Laboratory Experiment pubs.acs.org/jchemeduc
Instrumental Analysis of Biodiesel Content in Commercial Diesel Blends: An Experiment for Undergraduate Analytical Chemistry Z. Vivian Feng* and Joseph T. Buchman Chemistry Department, Augsburg College, Minneapolis, Minnesota 55454, United States S Supporting Information *
ABSTRACT: The potential of replacing petroleum fuels with renewable biofuels has drawn significant public interest. Many states have imposed biodiesel mandates or incentives to use commercial biodiesel blends. We present an inquiry-driven experiment where students are given the tasks to gather samples, develop analytical methods using various instrumental methods, such as HPLC, 1H-NMR, and ATR-FTIR, make measurements, and analyze the results to determine the volume percent of biodiesel in commercial diesel blends. The project develops students’ appreciation of the usefulness of chemistry by working with “real” samples from their daily lives, and skills to critically compare and contrast the strengths and weaknesses of various instrumental techniques for quantitative analysis.
KEYWORDS: Upper-division Undergraduate, Analytical Chemistry, Laboratory Instruction, Inquiry Based/Discovery Learning, Instrumental Methods, HPLC, IR Spectroscopy, NMR Spectroscopy, Quantitative Analysis, Student-Centered Learning
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sometimes used in conjunction with GC or GCMS to separate biodiesel from diesel prior to analysis to produce less-complex chromatograms. In contrast to GC, normal-phase HPLC equipped with UV or evaporative light scattering detectors (ELSD) has proven to be more practical3a,c,5 because classes of chemicals may elute instead of individual components. Spectroscopic methods have also been developed. Interestingly, the method of choice by the European Standard Reference (EN 14078)4 and the local Minnesota Department of Commerce is mid-IR spectroscopy. In this method, the IR peak of the ester carbonyl moiety at ∼1740 cm−1, unique to biodiesel, is examined.6 This has been a popular method for the purpose of quantifying levels of biodiesel because of its simplicity and speed. Partial least-squares (PLS) methods have also been applied to model the IR spectral results to better account for the differences in sources of biodiesel.7 Another spectroscopic method commonly used is1H NMR spectroscopy where the singlet produced by the methyl protons on the methoxy group in biodiesel is examined.6a,8 Monteiro et al. has demonstrated that the 1H NMR results of quantification of biodiesel in diesel blends were not affected by the biodiesel feedstock, which makes this method particularly valuable for such determination.8b Several educational activities for college courses involving alternative fuels have been published in the Journal recently.9 Most activities focused on the production and fuel properties of biofuels, such as viscosity and flash point, which are more suitable for general and organic chemistry courses. Laboratory activities suitable for analytical chemistry courses include work
ith the current economic and political discussions on renewable energy sources, feasibility of replacing petroleum fuel with biofuels has been a hot topic. Biodiesel, a mixture of fatty acid methyl esters produced from the transesterification process of oil from renewable sources, has entered the consumer market, especially in truck fleets and the airline industry. Compared to conventional petroleum diesel, biodiesel features a high cetane number with improved lubricity even at low blend levels of 1−2%. Biodiesel also produces ultralow sulfur level, which reduces toxic gas emission in combustion.1 Because the production and consumption of biodiesel follow a closed carbon cycle, by replacing petroleum diesel with biodiesel, greenhouse gas emissions can be significantly reduced. These benefits have motivated the lawmakers in many states to implement various mandates and incentives to encourage the use of biodiesel blends in commercial diesel. Since 2009, Minnesota has implemented a B5 mandate, requiring all diesel sold in the state to contain a minimum of 5% biodiesel and plans to increase the level to B10 by May 2012 and B20 by 2015.2 The quantification of biodiesel in commercial diesel blends has become an area of interest for chemists. Petroleum diesel is mostly composed of aliphatic and aromatic hydrocarbons with 8−21 carbons, whereas biodiesel is a mixture of long-chain (mostly greater than 12 carbons) mono alkyl methyl esters, and the differences in their chemical properties allow chemists to directly determine the blend level. Chromatographic methods have been developed to analyze biodiesel blends.3 However, due to the complexity of petroleum diesel, GC produces numerous peaks and has been less suitable for quantifying biodiesel in diesel blends.3b,4 Solid phase extraction (SPE) is © 2012 American Chemical Society and Division of Chemical Education, Inc.
Published: September 28, 2012 1561
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by Pierce et al.10 on analyzing biodiesel blends using GCMS and GC-TIC (total ion current GCMS) in conjunction with PLS modeling and by El Seoud et al.9e on a colorimetric analysis to quantify ethanol in diesel fuel with the aid of a solvatochromic dye. We present a project exploring the applications of multiple analytical instruments to analyze the composition of commercial diesel blends. On the basis of the availability of the instruments, students conducted primary literature search to identify and design experimental procedures suitable for each method. FT-IR, HPLC, and 1H NMR were used to quantify the biodiesel content in various commercial diesel samples. The project provides a novel experience as students design and conduct analysis of the same commercial samples using various instruments and allows them to apply statistical analysis to better understand the strengths and weaknesses of these techniques as well as the importance in sample preparation for the purpose of quantitative analysis.
using Beer−Lambert law, all IR spectra were recorded in absorbance mode at 1744 cm−1. All 1H NMR samples were prepared in a CDCl3 solvent spiked with a known quantity of internal standard, ethylene carbonate (Figure 1). Calibration solutions were 2, 4, 5, 6, and
Figure 1. Molecular structure of ethylene carbonate, the internal standard used in NMR analysis.
8% (v/v) of pure biodiesel in pure petrodiesel. Samples were measured on a Varian Unity 300 MHz NMR with 32 scans of 45° pulses, a relaxation delay of 1.500 s, and an acquisition time of 2.000 s. Ratios of the height of the methoxy peak at 3.6−3.7 ppm to that of the ethylene carbonate peak at 4.5 ppm were collected and plotted to establish a calibration curve. HPLC calibration samples were prepared by mixing 2, 4, 5, 6, or 8% (v/v) pure biodiesel in pure petrodiesel and doing a 1:500 dilution in 95% n-hexane. Waters LC Module 1 Plus with an autosampler and a 10 cm silica column (Thermo Scientific Hypersil silica, 250 × 4.6 mm, 5 μm particle size) was used. The HPLC method was developed with dodecane and methyl stearate to mimic diesel and biodiesel, respectively. A program with an isocratic mobile phase of 95:5 hexane/t-butyl methyl ether with a flow rate of 1.0 mL/min and an injection volume of 2 μL delivered by a sample loop was used for all measurements. The UV detector was set to monitor at 201 nm.
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EXPERIMENT OVERVIEW This capstone project is intended for upper-level analytical undergraduate students. With minimal direction, the students were tasked to use multiple instrumental methods to verify if various gas stations are complying with the 5% biodiesel mandate. They were allowed one week outside classroom time to conduct a literature search and design an experimental procedure for at least two different instruments in which they presented a (1) material and chemical list, (2) list of required solutions, (3) experimental parameters, and (4) an estimated experimental time. The literature search and experimental design were completed individually by each student, whereas collaboration to select one procedure for each instrument was encouraged. The students then worked in groups of two to four for three, 4 h lab periods to perform the experiments and collect data. Over the course of three years, a total of 16 students have participated in this capstone project. This project culminated in individual research papers.
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HAZARDS Safety goggles should always be worn when working in the laboratory. Commercial diesel, biodiesel, chloroform-d, nhexane, and t-butyl methyl ether can cause skin and eye irritation and are harmful if ingested. Chloroform-d is a toxic substance that is extremely volatile; always use CDCl3 in a fume hood. Diesel, biodiesel, n-hexane, and t-butyl methyl ether are very flammable. It is recommended to use gloves and a fume hood for all sample preparation. Disposal must follow proper waste disposal regulations. Use of laboratory gloves is strongly recommended throughout the experiment.
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EXPERIMENTAL DETAILS Commercial diesel blends were collected from various gas stations. Soybean biodiesel was purchased from the EverCat Company and 100% petroleum diesel was generously provided by SarTec Company. Because the majority of biodiesel on the market is soybean oil based, it was assumed that soybean biodiesel would make the most representative calibration samples. Hexane, t-butyl methyl ether, dodecane, methyl stearate, CDCl3, and ethylene carbonate were purchased from VWR and were used as received. Syringe filters with 0.45 μm pore size (Corning PTFE Acrodisc CR 13) were used to filter HPLC samples before analysis. A petroleum diesel sample, 100%, was used as a blank in the three instrumental methods, and the signals were subtracted to obtain the “corrected signals” in the three calibration curves. Hence, the curves were forced through the origins. ATR-FTIR measurements were conducted on a PerkinElmer Spectrum 100 with a diamond ATR stage. Calibration samples used were 2, 4, 5, 6, and 8% (v/v) pure biodiesel in pure petrodiesel. Commercial diesel blend samples were measured directly without further modification. All spectra were recorded at 23 ± 1 °C using an average of 16 scans with a spectral resolution of 4 cm−1. To construct the calibration curve
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RESULTS AND DISCUSSION
Part I: ATR-FTIR Spectroscopy
Figure 2 shows a sample IR spectrum of biodiesel in diesel blend with an insert of the calibration curve constructed using the carbonyl peak absorbance at 1744 cm−1 determined by a group of two students. The entire calibration range from 0 to 8% shows good linearity with greater deviation at the lower percent of biodiesel. These deviations may have occurred because the absorbance at 2% is approaching the limit of detection. The linear correlation was comparable to those in the literature references7,11 with an R2 value of 0.965. The linear correlation was used to assess the biodiesel component in the commercial diesel blends. The student data are shown in Table 1. Although FTIR is not a common choice for quantitative analysis, students soon realized the beauty of this method. The samples used in the IR analysis required minimal preparation, and the measurements were fast, which allowed students ample time to obtain multiple measurements on the same sample to improve precision. The ATR sampling accessory made it especially easy for students to switch samples using simple 1562
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The inset calibration curve, plotting the ratio of the integrations from methyl protons in biodiesel and that from ethylene carbonate versus volume fraction of biodiesel, shows a strong correlation with a R2 above of 0.985. The linear correlation was used to assess the biodiesel component in the commercial diesel blends. The student data are shown in Table 1. Use of an internal standard helped to correct any instrumental fluctuation to improve precision. Students have expressed that their understanding in the use of internal standard was greatly enhanced. However, students observed that multiple steps in sample preparations, including mixing and dilutions, could have contributed to the variability in the measurements. Overall, they found it refreshing to apply 1H NMR, a technique most frequently used for qualitative analysis in organic chemistry, to solve a quantitative problem in this case.
Figure 2. FTIR absorption spectrum of 5% (v/v) pure biodiesel in pure petroleum diesel. The inset shows the calibration curve constructed from the biodiesel carbonyl peak at 1744 cm−1. The data was obtained by a group of 2 students.
Part III: HPLC
Figure 4 shows a representative chromatogram obtained from a sample using HPLC with a UV detector. The HPLC method
rinsing with ethanol and acetone on the sample stage between samples. Concern regarding the use of the mid-IR 1700−1800 cm−1 carbonyl peak for analysis has been brought up in the literature.6a,12 It arises from the fact that both methyl esters and vegetable oil contaminants contain carbonyl peaks. By monitoring the carbonyl peak, one cannot exclude the possibility that absorbance may come from vegetable oil from either poor control of the biodiesel production process or illegal addition of cheap raw oil. The alternative to using the mid-IR region is to monitor absorbance at 5500−6100 cm−1 in the NIR region.6a However, because absorbance at a given wavelength in the NIR region may be the result of multiple analytes in chemically complex matrices, such analysis often requires the use of tools, such as PLS, for biodiesel quantification purposes.12 In this project, because multiple analysis methods were used on the same samples, we chose to use the mid-IR region for simplicity.
Figure 4. HPLC chromatogram of 5% (v/v) pure biodiesel in pure petroleum diesel. The peaks at 3.3 and 4.2 min correspond to the diesel and biodiesel components, respectively. The inset shows the calibration curve constructed from the integration of biodiesel peak area. The data was obtained by a group of 4 students.
Part II: 1H NMR Spectroscopy
Figure 3 shows a representative 1H NMR spectrum of a blend sample diluted in CDCl3 and spiked with ethylene carbonate as an internal standard. The reasons for choosing ethylene carbonate as the internal standard are threefold: (1) its four equivalent protons produce a simple singlet peak at ∼4.5 ppm, away from other peaks in the sample matrix; (2) it is physically stable with low vapor pressure; and (3) it is chemically inert.
was developed using model compounds dodecane (C12) and methyl stearate (C18:0) to mimic diesel and biodiesel, respectively, as methyl stearate is a major component in soybean and canola biodiesels. Once the model compounds were separated with reasonable resolution and elution time, the method (see the Supporting Information) was applied to real samples. The large peak at 3.3 min resulted from the diesel component, and the small peak at 4.2 min was from the biodiesel component. The linear correlation was used to assess the biodiesel component in the commercial diesel blends. The student data are shown in Table 1. The HPLC method offered great sensitivity and detection limit with the calibration curve showing excellent correlation (R2 = 0.992). Students noted the much longer sample preparation process with multiple steps of dilution with hexane, which could have been a major source of error with this analysis. Differences in manual peak integration have also resulted in some variability. A literature reference5 observed that the UV detector relies on the presence of unsaturated bonds in these samples. This method would be flawed if the biodiesel used for calibration standards has a significantly different lipid profile than those in the samples tested. An
Figure 3. 1H NMR spectrum of 5% (v/v) pure biodiesel in pure petroleum diesel containing ethylene carbonate as an internal standard. The inset shows the calibration curve constructed from the ratio of peak intensity of methyl ester proton singlet in biodiesel at 3.7 ppm to that of the ethylene carbonate proton singlet at 4.5 ppm. The data was obtained by a group of 4 students. 1563
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namely, FTIR, NMR, and HPLC, in the unique context of renewable energy. As a result of implementing this capstone project, students gained confidence and competence in designing experiments, operating instruments, and interpreting data. Using real commercial samples that they collected resulted in students’ genuine interest in the data outcome and an enthusiasm to “make sense of the data”. The advantages and disadvantages of certain techniques were no longer dry bulletpoints in lecture notes because students have had first-hand experience comparing the methods and drawing conclusions on their own. Their scientific communication and critical-thinking skills were also enhanced through this experience.
evaporative light scattering detector (ELSD), which is a mass detector, would have worked better for this purpose. Comparison of Results
Table 1 summarizes the results on biodiesel content in 12 commercial diesel samples collected and tested in April 2011 by Table 1. Summary of the Commercial Biodiesel Samples Analyzed with Three Analytical Methods Volume Fraction of Biodiesel in the Commercial Diesel (%) Station
IR
LC
NMR
Avga
SD
KwikTrip-Andover Marathon-Andover SA-Andover BP-Minneapolis Holiday-Minneapolis SA- Minneapolis SA-St. Paul BP- St. Paul SA-Roseville SA-New Brighton Holiday-Bloomington SA-Bloomington
4.83 4.67 4.00 5.11 4.75 3.96 4.94 4.96 4.31 3.03 5.97 4.14
4.20 5.97 3.88 5.32 6.07 5.15 4.89 6.01 3.95 2.98 4.82 6.06
5.33 5.47 3.87 5.41 5.66 5.38 4.37 5.46 5.69 3.78 6.20 4.97
4.79 5.37 3.92 5.28 5.49 4.83 4.73 5.48 4.65 3.27 5.67 5.06
0.57 0.66 0.07 0.16 0.68 0.76 0.32 0.53 0.92 0.45 0.74 0.96
Avg SD
4.56 0.74
4.94 1.02
5.13 0.75
4.88
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ASSOCIATED CONTENT
S Supporting Information *
Detailed instructor’s notes, student handout, and CAS numbers of all chemicals. This material is available via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We thank our CHM 481 students spring class of 2010, 2011, and 2012 for pioneering this laboratory module. We acknowledge Clayton McNeff, Dan Nowlan, and Ben Yan at SarTec Company for their suggestions and generous donations of biodiesel samples and HPLC column used in this study. We thank Sue Hill and Arlin Gyberg at Augsburg College for their laboratory support.
a
The bold numbers indicated noncompliance with the 5% biodiesel mandate requirement.
four students. The diesel samples averaging at 4.88% fell slightly short of the 5% biodiesel mandate requirement. Six out of 12 stations failed to comply (bolded in the table), with 2 stations that were even below 4%. These results are representative for what has been observed for the three consecutive years this project was conducted. Several aspects of the results should be noted. First, comparing the averages produced from three different methods, IR consistently produced lower results, whereas NMR results were higher. Students realized that the accuracy of quantitative analysis depended heavily on the accuracy of the calibration standards even when all three methods showed excellent linear correlations in calibration curves. Without a “true” 5% biodiesel standard, it is impossible to discuss the accuracy of the three methods. Yet, students critically compared the strengths and weaknesses of these methods. The IR method suffered largely from the low signal strength at low levels of biodiesel, whereas HPLC and NMR methods might give more error with the multiple steps of sample preparation. Second, despite some large deviations (e.g., SA Bloomington and SA Roseville), most of the results on the same sample were consistent using all three methods, as depicted in the column of SD. Students were encouraged to use statistical methods to further analyze the data. An example of a spreadsheet to perform paired t test on the final result is given in Supporting Information.
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REFERENCES
(1) Biodiesel Handling and Use Guide; National Renewable Energy Laboratory: 2009. http://www.nrel.gov/vehiclesandfuels/npbf/pdfs/ 43672.pdf (accessed Sep 2012). (2) Schill, S. R., Minnesota Passes B20 Mandate. Biodiesel Magazine, June 17, 2008. http://www.biodieselmagazine.com/articles/2444/ minnesota-passes-b20-mandate/ (accessed Sep 2012). (3) (a) Pauls, R. E. J. Chromatogr. Sci. 2011, 49 (5), 384−396. (b) Yang, Z.; Hollebone, B. P.; Wang, Z.; Yang, C.; Landriault, M. J. Sep. Sci. 2011, 34 (22), 3253−3264. (c) Kamiński, M.; Gilgenast, E.; Przyjazny, A.; Romanik, G. J. Chromatogr., A 2006, 1122 (1−2), 153− 160. (4) Knothe, G. Journal of the American Oil Chemists’ Society 2006, 83 (10), 823−833. (5) Foglia, T. A.; Jones, K. C.; Phillips, J. G. Chromatographia 2005, 62 (3−4), 115−119. (6) (a) Knothe, G. J. Am. Oil Chem. Soc. 2001, 78 (10), 1025−1028. (b) Oliveira, J. S.; Montalvão, R.; Daher, L.; Suarez, P. A. Z.; Rubim, J. C. Talanta 2006, 69 (5), 1278−1284. (c) Sastry, G. S. R.; Krishna Murthy, A. S. R.; Prasad, P. R.; Bhuvaneswari, K.; Ravi, P. V. Energy Sources, Part A 2006, 28 (14), 1337−1342. (7) Fernanda Pimentel, M.; Ribeiro, G. M. G. S.; Da Cruz, R. S.; Stragevitch, L.; Pacheco Filho, J. G. A.; Teixeira, L. S. G. Microchem. J. 2006, 82 (2), 201−206. (8) (a) Monteiro, M. R.; Ambrozin, A. R. P.; da Silva Santos, M.; Boffo, E. F.; Pereira-Filho, E. R.; Lião, L. M.; Ferreira, A. G. Talanta 2009, 78 (3), 660−664. (b) Monteiro, M. R.; Ambrozin, A. R. P.; Lião, L. M.; Ferreira, A. G. Fuel 2009, 88 (4), 691−696. (9) (a) Akers, S. M.; Conkle, J. L.; Thomas, S. N.; Rider, K. B. J. Chem. Educ. 2006, 83 (2), 260−262. (b) Bladt, D.; Murray, S.; Gitch,
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CONCLUSION Pedagogically, this project has served as a great capstone for the instrumental analysis course. This experiment focuses on a quantitative determination of biodiesel in commercial diesel blends by applying several instrumental methods frequently covered in the undergraduate analytical chemistry curriculum, 1564
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B.; Trout, H.; Liberko, C. J. Chem. Educ. 2011, 88 (2), 201−203. (c) Bucholtz, E. C. J. Chem. Educ. 2007, 84 (2), 296−298. (d) Clarke, N. R.; Casey, J. P.; Brown, E. D.; Oneyma, E.; Donaghy, K. J. J. Chem. Educ. 2006, 83 (2), 257−259. (e) El Seoud, O. A.; Loffredo, C.; Galgano, P. D.; Sato, B. M.; Reichardt, C. J. Chem. Educ. 2011, 88 (9), 1293−1297. (f) Hoffman, A. R.; Britton, S. L.; Cadwell, K. D.; Walz, K. A. J. Chem. Educ. 2011, 88 (2), 197−200. (g) Stout, R. J. Chem. Educ. 2007, 84 (11), 1765. (h) Wagner, E. P.; Koehle, M. A.; Moyle, T. M.; Lambert, P. D. J. Chem. Educ. 2010, 87 (7), 711−713. (10) Pierce, K. M.; Schale, S. P.; Le, T. M.; Larson, J. C. J. Chem. Educ. 2011, 88 (6), 806−810. (11) Seelenbinder, J.; Higgins, F. Test Method for Low Level Detection of Biodiesel in Biesel Using the Agilent 5500t FTIR Spectrometer. In Agilent Technologies, 2011; Vol. 5990-7804EN. (12) Pinzi, S.; Alonso, F.; García Olmo, J.; Dorado, M. P. Fuel 2012, 92 (1), 354−359.
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