Cold Flow Properties of Fatty Acid Methyl Ester ... - ACS Publications

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Cold Flow Properties Of Fatty Acid Methyl Ester Blends With and Without Triacetin Rachel Cassidy Elias, Michael Senra, and Lindsay Soh Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b01334 • Publication Date (Web): 24 Aug 2016 Downloaded from http://pubs.acs.org on August 30, 2016

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Cold Flow Properties of Fatty Acid Methyl Ester Blends With and Without Triacetin Rachel C. Elias, Michael Senra,* Lindsay Soh* Lafayette College, Department of Chemical and Biomolecular Engineering, 740 High Street, Easton, PA, 18042 KEYWORDS: cloud point, melting point, biodiesel, DSC, fuel additive

Abstract: Optimizing the cold flow properties of biodiesel is pertinent to its applicability as an alternative to conventional petrodiesel products. This work provides a systematic study of specific cold flow properties of binary blends of fatty acid methyl esters (FAME) and cold flow improver, triacetin. Cloud point, melting point, and heat of crystallization of various blends of FAME and triacetin were analyzed to further understand the molecular interactions affecting crystallization. Cloud point analysis revealed trends based on FAME and additive composition. Generally, the cloud point of pure FAME decreased with decreasing carbon number and increasing degree of unsaturation. The use of triacetin, a potential fuel component, as a cloud point depressant was also investigated for pure component and binary FAME fuel blends. The addition of triacetin depressed the cloud point up to 2.7 K in proportions of up to 20 wt%. Thermodynamic analysis and predictive modeling revealed the effect of component cocrystallization on the cloud point of a mixture. The role of triacetin in reducing a mixture’s cloud point appears to be caused by its functioning as a diluent rather than as a crystal modifier. As such, the

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presence of triacetin can moderately improve the cold flow behavior of biodiesel blends, indicating that triacetin may be a promising biodiesel component.

1. Introduction The development of alternative energy sources has become critical to addressing the limitations of fossil fuels.1 Biodiesel – commonly consisting of fatty acid methyl esters (FAME) derived from vegetable oils, animal fats, and similar feedstocks – is an alternative that can be used both as a direct drop-in substitute to conventional diesel fuel or as a miscible petrodiesel additive.2, 3 Today, its use is further incentivized by environmental benefits such as improved emissions (CO2, particulate matter, and sulfur), lower toxicity, and biodegradability (though the degradation products have environmental implications themselves and warrant further investigation).4, 5 In terms of fuel properties, biodiesel demonstrates higher cetane number and lubricity compared to petroleumderived diesel.6-8 Domestic production of biodiesel has been pursued as a means of achieving energy independence.9 Currently, biodiesel is commonly blended with petrodiesel to allow for integration within the current diesel infrastructure.10, 11 B20 (20% biodiesel in petrodiesel) blends have been shown to reduce life cycle petroleum consumption by 19%.12 However, several implementation-related disadvantages hinder the broad adoption of biodiesel as an alternative fuel source. These shortcomings include the high resource and economic costs of feedstock growth, generally poor oxidative stability, and lower energy content and higher NOx emissions than petrodiesel.13 Some of these issues may be addressed by utilizing specific biodiesel feedstocks with preferred FAME profiles and


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assuming better combustion practices, i.e. exhaust gas recirculation and selective catalytic reduction.13, 14 A major disadvantage of biodiesel is its relatively poor cold flow performance, which reduces its feasibility as a dependable fuel source, especially for transportation applications in cold weather environments.8 Exposure to cold temperatures can cause crystal nucleation and the solidification of the saturated FAME2 – occurrences that may result in clogged pipelines and fuel filters.7, 15 These wax crystals begin to develop at a mixture’s cloud point, the temperature at which crystals of diameter at or above 0.5 µm are created.16 The cloud point is a common measurement used to represent cold flow behavior of fuels, and varies depending on the chemical composition. Several methodologies exist for cloud point determination. Commonly used methods include visual observation, differential scanning calorimetry, and cloud point meters that function via transmission of light through fuel samples.17, 18 Currently, cloud points for biodiesel are on average 15–20 K higher than for conventional diesel fuels. Biodiesel cloud point is a strong function of the FAME composition, which is highly dependent on the feedstock type.7,19 Several studies have shown that blending biodiesel from multiple fuel feedstocks may enhance cold flow properties of the fuel.20-23 In order to improve the feasibility of biodiesel use, cold flow properties can be optimized via adjusting the FAME profile2, 24 and using additives.11 For example, long-chain and saturated FAME tend to crystallize at a higher temperature compared to their shorter chain and/or unsaturated counterparts, causing an elevation in the overall mixture’s cloud point.7, 8 In order to better understand the behavior of biodiesel blends, the cold flow properties of individual FAME and simple FAME interactions have previously been


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analyzed.22,25 These works used pure FAME to produce controlled blends for systematic investigation of FAME structure on cold flow properties. Knothe and Dunn have developed a rigorous set of melting point data for pure fatty acids and esters of different chain lengths.25 Imahara et al. contributed a methodical study on the cloud point behavior of several common FAME compounds in binary blends, and created a thermodynamic model to describe the cold flow behavior.24 The model could potentially be used to predict the cloud points of FAME mixtures and optimize biodiesel compositions for cold flow properties. However, the literature is overall quite sparse in the area of raw melting and cloud point data for binary blends of pure component FAME and the effect of additives on the cold flow properties of biofuels. A more rigorous quantitative study of cloud point trends for pure component FAME would aid in understanding FAME interactions during crystallization and enable the characterization of cold flow behavior in multi-component biodiesel fuels. In addition to careful FAME selection, fuel additives may be used to enhance biodiesel cold flow properties. Fuel additives are typically designed to modify crystal structure in ways that alter size and shape of wax crystals.16 Some additives deter nucleation, crystal-crystal adhesion, and/or crystal agglomeration by forcing initial cocrystallization of paraffin molecules and additives.15 Current incorporation of additives intended to enhance cold flow properties of petrodiesel have seen limited success when used with biodiesel.8, 26 While pour point improvements of biodiesel have occurred upon introduction of petrodiesel cloud point improvers, the cloud point is not significantly modified.26 This occurs because these additives were designed to inhibit alkane crystal agglomeration rather than disrupt crystal formation of FAME-like molecules.8 It should


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be noted that the modes of action of these additives are wide-ranging, and include crystal modification via cocrystallization, nucleation, adsorption, and increasing the solubility of the waxes in the solvent.27 Crystal modification often leads to the formation of smaller crystals that are less capable of forming the volume-spanning networks that are necessary to form gels. In many cases, the action of the additive is oil (composition) specific, greatly impacting the cold flow properties of one oil, but having no or deleterious effects on the cold flow properties of other oils.28 Although multiple biodiesel additives have been developed and studied for their quantitative impact on cold flow properties, few have seen fruition for cloud point depression.8, 16, 29 Many of these additive compounds are polymeric in nature, which function by modifying crystal morphology in a way that limits crystal agglomeration. However, these types of additives do not inhibit nucleation.30 Industrial additives include OS-110050, Bio-Flow 870, Bio Flow-875, and Diesel Fuel Anti-Gel.16 However, for these additives, no analysis could be found with respect to cloud point behavior when introduced to pure component FAME blends. A potential additive, triacetin, has been explored as a cold flow enhancer for biodiesel fuels with potential to improve or maintain other fuel properties.31 Triacetin is characterized by a low cloud point, with crystallization onset temperatures as low as -78°C without a seed, and as high as 3.2°C with a seed.32 Triacetin has also been shown to exhibit positive properties in petrofuels, providing enhanced anti-knocking performance in gasoline.33 Specific to biodiesel, triacetin has an added advantage in that it is formed in particular biodiesel production reaction pathways.34 Currently, biodiesel is typically produced via the transesterification of


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triglycerides with methanol to yield FAME and a crude glycerol byproduct. Although pure glycerol has a large market as a humectant in several industries including the production of cosmetics and pharmaceuticals, excessive crude glycerol production has led to market saturation, leading to its low economic value.23, 34-36 Since glycerol is immiscible with FAME, several removal and purification steps are required to increase its utility.23 The interesterification of triglycerides with methyl acetate, as presented in Figure 1, can be implemented to yield FAME alongside triacetin as a byproduct instead of glycerol. This allows for in situ production of triacetin and potentially reduces the energy input required for byproduct refining.1 Furthermore, direct use of this co-product in the fuel mix could improve effective fuel yields compared to conventional transesterification due to the utility as fuel component.10 It is worth noting that while ASTM D6751 guidelines impose no restrictions on a triacetin composition of 20% in biofuels, EN 14214 would restrict triacetin concentration to 10% by weight in biodiesel fuels if its properties were considered different than those of traditional FAME.31 While triacetin has been shown to improve certain fuel properties, its effect on cold flow properties of FAME is largely un-quantified. This research aims to improve understanding of biodiesel cold flow properties based on FAME structure and composition. The cloud point, melting point, and enthalpy of crystallization of fabricated FAME blends were systematically evaluated with emphasis placed on cloud point analysis. The use of triacetin as a potential cold flow enhancer was tested to ascertain the feasibility of using this possible co-product in biodiesel blends. A thermodynamic model was also utilized to determine the effects of cocrystallization on biodiesel blends both with and without triacetin.


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2. Materials and Methods A matrix of fuel blends was created for analysis via differential scanning calorimetry (DSC). Testing was completed using standard aluminum sample pans obtained from TA Instruments. All initial samples were composed of single or binary FAME blends consisting of methyl myristate (C14:0 , >99%, Sigma Aldrich), methyl palmitate (C16:0 , >99%, Sigma Aldrich),, methyl stearate (C18:0 , >99%, Sigma Aldrich), methyl oleate (C18:1 , >99%, Sigma Aldrich), and methyl linoleate (C18:2 , >99%, Sigma Aldrich). Non-additive samples were composed of either a single pure FAME or binary FAME mixtures of 25:75, 50:50, and 75:25 mass ratio blends. Additionally, binary FAME mixtures (1:1 mass ratio) blended with 10 wt% and 20 wt% triacetin (>99%, Sigma Aldrich), were tested. Binary and ternary samples were briefly heated to a temperature that would allow for phase continuity without disturbing the chemical integrity of the sample. These samples were vortexed, reheated, and re-vortexed before transferred to an aluminum DSC sample pan. Preheated Pasteur pipettes were used for all sample transfer, in order to prevent premature crystallization upon contact with the pipette. All final sample masses in the aluminum pans were recorded. Each sample was performed in experimental duplicate, with analytical duplicates randomly being completed to ensure consistency of DSC performance. Cloud point, melting point, heat of crystallization and heat of melting were analyzed using a TA Instruments DSC 2920. The DSC was calibrated using deionized water, as suggested in the work by Knothe and Dunn because of the low phase transition temperatures observed with FAME.25 To mitigate the effects of cooling rate on the data,


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the melting point onset was utilized for analysis. Six calibration trials for water yielded a melting point onset of 272.8K (-0.3°C) with a standard deviation of 0.2K. Samples were first equilibrated to 10-20 K above the estimated cloud point. They were held isothermally for 10 minutes, before being ramped at 5 K/min to a temperature significantly below the anticipated completion of the phase transition. Samples were equilibrated at this temperature, held isothermally for 10 minutes, and then ramped at 5 K/min to a temperature significantly above the anticipated melting point to once again allow for completion of the phase transition. Thermodynamic analysis was primarily completed using the cloud point. The cloud point of a solution occurs at the onset of thermodynamic solid-liquid equilibrium; as such, a focus on the cloud point as a quantitative cold flow metric allowed data and results to be made compatible with Imahara’s model. Additionally, the cloud point is a feature of interest because the presence of solid-liquid multiphase flow in engines can be very problematic. Traces were created automatically via Thermal AdvantageTM software, and data analysis was completed using TA Universal Analysis. Cloud point was obtained at the location at which heat flow began to change upon cooling. The melting point was defined as the onset of the highest temperature peak as determined by the Universal Analysis software. For samples that experienced cocrystallization, the melting point was defined as the onset of the merged peak. 2.1 Modeling Methodology Imahara et al. developed a thermodynamic model intended to predict cloud point data for binary biodiesel fuel blends based on solid-liquid equilibrium. Results for saturated-unsaturated blends indicated that the cloud point of biodiesel was a function of


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the saturated FAME rather than the unsaturated FAME.24 This is a result of the significantly higher cloud point values of saturated FAME in comparison to unsaturated FAME of similar carbon numbers. Equation 1 from Imahara et al. is dictated by thermodynamic theory24, 37 and is shown below: ಽ ௙••

݈݊

ೄ ೔ ௙

where, ݂௜ is the fugacity of i in the liquid or solid phase, Δ‫ܪ‬௠,௜ is the enthalpy of melting in kJ/mol, ܶ௠,௜ is melting temperature in K, and Δ‫ܥ‬௜ is the heat capacity change i between liquid and solid in kJ/ mol K. Assumptions were made by Imahara et al. to simplify Equation 1: 1) ‫ܥ‬௜ is relatively constant, meaning that the Δ‫ܥ‬௜ term can be neglected; 2) The solution is assumed to be ideal, yielding a liquid phase activity coefficient of unity; 3) The seed crystal is a single component, which means that the solid phase activity coefficient and mole fraction are both unity. Utilizing these assumptions, Equation 1 can be simplified and rearranged to yield Equation 2. ܶ= ଵି

்೘,೔ ೃ೅೘,೔ ౴ಹ೘,೔

(2) ௟௡௫೔

Equation 2 was used to predict the cloud points of a solution, provided the experimental cloud point, the enthalpy of melting, and the mole fraction of species i, ‫ݔ‬௜ . Because of assumption 3, this equation incorporates the mole fraction of the component in the blend with the highest cloud point. Experimental cloud points were compared to theoretical values, which were produced via the ideal solution theory model in Equation 2.


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3. Results and Discussion 3.1 Analysis of Additive-Free FAME Samples In order to ascertain the effects of FAME structure (i.e. chain length and degree of unsaturation) on cold flow properties, data was initially obtained for pure component and binary FAME blends. The cloud points for saturated FAME (C14:0, C16:0, and C18:0) and unsaturated analogs (C18:1 and C18:2) were analyzed to establish the trends for chain length and degree of unsaturation. 3.1.1 Saturated-Saturated FAME Samples DSC results for saturated FAME blends are presented in Table 1. Cloud point and melting point data for single FAME species were consistent with existing literature,24, 25 as well as manufacturer information. In general, as chain length increased, cloud point and melting point increased. For example, comparing the effect of alkyl chain length, cloud point decreased 10.2 K between C18:0 and C16:0, and 10.7 K between C16:0 and C14:0. Binary saturated mixtures were also analyzed and the observed cloud points were compared to those predicted via the thermodynamic model in Section 2.1.Values coincided with those found in literature.24 As expected, increasing the percentage of the lower cloud point FAME generally decreases the mixture cloud point, however an exception exists in saturated-saturated blends, when the fraction of the lower cloud point FAME becomes high enough to surpass the eutectic point of the blend cloud point. This trend indicates the importance of incorporating solution characteristics when modeling the transition of biodiesel from a purely liquid system to a liquid containing solid crystals. Table 1 also shows the differences between the experimentally and theoretically


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determined cloud points, indicating deviations from ideal solution theory. Further analysis of this finding is discussed in Section 3.3. 3.1.2 Saturated-Unsaturated FAME Samples Table 2 details results for saturated-unsaturated blends. Data for both pure methyl linoleate (C18:2) and binary unsaturated FAME blends could not be studied because the cloud points of these materials were generally below the reproducible DSC detection limit (DL) of approximately 238K. Cloud point and melting point temperatures were verified with existing studies and followed expected cold flow trends with respect to molecule chain length and degree of unsaturation.9, 24, 38 Comparing C18:0 and its monounsaturated counterpart C18:1 indicates that adding a degree of unsaturation leads to a 69.0 K decrease in observed cloud point. This result indicates that changes in the degree of unsaturation have a much greater effect on cloud point than changes in the carbon number. Figure 2 illustrates the resulting cloud point and melting point onset temperature trends dictated by saturated and saturated-unsaturated behavior for binary blends. For saturated FAME (Figures 2A and 2B), as the weight percent of the shorter FAME is increased, cloud point and melting point pass through a minimum, indicating the presence of a eutectic point. The presence of a eutectic point is an indication of interaction effects between the components present in the solution. These effects suggest that these mixtures deviate from ideal solution theory. Practically, the presence of a eutectic point provides an opportunity to optimize a fuel blend in order to minimize the cloud point of formulated biodiesel.


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Binary blends of saturated-unsaturated FAME (Figures 2C and 2D) lacked a eutectic point. This finding is consistent with existing literature, which indicate that eutectic points only develop for blends containing FAME with pure component melting points within 30 K of one another.39 Generally, cloud point and melting point values decreased with only 25% addition of an unsaturated compound. This decrease can be explained by the saturated material crystallizing in a solution of the unsaturated material, which influences the mechanism by which crystallization occurs.

3.2 FAME Samples with Triacetin Triacetin was added to pure component FAME and the aforementioned binary FAME mixtures to assess its impact on cold flow properties. 10 and 20 wt% of triacetin was added to pure FAME and binary, equal mass blends of saturated and saturatedunsaturated components. 20 wt% represents the highest possible yield of triacetin via the interesterification reaction for biodiesel production. 3.2.1 Phase Transition Temperatures with Triacetin The addition of triacetin depressed cloud point up to 2.7 K in proportions of up to 20 wt% (Table 3). Melting point onset temperatures similarly decreased with the addition of triacetin; however, these values tended to fluctuate more so than corresponding experimental cloud points. Practically, the fact that triacetin does not negatively impact the cloud point is important, because of its ability to impart anti-knocking properties to biodiesel.33 These results indicate that co-production of triacetin during interesterification can potentially enhance cold flow properties while also increasing fuel yields and reducing separation costs.


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The addition of triacetin depressed the cloud points of saturated FAME blends (Table 4). In general, both binary saturated blends and pure FAME blended with triacetin experienced similar cloud point depression. Samples tended to experience a larger drop in cloud point upon the addition of 10% triacetin, and a smaller decrease when triacetin was increased to 20% by mass. This trend did not, however, hold true for C14:0 and C18:0 , which saw only a 0.1 K and 0.7 K decrease, respectively. The concept that additive increases become incrementally less advantageous and that additives will act differently for mondisperse and polydisperse systems is consistent with findings in the inhibitor literature for cold flow properties for n-alkane waxes in analyzing petroleum systems.40 These effects are generally accepted to be related to a change in crystal morphology and/or growth kinetics.41, 42 3.2.2 Analysis of DSC Traces Further insight into the behavior of FAME, both with and without triacetin can be gained by analyzing the relevant DSC traces. An example of a comparison presented in Figure 3 shows the DSC traces for binary blends of varying compositions of C16:0 and C18:0 , with and without triacetin. Figure 3A corroborates the presence of the eutectic point, as noted in Table 1. The peak locations and areas provide additional information concerning the interactions between C16:0 and C18:0 . If the materials crystallized independently of one another, the DSC traces would consist of two relatively sharp peaks, representing the two distinct FAME. Depending on the relative concentrations, it would be possible for these two peaks to show some degree of overlap. A cloud point shift would occur if crystallization converted from pure component melt crystallization to crystallization out of solution in the blend. Additionally, if no cocrystallization occurred,


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the areas under the peaks would be approximately equal to the ratio of the presence of C16:0 and C18:0 because these molecules have reasonably similar enthalpies. The fact that the cloud point peaks overlap and show a shift in value as well as area indicates the occurrence of cocrystallization. It should also be noted that the amount of material that cocrystallizes is not constant, and is a function of composition. For example, the area under the second peak for the 50:50 C16:0 and C18:0 sample and the 75:25 C16:0 and C18:0 sample are similar. If the magnitude of cocrystallization were unchanged, it would be expected that the second peak for the 75:25 solution would be significantly larger than the 50:50 solution. Cocrystallization can occur when two molecules that are similar in chemical formulation, molecular size, and crystal shape are present in the same solution.43 During cocrystallization, the longer molecule will bend to associate with the shorter molecule to form a shared crystal structure.44 The fact that there are two peaks present in Figure 3A indicates that the C18:0 present in solution was unable to accommodate all of the C16:0 in its crystal structure. The broadness of the secondary peak (in comparison to the relative sharpness of the monodisperse systems) is indicative of heterogeneous nucleation and crystallization, wherein the more soluble material is using crystals that have already formed to catalyze its own precipitation from solution. Although cocrystallization was evident in the saturated-saturated blends, it did not occur for the saturated-unsaturated blends. Thus, the presence of the double bond caused a sufficient change in the molecule, most notably from a thermodynamic standpoint, to prevent the saturated and unsaturated FAME from cocrystallizing.


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Additionally, the DSC traces reveal that binary mixtures experienced slight decreases in enthalpy change, as evidenced by the smaller areas under each curve for these peaks. This reduction is likely due to lower enthalpies associated with mixing. This trend was expected, as cocrystallization of species is known to impact the heat released in these systems.45 3.2.3 Saturated-Unsaturated Blends with Triacetin DSC phase transition data for saturated-unsaturated blends mixed with triacetin is provided in Table 5. The results indicate that the addition of triacetin has a slight to negligible effect on the melting point and cloud point of the saturated-unsaturated blends. The addition of triacetin had a greater influence on the cloud point for C18:0 and C18:1 blends than for C18:0 and C18:2 blends, where the addition of triacetin had negligible effect on the cloud point. Furthermore, the effect of triacetin on the cloud point of saturated-unsaturated blends was less than the effect on saturated-saturated blends. This observation is attributed to the occurrence of cocrystallization within saturated-saturated blends. Similarly to the saturated-saturated blends, the impact of triacetin on cloud point decreases at higher concentrations.

3.3 Assessment of Model Parity plots comparing the experimental cloud points found using DSC with the theoretical cloud points predicted by Equation 2 are provided in Figure 4. Data points that fall on or close to the line indicate that the solution closely obeys ideal solution theory, whereas points that deviate from the line indicate that the solution does not follow ideal solution theory. It is clear that the saturated blends both with and without triacetin deviate


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more from ideal solution theory than the saturated-unsaturated blends. This deviation can be explained by the occurrence of cocrystallization in the saturated blends. Percent errors were calculated between average experimentally observed and theoretical cloud point values. It should be noted that for the model proposed by Imahara, the seed crystal is assumed to be a pure component.24 For systems where the least soluble material (the first to crystallize out of solution) is capable of cocrystallizing, this assumption is not valid. For FAME mixtures without triacetin, percent error increased as the fraction of lower cloud point FAME increased. This result would be consistent with the idea of a larger degree of cocrystallization occurring when there is more of the shorter, more soluble material present in solution, a result that is corroborated by the DSC traces. The highest percent error for saturated blends was 2.5% for a 25:75 blend of C18:0 and C14:0. As there is co-crystallization between C14:0 and C18:0 it is expected that the system would deviate from ideal solution theory, and this deviation would be greater than for mixtures such as C18:0 and C16:0 or C16:0 and C14:0 as the molecular length difference between C14:0 and C18:0 is larger. In binary saturated-unsaturated blends the highest percent error, 1%, was evidenced for a 25:75 blend of C18:0 and C18:1. In all samples in Table 2, the theoretical model overpredicted the experimentally obtained values. For samples with triacetin, single component blends did not appreciably increase the percent error between the experimental data and the model. The percent error between experimentally and theoretically obtained cloud points for these trials never exceeded 0.3%. The percent errors did not increase as triacetin concentration increased, indicating that the addition of triacetin does not change the fact that the system is acting as an ideal


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solution. This finding implies that triacetin’s effect in reducing the cloud point is caused more by its action as a diluent rather than its role as a crystal modifier. The highest deviation from ideal solution theory occurred with blends containing C14:0, C18:0, and triacetin, however as the fraction of triacetin increased, the deviation lessened. As noted earlier, cocrystallization between C14:0 and C18:0 led to the largest deviation from the model assumptions. With triacetin, because C14:0 is the most similar to triacetin in molecular length of all the components analyzed one may expect interactions between these two components to be the greatest, potentially decreasing interactions between C14:0, C18:0. Nevertheless , the highest percent error obtained was only 2.2%, indicating only a minor deviation from the predictive model. For saturatedunsaturated blends with triacetin, percent errors generally decreased as the weight percentage of triacetin increased. When triacetin was introduced at 20% by weight into both of these saturated-unsaturated blends, percent error decreased to 0.1% for both binary blends with unsaturated compounds, indicating that the saturated-unsaturatedtriacetin solution acted as an ideal solution.

3.4 Enthalpy of Crystallization The effect of cocrystallization on the enthalpy of crystallization was also analyzed by comparing normalized enthalpy values between pure and mixed samples of FAME. If cocrystallization or polydispersity had no impact on the enthalpy crystallization, then the enthalpy of crystallization would be a simple weighted average of the enthalpy of crystallization of the individual components. It was hypothesized that samples that experienced cocrystallization would see a larger deviation from the weighted average


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enthalpy of crystallization than systems where cocrystallization did not occur. Enthalpy values of binary blends of equal mass composition were normalized per mole of the higher cloud point compound. For example, the enthalpy of a 50:50 blend of C16:0 and C18:0 was normalized per mole of C18:0 . This value was compared to the enthalpy obtained from a pure sample of C18:0. When the enthalpies of these normalized binary saturated FAME blends were compared to those of the pure components, it was shown (Tables 6 and 7) that the enthalpy of crystallization decreases, which indicates that cocrystallization reduces the amount of energy that needs to be removed for crystals to form. This result is consistent with work done with long chained n-alkanes crystallizing out of solution.45 Tables 6 and 7 also clearly show that cocrystallization occurred. If cocrystallization did not occur, then the enthalpy of crystallization from the primary peak at the highest temperature would be quite similar to the value of the longer component. However, the enthalpy of crystallization was also noticeably higher, indicating that more than one material cocrystallized. Analysis of samples containing triacetin may also provide insight to the role of the additive on the enthalpy values. Enthalpies of pure component FAME blended with triacetin at 10 and 20% by mass were normalized per mole of FAME. These values were compared with those of the pure component FAME samples. Generally, the amount of triacetin added imparted minimal deviation from the ideal enthalpy of crystallization. The largest deviation was observed when the molar enthalpy values of C18:0 with 20% triacetin normalized per mole of C18:0 was compared to those enthalpies of pure C18:0 . Here, an enthalpy difference of just under 8 kJ/mol (11%) was observed. This result


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suggests that triacetin does not greatly influence how the single component crystallizes out of solution. This finding was applicable for C14:0 and triacetin samples, since C14:0 and triacetin are similar enough to allow for cocrystallization. In fact, a smaller difference existed between the enthalpy values for C14:0 with and without triacetin. This finding likely indicates that any discrepancies between enthalpy values of pure components and binary FAME/triacetin blends can be attributed to experimental and/or analytical error. Enthalpies of blends of saturated FAME with triacetin were also normalized per mole of FAME (Table 7). These enthalpy values were compared with the corresponding blends without triacetin. It should be noted that the enthalpy of crystallization exhibited an increasing trend for the C16:0 and C14:0 trial as well as the C18:0 and C14:0 trial, but a decreasing trend for the C18:0 and C16:0 trial. This finding would indicate that although triacetin does not influence the system with C14:0 by itself, it seems to have a marked impact when C14:0 is capable of cocrystallizing with other components. A potential explanation could be triacetin’s ability to heterogeneously nucleate on the cocrystal, causing it to crystallize out of solution. Similar analysis was completed with saturated-unsaturated blends with triacetin, as seen in Table 8. In general, the enthalpy values as triacetin was increased did not appreciably change, likely indicating that triacetin did not influence the saturatedunsaturated blend in any significant way.

4. Conclusions Cold flow properties were analyzed for their dependence on interactions between each fuel blend component in model biodiesel systems. Cocrystallization was evidenced


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in binary blends where the constituent FAME had similar structure (i.e. chain length and degree of unsaturation). In binary saturated blends, the lower cloud point component had a greater impact on the cloud point than what would be predicted from normalizing the cloud points of the individual components. This result is caused by the fact that the least soluble (higher cloud point) material crystallized from solution instead of from the melt. As the difference in carbon number for each component decreased, the cloud point experienced a larger deviation toward the component with the lower cloud point. For binary saturatedunsaturated blends the cloud point was dictated by the component with the higher cloud point. It can be concluded that triacetin does not negatively affect cloud point and can depress the cloud point of biodiesel depending on the FAME constituents. Most blends experienced the largest drop in cloud point between the addition of 0% to 10 wt% triacetin, and a smaller drop in cloud point after the addition of another 10 wt%. These results indicate that triacetin may be a promising biodiesel additive when incorporated at levels at or below 20% by mass, depending on specific fuel composition. Biodiesel blends have the potential to provide a fuel source that may eventually be viable in cold climate applications. The results of this study indicate that triacetin behaves similarly to FAME compounds when introduced into biodiesel blends, and that the temperature could be predicted via the model referenced from Imahara et al.24 Triacetin’s adherence to ideal solution theory indicates that the cloud point depression seen with the addition of triacetin is more of a function of it acting as a diluent versus a crystal modifier. Additives like triacetin, which offer attractive qualities including


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miscibility and easy co-production through interesterification, could prove relevant to the engineering of usable biodiesel. It is possible that other additives of structure similar to triacetin may also affect cloud point trends in a similar manner, which may be modeled as outlined in this work. The continued study of pure component FAME blends may prove useful to determining the cold flow behavior of biodiesel from a variety of triglyceride feedstocks. These more complex blends can be appropriately blended to optimize cold flow properties as suggested for other properties.19 Furthermore, conversion and fractionation processes can be used to enrich FAME blends for desirable components so as to produce biodiesel with appropriate fuel properties.46, 47 Referencing the pure FAME and binary blend FAME cloud point data obtained in this work may be useful to carefully engineer biodiesel blends, with or without additives, that perform well in cold weather environments.

AUTHOR INFORMATION Corresponding Authors: Michael Senra, [email protected]; Lindsay Soh, [email protected] Author Contributions: The manuscript was written through contribution of all authors. All authors have approved the final version of the manuscript.

ACKNOWLEDGMENTS: The authors thank Professor Kenneth Haug and the Department of Chemistry at Lafayette College for providing access to the DSC. Patrick Leggieri, Rebecca Miller, Stephanie McCartney and David Woods contributed to some 21 ACS Paragon Plus Environment

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sample testing. The authors are grateful to the William T. Morris Foundation as well as the Lafayette College EXCEL Scholar Program for helping to fund the work. This publication was developed under GRO Fellowship Assistance Agreement no. MA91775901-0 awarded by the U.S. Environmental Protection Agency (EPA). It has not been formally reviewed by EPA. The views expressed in this publication are solely those of authors, and EPA does not endorse any products or commercial services mentioned in this publication. Dr. Soh also receives funding from NSF award #152432.


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Figure 1. Schematic of the interesterification reaction for biodiesel synthesis

Figure 2. Cloud point ( ) and melting point onset temperatures ( ) for saturated and saturated-unsaturated blends with methyl stearate - (A) binary blends of C14:0 in C18:0, (B) binary blends of C16:0 in C18:0, (C) binary blends of C18:1 in C18:0, (D) binary blends of C18:2 in C18:0). represents a cloud point temperature obtained from Imahara24, and represents a melting point onset temperature obtained from Knothe and Dunn.25, Error bars represent the variance between experimental duplicates. 23 ACS Paragon Plus Environment

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Figure 3. DSC traces of C16:0 and C18:0 binary blends (A) without triacetin, and (B) with triacetin


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Figure 4. Parity plots for (A) saturated blends, (B) saturated-unsaturated blends, (C) saturated blends with triacetin, (D) saturated-unsaturated blends with triacetin


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Table 1. DSC data for saturated binary blends C14:0 C16:0 C18:0 Experimental (wt. %) (wt. %) (wt. %) Melting Point (K) 100 289.8 +/- 0.6 75 25 283.2 +/- 0.1 50 50 282.6 +/- 0.0 25 75 282.8 +/- 0.1 100 300.3 +/- 0.2 100 75 50 25

100 75 50 25

Experimental Cloud Point (K) 286.3 +/- 0.2 280.8 +/- 0.4 285.6 +/- 0.3 290.4 +/- 0.6 297.0 +/- 0.1

Theoretical Cloud Point (K)a 286.3 +/- 0.2 280.4 +/- 7.3 288.4 +/- 3.9 293.4 +/- 1.7 297.0 +/- 0.1

25 50 75 100

289.8 +/- 0.6 283.9 +/- 0.1 283.7 +/- 0.6 283.7 +/- 0.1 309.6 +/- 0.0

286.3 +/- 0.2 284.4 +/- 0.1 292.6 +/- 0.4 299.8 +/- 0.2 307.2 +/- 0.5

286.3 +/- 0.2 291.7 +/- 5.8 299.2 +/- 3.1 303.8 +/- 1.4 307.2 +/- 0.5

25 50 75 100

300.3 +/- 0.2 290.8 +/- 0.4 290.7 +/- 0.0 299.1 +/- 0.0 309.6 +/- 0.0

297.0 +/- 0.1 295.7 +/- 0.2 298.9 +/- 0.1 301.6 +/- 0.1 307.2 +/- 0.5

297.0 +/- 0.1 291.7 +/- 5.8 299.2 +/- 3.1 303.8 +/- 1.4 307.2 +/- 0.5

Table 2. DSC data for saturated-unsaturated binary blends. C18:0 C18:1 C18:2 Experimental (wt. %) (wt. %) (wt. %) Melting Point (K) 100 75 50 25

100 75 50 25

25 50 75 100

25 50 75 100

Experimental Cloud Point (K)

Theoretical Cloud Point (K)

309.6 +/- 0.0 301.2 +/- 0.3 293.3 +/- 0.0 283.5 +/- 0.3 251.4 +/- 0.0

307.2 +/- 0.5 303.7 +/- 0.4 298.7 +/- 0.2 288.9 +/- 0.1 238.2 +/- 0.0

307.2 +/- 0.5 303.8 +/- 1.4 299.2 +/- 3.1 291.7 +/- 5.8 --b

309.6 +/- 0.0 301.5 +/- 0.0 293.4 +/- 0.1 282.7 +/- 0.7

Cold Flow Properties of Fatty Acid Methyl Ester ... - ACS Publications

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