Article pubs.acs.org/IECR
Estimation of Pure-Component Properties of Biodiesel-Related Components: Fatty Acid Methyl Esters, Fatty Acids, and Triglycerides Thomas Wallek,*,† Jürgen Rarey,‡,§,∥ Jürgen O. Metzger,∥ and Jürgen Gmehling‡,∥ †
Graz University of Technology, Inffeldgasse 25/C/I, 8010 Graz, Austria DDBST GmbH, Marie-Curie-Straße 10, 26129 Oldenburg, Germany § University of KwaZulu-Natal, King George V Avenue, Durban 4041, South Africa ∥ Carl von Ossietzky University of Oldenburg, Carl-von-Ossietzky-Straße 9-11, 26129 Oldenburg, Germany ‡
S Supporting Information *
ABSTRACT: Common group-contribution and corresponding-state models for the estimation of normal boiling points, vapor pressures, liquid densities, and dynamic viscosities are reviewed in view of their application to fatty acid methyl esters, related fatty acids and triglycerides. Because of the limited representation of measured data for triglycerides, three previously published group-contribution models for normal boiling points, vapor pressures, and dynamic viscosities are extended through the introduction of a new group, representing the backbone structure common to all triglycerides and improving the performance of these models significantly. Conclusions are drawn in view of further refinement of the group-contribution approach for application to complex branched molecules.
1. INTRODUCTION Growing interest in non-fossil-fuel components has led to an increased need for physical property data of biodiesel-related components such as fatty acid methyl esters, related fatty acids, and triglycerides. For production, purification, and application as fuel components in a mixture with fossil components, purecomponent properties of these biogenic substances are the basis for engineering calculations. In this context, particularly normal boiling point, vapor pressure, liquid density, and dynamic viscosity are of interest. Because of the great variety of species of esters and, in particular, triglycerides, group-contribution and correspondingstate approaches are methods of choice for the estimation of pure-component properties. Whereas group-contribution methods usually require only knowledge about the molecular structure, corresponding-state methods are based on a very limited number of property values such as the critical point and a vapor pressure value in the vicinity of the normal boiling point and are therefore not truly predictive. Despite the great variety and practical importance of these families of substances, pure-component data are scarce and have been taken into account to a very limited extent for the development of thermodynamic models intended for a broad variety of substances. One of the reasons is that these components are mostly only available as constituents of complex mixtures and are difficult to obtain in pure form. Therefore, mainly specialized approaches have been developed for the estimation of pure-component properties of biodiesel-related substances, and little has been published on model comparisons. Sales-Cruz et al.1 predicted critical properties of fatty acids, fatty acid methyl esters, and triglycerides using groupcontribution approaches and applied them to density and viscosity predictions. Zéberg-Mikkelsen and Stenby2 developed © 2013 American Chemical Society
a group-contribution model for the prediction of melting points and enthalpies of fusion for saturated triglycerides. Ceriani and co-workers3,4 presented a group-contribution model for the estimation of the vapor pressures and heats of vaporization of fatty compounds. This approach was used by Yuan et al.5 for the calculation of Antoine parameters for fatty acid methyl esters. Another vapor pressure group-contribution approach presented by Bokis et al.6 focused on compounds encountered in the fractionation of tall oil. Zong et al.7 developed a chemical constituent fragment-based estimation model for vapor pressures, enthalpies of vaporization, liquid heat capacities, liquid densities, and liquid viscosities of triglycerides. Halvorsen et al.8 reported experimentally regressed parameters for a modified Rackett equation for the estimation of densities of fatty acids and vegetable oils. Krisnangkura et al.9 used an empirical approach for predicting dynamic viscosities of saturated fatty acid methyl esters. Goodrum and Eiteman10 published parameters for the empirical description of densities, viscosities, heat capacities, surface tensions, and vapor pressures of selected triglycerides. Ceriani et al.11 proposed a groupcontribution model for the estimation of viscosities of compounds involved in the vegetable oil industry that was used by Gonçalves et al.12 for the prediction of the mixture behavior of these compounds; an updated model based on an extended database was published subsequently.13 Pratas et al.14,15 evaluated the GCVOL16,17 density model and compared the viscosity model of Ceriani et al.11 to that of Marrero and Gani,18 using measured data for fatty acid methyl and ethyl esters. Rabelo et al.19 proposed an equation for viscosity Received: Revised: Accepted: Published: 16966
August 8, 2013 October 28, 2013 October 28, 2013 November 19, 2013 dx.doi.org/10.1021/ie402591g | Ind. Eng. Chem. Res. 2013, 52, 16966−16978
Industrial & Engineering Chemistry Research
Article
Table 1. Normal Boiling Point Data for Esters and Acids from Data Banks (DDB, Beilstein)
a
fatty acid
component
formula
molar mass
CAS no.
DDB no.
Pmaxa (kPa)
Tbb (K)
C12:0 C14:0 C16:0 C18:0 C18:1 C18:2 C18:3 C20:0 C22:0 C22:1 C12:0 C14:0 C16:0 C18:0 C18:1 C18:2 C18:3
methyl laurate methyl myristate methyl palmitate methyl stearate methyl oleate methyl linoleate methyl linolenate methyl arachidate methyl behenate methyl erucate lauric acid myristic acid palmitic acid stearic acid oleic acid linoleic acid linolenic acid
C13H26O2 C15H30O2 C17H34O2 C19H38O2 C19H36O2 C19H34O2 C19H32O2 C21H42O2 C23H46O2 C23H44O2 C12H24O2 C14H28O2 C16H32O2 C18H36O2 C18H34O2 C18H32O2 C18H30O2
214.3 242.4 270.5 298.5 296.5 294.5 292.5 326.6 354.6 352.6 200.3 228.4 256.4 284.5 282.5 280.5 278.4
111-82-0 124-10-7 112-39-0 112-61-8 112-62-9 112-63-0 301-00-8 1120-28-1 929-77-1 1120-34-9 143-07-7 544-63-8 57-10-3 57-11-4 112-80-1 60-33-3 463-40-1
348 248 253 349 635 340 5323 7088 11400 15014 346 347 239 265 242 2628 2627
102.3 100.1 99.6 99.6 101.3 101.3 101.3 101.3 101.3 101.3 101.3 68.3 34.1 34.1 102.0 NA NA
540.0 568.9 595.2 612.7 617.0 619.2 620.2 642.2 666.2 666.2 571.8 599.3c 624.0c 648.2c 625.3 NA NA
Maximum vapor pressure measured. bNormal boiling temperature. cExtrapolated.
as the respective acids, can be relevant for characterization of biodiesel. Throughout this article, we mention only those substances for which sufficient information is available for model comparison of the respective physical property.] The normal boiling point as a function of molar mass is shown in Figure 1. In this plot, the boiling points of the
estimation for mixtures that incorporates the number of carbon atoms as well as the number of double bonds. Cunico et al.20 reviewed the application of the Marrero and Gani18 model to lipids, using model parameters from Hukkerikar et al.21 as well as lipid-specific parameters. Díaz-Tovar et al.22 estimated a variety of pure-component properties for edible oils and biodiesel-related compounds, based on the approaches of Ceriani et al.11 and Marrero and Gani18 and their respective extensions. Su et al.23 provided a broad-based review of prediction methods for thermophysical properties of biodieselrelated substances. In this work, broadly available experimental information mainly from the Dortmund Data Bank (DDB)24,25 is used to verify the applicability of established, nonspecialized models to biodiesel-related data and to extend these models where required.
2. FATTY ACID METHYL ESTERS AND FATTY ACIDS 2.1. Normal Boiling Point. Available normal boiling point information from the DDB and the Beilstein/Reaxys26 data bank employed for the comparison with thermodynamic models is summarized in Table 1. The nomenclature “Cm:n” characterizes a fatty acid as well as the associated methyl ester by the number of carbon atoms m and the number of double bonds n of the fatty acid. All double bonds are cis-configured in the examples considered. The values were partly measured and partly extrapolated from low-pressure vapor−liquid equilibrium (VLE) data. For two of the unsaturated acids, C18:2 and C18:3, however, no experimental data are available; extrapolation from low-pressure data for these components was avoided because of the very low values of the pressures measured. We note that the substances compiled in Table 1 do not represent the whole bandwidth of components found in biodiesel; rather, they represent those for which sufficient information about normal boiling point and vapor pressure is available for the purpose of model comparison. [Specifically, in addition to the substances listed in Table 1, C16:1 (methyl palmitoleate, C17H32O2, CAS no. 1120-25-8), C20:1 (methyl cis-11-eicosenoate, C21H40O2, CAS no. 2390-09-2), C24:0 (methyl tetracosanoate, C25H50O2, CAS no. 2442-49-1), and C24:1 (methyl cis-15-tetracosenoate, C25H48O2, CAS no. 2733-88-2), as well
Figure 1. Normal boiling points of esters and acids as a function of molar mass. Saturated compounds essentially show linear trends (R2 = 0.9967 for esters and R2 = 0.999 for acids).
saturated components show a slightly curved, nearly linear characteristic, as is known from other homologous series,30 and an increase (esters) or decrease (acids) with increasing degree of unsaturation (number of C−C double bonds). The decrease with unsaturation for acids corresponds to the behavior of alkenes/alkanes, comparing substances with the same carbon number with or without a double bond.27 For esters, Graboski and McCormick28 reported the normal boiling temperatures for C18:0 and C18:1 in a synoptical table, reporting a lower value for C18:1 than C18:0. We used the data set of Krop et al.,29 who reported increasing boiling temperatures with increasing degree of unsaturation for C18 16967
dx.doi.org/10.1021/ie402591g | Ind. Eng. Chem. Res. 2013, 52, 16966−16978
Industrial & Engineering Chemistry Research
Article
Table 2. Selected Models for Normal Boiling Point Estimation
a
input dataa
model
abbreviation
method
Cordes/Rarey Nannoolal/Rarey/Ramjugernath/Cordes Constantinou/Gani Stein/Brown Marrero-Morejón/Pardillo-Fontdevila Marrero/Gani Ericksen/Wilding/Oscarson/Rowley Joback/Reid Lee/Kesler
CR NR CG SB MP MG EW JR LK
group contribution group contribution group contribution group contribution group contribution group contribution group contribution group contribution corresponding state
molecular molecular molecular molecular molecular molecular molecular molecular Tc, Pc, ω
structure structure structure structure structure, molar mass structure structure, UNIQUAC r, van der Waals volume structure
ref 30 31 32 33 34 18 35 36 37
Tc, critical temperature; Pc, critical pressure; ω, acentric factor.
2.2. Vapor Pressure. A set of 818 data points from the DDB and Beilstein/Reaxys data bank was used for model comparison. As can be seen in Table 5, most measurements were conducted at very low pressures, more than 90% in the range
