Article pubs.acs.org/EF
Simulated Distillation Approach to the Gas Chromatographic Analysis of Feedstock and Products in the Deoxygenation of Lipids to Hydrocarbon Biofuels Tonya Morgan, Eduardo Santillan-Jimenez, and Mark Crocker* Center for Applied Energy Research, University of Kentucky, 2540 Research Park Drive, Lexington, Kentucky 40511, United States S Supporting Information *
ABSTRACT: This study focused on devising a method for accurately analyzing the reaction products derived from the upgrading of fats and oils to hydrocarbons. A single method capable of identifying and quantifying all the major constituents commonly found in samples of interest was developed, including the triglycerides and fatty acids constituting the feed, the alkanes resulting from the deoxygenation of the feed, and other intermediates and byproducts, such as alkenes, alcohols, aldehydes, and esters. A standard GC−FID-based method for the analysis of hydrocarbon mixtures (ASTM D 2887) was used as a starting point, and through a number of modifications to both hardware and programming, a method capable of affording a single chromatogram in which all the aforementioned components are fully eluted and well-resolved was developed. In addition to its reliability and its versatility, this approach is relatively fast, straightforward, and inexpensive, as no sample derivatization prior to analysis is required.
1. INTRODUCTION To obtain a product serviceable as liquid transportation fuel, lipid-based feeds have traditionally been converted to the mixture of fatty acid esters commonly known as biodiesel. Unfortunately, biodiesel displays a number of shortcomings associated with its high oxygen content, and therefore, attention has shifted to the deoxygenation of lipids to hydrocarbon biofuels,1−4 which are chemically indistinguishable from petroleum-derived fuels and thus offer a number of advantages over biodiesel.5−7 To gauge the effectiveness of deoxygenation processes, the quantitative analysis of both lipid-based feeds and their reaction productswhich can be a mixture of different hydrocarbons and unconverted (or partially converted) lipidsis essential. Considering these analytes separately, fuel-like hydrocarbons are routinely analyzed in the petroleum industry via Simulated Distillation GC (SimDist) using standard methods of the American Society for Testing and Materials (ASTM), such as ASTM D 28878 and ASTM D 7213.9 These methods establish a linear relationship between the retention time of different hydrocarbons and their boiling point, thus affording the ability to transform chromatographic data into a boiling point distribution plot (BPDP), which graphically represents the fraction of the sample boiling within different temperature ranges. In the case of lipids, standard methods exist for the analysis of glycerides10 and fatty acids;11,12 however, these methods focus on the determination of these analytes within very specific matrices, namely, biodiesel methyl esters, fats, and oils. In addition to these standard methods, a host of other methods based on a number of different techniquessuch as gas chromatography (GC), 13−15 liquid chromatography (LC),16−19 online LC−GC,20 size exclusion chromatography (SEC),21−23 thin layer chromatography (TLC),24,25 electrospray ionization−mass spectrometry (ESI-MS),26 and nuclear magnetic resonance (NMR)27have been reported in the © 2014 American Chemical Society
scientific literature for the analysis of lipids, although most of these references focus on the analysis of glycerides and/or fatty acids either as feedstock for biodiesel production or as impurities within biodiesel.28,29 In view of the fact that attention is shifting away from biodiesel to focus on the synthesis of hydrocarbon biofuels, a method capable of simultaneously quantifying both lipids and fuel-like hydrocarbons is needed to assess the extent of lipid deoxygenation reactions. A survey of the articles recently published by authors working on the deoxygenation of lipid-based feeds to fuel-like hydrocarbons reveals the use of a plethora of analytical methods mostly based on gas chromatography-flame ionization detector (GC−FID) and gas chromatography-mass spectrometry (GC−MS),30−53 although techniques such as SEC50,51 and NMR31 are also employed. Unfortunately, a considerable number of these methods require a costly and time-consuming derivatization step in which the lipids within the samples are silylated prior to chromatographic analysis in order to increase their volatility and detectability.45−53 In short, the acquisition of a complete set of quantitative data for a sample comprising both lipids and hydrocarbons can be rather involved, either because the analysis of the different components within the sample requires the use of different methods or techniques, or because the methods employed involve ancillary steps such as silylation. Interestingly, Kim et al. recently reported a one-step method for the analysis of renewable diesel (obtained from natural triglycerides) based on a four-dimensional GC approach in conjunction with time-of-flight mass spectrometry.54 However, the instrumentation employed is both costly and Received: January 22, 2014 Revised: March 14, 2014 Published: March 17, 2014 2654
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2.3.2. GC−FID Measurements. All GC analyses were performed on an Agilent 7890A GC equipped with an Agilent Multimode inlet, a deactivated open ended helix liner and a flame ionization detector. A 1 μL injection was employed, and helium was used as the carrier gas. The FID was set to 350 °C with the following flow rates: H2 = 30 mL/ min; air = 400 mL/min; makeup He = 5 mL/min. Two main GC methods were essayed. In Method A, the inlet was run in programmed temperature vaporizer (PTV) solvent vent mode using an initial temperature of 100 °C. Immediately upon injection, the inlet temperature was increased at a rate of 15 °C/min to a final temperature of 350 °C, which was maintained for the duration of the analysis. Similarly, the oven temperature (initially 35 °C) was increased immediately upon injection at a rate of 15 °C/min to 350 °C and held for 7 min, the total run time being 27 min. An Agilent J&W DB-2887 column (10 m × 530 μm × 3.0 μm; 350 °C max.) operated under a constant flow (26 mL/min) of He was employed. In Method B, the inlet was operated in split mode (split ratio 25:1; split flow 50 mL/min) using an initial temperature of 100 °C. Immediately upon injection, the inlet temperature was increased at a rate of 8 °C/min to a final temperature of 320 °C maintained for the duration of the analysis. The oven temperature (initially 45 °C) was immediately increased upon injection to 325 °C at a rate of 4 °C/min and then to 400 °C at a rate of 10 °C/min. The maximum temperature was maintained for 12.5 min, the total run time being 90 min. An Agilent J&W DB-5HT column (30 m × 250 μm × 0.1 μm; 400 °C max.) operated under a constant flow (2 mL/min) of He was employed. Chromatographic programming was performed using Agilent Chemstation software. Data acquired using the above GC−FID methods were processed using SimDis Expert 9 software purchased from Separation Systems, Inc. Solvents such as chloroform and dodecane were subtracted and/or quenched from the chromatogram prior to any calculations. 2.3.3. GC−MS Measurements. GC−MS analyses were performed on an Agilent 7890A GC coupled to an Agilent 5975C Inert MSD with a triple axis detector following Method B above, albeit the inlet was run in split mode (split ratio 25:1; split flow 25 mL/min) and kept at a constant temperature (300 °C) for the duration of the analysis. The GC was equipped with an Agilent J&W DB5-HT column (30 m × 250 μm × 0.1 μm; 400 °C max.). Zone temperaturesincluding those of the MS source (250 °C) and quadrupole (200 °C) remained constant for the duration of the analysis. The mass spectrometer scanned from 10 to 700 Da in 0.4 s.
difficult to operate, which is likely to limit the widespread adoption of this method. In view of the foregoing, we have developed a GC method that yields a single chromatogram containing all the data necessary to quantify the constituents of a sample containing both lipids and hydrocarbons. Notably, this method does not require a derivatization step and the absence of such a step does not compromise the quality of the chromatographic data. In this contribution, this method is described and its consistency and versatility are illustrated through its application to a variety of samples, including lipid-based feedssuch as saturated and unsaturated model lipids, an industrial free fatty acid (FFA) waste stream, and an algal lipid samplein addition to their respective deoxygenation products.
2. MATERIALS AND METHODS 2.1. Reagents. Triolein (99% and 65%), methyl stearate (97%), methyl oleate (70%), decane (≥99%), tetradecane (99%), nheptadecane (99%), 8-heptadecene (≥96%), and a mixture of 37 fatty acid methyl esters (FAMEs) were purchased from Sigma Aldrich. Tristearin (95%), ethyl stearate (99%), and palmitic acid (≥96%) were purchased from City Chemical. Dodecane (>99%), cyclohexanone (>99%), 1-octadecanol (97%), oleyl alcohol (80−85%), and oleic acid (90%) were purchased from Alfa Aesar. Octadecanal (>95%) was purchased from TCI America. Stearic acid (97%) and ethyl oleate (90%) were purchased from Acros Organics. Chloroform (HPLC grade) was purchased from Fisher Scientific. Pentadecane (≥98%) was purchased from Fluka. Boiling Point Calibration Sample Kits #1 and #2 were purchased from Agilent Technologies. A mixture of FFAsproduced as a waste stream in the biodiesel industry during the purification of the oleaginous feedstock via steam strippingwas obtained from ESC Energy. According to GC−MS analysis (see section 2.3.3 for details of the analysis), this sample consisted mostly of oleic, palmitic, and myristic acids (62.2, 22.5, and 1.7 wt %, respectively) with various trace compounds as the remaining constituents. Algal lipids were extracted from a sample of dry Scenedesmus acutusgrown in a photobioreactor fed with the flue gas of a coal-fired power plantby the Bligh−Dyer method55 and purified (to remove chlorophyll) using a column containing both K10 montmorillonite clay (Sigma-Aldrich) and silica gel. Canola, corn, soybean, and coconut oils (all food grade) were purchased from a local supermarket. Tall oil fatty acid samples (XTOL 100, 101, 300, and 304) were provided by Georgia-Pacific Chemicals. 2.2. Deoxygenation Reactions. Lipid deoxygenation experiments in semibatch mode were performed using previously described materials, procedures, and reaction conditions.38 Unless otherwise stated, lipid deoxygenation experiments in continuous mode were performed using a Ni-Al layered double hydroxide (LDH) catalyst described elsewhere37,56 and previously reported reaction conditions.57 2.3. GC Analyses. 2.3.1. Calibration Standards. Boiling Point Calibration Sample Kit #2 was mixed with two different amounts of cylohexanone (internal standard) to yield the same mixture of C10− C18 n-alkanes in two different concentrations (see Table S1 in the Supporting Information), and the resulting mixtures were used to determine the response factors for these alkanes. The other calibration standards in Table S1 (columns B−F) were similarly prepared using representative constituents detected via the GC−MS analysis of several deoxygenation reaction products. Unless otherwise indicated, 0.5 g of each compound mixture and the respective amount of cyclohexanone were diluted with 1 g of chloroform prior to GC analysis. Solutions corresponding to different functional groups were prepared and stored at −18 °C until analysis. Boiling Point Calibration Sample Kit #1 was used neat to obtain qualitative boiling point calibration curves (Figure S1) using the GC methods and the SimDist software described in section 2.3.2 below. The mixture of 37 FAMEs, which was purchased as a solution (10 mg/mL in methylene chloride), was further diluted 10:1 in cyclohexane and mixed with 0.05 g of cyclohexanone as internal standard prior to GC analysis.
3. RESULTS AND DISCUSSION 3.1. Scope and Limitations of Method A. Method A represents a SimDist GC method consistent with ASTM D 2887, which was designed to analyze n-alkanes boiling up to 545 °C in a relatively short time in order to provide for high throughput. As expected, the analysis of a boiling point (b.p.) calibration sample (Kit #1) containing a series of n-alkanes ranging from C5 to C40 yielded a b.p. calibration curve showing high linearity (r2 ≥ 0.999) between C8 and C40 (constituents smaller than C8 losing linearity due to vapor pressure effects encountered during sampling at room temperature) (see Figure S1 in the Supporting Information). Unfortunately, very few biofuel samples obtained through the deoxygenation of lipids contain exclusively n-alkanes. Indeed, unconverted lipid feedstock and potential reaction intermediates, such as alkenes,39,48 carboxylic acids,36,37,48 esters,58 aldehydes, and alcohols,39,49,52,57,58 can also be present. Therefore, the impact of these additional constituents on the SimDist GC analysis must be considered and the method must be modified accordingly. For instance, ASTM D 2887 prescribes the use of carbon disulfide as solvent, as its nonpolar nature (ε = 2.6) makes CS2 ideally suited to dissolve the 2655
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nonpolar hydrocarbons the D2887 method is designed to analyze. However, lipids have more polar characteristics, and thus, the dissolution of samples containing fatty acids and triglycerides using carbon disulfide presents an immediate problem, making it necessary to modify the solvent. Chloroform (ε = 4.81) was ultimately chosen due to its ability to solubilize all constituents and to interact satisfactorily with a nonpolar GC column. Although Method A is a widely accepted analytical procedure, the method still needed to be validated using samples containing lipids commonly used as feedstock for biofuel production. To this end, samples were prepared containing known concentrations of a model triglyceride and an analogous fatty acid (mixtures of tristearin and stearic acid and of triolein and oleic acid being chosen to represent saturated and unsaturated lipids, respectively). The analysis of these samples afforded unsatisfactory resultsas illustrated by the discrepancy between the known concentrations and the experimental values obtained (see Figure 1)which beckoned
Table 1. List of Representative Lipid Deoxygenation Products and Relevant Chromatographic Data As Acquired Using Method B retention times compound
start
apex
decane undecane tetradecane pentadecane hexadecane 8-heptadecene heptadecane octadecane methyl palmitate ethyl stearate octadecanal palmitic acid oleyl alcohol stearyl alcohol methyl oleate methyl stearate oleic acid stearic acid stearyl stearate triolein tristearina
5.3 8.0 17.1 20.0 22.8 24.8 25.5 28.0 31.0 32.6 33.2 34.0 34.3 34.7 35.0 35.6 36.4 37.1 62.4 77.4 76.9
6.0 8.7 18.5 21.2 24.3 25.0 26.7 29.0 31.4 32.9 33.6 34.3 34.4 34.9 35.3 35.9 36.8 37.3 62.7 77.9 77.1
response factor 1.43 1.37 1.36 1.40 1.74 0.37 1.46 1.68 0.90 0.37 0.97 2.59 0.09 1.70 0.78 1.19 0.66 0.70 0.54 0.78 0.22
a
Four peaks were obtained, the peak showing the largest area being used to calculate the response factor.
satisfactory analysis (with complete elution) of the lipids commonly used as feedstock for biofuel production; (2) maintaining a linear relationship between the retention time and the boiling point of fuel-like hydrocarbons; and (3) resolving all major compounds observed during the conversion of the former into the latter. Although the primary difference between Method A and the GC−MS protocol is the column employed, the composition and the polarity of both columns are very similar (the DB-2887 being 100% dimethylpolysiloxane and the DB-5HT being 5% phenyl, 95% dimethylpolysiloxane). However, the lengths, film thickness, and internal diameters of these two columns differ significantly, which can lead to differences in analyte retention capacity between the two methods. After optimization of the temperature and other method parameters, the DB-5HT column was able to satisfactorily analyze triglycerides with complete elution as illustrated in Figure S2 (Supporting Information). This method (“Method B”) was also successful in maintaining the linear relationship between the retention time and b.p. of the C8−C40 n-alkanes, as shown in Figure S1b (Supporting Information). Moreover, the ability of Method B to resolve all the compounds listed in Table 1 was confirmed, as illustrated by Figure 2 and by the retention times included in Table 1. To ensure the correct identification of each peak, the retention time calibration standards described in Table S1 (Supporting Information) were employed. It should be noted that the retention times are given both as the traditional apex retention time and as initial elution time, due to the fact that the initial elution time was more useful in the identification process. Unsurprisingly, due to column interactions with the oxygenated constituents, compounds possessing similar boiling points, but different functional groups, display slightly different
Figure 1. Actual vs analyzed composition of triglyceride and fatty acid reference samples.
the need for further method modifications. Simply applying a higher flow rate afforded the ability to use less stringent temperature conditions, which helped preserve the integrity of the lipid. This initial optimization (denoted hereafter as Method A*) afforded considerable improvements relative to the results obtained with Method A in the analysis of the aforementioned triglyceride−fatty acid mixtures (results not shown). Tellingly, the analysis of the pure triglycerides by both methods disclosed the incomplete elution of both tristearin and triolein, which partially explains the unsatisfactory results mentioned above. 3.2. Scope of Method B. Method B was developed to include the major intermediates and byproducts that can be obtained during the deoxygenation of lipids to fuel-like hydrocarbons while ensuring complete elution of triglycerides. A matrix of samples was analyzed via GC−MS in order to identify the most prominent compounds produced by deoxygenation reactions (see Table 1). Starting from Method A and the protocol used for GC−MS, efforts were made to develop a hybrid method capable of (1) ensuring the 2656
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Figure 2. Gas chromatogram of a sample containing representative lipid deoxygenation products acquired using Method B.
Table 2. Boiling Points and Retention Times for Major Compounds Typically Observed during the Conversion of Lipids to Hydrocarbons As Determined Using Method B compound Alkanes C5 C6 C7 C8 C9 C10 C11 C12 C14 C15 C16 C17 C18 C20 C24 C28 C32 C36 C40 a
b.p.a (lit.) 36 69 98 126 151 174 196 216 254 271 287 302 316 344 391 431 466 496 522
b.p.a (exp.) 36 69 98 126 151 174 196 216 254 271 287 302 316 344 391 431 466 496 522
RT (min) 1.3 1.6 1.8 2.5 3.8 6.0 8.7 12.4 18.5 21.2 24.3 26.7 29.0 33.6 41.9 49.1 55.4 61.0 65.9
compound Fatty Acids C14:0-myristic C16:0-palmitic C18:0-stearic C18:1-oleic Alcohols C18:0-stearyl C18:1-oleyl Esters stearyl stearate Other 8-heptadecene octadecanal Triglycerides C18:0-tristearin C18:1-triolein
b.p.a (lit.)
b.p.a (exp.)
RT (min)
326 351 376 360
309 343 361 358
28.4 34.3 37.3 36.8
336 334
347 344
34.9 34.4
550
509
62.5
305 320
289 339
25.0 33.6
550 554
594 599
77.1 77.9
All boiling point values are expressed in °C.
(corresponding to an approximate b.p. of 590 °C), which is more consistent with the BPDP expected for a pure analyte. Boiling points as different as 412 and 880 °C have been reported for triolein59−61 (the b.p. of triglycerides being difficult to determine due to simultaneous thermal decomposition), although most reports center on a value around 550 °C. Notably, the b.p. values obtained via Method B for the major
elution rates, as demonstrated in Table 2 and Figure S3 (Supporting Information). Method B also proved to be superior to Method A* in terms of the boiling point distribution plots obtained for pure triolein (see Figure 3). Indeed, whereas Method A* afforded a triolein BPDP consisting of a series of sloping lines, Method B resulted in a BPDP composed mostly of a single horizontal line 2657
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Table 3. Actual vs Analyzed Composition Using Method A and Method B* for a Sample Representative of a Typical Lipid Deoxygenation Reaction Mixture Method B* (mg)
Figure 3. Boiling point distribution plots of triolein obtained using Method A* and Method B.
compounds observed during the conversion of lipids to hydrocarbons also showed a reasonable correlation with previously reported values (see Table 2). Unfortunately, the superiority of Method B over Methods A and A* did not extend to include the ability to yield more accurate results when tested in the quantitative analysis of triglyceride and fatty acids mixtures (see Figure 1), which spurred efforts to address this shortcoming. 3.3. Development of a Fully Quantitative Method through the Use of an Internal Standard. As mentioned in section 2.3, cyclohexanonewhich shows a retention time of 2.9−3.5 min in Method B (see Figure 2)was chosen as an internal standard and is included in the calibration standards shown in Table S1 (Supporting Information). Linear calibration curves were created for each compound using raw area values, r2 ≥ 0.99 being obtained in all cases. The resulting response factors are shown in Table 1 (calculated according to the formula R = (Ax/AIS)/(Mx/MIS), where R is the response factor, Ax is the peak area of the analyte, AIS is the peak area of the internal standard, Mx is the mass of the analyte, and MIS is the mass of the internal standard). Notably, the response factors for n-alkanes, trigylcerides, and fatty acids were found to differ significantly. Hence, the inability of Method B to accurately quantify the triglyceride and fatty acid concentration in the mixtures shown in Figure 1 using a method involving peak area % is unsurprising. Notably, when the chromatographic data obtained via Method B is interpreted incorporating the response factors listed in Table 1 (Method B*), the resulting values are considerably closer to the actual concentrations (see Figure 1). To fully validate the potential of Method B* to analyze samples resulting from the deoxygenation of lipid-based feeds to fuel-like hydrocarbons, a mixture of known composition representative of a typical reaction mixture was prepared and analyzed (see Table 3). The results obtained via Method B* were found to show good agreement with the known concentrations. Indeed, in most cases, the relative standard deviation was found to be within 1−4% of the mean value, the exception being octadecanal for which the relative standard deviation was 10%. 3.4. Analysis of Lipid-Based Feeds, Their Fatty Acid Methyl Esters, and Their Deoxygenation Products. Method B* is suitable for performing the analysis not only of model lipids but also of realistic lipid-based feedssuch as a mixture of FFAs produced as a waste stream in the biodiesel industry and algal lipidsas well as the methyl esters and the
compound
actual (mg)
Method A (mg)
average
% rel std. dev.
% error
decane undecane tetradecane pentadecane heptadecane palmitic acid octadecanal oleyl alcohol stearyl alcohol methyl oleate methyl stearate oleic acid stearic acid stearyl stearate tristearina
67 142 53 93 90 49 18 147 38 101 33 87 26 67 62
73 83 55 53 103 19 9 41 9 35 142 95 62 21 19
68 145 54 93 89 47 17 146 38 101 33 87 26 65 58
1 2 1 1 1 2 10 1 1 1 1 3 3 3 4
1 2 2 0 1 3 6 1 1 0 1 1 1 3 6
a
Four peaks were obtained, the peak showing the largest area being used to calculate the response factor.
hydrocarbons derived from these feedstocks. Particularly illustrative is the analysis of algal lipids, which represent one of the most challenging samples to analyze due to the fact that the extraction method described in section 2.1 yields a mixture containing triglycerides, fatty acid esters, fatty acids, and hydrocarbons. The identity of the fatty acid chains in lipid feeds is customarily determined by first converting them to the corresponding methyl esters (by means of transesterification with methanol), followed by GC analysis. Consequently, a calibration standard containing all potential FAME products must be analyzed prior to tackling the analysis of the methyl esters resulting from transesterification of the feed. Figure 4 shows the chromatogramacquired via Method Bof a calibration standard containing 37 FAMEs, whereas boiling points and retention times for selected FAMEs are given in Table S2 (Supporting Information). Evidently, despite the apparent mismatch between the polarity of the column and that of the FAMEs, excellent peak resolution and peak symmetry are obtained. Indeed, FAMEs are commonly analyzed using polar columnssuch as DB-Wax in ASTM D 6751the DB-5HT column used in Method B being considerably less polar. Figure 5 shows the chromatogramalso acquired using Method B of the methyl esters resulting from the transesterification of algae oil, and Table S3 (Supporting Information) shows the identity and relative amount of the fatty acid chains in the algal lipids employed in this study as well as the acid number. As was the case for the analysis of the FAMEs calibration standard, the chromatogram of the transesterified algae extract also shows notable peak resolution and symmetry (see Figure 5). Considering the data in Table S3, while the acid number suggests that the algae extract employed in this study contains a significant amount of free fatty acids, the analysis of the transesterification products shows that the fatty acid chains in the lipids display a wide range of lengths, C16 and C18 chains being particularly prevalent. The analysis of the raw algae extract via Method B both confirms and complements the aforementioned data. Indeed, the resulting chromatogram (shown in Figure 6a) shows that 2658
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Figure 4. Gas chromatogram of a calibration standard containing 37 FAMEs acquired using Method B.
Figure 5. Gas chromatogram of algae oil transesterification products acquired using Method B.
the algae extract represents a complex mixture containing triglycerides, a significant amount of fatty acids, C13−C17
hydrocarbons, and stearyl stearate as well as other less abundant components. The SimDist boiling point distribution plot of the 2659
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that the chromatographic data used to obtain Figures 6 and 7 can also be used to calculate catalytic performance parameters, such as conversion, selectivity, and yield.56 As noted above, Method B is also suitable for analyzing other feeds and the products of their catalytic deoxygenation. By means of example, the chromatograms and the boiling point distribution plots of stearic acid, tristearin, triolein, and an industrial FFA-based waste stream, along with the products of their catalytic deoxygenation in either a semibatch system (for stearic acid and tristearin) or in a continuous reactor (for triolein and the FFA feed), are included as Supporting Information (Figures S4−S8). The versatility and wide applicability of Method B have been further gauged through the analysis of a considerable number of oils used as feedstock in the production of renewable fuels, such as triglyceride-based canola oil,62 corn oil,63 soybean oil,64 and coconut oil31 (Figure S9), and fatty acid-based tall oils51,65−67 (Figure S10) (Supporting Information). Particularly noteworthy is the fact that the results obtained with Method B are comparable to those afforded by methods specifically designed to analyze some of these feeds, the chromatographs of coconut oil included in Figure S9 and in a previous literature report68 constituting a prime example.
Figure 6. GC chromatograms acquired using Method B of (a) raw algae oil and (b) the product mixture resulting from its deoxygenation sampled after 4 h.
algae extract (shown in Figure 7), illustrates the relative amounts of these compounds, hydrocarbons (boiling below 300 °C) representing ∼30% of the extract and fatty acids (boiling between 300 and 400 °C) constituting ∼55% of the mixture, the remainder being compounds with higher boiling points, such as stearyl stearate and triglycerides. In addition to its ability to analyze both the raw and the transesterified algae extract, Method B is suitable for the analysis of the hydrocarbon-based biofuels obtained through catalytic deoxygenation processes. Figure 6b shows the chromatogram of the product mixture obtained from the continuous deoxygenation of the algae extract at a reaction time of 4 h. A comparison of parts (a) and (b) in Figure 6 clearly illustrates that the catalytic process successfully converts the lipids, i.e., triglycerides, fatty acids, and esters, in the feed into C10−C18 hydrocarbons. This is even more clearly demonstrated in Figure 7, which shows the SimDist BPDP of the reaction products obtained after 1, 2, 3, and 4 h. Indeed, the hydrocarbon content of the analytes increases from ∼30% in the feed to >95% in the reaction products, >70% of the latter being hydrocarbons within the boiling point range of diesel fuel (∼180−350 °C) at all reaction times sampled. Additionally, the boiling point distribution plots of the reaction products shown in Figure 7 suggest that the selectivity toward different hydrocarbon products changes as the reaction progresses. In this regard, it is important to note
4. CONCLUSIONS The analysis of reagents and products in the deoxygenation of lipid-based feeds to hydrocarbon biofuels presents a series of challenges. Currently, the analytical methodology found in the literature on this topic includes a profusion of techniques, hardware, software, sample preparation procedures, and data interpretation approaches, which makes data comparison difficult. The present contribution reports the development of a single method capable of identifying and quantifying all the major constituents commonly found in samples of interest, including the triglycerides and fatty acids constituting the feed, the alkanes resulting from the deoxygenation of the feed, and other intermediates and byproducts, such as alkenes, alcohols, aldehydes, and esters. A standard GC−FID-based method for the analysis of hydrocarbon mixtures (ASTM D 2887) was used as a starting point, and through a number of modifications to both hardware and programming, a method capable of affording a single chromatogram in which all the aforementioned components are fully eluted and well-resolved was developed. In addition, an approach based on the use of an internal standard was shown to be suitable for extracting quantitative information from the chromatograms obtained. Notably, the proposed method of acquiring and interpreting chromatographic data has been validated through the analysis of a number of lipid feedsincluding pure triglycerides and fatty acids but also realistic feeds such as an industrial FFA waste stream and algal lipidsand their corresponding hydrocarbon products. In addition to its reliability and versatility, this approach is relatively fast, straightforward, and inexpensive, as no sample derivatization prior to analysis is required.
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ASSOCIATED CONTENT
S Supporting Information *
Tables showing the composition of qualitative calibration standards, the boiling point and retention times of relevant FAMEs, and the acid number and fatty acid profile of algal lipids; figures showing boiling point calibration plots and the chromatograms and BPDPs of ten types of feed (model
Figure 7. SimDist GC boiling point distribution plots of the algae extract and the products of its catalytic deoxygenation in a continuous reactor. 2660
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compounds and biomass) along with selected deoxygenation products. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Tel.: +1 859 257 0295. Fax: +1 859 257 0220. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS The authors would like to thank Dr. A. E. Harman-Ware for her assistance with GC−MS method development. Brad Davis of ESC Energy is thanked for providing FFA mixtures. Jeffery Yost of Georgia-Pacific Chemicals is thanked for providing tall oil fatty acid samples. The U.S. Department of Energy (award no. DE-FG36-08GO88043), the Kentucky Department of Energy Development and Independence, and the University of Kentucky Center for Applied Energy Research are thanked for financial support. Any opinions, findings, conclusions or recommendations expressed herein are those of the authors and do not necessarily reflect the views of the Department of Energy.
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