermodynamic derivative properties of the pure fluids based on a single set of group parameters. Furthermore, the application of the perturbation expansion to third order for the description of the reference monomeric fluid improves the predictions of the theory for the fluid-phase behavior of pure components in the near-critical region. The predictive capabilities of the approach stem from its formulation within a group-contribution formalism: predictions of the fluid-phase behavior and thermodynamic derivative properties of compounds not included in the development of group parameters are demonstrated. The performance of the theory is also critically assessed with predictions of the fluid-phase behavior (vapor-liquid and liquid-liquid equilibria) and excess thermodynamic properties of a variety of binary mixtures, including polymer solutions, where very good agreement with the experimental data is seen, without the need for adjustable mixture parameters.
I. INTRODUCTION
Thermodynamic tools are being continually developed and improved in order to meet the need for accurate property prediction in many sectors of the chemical industries. Predictive approaches have come to play an important role in the design of processes and the accuracy of the description of the thermodynamic properties can significantly affect process-design decisions.1,2 Despite the wide variety of methods that are available, industrial requirements in property prediction highlight the need for approaches that can be applied in an ever-expanding range of applications, including, among others, polymer processing, biotechnology, and solvent screening.3 Advances in thermodynamic modeling have led to novel applications, such as the integrated design of solvents and processes, where molecular characteristics of solvents are determined as part of the optimization of the process.4–7 An important aspect in the development of thermodynamic methodologies is a predictive capability, which is commonly perceived as the ability to provide predictions of phase behavior and other bulk properties without the need for experimental data for the determination of molecular model parameters.
An important class of thermodynamic methodologies with high predictive power include group contribution (GC) approaches. GC methods are developed based on the assumption that the properties of a given compound can be determined as appropriate functions of the chemically distinct functional groups that the compound comprises. The contribution of each functional group to the molecular properties is assumed to be independent of the molecular structure that the group appears in. Such approaches have a long history of research and application; the first developments focused on the prediction of pure-component properties, such as the GC methods of Lydersen,8 Joback and Reid,9 and the subsequent work of Gani and co-workers,10,11 to name but a few. Furthermore, GC approaches have found extensive application to the study of the thermodynamic properties of binary and multi-component mixtures, often with an emphasis on fluid-phase behavior, initially within the framework of activity coefficient methods. An example of this type of methodology is the well-established universal quasi-chemical functional group activity coefficient (UNIFAC) formalism.12 The UNIFAC approach and its subsequent modifications13 are widely considered to be the state-of-the-art predictive methodologies for industrial applications due to their accuracy in predicting the phase behavior of a wide range of mixtures and the availability of extensive parameter tables. Alongside UNIFAC other predictive activity coefficient approaches have been developed, a prominent example of which is the computational-chemistry based conductor-like screening model for real solvents (COSMO-RS).14 Such methods are however subject to a number of limitations: in these approaches one resorts to a treatment of the liquid phase only, neglecting pressure effects and only the subset of thermodynamic properties that can be determined from activity coefficients are obtained. With the aim of overcoming these limitations, GC methods have been coupled with equations of state (EoSs); prominent examples include the PSRK EoS,15 the GC16 and GCA17 EoSs, and more recently the VTPR EoS.18–20 Equations of state have the advantage of treating the vapor and liquid phases on an equal footing, can account for pressure effects, and can be applied to the study of a wide range of thermodynamic properties. Of particular relevance to the work presented in our current paper are the applications of GC within the framework of the statistical associating fluid theory (SAFT).21,22 These are reviewed briefly in the following discussion; for more details of the different applications of GC methods, the reader is directed to the reviews of Refs. 23 and 24.
Various versions of the SAFT EoS have been successfully applied to the study of the properties of thermodynamically challenging systems, such as polymeric, hydrogen-bonding, and reactive systems. Details of the underlying theory and the different applications of SAFT can be found in a number of comprehensive reviews.25–28 Early work dedicated to developing SAFT-based GC approaches involved the application of the group contribution concept at the level of determining the molecular parameters that describe a compound. In these homonuclear approaches the molecular model employed was the traditional SAFT representation of molecular chains formed from identical bonded segments, with all segments described by the same set of parameters, so that the underlying theory remained unchanged. Lora et al.29 were one of the first to combine a group contribution method with the original SAFT EoS,21,22 determining the molecular parameters that describe several poly(acrylates) by examining compounds of lower molecular weight. Subsequently, Vijande et al.30 developed a SAFT-based GC approach with an emphasis on the prediction of the properties of hydrofluoroethers. In the same spirit, Tamouza et al.31,32 have developed GC methods based on SAFT approaches which employ both fixed and variable-range interaction potentials for the study of the chemical families of the n-alkanes, alkylbenzenes, olefins, and alcohols. The methodology was then extended to account explicitly for interactions due to polarity (based on the treatment of Gubbins and Twu33) for the study of light and heavy esters,34 and has since been applied to a wide range of systems including polycyclic hydrocarbons,35 ethers, aldehydes, ketones,36 amines,37 and long-chain multifunctional molecules including alkanediols and alkanolamines.38 Alongside the aforementioned SAFT-based group contribution methods, other techniques have been developed where molecular properties are not calculated as functions of the occurrences of functional groups alone, but also account for the positioning of the groups in the molecule by defining super-structures. In the context of GC methods this invariably involves a consideration of second-order groups (as in the work of Constantinou and Gani10). The aim of such an approach is to account for proximity effects (i.e., how the presence of a functional group influences the physicochemical properties of a neighboring group) and to distinguish the representation of isomers.39–41
As has been mentioned earlier, homonuclear SAFT-based GC can be used successfully to describe the thermodynamic properties of a wide range of systems. Nevertheless, the predictive capabilities of these methodologies are typically limited to the prediction of the properties of pure compounds as no information on the nature of the unlike interactions between groups and/or molecules can be extracted from the pure-component data that are used in the characterization of the functional groups. The determination of the unlike interaction parameters, which can also be calculated in a GC fashion as described by Le Thi et al.,42 typically relies on the use of experimental data for mixtures. Methods based on London's theory can also be used to predict the values of the unlike interaction parameters from the physicochemical properties of the molecules within the SAFT formalism:43 this type of approach has been applied to mixtures of CO2, methane, and ethane with n-alkanes,44,45 methanol with n-alkanes,46 and aqueous solutions of alkanes, aromatic hydrocarbons, and alcohols.36
Group contribution approaches have also been developed within the framework of SAFT incorporating heteronuclear molecular models (and the corresponding theory). In heteronuclear approaches molecules are represented as chains of segments that are not necessarily identical. Within the Wertheim TPT1 methodology47–53 it is possible to develop formally, on the premise of a detailed heteronuclear molecular model, an equation of state maintaining a link between the nature of the different segments making up the molecules and the corresponding parameters. The first such studies of bonded heteronuclear models formed from hard-sphere segments included heteronuclear dimer,54 linear triatomic,55 and arbitrary polyatomic molecules.56,57 Within the context of a SAFT treatment, several variants have been reformulated based on a heteronuclear tangent molecular model. Examples include the work of Banaszak et al.,58,59 Adidharma and Radosz,60,61 McCabe et al.62 and Peng et al.63 who implement a square-well (SW) potential to describe the group-group interactions, the work of Blas and Vega64 based on molecules formed from Lennard-Jones (LJ) segments, and the work of Gross et al.65 As well as describing molecules with heteronuclear models, it is apparent that a model with fused (as opposed to tangent) segments is needed to provide accurate thermodynamic properties of real fluids.66,67 Fused models are treated within the SAFT-γ GC approach by representing the heteronuclear molecules as fused SW segments of different type with a shape factor to characterize the degree of overlap between the different groups. The method was shown to describe accurately the fluid-phase behavior of a wide range of pure components including the chemical families of n-alkanes, branched alkanes, alkylbenzenes, olefins, carboxylic acids, alcohols, ketones, and amines,66,67 and was used to study aqueous solutions of alkanes and alcohols,68 and systems of ionic liquids.69 Peng et al.70 have presented a closely related heteronuclear generalization of the SAFT-VR EoS based on the use of SW potentials. As discussed in a recent review,28 the two theories, which were developed independently, are essentially identical, the only distinguishing feature being the treatment of the contribution due to the formation of chain-like molecules from distinct functional groups. Within the SAFT-γ EoS the contribution to the free energy due to the formation of the heteronuclear chain molecules is calculated based on a molecular average of the contact value of the radial distribution function; in the case of the GC-SAFT-VR EoS of Peng et al.70 the contact values of the different monomeric segments are appropriately summed, with the aim to retain the connectivity of the distinct groups that form the molecule. As shown in the Appendix both approaches provide an essentially equivalent description of the thermodynamic properties of heteronuclear diatomic and triatomic molecules. We should also mention that a similar treatment to that of Peng et al.70 has been followed in the recent work of Paduszyński and Domańska.71 A key advantage of heteronuclear molecular approaches is that they can be used to predict the thermodynamic properties of mixtures based on unlike interaction parameters obtained from pure-component data alone.
In the context of group contribution approaches based on heteronuclear molecular models only potentials comprising hard-repulsive cores (e.g., the hard-sphere or square-well potentials) or of fixed form (e.g., the Lennard-Jones potential) have been considered thus far to describe the interactions between the molecular segments. Both the SW and the LJ form of interaction provide a successful representation of the fluid-phase equilibria for a wide variety of systems, but are known to have limitations. Potentials with infinitely repulsive cores are limited in the range of properties that can be described accurately (e.g., the inability to provide a simultaneous description of the fluid-phase behavior and thermodynamic derivative properties), due to the simplified representation of intermolecular forces.72,73 On the other hand, potentials of fixed form are limited in terms of the types of compound that can be represented accurately. As an example, the LJ potential cannot be applied to describe the intermolecular interactions of perfluorocarbons which are known to be characterized by much steeper repulsive interactions than can be represented with the LJ form.74 The development of a SAFT-based group contribution approach that incorporates the versatile Mie intermolecular potential of variable attractive and repulsive range is a key objective of our current work. We show that the resulting SAFT-γ Mie methodology constitutes a thermodynamic approach with a high predictive capability that can be applied to a wide variety of systems of different chemical nature providing an accurate description of thermodynamic properties, ranging from fluid-phase behavior to second-order derivative properties, such as the speed of sound, heat capacity, or isothermal compressibility.
Over the past decade there has been increased interest in the performance of EoSs in the description of second-order derivative properties. These derivative properties are of interest from a practical perspective (e.g., the use of the Joule-Thomson inversion curve in the Linde technique as a standard industrial process), and a precise description of such properties, for which the performance of traditional cubic EoSs has been shown to be relatively poor,75–78 is highly challenging from a theoretical perspective.75 An accurate representation of derivative properties is a stringent test even with a more sophisticated thermodynamic treatment such as SAFT. One of the first detailed studies of the performance of SAFT-type methods in the description of such properties was carried out by Colina et al.79 These authors examined the Joule-Thomson inversion curve obtained with the LJ-based soft-SAFT EoS64,80 and found that although good agreement could be achieved, the description was very sensitive to the values of the molecular parameters. In a subsequent study different versions of the SAFT EoS were compared, and deviations of up to 20% from the experimental values of the derivative properties were found.81 Llovell et al.82 have also presented a detailed analysis on the performance of the soft-SAFT EoS for the derivative properties of pure components and mixtures83 concluding that the accuracy of the description can range from 1% to 20% depending on the compound and the property of interest, with the highest deviations typically obtained for the speed of sound of long-chain n-alkanes. In other work on smaller molecules where SW or LJ forms of the potential are implemented, the reported errors for the description of the derivative properties is found to be within 10%.84 A number of studies have been carried out with the aim of improving the description of the derivative properties.76,77,85–87 However, the simultaneous representation of fluid-phase behavior and derivative properties is found to come at a cost: Maghari et al.86,87 have employed an empirical temperature dependence of the dispersion energy by means of compound-specific constants, while Kontogeorgis and co-workers77 re-correlated the universal constants of the PC-SAFT EoS to include derivative property data.
Derivative properties have also been extensively studied with renormalization-group crossover approaches as their singular behavior at the critical point makes them especially interesting. Examples of such studies that relate to the general SAFT framework include the work of Llovell et al.,88 Dias et al.,89 Vilaseca et al.,90 and Forte et al.91 Other crossover methods have also been applied to the study of derivative properties, such as the crossover-cubic92 and the crossover-lattice EoSs.93
An aim our current work is to demonstrate the impact of the intermolecular potential model that is employed within a SAFT GC treatment on the accuracy that can be achieved in the simultaneous description of the fluid-phase behavior and second-order derivative thermodynamic properties. It is important to note that SAFT approaches based on segment-segment interactions treated with Mie potentials of variable attractive and repulsive ranges are recognized to provide such a capability.72,94
An improved version of the SAFT-VR Mie EoS has been recently developed,73 where the various approximations inherent in the underlying theory of the EoS presented in 200672,95 are revisited and the perturbation expansion (in the description of the free energy due to monomeric interactions) are taken to third order to incorporate the effect of higher-order contributions. The SAFT-VR Mie approach has been shown to be very accurate for the simultaneous description of the fluid-phase behavior and thermodynamic derivative properties of pure substances and mixtures. In view of its success in describing the thermodynamic properties of real systems, we now reformulate SAFT-VR Mie as a group contribution approach based on a heteronuclear model of fused segments interacting via Mie potentials of variable repulsive and attractive range: SAFT-γ Mie. The goal is to develop a predictive group-contribution capability that provides accurate thermodynamic properties, including both fluid-phase behavior and second-order derivatives of the free energy, such as the heat capacity, compressibility, or speed of sound.
The remainder of the paper is organized as follows: A brief discussion on the underlying molecular model and the intermolecular potential is first presented in Sec. II, followed by a detailed description of the SAFT-γ Mie group contribution approach (Sec. III) and the procedure adopted for the estimation of group parameters (Sec. IV). The parameters for the functional groups of two chemical families (n-alkanes and n-alkyl esters) are presented in Sec. V A and the performance of the theory in describing the fluid-phase behavior of pure compounds is thoroughly assessed. The predictive capabilities of the approach in the prediction of second-order thermodynamic derivatives of pure components and the fluid-phase behavior and excess properties of binary mixtures are demonstrated in Sec. V B.
II. MOLECULAR MODEL AND INTERMOLECULAR POTENTIAL
As with other group contribution approaches the determination of molecular properties with the SAFT-γ Mie EoS is achieved by subdividing the molecules into distinct functional groups chosen to represent their various chemical moieties, with appropriate summations over the contributions of each of the functional groups. A fused heteronuclear model is employed, where the molecules are constructed from distinct monomeric segments which in our case are taken to interact through Mie potentials of variable attractive and repulsive range. An example of the fused heteronuclear molecular model used to represent n-hexane is shown in Figure 1, where the CH3 and CH2 functional groups that characterize n-hexane are denoted. In line with physical expectations a fused heteronuclear united-atom representation has been shown to be more appropriate than tangential heteronuclear models in the description of the fluid-phase equilibria of real compounds within a SAFT-γ treatment.66 A potential of the Mie form has been used for homonuclear models within the SAFT-VR framework by Davies et al.,96 as well as in the original development of the SAFT-VR Mie EoS.72,95 The main difference between these two approaches is in the treatment of the radial distribution function (RDF) of the Mie fluid, which in the approach of Davies et al.96 is approximated as the RDF of the Sutherland-6 potential. However, it is known that the accuracy of the representation of the RDF of the monomer reference system is of great importance in the development of EoSs based on the first-order thermodynamic perturbation theory (TPT1) of Wertheim.47–50 In the latest incarnation of the SAFT-VR Mie EoS73 an accurate second-order expansion of the RDF is developed; we use this latter form of the RDF in our current work.
The Mie intermolecular potential97 is a generalized Lennard-Jonesium potential,98–102 where the repulsive and attractive exponents which characterize the hardness/softness and the range of the interaction are allowed to vary freely. The form of the pair interaction energy between two segments k and l as a function of the intersegment distance rkl is given by
where σkl is the segment diameter, εkl is the depth of the potential well, and
In common with other SAFT approaches, additional short-range association sites can be placed on the segments to mimic the association interactions (hydrogen bonding and other short-range interactions) present in some polar compounds. More specifically the association interactions are modeled by means of square-well sites, so that the interaction between a site of type a placed on a segment of type k and a site of type b placed on a segment of type l is given by
where rkl, ab is the center-center distance between sites a and b,
We should also note that within the SAFT-γ treatment a group may comprise several identical segments.67 The number of identical segments forming a group k is labeled
III. SAFT-γ MIE
The total Helmholtz free energy A of a mixture of heteronuclear associating molecules formed from Mie segments is written in dimensionless form as the sum of four separate contributions,
where Aideal is the free energy of the ideal gas, Amono. is the term accounting for interactions between monomeric Mie segments, Achain is the contribution to the free energy for the formation of molecules from Mie segments, Aassoc. is the term accounting for the association interactions, N is the total number of molecules, kB is the Boltzmann constant, and T is the absolute temperature. In Secs. III A–III E, the separate contributions to the free energy are described in detail.
A. Ideal term
The ideal contribution to the free energy of the mixture is given by103
where xi is the mole fraction of component i in the mixture, ρi = Ni/V is the number density of component i, Ni being the number of molecules of component i and V the volume of the system. The summation in Eq. (5) is over all of the components NC present in the mixture (and
B. Monomer term
The monomer term Amono. describes the contribution of segment-segment interactions, taken to be of the Mie form in our case, to the total Helmholtz free energy of the system. This contribution is obtained with a Barker and Henderson104,105 perturbation expansion to third order. The intermolecular potential of Eq. (1) is first written as the sum of a reference repulsive contribution Φ0(rkl), and a perturbation attractive contribution Φ1(rkl):
where
and
Barker and Henderson105 have shown that the free energy of the system can then be obtained as a perturbation expansion in the inverse temperature with respect to the properties of the reference system. In the case of soft-core potentials, such as the Mie potential, the reference system can be approximated as an equivalent system of hard spheres with an effective (temperature-dependent) diameter dkk, since the properties of the reference system described by the potential in Eq. (7) are not generally known. The high-temperature perturbation expansion can then be expressed as
where AHS is the free energy of the hard-sphere reference system of diameter dkk. For a given group k, the effective hard-sphere diameter is obtained from105
The integral of Eq. (10) is obtained by means of Gauss-Legendre quadrature, a technique previously employed by Paricaud106 who showed that a 5-point Gauss-Legendre procedure is adequate for an accurate representation of the effective hard-sphere diameter dkk.
The hard-sphere Helmholtz free energy of the mixture is given by66
where NG is the number of types of groups present, νk, i the number of occurrences of a group of type k on component i, and aHS is the dimensionless contribution to the hard-sphere free energy per segment, obtained using the expression of Boublík107 and Mansoori et al.:108
In Eq. (12), ρs is the segment number density which is related to the molecular density ρ through
and the moment densities ζm are expressed as
where the effective hard-sphere diameter dkk of the reference fluid (cf. Eq. (10)) is used. The summation of Eq. (14) is expressed in terms of the fraction xs,k of segments of a group of type k in the mixture, which is defined as
After substituting the expression of the group fraction xs,k (Eq. (15)) in the definition of the reduced densities (Eq. (14)) and expressing the reference expression per segment as a function of the molecular density, one obtains the following expression for the hard-sphere Helmholtz free energy per molecule:
which is identical to the form of the Helmholtz free energy of a hard-sphere mixture.
The first-order term A1 of the perturbation expansion corresponds to the mean-attractive energy and, as for the hard-sphere term, it is obtained as a summation of the contributions to the mean-attractive energy per segment a1:
The mean-attractive energy per segment is obtained by summing the pairwise interactions a1, kl between groups k and l over all types of functional groups present in the system,
where it can be shown73 that
Here,
This expression is written using a generalized notation where the parameter λkl indicates that the expression can be evaluated for both the repulsive
so that
The unlike effective hard-sphere diameter dkl is obtained with an appropriate combining rule (cf. Sec. III E). The quantities I(λkl) and J(λkl) are introduced in order to simplify the integration of the potential so as to obtain analytical expressions for the first-order perturbation term as discussed in detail in Ref. 73. Both I(λkl) and J(λkl) are functions of the parameters of the intermolecular interaction potential alone and are calculated (for either
and
The free energy
The effective packing fraction has been parameterized73 for ranges of the exponents of 5 < λkl ⩽ 100 and can be expressed as a function of the vdW one-fluid packing fraction ζx as
where the coefficients (c1,kl, c2,kl, c3,kl, c4,kl) are obtained as functions of the exponent λkl from
The second-order perturbation term of the high-temperature expansion (cf. Eq. (9)) represents the fluctuation of the attractive energy in the system and is obtained as
where the fluctuation term per segment a2 is obtained from the appropriate sum of the contributions of the pairwise interactions a2,kl between groups k and l as
The expression for a2 is obtained based on the improved macroscopic compressibility approximation (MCA) proposed by Zhang et al.111 combined with a correction in the same spirit as that proposed by Paricaud106 for soft potentials. The final expression for a2,kl is given by
where KHS is the isothermal compressibility of the hypothetical vdW one-fluid (vdW-1) system (with the packing fraction ζx of Eq. (22)), and is obtained from the Carnahan and Starling hard-sphere expression112 as
The correction factor χkl is obtained from73
where the quantities fm, for m = 1, 2, 3, as given in Eq. (39), are functions of αkl, a dimensionless form of the integrated van der Waals energy of the Mie potential:
Note that in Eq. (32) a quantity
so that the packing fraction
The third-order perturbation term is obtained from the contribution per segment a3 as
where a3 is obtained by summing the pairwise segment-segment contributions a3,kl on groups k and l as previously for the a1 and a2 terms:
The contribution a3, kl, is obtained using the following empirical expression73
A temperature dependence of the a3,kl term is avoided by expressing it as a function of
The functions fm for (m = 1, …, 6) appearing in Eqs. (32) and (38) are determined from73
The values of the coefficients ϕm,n are listed in Table I. The coefficients that appear in the modified MCA expression for the a2,kl term, i.e., fm for m = 1, 2, 3, were obtained from an analysis of the Monte Carlo simulation data for the fluctuation term and pure-component vapor-liquid equilibrium data of selected Mie fluids (λr,λa).73 The coefficients employed for the calculation of the a3, kl term were obtained in order to best reproduce the simulation data for vapor-liquid equilibrium data and critical points of the selected Mie (λr,λa) fluids as explained in Ref. 73. It is important to note that the coefficients included in the calculation of the a3,kl are obtained from simulation data of the fluid-phase behavior of monomers, and as a consequence the final expression for the free energy effectively incorporates higher-order terms of the perturbation expansion of Barker and Henderson104 (in fact, for the complete series), rather than just the third-order term. A retrospective analysis of the third-order perturbation term has shown that calculations using the empirical expression of Eq. (38) are in good agreement with evaluations of the equivalent term obtained from molecular simulation,73 which indicates that the series is convergent and terms beyond the third-order make a reduced contribution to the Helmholtz free energy.
n . | ϕ1,n . | ϕ2,n . | ϕ3,n . | ϕ4,n . | ϕ5,n . | ϕ6,n . | ϕ7,n . |
---|---|---|---|---|---|---|---|
0 | 7.5365557 | −359.44 | 1550.9 | −1.19932 | −1911.28 | 9236.9 | 10 |
1 | −37.60463 | 1825.6 | −5070.1 | 9.063632 | 21390.175 | −129430 | 10 |
2 | 71.745953 | −3168.0 | 6534.6 | −17.9482 | −51320.7 | 357230 | 0.57 |
3 | −46.83552 | 1884.2 | −3288.7 | 11.34027 | 37064.54 | −315530 | −6.7 |
4 | −2.467982 | −0.82376 | −2.7171 | 20.52142 | 1103.742 | 1390.2 | −8 |
5 | −0.50272 | −3.1935 | 2.0883 | −56.6377 | −3264.61 | −4518.2 | N/A |
6 | 8.0956883 | 3.7090 | 0 | 40.53683 | 2556.181 | 4241.6 | N/A |
n . | ϕ1,n . | ϕ2,n . | ϕ3,n . | ϕ4,n . | ϕ5,n . | ϕ6,n . | ϕ7,n . |
---|---|---|---|---|---|---|---|
0 | 7.5365557 | −359.44 | 1550.9 | −1.19932 | −1911.28 | 9236.9 | 10 |
1 | −37.60463 | 1825.6 | −5070.1 | 9.063632 | 21390.175 | −129430 | 10 |
2 | 71.745953 | −3168.0 | 6534.6 | −17.9482 | −51320.7 | 357230 | 0.57 |
3 | −46.83552 | 1884.2 | −3288.7 | 11.34027 | 37064.54 | −315530 | −6.7 |
4 | −2.467982 | −0.82376 | −2.7171 | 20.52142 | 1103.742 | 1390.2 | −8 |
5 | −0.50272 | −3.1935 | 2.0883 | −56.6377 | −3264.61 | −4518.2 | N/A |
6 | 8.0956883 | 3.7090 | 0 | 40.53683 | 2556.181 | 4241.6 | N/A |
C. Chain term
The treatment of the contribution to the free energy due to the formation of molecules from fused Mie segments is undertaken following a formal TPT1 treatment, where the contact value of the radial distribution function at an effective average diameter is required.66,67 An alternative treatment has been proposed by Peng et al.,70 and later employed in the work of Paduszyński and Domańska,71 where the chain contribution is calculated using the segment-segment contact values of the RDF. In that way the connectivity of the molecule is retained in the theoretical description. However, as shown in the Appendix, both the RDF of a chain with an average diameter used in our current work and the segment-segment contact approach70,71 reproduce the thermodynamic behavior of tangentially bonded heteronuclear molecules with similar accuracy in comparison with simulation data.
In order to apply the SAFT-γ treatment of the chain contribution, average molecular parameters (
The quantity zk,i is not to be confused with the fraction xs,k of a given group k in the mixture, which is composition dependent (cf. Eq. (15)). The average molecular segment size
and
The averaging rule for the effective hard-sphere diameter
Other effective molecular parameters are obtained in the same way, so that the average interaction energy
and
Relation (45) holds for both the repulsive,
The contribution to the free energy of the mixture due to the formation of a chain of tangent or fused segments is based on the first-order perturbation theory (TPT1) of Wertheim47–50,52 but using the effective molecular parameters:
where
The zeroth-order term of the expansion,
which is valid for
and
The first-order term
In this expression
but with
The first-order term of the radial distribution function further depends on the density derivative of the effective first-order perturbation term
The integrated energy of the Sutherland fluid
where the effective packing fraction
The coefficients of Eq. (57) are obtained based on the averaged values of the exponents of the potential (
The second-order term
The correction factor γc, ii is given as a function of temperature, the one-fluid packing fraction
where
The second-order term from the macroscopic compressibility approximation
where all of the parameters and free energy terms are evaluated using the effective molecular parameters. Note that the empirical correction to the MCA expression is based on the molecular parameters:
where the coefficients f1, f2, f3 are obtained from Eq. (39) by using
D. Association term
The contribution to the Helmholtz free energy arising from the association of molecules due to the bonding sites is obtained in the Wertheim TPT1 form as47–50,52,53
where NST,k is the total number of site types on a given group k, and nk,a is the number of sites of type a on group k. Xi,k,a represents the fraction of molecules of component i that are not bonded at a site of type a on group k. It is obtained from the solution of the mass action equation as50,53,66
Here, Δij,kl,ab characterizes the association strength between a site of type a on a group of type k of component i and a site of type b on a group of type l of component j. By introducing the square-well bonding potential and carrying out an angle average, the following expression can be obtained:53
where
The determination of the integral in Eq. (67) requires an expression for the RDF of the reference Mie fluid over a range of distances. For a detailed discussion of the various options on how the integral can be evaluated, see Refs. 73 and 114. For example, the RDF can be approximated based on a Barker-Henderson zeroth-order perturbation approach, so that
The bonding volume Kij,kl,ab is obtained from73
The value of the radial distribution function at contact,
E. Combining rules
Combining rules for the unlike intermolecular parameters are commonly employed within equations of state to facilitate the study of binary and multicomponent systems. In the specific case of the methodology presented in our current work, the interactions between groups of different type also contribute to the description of pure components when represented with a heteronuclear molecular model. The unlike segment diameter is obtained from a simple arithmetic mean (Lorentz rule115) as
and the same combining rule is applied for the calculation of the unlike effective hard-sphere diameter, so that dkl is calculated as
Bearing in mind the definition of the Barker and Henderson hard-sphere diameter (cf. Eq. (10)), a more rigorous way to obtain dkl would be to integrate the potential of the unlike interaction between groups k and l as
However, such an approach would require extensive numerical calculations. Moreover, in agreement with earlier findings,73 the approximation of dkl as an arithmetic mean is found to have minimal impact on the performance of the method, as judged by the quality of the description of the properties of real compounds.
The unlike dispersion energy εkl between groups k and l, can be obtained by applying an augmented geometric mean rule, which also accounts for the asymmetry in size:
The combining rule for the repulsive
and by imposing the Berthelot condition,115
The combining rule of Eq. (74) provides a first estimate of the value of the unlike dispersion energy. It is known, however, that real systems often exhibit large deviations from simple or augmented combining rules, especially when the molecules comprise chemically different components and groups. As will be discussed in Secs. IV and V, the unlike dispersion energy εkl often has to be treated as an adjustable parameter in practice.
In the case of associating compounds, the unlike range of the association site-site interaction is obtained as
The unlike value of the association energy can be obtained by means of a simple geometric mean rule:
However, typically
A number of combining rules for the average molecular parameters required for the calculation of the chain and association contributions to the free energy also need to be considered. The unlike values for the effective segment size,
and
Once the functional form of the Helmholtz free energy has been specified other properties, such as the pressure p, chemical potential (or activity) of each component μi, internal energy u, enthalpy h, entropy S, Gibbs free energy G, and second-order derivative properties including the isochoric cV and isobaric cp heat capacities, the speed of sound u, isothermal compressibility kT, thermal expansion coefficient α, and Joule-Thomson coefficient μJT can be obtained algebraically from the standard thermodynamic relations.116 In order to determine the fluid-phase equilibria the conditions of thermal, mechanical, and chemical equilibria are solved by ensuring that the temperature, pressure, and chemical potential of each component are equal in each phase and that the state corresponds to a global minimum in the Gibbs free energy (e.g., see Ref. 117).
IV. ESTIMATION OF GROUP PARAMETERS
The parameters that describe the contribution of each functional group to the molecular properties are typically estimated from appropriate experimental data. In our SAFT-γ Mie approach, the compounds are modeled as heteronuclear molecules formed from distinct functional (chemical) groups, and each non-associating group is fully characterized by the following set of parameters (cf. Sec. II for more details): the number of segments
As discussed in Sec. III E, the unlike segment diameter, σkl, and the values of the exponents of the unlike interaction potential,
The group parameters are estimated from experimental data for a series of pure substances belonging to a given chemical family. In most group contribution approaches, one first considers the n-alkane series in the parameter estimation procedure, where the parameters for the methyl (CH3) and the methylene (CH2) groups are obtained. Once the parameters for these groups have been determined, they are transferred to the representation of compounds with additional functional groups based on experimental data for the corresponding homologous series, e.g., the n-alkyl esters for the carboxylate (COO) group. The parameters that describe each functional group in the SAFT-γ Mie EoS are obtained by regression to pure-component vapor-liquid equilibrium data (i.e., vapor pressures pvap, and saturated liquid densities ρsat), as well as single-phase densities ρliq(T, p) at given temperatures and pressures. The temperature range commonly used for vapor-liquid equilibrium data is between the triple point and
where
V. RESULTS AND DISCUSSION
A. SAFT-γ Mie group parameters
In the first instance models for the characterization of the functional groups of two chemical families are developed within our novel SAFT-γ Mie framework: the n-alkanes and n-alkyl esters. In Secs. V A 1 and V A 2, the development of models for the functional groups for each chemical family, together with the detailed results of the regression to the experimental data are presented. The metric used in our work to quantify the accuracy of the theoretical description of the experimental data for a property R of a given compound is the percentage average absolute deviation (%AAD) defined as
where nR is the number of data points of a property,
1. n-Alkanes
The chemical family of the n-alkanes is considered first in order to obtain the model parameters that describe the methyl (CH3) and methylene (CH2) functional groups. The parameters estimated for these functional groups, summarized in Tables II and III, are estimated from experimental data for the vapor pressure, saturated liquid density, and single-phase density of linear alkanes from ethane to n-decane. The number of data points and the temperature range (and pressure range for the single-phase density) for each compound and property considered are reported in Table IV.
Functional group k . | $\nu _{k}^{*}$
. | Sk . | $\lambda ^{\rm {r}}_{kk}$
. | $\lambda ^{\rm {a}}_{kk}$
. | σkk [Å] . | εkk/kB [K] . |
---|---|---|---|---|---|---|
CH3 | 1 | 0.57255 | 15.050 | 6 | 4.0772 | 256.77 |
CH2 | 1 | 0.22932 | 19.871 | 6 | 4.8801 | 473.39 |
COO | 1 | 0.65264 | 31.189 | 6 | 3.9939 | 868.92 |
Functional group k . | $\nu _{k}^{*}$
. | Sk . | $\lambda ^{\rm {r}}_{kk}$
. | $\lambda ^{\rm {a}}_{kk}$
. | σkk [Å] . | εkk/kB [K] . |
---|---|---|---|---|---|---|
CH3 | 1 | 0.57255 | 15.050 | 6 | 4.0772 | 256.77 |
CH2 | 1 | 0.22932 | 19.871 | 6 | 4.8801 | 473.39 |
COO | 1 | 0.65264 | 31.189 | 6 | 3.9939 | 868.92 |
εkl/kB [K] . | CH3 . | CH2 . | COO . |
---|---|---|---|
CH3 | 256.77 | 350.77 | 402.75 |
CH2 | 350.77 | 473.39 | 498.86 |
COO | 402.75 | 498.86 | 868.92 |
εkl/kB [K] . | CH3 . | CH2 . | COO . |
---|---|---|---|
CH3 | 256.77 | 350.77 | 402.75 |
CH2 | 350.77 | 473.39 | 498.86 |
COO | 402.75 | 498.86 | 868.92 |
. | T range . | . | %AAD . | T range . | . | %AAD . | T range . | p range . | . | %AAD . |
---|---|---|---|---|---|---|---|---|---|---|
Compound . | [K] . | n . | pvap(T) . | [K] . | n . | ρsat(T) . | [K] . | [MPa] . | n . | ρliq(T, p) . |
C2H6 | 125–275 | 31 | 2.24 | 125–275 | 31 | 1.48 | 150–550 | 10–50 | 123 | 0.96 |
n-C3H8 | 147–332 | 38 | 2.22 | 147–332 | 38 | 0.74 | 150–500 | 10–50 | 108 | 0.49 |
n-C4H10 | 170–385 | 44 | 1.27 | 170–385 | 44 | 0.37 | 150–550 | 10–50 | 123 | 0.50 |
n-C5H12 | 187–422 | 48 | 1.90 | 187–422 | 48 | 0.36 | 150–550 | 10–50 | 120 | 0.60 |
n-C6H14 | 201–456 | 52 | 1.68 | 201–456 | 52 | 0.27 | 188–548 | 10–50 | 108 | 0.52 |
n-C7H16 | 216–486 | 55 | 1.01 | 216–486 | 55 | 0.46 | 193–553 | 10–50 | 108 | 0.62 |
n-C8H18 | 227–512 | 58 | 1.22 | 227–512 | 58 | 0.54 | 226–546 | 10–50 | 95 | 0.64 |
n-C9H20 | 237–532 | 60 | 0.69 | 237–532 | 60 | 0.59 | 230–550 | 10–50 | 95 | 0.50 |
n-C10H22 | 245–555 | 63 | 1.75 | 245–555 | 63 | 0.52 | 253–553 | 10–50 | 89 | 0.47 |
Average | … | … | 1.55 | … | … | 0.59 | … | … | … | 0.59 |
. | T range . | . | %AAD . | T range . | . | %AAD . | T range . | p range . | . | %AAD . |
---|---|---|---|---|---|---|---|---|---|---|
Compound . | [K] . | n . | pvap(T) . | [K] . | n . | ρsat(T) . | [K] . | [MPa] . | n . | ρliq(T, p) . |
C2H6 | 125–275 | 31 | 2.24 | 125–275 | 31 | 1.48 | 150–550 | 10–50 | 123 | 0.96 |
n-C3H8 | 147–332 | 38 | 2.22 | 147–332 | 38 | 0.74 | 150–500 | 10–50 | 108 | 0.49 |
n-C4H10 | 170–385 | 44 | 1.27 | 170–385 | 44 | 0.37 | 150–550 | 10–50 | 123 | 0.50 |
n-C5H12 | 187–422 | 48 | 1.90 | 187–422 | 48 | 0.36 | 150–550 | 10–50 | 120 | 0.60 |
n-C6H14 | 201–456 | 52 | 1.68 | 201–456 | 52 | 0.27 | 188–548 | 10–50 | 108 | 0.52 |
n-C7H16 | 216–486 | 55 | 1.01 | 216–486 | 55 | 0.46 | 193–553 | 10–50 | 108 | 0.62 |
n-C8H18 | 227–512 | 58 | 1.22 | 227–512 | 58 | 0.54 | 226–546 | 10–50 | 95 | 0.64 |
n-C9H20 | 237–532 | 60 | 0.69 | 237–532 | 60 | 0.59 | 230–550 | 10–50 | 95 | 0.50 |
n-C10H22 | 245–555 | 63 | 1.75 | 245–555 | 63 | 0.52 | 253–553 | 10–50 | 89 | 0.47 |
Average | … | … | 1.55 | … | … | 0.59 | … | … | … | 0.59 |
The quality of the description of the pure-component vapor-liquid equilibria of the n-alkanes included in the regression is depicted for the coexistence densities in Figure 2(a) and for the vapor pressure in Figure 2(b). From the figures it can be seen that the SAFT-γ Mie group contribution approach allows for an excellent description of the phase behavior of the correlated compounds, from ethane to n-decane. The deviations (%AAD) from the experimental data for the vapor pressure and saturated liquid density are summarized in Table IV. The average deviation for all correlated n-alkanes was found to be 1.55% for pvap and 0.59% for ρsat and shows a significant improvement when compared to the results obtained by with the SAFT-γ approach for models based on the square-well potential (3.98% for pvap and 0.57% for ρsat) for the vapor pressure, with a similar performance for the saturated densities.66 The level of accuracy of the SAFT-γ Mie approach constitutes a clear improvement in the description of the pure-component phase behavior of the n-alkanes when compared to other group contribution approaches within SAFT: Tamouza et al.31 have reported average deviations of 2.63% for the vapor pressure and 2.29% for the saturated liquid density with their homonuclear GC approach based on the SAFT-0,119 and 1.66% and 2.23% with that based on SAFT-VR SW;109,110 in the case of the hetero GC-SAFT-VR of Peng et al.70 deviations of 5.95% and 3.07% are reported for the vapor pressure and saturated liquid density, respectively. The deviations with our SAFT-γ Mie approach are similar to the hs PC-SAFT71 deviations of 0.96% for pvap and 0.56% for ρsat, which are obtained for a smaller temperature range, namely, from
The deviations reported here are based on data within a temperature range up to
The description of the n-alkane single-phase densities ρliq (cf. Table IV) is also excellent, with an average deviation for all compounds of 0.59%. When examining each compound it can be seen that the highest deviations are observed for ethane, as was also observed for the SAFT-γ SW approach.66 One may argue that ethane should not be included in the parameter estimation procedure, since ethane does not contain a CH3–CH2 interaction, while all longer n-alkanes do. Furthermore, group contribution techniques are generally not well suited to the study of small molecules as proximity effects are neglected. With this in mind the procedure was repeated omitting the data for ethane and the inclusion of these experimental data was not found to bias the parameters of the groups in a way that would result in a sub-optimal description for the higher n-alkanes. When a more accurate model is needed, ethane can be described as a separate functional group (e.g., as would be the case for water, methanol, etc.). This strategy has been followed within the hetero GC-SAFT-VR of Peng et al.70 and the GC-SAFT of Tamouza et al.31 where n-propane was the first molecule considered in the series for the estimation of the parameters for the n-alkanes.
As has already been mentioned, a particular advantage of the Mie potential is that the detailed form of the pair interaction potential between segments can be modified by adjusting the values of the repulsive and attractive exponents. This allows one to capture the finer features of the interaction which are important in providing an accurate description of the thermodynamic derivative properties. For the parameters that determine the form of the interaction potential between the CH3 and CH2 functional groups, the value of the attractive exponent is fixed to
2. n-Alkyl esters
Having determined the parameters for the CH3 and CH2 functional groups, these can be transferred in the description of other homologous series of compounds to determine the parameters of additional functional groups. In the current work we develop parameters for the COO group, and its interactions with the CH3 and CH2 groups, based on experimental data for selected n-alkyl acetates. A number of different GC schemes have been suggested to represent these compounds: in the modified UNIFAC (Dortmund) approach an acetyl (CH3COO) functional group is employed;127 in the case of SAFT-based group contribution methods, a carboxylate COO group is used in the work of Thi et al.34 with the homonuclear GC-SAFT approach, and Peng et al.70 employ a methoxyl CH3O group (in conjunction with a carbonyl C=O group) in the framework of the hetero GC-SAFT-VR approach. In our work the COO group is treated as comprising one segment (
In our case the value of the attractive exponent is fixed to the London
Experimental data for selected mixtures are included in the estimation procedure so as to have a more complete characterization of the unlike interactions between the alkyl and carboxylate functional groups, to ensure an accurate description of the highly non-ideal phase behavior that these mixtures exhibit, and to increase the statistical significance of the interaction parameters.
. | T range . | . | %AAD . | . | T range . | . | %AAD . | . | T range . | p range . | . | . | %AAD . |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Compound . | [K] . | n . | pvap(T) . | Ref. . | [K] . | n . | ρsat(T) . | Ref. . | [K] . | [MPa] . | n . | Ref. . | ρliq(T, p) . |
CH3COOCH2CH3 | 307–473 | 29 | 0.37 | [147 and 148] | 273–473 | 21 | 0.25 | [147] | 298–393 | 1 - 20 | 80 | [149] | 0.43 |
CH3COO(CH2)2CH3 | 303–493 | 20 | 0.49 | [150] | 303–493 | 20 | 0.17 | [150] | 298–393 | 1 - 20 | 80 | [149] | 0.43 |
CH3COO(CH2)3CH3 | 334–399 | 27 | 0.73 | [151] | 298–523 | 25 | 0.42 | [149 and 152] | 298–393 | 1 - 20 | 80 | [149] | 0.19 |
CH3COO(CH2)4CH3 | 321–462 | 23 | 0.85 | [153] | 298–393 | 20 | 0.18 | [149] | 298–393 | 1 - 20 | 80 | [149] | 0.19 |
CH3COO(CH2)5CH3 | 274–459 | 33 | 1.86 | [154] | 273–431 | 18 | 0.24 | [155] | … | … | … | … | … |
CH3COO(CH2)6CH3 | 274–478 | 30 | 0.67 | [154 and 155] | 273–428 | 19 | 0.20 | [155] | … | … | … | … | … |
Average | … | … | 0.83 | … | … | … | 0.24 | … | … | … | … | … | 0.31 |
. | T range . | . | %AAD . | . | T range . | . | %AAD . | . | T range . | p range . | . | . | %AAD . |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Compound . | [K] . | n . | pvap(T) . | Ref. . | [K] . | n . | ρsat(T) . | Ref. . | [K] . | [MPa] . | n . | Ref. . | ρliq(T, p) . |
CH3COOCH2CH3 | 307–473 | 29 | 0.37 | [147 and 148] | 273–473 | 21 | 0.25 | [147] | 298–393 | 1 - 20 | 80 | [149] | 0.43 |
CH3COO(CH2)2CH3 | 303–493 | 20 | 0.49 | [150] | 303–493 | 20 | 0.17 | [150] | 298–393 | 1 - 20 | 80 | [149] | 0.43 |
CH3COO(CH2)3CH3 | 334–399 | 27 | 0.73 | [151] | 298–523 | 25 | 0.42 | [149 and 152] | 298–393 | 1 - 20 | 80 | [149] | 0.19 |
CH3COO(CH2)4CH3 | 321–462 | 23 | 0.85 | [153] | 298–393 | 20 | 0.18 | [149] | 298–393 | 1 - 20 | 80 | [149] | 0.19 |
CH3COO(CH2)5CH3 | 274–459 | 33 | 1.86 | [154] | 273–431 | 18 | 0.24 | [155] | … | … | … | … | … |
CH3COO(CH2)6CH3 | 274–478 | 30 | 0.67 | [154 and 155] | 273–428 | 19 | 0.20 | [155] | … | … | … | … | … |
Average | … | … | 0.83 | … | … | … | 0.24 | … | … | … | … | … | 0.31 |
A comparison of the SAFT-γ Mie description with the experimental data is given for the saturated liquid densities in Figure 4(a) and for the vapor pressures in Figure 4(b). The overall deviations (%AAD) for the correlated compounds (cf. Table V) are 0.83% for pvap, 0.24% for ρsat, and 0.31% for ρliq. It is evident from the reported deviations and the figures that the SAFT-γ Mie approach leads to an excellent description of the coexistence and single-phase properties of the compounds considered in the parameter estimation procedure. Thi et al.34 have applied three versions of SAFT (the SAFT-0,119 SAFT-VR,109,110 and PC-SAFT129) combined with a polar term and parameterized the COO functional group (for esters other than formates, HCOOR). The parameters for the COO group were obtained based on a selection of acetates, propanoates, butanoates, and other esters. For the same compounds as the ones used in the development of the SAFT-γ Mie parameters for the COO group presented in our current work, the deviations reported by Thi et al. were 4.76%, 3.05%, and 4.20% for pvap, and 1.62%, 1.72%, and 2.87% for ρsat with the GC-SAFT based on SAFT-0, SAFT-VR, and PC-SAFT, respectively. The performance of the hetero GC-SAFT-VR of Peng et al.,70 where alkyl acetates are modeled by using separate CH3O and C=O groups is somewhat less accurate with average deviations (from n-propyl to n-heptyl acetate) of 7.29% for pvap and 2.14% for ρsat. Although a direct comparison with the other methods is difficult due to the different experimental data used, the reported deviations for each methodology indicate that our new SAFT-γ Mie EoS leads to a significant improvement in the description of the pure-component fluid-phase behavior of n-alkyl acetates.
The limited mixture data included in the regression are also well represented with SAFT-γ Mie approach, as shown in Figure 5. The average deviation (%AAD) of the excess enthalpies for the binary systems included in the estimation was found to be 7.37% (8.78% for ethyl acetate + n-hexane, and 5.95% for n-butyl acetate + n-octane), and the level of agreement was deemed satisfactory based on the sensitivity of the selected properties to the unlike interaction parameters between the functional groups and the small values of the excess enthalpies exhibited by these mixtures (∼0.5 to 1.5 kJ/mol). In order to assess the level of accuracy, the description of the heat of mixing obtained with the SAFT-γ Mie approach was compared with the corresponding description using modified UNIFAC (Dortmund),127 where the group parameters were obtained by regression to data for different mixture properties including phase equilibria and excess enthalpies. From the comparison shown in Figure 5, it can be seen that the modified UNIFAC (Dortmund) provides a better description of the experimental excess enthalpies with an average deviation of 3.91%. Bearing in mind that within the modified UNIFAC approach group parameters are exclusively developed to describe (limited) properties of binary and multi-component mixtures, and that within the SAFT-γ Mie approach the primary target is a more complete thermodynamic description of pure components and mixtures, the performance of SAFT-γ Mie in the description of the excess enthalpies is very satisfactory.
The resulting form of the interaction potential of the COO group is described by an optimal value of the repulsive exponent of
B. Predictions
1. Pure components
An assessment of the adequacy of the parameters obtained for the CH3, CH2, and COO functional groups can be made by examining the performance of the theory in describing the thermodynamic properties of compounds not included in the parameter estimation procedure. The application of the Mie intermolecular potential was previously shown to allow for an accurate simultaneous description of fluid-phase equilibria and thermodynamic derivative properties72,73 when cast as a theory for homonuclear models. The prediction of derivative properties is a stringent test in any thermodynamic description, and high deviations are to be expected with most equations of state, be it with traditional cubic EoSs or the SAFT variants based on a fixed form of the intermolecular potential.72,73 Here, we examine the performance of the SAFT-γ Mie approach in the description of second-order thermodynamic derivative properties of representative n-alkanes and n-alkyl esters (cf. Tables VI and VII). A comparison of the predictions of our current approach and the corresponding results obtained with the SAFT-γ SW EoS66 in representing the experimental data from REFPROP130 for the isobaric and isochoric heat capacities, the speed of sound, the isothermal compressibility, and the thermal expansion coefficient of the linear n-alkanes from ethane to n-decane is provided in Table VI. For the calculation of caloric and derivative properties, the free energy of the ideal gas is determined based on the GC approach of Joback and Reid9 for the ideal gas heat capacity, cp,0. Though these expressions are based on correlations for a temperature range between 273 and ∼1000 K, a reliable description is found when extrapolated to lower temperatures. From Table VI it can be seen that the SAFT-γ Mie EoS provides a very accurate prediction of the second-order thermodynamic derivative properties of the n-alkanes examined, and constitutes a significant improvement to the description obtained with the SAFT-γ SW EoS based on the square-well potential.66 The level of agreement between the predictions of the SAFT-γ Mie theory and the correlated experimental data from REFPROP130 for the speed of sound, isothermal compressibility, isobaric heat capacity, and thermal expansion coefficient of selected n-alkanes at different thermodynamic conditions is also depicted in Figure 6. In Figure 7 the predictions of our SAFT-γ Mie approach are compared to the experimental data for the isochoric heat capacity of selected n-alkanes, at conditions both close to and far from the critical point. From Figure 7(a) it is evident that the theory provides an excellent representation of the temperature dependence of the isochoric heat capacity for three prototypical alkanes (n-butane, n-hexane, and n-octane), for both the liquid and the vapor branches, including the discontinuity at the liquid-vapor transition. The description of the pressure dependence of the isochoric heat capacity is depicted in Figure 7(b) for n-propane along both sub- and super-critical isotherms. The theory is shown to provide a satisfactory description of the isochoric heat capacity at all conditions; slight deviations are observed for the near-critical isotherm at T = 350 K (with
. | . | . | . | %AAD SAFT-γ Mie . | %AAD SAFT-γ SW . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Compound . | T range [K] . | p range [MPa] . | n . | cp(T, p) . | cV(T, p) . | u(T, p) . | kT(T, p) . | αV(T, p) . | cp(T, p) . | cV(T, p) . | u(T, p) . | kT(T, p) . | αV(T, p) . |
C2H6 | 150–600 | 10–50 | 138 | 3.18 | 3.76 | 2.49 | 3.53 | 3.50 | 7.86 | 10.30 | 7.42 | 8.27 | 9.78 |
n-C3H8 | 150–600 | 10–50 | 138 | 1.76 | 0.79 | 1.31 | 2.70 | 3.31 | 6.98 | 8.43 | 4.16 | 9.65 | 9.32 |
n-C4H10 | 150–570 | 10–50 | 129 | 1.98 | 1.92 | 0.78 | 1.84 | 3.70 | 7.96 | 11.06 | 4.48 | 12.40 | 10.45 |
n-C5H12 | 150–600 | 10–50 | 138 | 1.83 | 1.40 | 1.21 | 3.16 | 5.20 | 7.74 | 10.30 | 5.37 | 15.71 | 11.21 |
n-C6H14 | 190–600 | 10–50 | 124 | 0.96 | 1.31 | 0.82 | 3.36 | 5.91 | 5.33 | 7.48 | 4.62 | 11.55 | 10.12 |
n-C7H16 | 190–600 | 10–50 | 122 | 0.96 | 1.54 | 1.47 | 4.07 | 6.44 | 5.75 | 8.11 | 5.93 | 14.18 | 10.23 |
n-C8H18 | 230–600 | 10–50 | 111 | 0.59 | 2.19 | 0.92 | 3.45 | 7.33 | 4.73 | 7.51 | 5.29 | 12.07 | 10.61 |
n-C9H20 | 230–600 | 10–50 | 110 | 0.47 | 1.23 | 2.08 | 5.47 | 6.32 | 4.83 | 6.57 | 6.15 | 14.56 | 9.22 |
n-C10H22 | 260–670 | 10–50 | 123 | 0.42 | 1.73 | 2.26 | 6.25 | 7.74 | 3.89 | 5.56 | 5.64 | 12.81 | 10.57 |
Average | … | … | … | 1.35 | 1.76 | 1.48 | 3.76 | 5.49 | 6.12 | 8.37 | 5.45 | 12.36 | 10.17 |
. | . | . | . | %AAD SAFT-γ Mie . | %AAD SAFT-γ SW . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Compound . | T range [K] . | p range [MPa] . | n . | cp(T, p) . | cV(T, p) . | u(T, p) . | kT(T, p) . | αV(T, p) . | cp(T, p) . | cV(T, p) . | u(T, p) . | kT(T, p) . | αV(T, p) . |
C2H6 | 150–600 | 10–50 | 138 | 3.18 | 3.76 | 2.49 | 3.53 | 3.50 | 7.86 | 10.30 | 7.42 | 8.27 | 9.78 |
n-C3H8 | 150–600 | 10–50 | 138 | 1.76 | 0.79 | 1.31 | 2.70 | 3.31 | 6.98 | 8.43 | 4.16 | 9.65 | 9.32 |
n-C4H10 | 150–570 | 10–50 | 129 | 1.98 | 1.92 | 0.78 | 1.84 | 3.70 | 7.96 | 11.06 | 4.48 | 12.40 | 10.45 |
n-C5H12 | 150–600 | 10–50 | 138 | 1.83 | 1.40 | 1.21 | 3.16 | 5.20 | 7.74 | 10.30 | 5.37 | 15.71 | 11.21 |
n-C6H14 | 190–600 | 10–50 | 124 | 0.96 | 1.31 | 0.82 | 3.36 | 5.91 | 5.33 | 7.48 | 4.62 | 11.55 | 10.12 |
n-C7H16 | 190–600 | 10–50 | 122 | 0.96 | 1.54 | 1.47 | 4.07 | 6.44 | 5.75 | 8.11 | 5.93 | 14.18 | 10.23 |
n-C8H18 | 230–600 | 10–50 | 111 | 0.59 | 2.19 | 0.92 | 3.45 | 7.33 | 4.73 | 7.51 | 5.29 | 12.07 | 10.61 |
n-C9H20 | 230–600 | 10–50 | 110 | 0.47 | 1.23 | 2.08 | 5.47 | 6.32 | 4.83 | 6.57 | 6.15 | 14.56 | 9.22 |
n-C10H22 | 260–670 | 10–50 | 123 | 0.42 | 1.73 | 2.26 | 6.25 | 7.74 | 3.89 | 5.56 | 5.64 | 12.81 | 10.57 |
Average | … | … | … | 1.35 | 1.76 | 1.48 | 3.76 | 5.49 | 6.12 | 8.37 | 5.45 | 12.36 | 10.17 |
. | . | . | %AAD SAFT-γ Mie . | ||||
---|---|---|---|---|---|---|---|
Compound . | T range [K] . | n . | cp(T, p) . | cV(T, p) . | u(T, p) . | kT(T, p) . | kS(T, p) . |
CH3COOCH2CH3 | 298–328 | 7 | 5.62 | 2.21 | 9.89 | 14.56 | 17.32 |
CH3COO(CH2)2CH3 | 298–328 | 7 | 4.53 | 1.19 | 7.12 | 10.11 | 13.08 |
CH3COO(CH2)3CH3 | 298–328 | 7 | 2.18 | 1.80 | 4.96 | 9.16 | 9.52 |
CH3COO(CH2)4CH3 | 298–328 | 7 | 0.76 | 0.68 | 3.88 | 6.34 | 7.54 |
CH3COO(CH2)9CH3 | 298–328 | 7 | 1.23 | 3.32 | 1.01 | 0.38 | 1.78 |
Average | … | … | 2.86 | 1.84 | 5.37 | 8.11 | 9.85 |
. | . | . | %AAD SAFT-γ Mie . | ||||
---|---|---|---|---|---|---|---|
Compound . | T range [K] . | n . | cp(T, p) . | cV(T, p) . | u(T, p) . | kT(T, p) . | kS(T, p) . |
CH3COOCH2CH3 | 298–328 | 7 | 5.62 | 2.21 | 9.89 | 14.56 | 17.32 |
CH3COO(CH2)2CH3 | 298–328 | 7 | 4.53 | 1.19 | 7.12 | 10.11 | 13.08 |
CH3COO(CH2)3CH3 | 298–328 | 7 | 2.18 | 1.80 | 4.96 | 9.16 | 9.52 |
CH3COO(CH2)4CH3 | 298–328 | 7 | 0.76 | 0.68 | 3.88 | 6.34 | 7.54 |
CH3COO(CH2)9CH3 | 298–328 | 7 | 1.23 | 3.32 | 1.01 | 0.38 | 1.78 |
Average | … | … | 2.86 | 1.84 | 5.37 | 8.11 | 9.85 |
It is important to reiterate that the calculations presented in this section for the second-order thermodynamic derivative properties of n-alkanes are predictions, as no such data were included in developing the parameters that characterize each functional group. The assessment of the performance of the theory for these challenging thermodynamic properties provides a good indication of the physical robustness of the parameters obtained for the CH3 and CH2 functional groups. This is of crucial importance as these functional groups constitute the molecular backbone of a wide variety of substances. Given that within the approach used here group parameters are obtained in a sequential manner, it is essential to ensure that high-fidelity parameters have been derived for the methyl and methylene groups.
A key advantage of a group contribution formulation lies in the transferability of the group parameters. In order to assess this feature, the parameters for the CH3 and the CH2 functional groups are applied to the prediction of pure-component properties of systems not used to estimate the group parameters. Predictions with the SAFT-γ Mie EoS of the fluid-phase behavior for some heavier n-alkanes (namely, n-pentadecane, n-eicosane, n-pentacosane, and n-triacontane) are compared with the experimental data in Figure 8, and the corresponding deviations are summarized in Table VIII. From this analysis it is clear that the methyl and methylene group parameters can be transferred successfully to the prediction of the pure-component fluid-phase behavior of longer n-alkanes; the description of the saturated liquid density remains good, while large deviations are seen for the vapor pressure. The latter could be related to the high uncertainty and low absolute values of the experimental data for the saturation pressure of the higher molecular-weight compounds at low temperatures. Apart from the fluid-phase behavior, the CH3 and CH2 group parameters result in a good description of derivative properties of long n-alkanes, as shown in Figure 9(a) for the speed of sound of n-pentadecane (n-C15H32) and Figure 9(b) for the isothermal compressibility of n-eicosane (n-C20H42). The results obtained with the SAFT-γ Mie approach and the parameters developed for the CH3 and CH2 groups show a significant improvement in the prediction of the derivative properties of the long chain n-alkanes studied compared to the predictions with the SAFT-γ SW EoS, also included in Figure 9.
Compound . | T range [K] . | n . | %AAD pvap(T) . | Ref. . | T range [K] . | n . | %AAD ρsat(T) . | Ref. . |
---|---|---|---|---|---|---|---|---|
n-C15H32 | 293–576 | 35 | 7.19 | [157 and 158] | 273–633 | 11 | 0.71 | [152] |
n-C20H42 | 388–625 | 29 | 15.66 | [159] | 293–683 | 11 | 0.98 | [152] |
n-C25H52 | 381–461 | 13 | 29.87 | [160] | 293–695 | 11 | 3.10 | [152] |
n-C30H62 | 432–452 | 5 | 37.50 | [160] | 293–727 | 11 | 4.01 | [152] |
CH3COO(CH2)8CH3 | 276–309 | 12 | 1.37 | [154] | … | … | … | … |
CH3COO(CH2)9CH3 | 284–530 | 32 | 2.94 | [154 and 155] | … | … | … | … |
CH3COO(CH2)10CH3 | 288–329 | 14 | 2.31 | [154] | … | … | … | … |
CH3COO(CH2)11CH3 | 288–333 | 15 | 4.46 | [154] | … | … | … | … |
CH3COO(CH2)13CH3 | 303–340 | 13 | 2.95 | [154] | … | … | … | … |
Average | … | … | 11.58 | … | … | … | 2.20 | … |
Compound . | T range [K] . | n . | %AAD pvap(T) . | Ref. . | T range [K] . | n . | %AAD ρsat(T) . | Ref. . |
---|---|---|---|---|---|---|---|---|
n-C15H32 | 293–576 | 35 | 7.19 | [157 and 158] | 273–633 | 11 | 0.71 | [152] |
n-C20H42 | 388–625 | 29 | 15.66 | [159] | 293–683 | 11 | 0.98 | [152] |
n-C25H52 | 381–461 | 13 | 29.87 | [160] | 293–695 | 11 | 3.10 | [152] |
n-C30H62 | 432–452 | 5 | 37.50 | [160] | 293–727 | 11 | 4.01 | [152] |
CH3COO(CH2)8CH3 | 276–309 | 12 | 1.37 | [154] | … | … | … | … |
CH3COO(CH2)9CH3 | 284–530 | 32 | 2.94 | [154 and 155] | … | … | … | … |
CH3COO(CH2)10CH3 | 288–329 | 14 | 2.31 | [154] | … | … | … | … |
CH3COO(CH2)11CH3 | 288–333 | 15 | 4.46 | [154] | … | … | … | … |
CH3COO(CH2)13CH3 | 303–340 | 13 | 2.95 | [154] | … | … | … | … |
Average | … | … | 11.58 | … | … | … | 2.20 | … |
The formulation of a SAFT-type approach within a group contribution concept combines the wide range of applicability of EoSs and the predictive nature of GC methods. This can be illustrated in the description of the thermodynamic properties of polymers. The SAFT EoS has been successfully applied as a general methodology to study polymeric systems (e.g., see Refs. 119 and 131–134); the theory is particularly suited to polymers due to the explicit consideration of the chain connectivity. Within the scope of the current work, and taking advantage of the group contribution formulation, the properties of polyethylene polymers can be predicted, using the parameters for the methyl and methylene groups estimated from the experimental data for the lower n-alkanes (cf. Sec. V A 1). The predictions of the SAFT-γ Mie approach are compared with the experimental single-phase densities of liquid (molten) linear polyethylene in Figure 10. The parameters for the methyl and (predominantly) for the methylene group are seen to allow for an accurate description of linear polyethylene with a molecular weight of 126 000 g mol−1 over a broad range of temperatures and pressures. Achieving this level of agreement with the experimental data is particularly challenging, especially when one recalls that the parameters for the CH3 and CH2 groups are developed from the properties of the much shorter n-alkanes, ranging from ethane to n-decane. The description obtained with the SAFT-γ SW EoS using published parameters66 is also plotted in Figure 10. From the comparison it is apparent that the representation of the density of polyethylene with Mie segments provides a marked improvement over that obtained with square-well segments, and lends credence to the physical relevance of the parameters for the CH3 and CH2 groups (cf. Table II).
A similar assessment is performed for the chemical family of the n-alkyl acetates, where the performance of the methodology in the prediction of second-order derivative properties is examined. The deviations of the SAFT-γ Mie predictions from the experimental data for the speed of sound, isobaric and isochoric heat capacities, and isothermal and isentropic compressibilities for selected n-alkyl acetates are summarized in Table VII. From the table it can be seen that higher deviations are observed in the description of the thermodynamic derivative properties considered for the lower molecular-weight compounds. This could be due to the dominance of the polar nature of the COO functional group for molecules with a short alkyl chain, which is not accurately reproduced by the theory in the case of derivative properties. It should be noted that this is somewhat expected, as group contribution approaches are less suitable for the description of small molecules. As the chain length of the n-alkyl acetates is increased, the level of agreement between the predictions of the theory and the experimental data improves, and a very good representation is seen in the case of n-decyl acetate. This is also depicted in Figure 11, where the predictions of the theory for the speed of sound and the isobaric heat capacity of n-alkyl acetates with varying chain lengths are plotted together with the experimental data.
An assessment of the SAFT-γ Mie EoS in the prediction of the pure-component fluid-phase behavior for longer compounds not included in the parameter estimation procedure has also been performed for the n-alkyl acetates. The parameters for the CH3, CH2, and COO groups are used to predict the fluid-phase behavior of five high-molecular-weight n-alkyl acetates, namely n-nonyl, n-decyl, n-undecyl, n-dodecyl, and n-tetradecyl acetate; the deviations from the experimental data, available for the vapor pressure only, are summarized in Table VIII. From the table it can be seen that the SAFT-γ Mie approach can be extrapolated with good accuracy to the prediction of the pure component fluid-phase behavior of long-chain n-alkyl acetates. Aside from predictions for pure-component fluid-phase behavior the SAFT-γ Mie approach can be successfully applied to the prediction of single-phase densities and second-order thermodynamic derivative properties of long-chain esters. This is demonstrated in Figure 12, where the predictions of the theory are compared with the experimental data for the single-phase density, the speed of sound, and the isothermal and isentropic compressibility of several long-chain ethyl esters, namely, ethyl caprylate (ethyl n-octanoate), ethyl caprate (ethyl n-decanoate), ethyl laurate (ethyl n-dodecanoate), ethyl myristate (ethyl n-tetradecanoate), and ethyl palmitate (ethyl n-hexadecanoate), fatty acid esters of key relevance in the production of biofuels. It should be noted that these compounds are not of the same category as the ones used in the development of the COO functional group, where data for alkyl acetates were used; however, since the functional group developed is the more versatile COO group (as opposed to models where a CH3COO group is employed) the properties of these ethyl esters can be predicted in a reliable and straightforward manner.
2. Binary systems
The ability to obtain information about the nature of the unlike dispersion interaction between segments belonging to the same molecule is an inherent advantageous feature of the SAFT-γ approach. For the specific case of the chemical families considered in this work, this means that the values of the unlike dispersion energies between the CH3 and CH2 groups are obtained from pure-component data of the n-alkanes alone (see Table III). This allows for calculations of the fluid-phase behavior and other properties of mixtures of n-alkanes and/or esters in a purely predictive manner.
An example of the predictive capabilities of the SAFT-γ Mie approach is shown in Figure 13, where the theoretical description is compared to experimental data for the vapor-liquid phase behavior of the binary system n-butane+n-decane at different temperatures. It is clear that the SAFT-γ Mie predictions are in very good agreement with the experimental data for the fluid-phase equilibria of the mixture. The improvement in the description of the near-critical fluid-phase behavior within the SAFT-γ Mie approach allows for an accurate representation of the system over a wide range of conditions, including the high-pressure critical region for isotherms at temperatures above the critical point of n-butane. The overshoot of the critical points of the phase envelopes of this binary system is significantly reduced in comparison to the results obtained with the SAFT-γ SW approach.66
The same parameter set can be applied to the prediction of the fluid-phase behavior of binary mixtures of compounds not included in the regression of the group parameters. An example of this is shown in Figure 14, where the predictions of the theory are compared to the experimental data for asymmetric systems of a short and an oligomeric long-chain n-alkane. More specifically, in Figure 14(a) the theoretical predictions are compared with the available experimental data for the liquid-liquid equilibria of the propane+n-hexacontane mixture at three different temperatures. This system is chosen as a prototypical example of the type of fluid-phase equilibria exhibited in polymer solutions of hydrocarbons.135 The n-C60H122 molecule is the highest molecular-weight monodisperse n-alkane commercially available, so the mixture can be modeled without the need to account for polydispersity.136 Polydispersity generally has to be considered in representing polymer+solvent systems and can have a significant effect on the phase boundaries, particularly in the description of liquid-liquid equilibria (e.g., see Ref. 134). From Figure 14(a) it can be seen that the SAFT-γ Mie predictions are in very good agreement with the experimentally determined phase behavior of the mixture, accurately reproducing the width of the coexistence region at higher pressures, with only a minor overshoot of the liquid-liquid critical point. The proposed methodology provides a significantly improved description of the mixture in comparison to the corresponding results obtained with the SAFT-γ SW EoS based on the SW potential.66,67 A comparison of the predictions of the theory for the vapor-liquid equilibria of polymer-solvent systems is shown in Figure 14(b) for the mixture of n-pentane and polyethylene of molecular weight 76 000 g mol−1 at two temperatures. The polymer in question has quite a high degree of polydispersity characterized by a polydispersity index of 6.91;137 this degree of polydispersity is not expected to significantly affect the vapor-liquid phase behavior of the system. From the figure it can be seen that both the SAFT-γ Mie and the SAFT-γ SW methods provide a description of similar accuracy for the vapor-liquid equilibrium of the system. As a final point it is important to emphasize that the same set of group parameters is employed for the prediction of different types of phase behavior: vapor-liquid equilibria for n-butane + n-decane and n-pentane + polyethylene, and liquid-liquid equilibria for propane + n-hexacontane.
The performance of SAFT-γ Mie can also be assessed in the prediction of excess thermodynamic properties of binary mixtures of n-alkanes. Properties such as the excess volume and enthalpy have been the subject of numerous studies,115 including among others the seminal work of Flory and co-workers138–140 and more recently the work of Blas and co-workers141–143 within the SAFT framework. An example of the performance of the SAFT-γ Mie approach is illustrated in Figure 15, where the predictions of the theory are compared to experimental data for the excess speed of sound (uE) of selected n-hexane + n-alkane binary mixtures144 (cf. Figure 15(a)), and the excess molar volumes (VE) of the binary mixture of n-hexane + n-hexadecane at different temperatures145 (cf. Figure 15(b)). As for the fluid-phase behavior, the predictions of the theory are in very good agreement with the experimental data. For the excess speed of sound, the predictions of the theory are seen to be in quantitative agreement with the experimental data; the trend to lower values of the excess speed of sound as the difference in the chain lengths of the components of the mixture decreases is correctly reproduced. Quantitative agreement for the excess molar volume is seen with the data at higher temperatures, and the trend of the data to lower values with decreasing temperature is reproduced by the theory. Given the small magnitude of the data (especially at lower temperatures), and the fact that one of the components of the mixture (n-hexadecane) is not included in the parameter estimation procedure, good overall agreement of the theory with the experimental data is found. Comparing the predictions of the SAFT-γ Mie approach to the corresponding description obtained with the SAFT-γ SW EoS, a clear improvement is seen for the excess speed of sound of the mixtures in Figure 15. In the case of the predictions of the excess volumes, both theories provide a description of equivalent accuracy, with the SAFT-γ SW in better agreement with the experimental data at the lower temperatures, and SAFT-γ Mie at the higher temperatures. Despite an accurate overall performance, it has to be noted that the theory cannot reproduce the fine features of the excess enthalpies of binary systems of asymmetric n-alkanes, which arise from conformational effects that the theory does not account for. Such effects can be incorporated in the general theoretical framework by including a term that treats the specific intramolecular interactions as has been shown by dos Ramos and Blas.143
The parameters obtained for the COO group and the unlike interaction values shown in Tables II and III allow for the prediction of properties of generic binary mixtures of n-alkanes and n-alkyl esters. A comparison between the predictions of the SAFT-γ Mie and the modified UNIFAC (Dortmund)13 approaches for the fluid-phase behavior of selected binary mixtures is presented in Figures 16 and 17. In Figure 16, the fluid-phase behavior of mixtures of ethyl acetate with n-alkanes of varying chain length (n-pentane, n-octane, and n-decane) is presented as an isobaric temperature-composition representation. The theory accurately describes the vapor-liquid phase behavior of the mixtures studied, which are characterized by a minimum boiling azeotrope, and the shift of the azeotropic composition to higher compositions of ethyl acetate with increasing chain length of the n-alkane is reproduced. In Figure 17 the vapor-liquid phase behavior of a selection of mixtures of n-hexane with n-alkyl acetates of varying chain length is shown. In this case, a more distinct azeotrope is observed for n-hexane + ethyl acetate, the composition of which is accurately reproduced by the theory. Regarding the performance of the SAFT-γ Mie EoS in comparison to the well-established modified UNIFAC (Dortmund) GC approach, it is apparent from Figures 16 and 17 that in the case of the systems studied both approaches provide an equivalent level of agreement with the experimental data.
The adequacy of the theory in describing excess properties of mixing of binary systems of n-alkanes with n-alkyl acetates is also examined. The excess enthalpy of mixing predicted with SAFT-γ Mie for three binary mixtures of n-heptane with n-alkyl acetates of varying size (n-propyl, n-butyl, and n-pentyl acetate) is compared to the experimental data in Figure 18(a). It can be seen that the enthalpy of mixing of the three selected mixtures is described well, and the correct dependence of the magnitude of the excess enthalpy with varying chain length of the n-alkyl acetate is also predicted. The SAFT-γ Mie predictions are seen to be of similar accuracy to those with the modified UNIFAC (Dortmund) approach, as shown in Figure 18(a). This is very pleasing, given the small absolute values of the excess enthalpy for these mixtures (hE ⩽ 1.5 kJ mol−1). One has to bear in mind that the SAFT-γ Mie parameters are obtained predominantly from pure-component experimental data and data for selected mixtures, while the UNIFAC parameters are the result of extensive regression to binary mixture (fluid-phase behavior and other properties) data. In Figure 18(b), the predictions of the SAFT-γ Mie theory for the excess volumes of the same mixtures are compared to the experimental data. In this case, comparisons with the modified UNIFAC (Dortmund) approach are not possible, as UNIFAC is based on a lattice-fluid model and thus cannot be used directly for density calculations. The performance of the SAFT-γ Mie approach is very satisfactory, and excellent agreement between the calculations and the experimental data is seen.
Finally, we examine the performance of the theory for the prediction of second-order thermodynamic derivative properties of binary mixtures of n-hexane with n-alkyl acetates of different chain lengths. In Figure 19 a comparison of the experimental data and the SAFT-γ Mie predictions for the speed of sound (Figure 19(a)) and the excess isentropic compressibility (Figure 19(b)) is shown for binary mixtures of n-hexane with ethyl, n-pentyl, and n-decyl acetate. In the case of the speed of sound, and in line with the deviations reported in Table VII, it can be seen that the theory provides a qualitative description of the experimental data; the deviation in the prediction of the speed of sound in the limit of pure ethyl acetate is, however, quite significant. As the chain length of the n-alkyl acetate is increased, the agreement of the predictions with experiments improves, and the results for n-hexane + n-decyl acetate are seen to be in excellent agreement with the experimental data. Regarding the predictions for the excess isentropic compressibility of the same mixtures (cf. Figure 19(b)), the SAFT-γ Mie predictions reproduce the change of sign observed for mixtures of n-hexane with ethyl and n-pentyl acetate.
VI. CONCLUDING REMARKS
We have presented the development of the SAFT-γ Mie approach as a reformulation of the SAFT-VR Mie EoS73 within a group contribution formalism, where the interactions between segments are represented by means of the Mie pair potential with variable attractive and repulsive exponents. The molecular model employed for the description of pure substances and mixtures is a fused heteronuclear model. Together with the implementation of the new intermolecular potential, a key novelty of the theory lies in the treatment of the monomeric segment contribution to the free energy, where a third-order perturbation expansion is employed. The performance of the theory in the description of real systems is examined in studies considering two chemical families (the n-alkanes and the n-alkyl esters), where parameters for the methyl, methylene, and carboxylate functional groups (CH3, CH2, and COO) are obtained from fluid-phase behavior data and single-phase densities of the pure components. In the development of the carboxylate group parameters (and the unlike parameters with the n-alkane groups) some data for the excess enthalpies of selected binary mixtures are used, in order to characterize better the nature of the unlike interactions.
The SAFT-γ Mie approach is shown to provide an excellent description of the pure-component properties of the correlated compounds, with average relative errors of 1.19% for the vapor pressure, 0.42% for the saturated liquid density, and 0.45% for the single-phase liquid density. It is also shown that the treatment of the monomer term proposed leads to a significant improvement in the description of the near-critical region compared to the SAFT-γ SW66 formulation.66 In addition to fluid-phase behavior, second-order thermodynamic derivative properties are also considered. The Mie intermolecular potential model employed in the proposed methodology allows for an accurate representation of properties such as the speed of sound, the isochoric and isobaric heat capacities, and the thermal expansion coefficient as shown in detail for the n-alkanes; slightly higher deviations are found for the n-alkyl esters.
The predictive capability of the method is examined in the description of the fluid-phase equilibria and, where available, the derivative properties of high-molecular-weight compounds not included in the estimation of the group parameters. The performance of the SAFT-γ Mie approach is found to be very satisfactory. An examination of the limit of high-molecular-weight polymers confirms the robustness of our methodology and the corresponding group parameters obtained in this work. Finally, the performance of SAFT-γ Mie is examined in the prediction of the fluid-phase behavior and excess properties of binary mixtures of n-alkanes and n-alkanes with n-alkyl esters. The theory is seen to describe accurately the fluid-phase behavior of a variety of systems, for different types of phase equilibria (vapor-liquid and liquid-liquid), over a wide range of conditions, including the high-pressure critical points of the mixtures. The excess and second-order thermodynamic derivative properties of binary mixtures are also very well described. For the mixtures considered, the predictions of the fluid-phase equilibria and excess enthalpy with SAFT-γ Mie compare favorably to the calculations using the well-established modified UNIFAC (Dortmund) GC approach. The description of excess and derivative properties is a challenging task as these are known to be very sensitive to the specific molecular details, and the performance of the SAFT-γ Mie demonstrates the future potential of the theory for the study of other chemical families.
ACKNOWLEDGMENTS
V.P. is very grateful to the Engineering and Physical Sciences Research Council (EPSRC) of the UK for the award of a Ph.D. studentship. T.L. and C.A. thank the Engineering and Physical Sciences Research Council (EPSRC) of the UK for the award of postdoctoral fellowships. Additional funding to the Molecular Systems Engineering Group from the EPSRC (Grant Nos. GR/T17595, GR/N35991, EP/E016340, EP/J003840, and EP/J014958), the Joint Research Equipment Initiative (JREI) (GR/M94426), and the Royal Society-Wolfson Foundation refurbishment scheme is also gratefully acknowledged.
APPENDIX: COMPARISON BETWEEN THE SAFT-γ AND HETERO GC-SAFT-VR TREATMENT OF THE CHAIN TERM
Within a SAFT treatment the contribution due to the formation of molecular chains from monomeric segments is determined from a knowledge of the radial distribution function of the reference monomeric fluid at contact, based on Wertheim's first-order thermodynamic perturbation theory (TPT1).47–50 Such a treatment is straightforward for homonuclear models formed from tangent segments, but, in the case of heteronuclear molecular models formed from fused segments, an alternative treatment is required since the monomeric segments forming the molecular chains may be bonded at different distances.
Different approaches have been suggested for the formulation of the chain contribution within SAFT-type theories based on fused heteronuclear molecular models. In SAFT-γ an effective TPT1 treatment is employed, where the following relation is used for the calculation of the chain term:
The radial distribution function of the reference system of monomers at contact,
where bi, kl denotes the number of bonds between segments k and l on molecule i. It is important to note that both expressions revert to the original treatment of the chain term in the case of homonuclear chains. Equations (A1) and (A2) are written in a general form in terms of the contact value of the radial distribution function; for a given intermolecular potential the RDF can be determined from the Barker-Henderson perturbation theory as shown for the square-well potential in Refs. 66 and 70 and for the Mie potential in Sec. III C.
Here, we examine the performance of the two methodologies presented for the chain term based on comparison with simulation data for square-well and hard-sphere heteronuclear diatomic and triatomic molecules. Though our main interest is in models based on the Mie potential, to our knowledge there are no suitable simulation data for heteronuclear molecules formed from Mie segments. Comparisons of the theoretical treatment with simulation data for heteronuclear SW molecules should however provide a good indication of the adequacy of the approximations made in the generic chain term. A first comparison is shown in Figure 20, where calculations with the SAFT-γ66,67 and the hetero GC-SAFT-VR63,70 treatments of the chain term are compared to the corresponding simulation data for several pressure-density isotherms of a tangentially bonded heteronuclear square-well diatomic fluid with a fixed segment size ratio of σ11 = 0.5 σ22. It should be noted that the only difference between the SAFT-γ SW and the hetero GC-SAFT-VR calculations shown in the plot is the treatment of the chain term; the SAFT-γ theory66,67 is used in both cases for the calculation of the monomer contribution, neglecting the minor differences between the two theories, as discussed in detail in Refs. 24 and 28. In the remainder of our current paper, this “hybrid” theory is referred to as SAFT-γ* to distinguigh it from the original hetero GC-SAFT-VR approach. From the figure it is apparent that both approaches accurately capture the effect of the heteronuclear nature of the diatomic square-well molecule.
It is of further interest to examine how the two approaches perform for heteronuclear dimers with different segment size ratios. Simulation data for pressure-density isotherms for purely repulsive tangentially bonded heteronuclear hard-sphere dimers are compared with the theoretical description in Figure 21. The calculations are performed using the SAFT-γ and SAFT-γ* approaches, disregarding the contributions arising from attractions between monomeric segments. From the comparison, it appears that the predictions of the two methodologies in the description of the thermodynamic properties of the heteronuclear hard-sphere dimer for similar segment sizes are almost indistinguishable. As the segments become more different in size, the SAFT-γ* description is in better agreement with the simulation data, compared to that with the SAFT-γ calculations. However, this is of little consequence in practice as such differences in the segment size (σ11/σ22 ≈ 0.25) would be rather unrealistic when representing real compounds, especially considering the extension of SAFT-γ to treat large chemical groups by means of multiple identical segments.67 The smallest segment size ratio reported in the published SAFT-γ parameter table67 is found for between the hydroxyl OH and carbonyl C=O functional groups with a value of σC = O/σOH ≈ 0.59.
As a final example we consider heteronuclear hard-sphere trimers. A comparison between the SAFT-γ and SAFT-γ* calculations and the corresponding simulation data for the pressure-density isotherms of tangentially bonded heteronuclear hard-sphere trimers with different segment ratios and/or connectivity is shown in Figure 22. It should be noted that in this case, the chain contribution in SAFT-γ* is calculated by explicitly accounting for the connectivity of the monomeric segments to form the molecular chain, while in SAFT-γ the only structural information that is taken into account is the number of occurrences of each monomeric segment. This difference in the description of the molecular chain term is not found, however, to affect the agreement of the theoretical description with the simulation data to a great extent. From this analysis it can be concluded that both approximations for the chain contribution provide a satisfactory description of the thermodynamic behavior of the heteronuclear trimers considered, with the SAFT-γ* approach performing marginally better. The calculation of the chain contribution within SAFT-γ successfully reproduces the thermodynamic properties of heteronuclear molecules, and in that way the heteronuclear nature of the molecular model is retained within the theory at the level of the formation of the molecular chain from distinct monomers. The SAFT-γ treatment is shown to be almost indistinguishable from a SAFT-γ* treatment, apart for extreme differences in the sizes of the segments forming the chain. However, such extreme values are of purely theoretical interest, as highly asymmetric molecular models are not usually expected to be appropriate in the modeling of real fluids. Nevertheless, it should be acknowledged that some isomers are treated differently when Eq. (A2) is used to calculate the chain contribution to the Helmholtz free-energy, whereas their properties would be the same when Eq. (A1) is used.
The comparison made thus far between SAFT-γ and SAFT-γ* is based on simulation data for tangentially bonded heteronuclear models. A full comparison for fused segments is more difficult as an explicit relationship between the degree of overlap and the bond length has to be established. However, an assessment of the two approaches can be made by examining the description of the properties of real compounds. This is undertaken here for the chemical family of n-alkanes, where the description of the SAFT-γ SW approach with the parameters from Ref. 66 is compared with the corresponding results obtained using SAFT-γ*. The SAFT-γ* parameters for the CH3 and CH2 groups are obtained here using the same approach as in previous work,66,67 with the same experimental data. Regarding the parameters, the shape factors for both the CH3 and the CH2 groups are assigned values of 1/3 and 2/3, respectively, while the only unlike parameter which is estimated is the energy of the unlike interaction,
Functional group k . | $\nu _{k}^{*}$
. | Sk . | λkk . | σkk [Å] . | εkk/kB [K] . |
---|---|---|---|---|---|
CH3 | 1 | 0.66667 | 1.4335 | 3.8059 | 244.63 |
CH2 | 1 | 0.33333 | 1.7139 | 3.9959 | 217.74 |
Functional group k . | $\nu _{k}^{*}$
. | Sk . | λkk . | σkk [Å] . | εkk/kB [K] . |
---|---|---|---|---|---|
CH3 | 1 | 0.66667 | 1.4335 | 3.8059 | 244.63 |
CH2 | 1 | 0.33333 | 1.7139 | 3.9959 | 217.74 |
. | . | . | SAFT-γ SW . | SAFT-γ* SW . | SAFT-γ SW . | SAFT-γ* SW . |
---|---|---|---|---|---|---|
Compound . | T range [K] . | n . | %AAD pvap(T) . | %AAD pvap(T) . | %AAD ρsat(T) . | %AAD ρsat(T) . |
C2H6 | 91–270 | 38 | 3.93 | 2.89 | 1.02 | 1.89 |
n-C3H8 | 97–331 | 38 | 4.09 | 6.46 | 0.65 | 1.80 |
n-C4H10 | 139–379 | 38 | 3.44 | 4.81 | 0.55 | 2.06 |
n-C5H12 | 144–417 | 38 | 5.39 | 7.08 | 0.54 | 1.56 |
n-C6H14 | 177–455 | 38 | 3.60 | 4.05 | 0.47 | 1.46 |
n-C7H16 | 191–483 | 37 | 4.09 | 5.08 | 0.51 | 1.46 |
n-C8H18 | 216–512 | 38 | 3.69 | 4.68 | 0.45 | 1.47 |
n-C9H20 | 344–424 | 15 | 3.01 | 6.19 | 0.40 | 0.97 |
n-C10H22 | 243–553 | 63 | 4.63 | 5.22 | 0.52 | 1.38 |
Average | … | … | 3.98 | 5.16 | 0.57 | 1.56 |
. | . | . | SAFT-γ SW . | SAFT-γ* SW . | SAFT-γ SW . | SAFT-γ* SW . |
---|---|---|---|---|---|---|
Compound . | T range [K] . | n . | %AAD pvap(T) . | %AAD pvap(T) . | %AAD ρsat(T) . | %AAD ρsat(T) . |
C2H6 | 91–270 | 38 | 3.93 | 2.89 | 1.02 | 1.89 |
n-C3H8 | 97–331 | 38 | 4.09 | 6.46 | 0.65 | 1.80 |
n-C4H10 | 139–379 | 38 | 3.44 | 4.81 | 0.55 | 2.06 |
n-C5H12 | 144–417 | 38 | 5.39 | 7.08 | 0.54 | 1.56 |
n-C6H14 | 177–455 | 38 | 3.60 | 4.05 | 0.47 | 1.46 |
n-C7H16 | 191–483 | 37 | 4.09 | 5.08 | 0.51 | 1.46 |
n-C8H18 | 216–512 | 38 | 3.69 | 4.68 | 0.45 | 1.47 |
n-C9H20 | 344–424 | 15 | 3.01 | 6.19 | 0.40 | 0.97 |
n-C10H22 | 243–553 | 63 | 4.63 | 5.22 | 0.52 | 1.38 |
Average | … | … | 3.98 | 5.16 | 0.57 | 1.56 |