Article pubs.acs.org/EF
Development of an Online Raman Analysis Technique for Monitoring the Production of Biofuels Keyvan Mollaeian,† Suying Wei,‡ Mohammad R. Islam,† Bleinie Dickerson,† William E. Holmes,§ and Tracy J. Benson*,† †
Dan F. Smith Department of Chemical Engineering, Lamar University, P.O. Box 10053, Beaumont, Texas 77710, United States Analytical, Environmental, and Material Chemistry Laboratory, Chemistry and Biochemistry Department, Lamar University, Beaumont, Texas 77710, United States § Energy Institute, The University of Louisiana-Lafayette, Lafayette, Louisiana 70504, United States ‡
ABSTRACT: In this study, the feasibility of Raman spectroscopy for studying the transesterification of canola oil with dimethyl carbonate to biofuel using triazabicyclodecene modified Mg−Al layered double hydroxide as a catalyst was investigated. The conversion of the oil was monitored at certain intervals over 1 h. The height of the CC stretching mode of unsaturated fatty acids of the oil at 1655 cm−1 was measured to determine the conversion of the oil. Deconvolution algorithms were developed to differentiate between the peaks and optimize the spectra for quantitative analysis using Gaussian distribution. The developed Raman spectroscopy method was validated by gas chromatography analysis of the reaction.
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INTRODUCTION With increasing demands for fossil energies and instability of petroleum markets as well as rising atmospheric CO 2 concentrations, attention toward alternative fuels is growing.1−4 Biofuels are in the form of liquid or gas and are manufactured from renewable resources, such as lipid-type oils, trees, and switchgrasses.3,5,6 Utilization of biofuel decreases the emission of exogenous carbon dioxide, which results from consuming fossil fuels.5,7 When using biodiesel, unburned hydrocarbons, carbon monoxide, and particulate matter are decreased by up to 75% in exhaust fumes compared to petroleum diesel fuel.7 Biodiesel can be used in different concentrations with petroleum diesel in a diesel engine without any engine modification. Furthermore, biofuel has additional advantages, such as zero SOx emissions and higher lubricity.6,7 Traditional biodiesel production methods from edible and nonedible seed oils consist of oil extraction, purification, deacidification, dewaxing, esterification of free fatty acids, and transesterification of glyceride compounds.8 Biodiesel is produced by transesterification of animal fats or various vegetable oils (i.e., soybean, rapeseed, sunflower, canola, corn, cottonseed, peanuts, palm, and jatropha) with alcohols in the presence of different base or acid catalysts (e.g., KOH, NaOH, or H2SO4).1,3−6,9 However, there is much concern about the availability of vegetable oils for long-term biodiesel production. Generally, highly refined oils are used as feedstock, which accounts for more than 70% of total biodiesel production costs.8 Problems have also risen due to the production of glycerol, an unwanted byproduct, as well as the need for process wash water. The crude glycerol is of little value due to impurities such as wastewater after neutralization, residual methanol, methyl esters, oil/fat, soap, and free fatty acids (FFAs). As reported by our group, replacing methanol with dimethyl carbonate (DMC) as a methylating agent offers many processing, and possibly feedstock, advantages.10−12 In © 2016 American Chemical Society
addition, if a heterogeneous catalyst, such as triazabicyclodecene supported on a layered double hydroxide (TBD-LDH), is used, the process wastewater is eliminated from the manufacturing process.11 Scheme 1 shows the biofuel reaction that leads to the production of fatty acid methyl esters (FAMEs) and fatty acid glycerol carbonates (FAGCs). Analysis of these reactions for conversion and kinetic parameters often requires gas chromatography (GC) with time-consuming material preparation steps prior to the GC analysis. An alternate, fast analytical method would be beneficial to both researchers and producers alike. Raman spectroscopy is commonly used for characterization of materials, such as chemical bonds and symmetry of molecules.13,14 When using in situ Raman spectroscopy to monitor the reaction, time-resolved information about molecular structure, intermediates, mechanisms, and rate of reaction can be obtained.15 Osswald et al. (2007) used in situ Raman for quantitative analysis of the disorder in multiwalled carbon nanotubes through the density ratio.15 Using this approach, they were able to monitor and control the formation of defects.15 Bell et al. (1998) combined in situ Raman spectroscopy with statistics to study the kinetics and thermodynamic aspects of hydrolysis reactions.16 In this study, the conversion of canola oil to biofuel with TBD-LDH was investigated using in situ Raman spectroscopy. A method, including a deconvolution algorithm, was developed for monitoring the conversion of oil to biofuel using Raman spectroscopy. Since Raman can be used via a fiber optic cable and can offer real-time data, it is a superior choice in analytical techniques. Furthermore, our complicated reacting system, including a heterogeneous catalyst and reactants/products of similar molecular structure, required the development and Received: February 6, 2016 Revised: April 18, 2016 Published: April 20, 2016 4112
DOI: 10.1021/acs.energyfuels.6b00313 Energy Fuels 2016, 30, 4112−4117
Article
Energy & Fuels Scheme 1. Two-Step Transesterification of Triglyceride with DMC in the Presence of TBD-LDH
subsequent use of a deconvolution algorithm. To validate our method, the Raman results were compared to GC analysis.
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MATERIALS AND METHODS
Chemicals. Magnesium nitrate hexahydrate (99%), aluminum nitrate nonahydrate (98%), 1,5,7- triazabicyclo[4.4.0]dec-5-ene (TBD, 98%), sodium dodecyl sulfate (SDS, 98.5%), N-cetyl- N,N,Ntrimethylammonium bromide (CTAB, 99%), anhydrous N,Ndimethylformamide (DMF, 99.8%), (trimethoxysilane) 3-glycidyloxypropyl (3GPS, 98%), dimethyl carbonate (DMC, 99.8%), dichloromethane (99.8%), anhydrous sodium sulfate (99.8%), and ammonium hydroxide solution (ACS reagent, 28.0−30.0% NH3 basis) were purchased from Sigma-Aldrich. Refined canola oil was purchased from a local grocery store. Crude corn oil (4.5 wt% FFA) was obtained from Renewable Biofuels, Inc. (Port Neches, TX USA). Preparation of Catalyst. LDH (4:1 Mg:Al molar ratio) was prepared using the coprecipitation method. A solution containing 21.5 mmol of Al(NO3)3·9H2O and 86 mmol of Mg(NO3)2·6H2O in 80 mL of DI water was stirred at 68 °C under a nitrogen atmosphere and an ammonium solution was added dropwise to maintain a constant pH 10. The solution was then stirred for 24 h. The final precipitate was washed with DI water and then dried at 65 °C for 24 h. The resulting white powder was calcined at 450 °C for 4 h under a nitrogen atmosphere and then cooled to room temperature. TBD-LDH was then synthesized according to the procedure described by Islam et al. (2013), except the SDS/LDH ratio that was used for the anionic exchange was 3:1 (SDS/LDH).11 Kinetic Experiments. Reactions were performed in a 500 mL three-neck round-bottom flask using a magnetic stir bar for agitation. A Raman fiber optic probe (PerkinElmer Flex 400 with 785 nm laser) was inserted into the flask for collection of Raman spectra, as shown in Figure 1. The temperature was controlled using a heated stir plate and sand bath. Before each reaction, the oil and DMC were passed through sodium sulfate to remove any residual water. Typically, a mixture containing 136.5 g oil and 83.8 g DMC (6:1 DMC to oil molar ratio) was prepared and heated to 70 °C. A 3 wt% TBD-LDH catalyst (on the basis of oil) was then added to the reaction. Raman spectra were recorded at desired intervals; meanwhile, samples for GC comparison were withdrawn from the flask at the same interval followed by quenching with 2 mL of 1% H2SO4 and extracting with toluene containing 100 μg/mL butylated hydroxytoluene. A high-temperature GC analysis, as described by ASTM D6751, was used to determine the conversion of triglycerides.
Figure 1. Experimental setup of in situ monitoring of transesterification reaction: (1) stirrer and hot plate; (2) sand bath; (3) 3-neck round-bottom flask; (4) thermometer; (5) cooling water in; (6) cooling water out; (7) condenser; (8) Raman probe; (9) Raman spectroscope; (10) processor.
Figure 2. XRD patterns of (A) uncalcined LDH, (B) calcined LDH, and (C) SDS-LDH.
°C was 2.3 Å. Furthermore, introducing SDS into the layers had a significant impact on the basal spacing of LDH. This study shows that anionic exchange of SDS in LDH increases the dspacing up to 27.2 Å. A schematic illustration of TBD arrangements within LDH galleries is shown in Figure 3. Raman Analysis of the Catalyst. The Raman spectrum of LDH indicated the presence of nitrate within the layers. The asymmetric deformation mode υ4 of NO3 of LDH was recorded ∼750 cm−1. Islam et al. (2013) observed the symmetric stretching mode υ1 of NO3 at 1060 cm−1.11 Similarly, υ1 mode in calcined LDH sample was observed at 1046 cm−1 as shown
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RESULTS AND DISCUSSION XRD Analysis. The XRD patterns of LDHs with Mg/Al molar ratio of 4:1 are presented in Figure 2. Uncalcined LDHs’ d-spacing was 8.2 Å. The basal spacing for LDH calcined at 450 4113
DOI: 10.1021/acs.energyfuels.6b00313 Energy Fuels 2016, 30, 4112−4117
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cm−1 of the SDS-LDH spectrum was due to the asymmetric stretching mode of SO. The SO peaks and the absence of nitrate peak at 1046 cm−1 are evidence of intercalation of SDS within layers. The bands found at more than 1452 cm−1 of SDS-LDH spectrum are ascribed to the symmetric and asymmetric stretching of CH2 and CH3 bonds. Table 1 summarizes the assignments of major bands for LDH and SDSLDH spectra and their comparison with literature. The Raman shift of the region 600−1800 cm−1 for TBDLDH is shown in Figure 6. The presence of nitrate, sulfate anions, and TBD-3GPS were observed. The peak at 1058 cm−1 was assigned to the symmetric stretching mode of NO3. The scissoring mode of NH2 was observed around 1776 cm−1. Moreover, the bands at 1128 and 1304 cm−1 are ascribed as CH aromatic in plane bending and SO asymmetric stretching, respectively. The major bands of TBD-LDH and their assignments are shown in the Table 2. Reaction Monitoring of Biofuel Production using Raman Spectroscopy. Quantum theory expresses that each molecule possesses certain energy levels. When a molecule absorbs or emits energy, changeover between these levels with a consequent vibrational movement occurs. The surrounding atoms of a molecule play an important role on the frequency of a band and its dynamic behavior in spectroscopy.18 Carbonyl group frequencies in DMC and canola oil spectra are 1752 and 1748 cm−1, respectively. This slight change is because of the carbonyl group environment in each molecule. Raman spectra of oil, FAME, and DMC are shown in Figures 7 and 8. In addition, the spectrum line shape is affected by the summation of different vibrations.18 Quantitative analysis of the transesterification of triglyceride oil and DMC in the presence of TBD-LDH catalyst (Scheme 1) using the in situ Raman method was carried out. The experiment was performed to investigate the feasibility of monitoring the conversion of oil to biofuel. For the conversion of 1 mol of oil, 1 mol of DMC is required; however, the oil/ DMC molar ratio of 1:6 was used to shift the reaction equilibrium to the right. Subsequently, the reaction of 1 mol FAGC with excess DMC yields 1 mol of FAME and 1 mol of glycerol dicarbonate. Therefore, the conversion of 1 mol of oil with DMC produces 3 mol of FAME and 1 mol of glycerol dicarbonate. Raman spectra were collected at certain intervals over 1 h. (Figure 9). The intensity and height of the peaks at 1268, 1304, 1656, and 1748 cm−1 for CC, CH2, CC, and CO, respectively, were changed during the course of the reaction. All of these peaks decreased over time. The peak at 1656 cm−1 regarding CC of unsaturated fatty acids was used for quantitative analysis. To validate and to quantitate the reaction results, five standard mixtures of DMC, canola oil, and methyl oleate with different mass ratios were prepared to simulate the conversion of canola oil with product formation. In all mixtures, DMC to oil molar ratio was kept constant at 6:1 since DMC was in excess in the reactions. Mixture 1 represents the reactants where there is no conversion, and Mixture 5 represents complete conversion of oil to product. Raman spectra of these mixtures and a calibration curve for the CC stretching peak are shown in Figure 10. The Raman Spectra were deconvoluted with Gaussian distribution to optimize the spectra for quantitative analysis. Using Microsoft Excel, a table was developed with wavelength and Raman intensity as the first two columns. From numerical derivatization, the first derivative of the spectrum was used to
Figure 3. Schematic illustration of TBD-3GPS arrangement in the interlayer of Mg/Al LDH.
in Figure 4. In addition, bands around 416 and 576 cm−1 are attributed to the stretching vibration of Al−O−Al and Al−O− Mg bonds, respectively.
Figure 4. Raman spectrum of LDH before addition of SDS.
The Raman spectra of SDS and SDS-LDH (Figure 5) in the region of 900−1600 cm−1 were similar in that they contained
Figure 5. Raman spectra of (A) SDS and (B) SDS-LDH.
the main bands of SDS. The peaks below 1100 cm−1 can be assigned to the symmetric stretching of SO. However, formation of a weak shoulder at 1084 cm−1 was due to the intensity increase of the peak at 1064 cm−1. The change in intensity of these peaks can be attributed to environmental change of sulfate group that is on account of sulfate group binding with aluminum atom.17 The peak at 1299 4114
DOI: 10.1021/acs.energyfuels.6b00313 Energy Fuels 2016, 30, 4112−4117
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Energy & Fuels Table 1. Assignments of Major Raman Bands for LDH and SDS-LDH LDH
SDS-LDH
observed (cm−1)
literature11 (cm−1)
assignment
observed (cm−1)
literature11 (cm−1)
assignment
416 576 750 1046 1365
420 548 724 1060 1380
Al−O−Al stretching Al−O−Mg stretching NO3 asym. bending NO3 sym. stretching NO3 asym. stretching
1064 1299 1440 1452 2852 2884 2896 2920 2940
1064 1296 1440 1458 2848 2872 2904 2920 2936 2960
SO sym. stretching SO asym. stretching CH2 scissoring CH3 asym. bending CH2 sym. stretching CH3 sym. stretching CH2 asym. stretching CH2 asym. stretching CH3 asym. stretching CH3 asym. stretching
Figure 7. Raman spectra of methyl oleate and canola oil.
Figure 6. Raman spectra of (A) TBD and (B) TBD-LDH.
Table 2. Assignments of Major Raman Bands for TBD-LDH TBD-LDH observed (cm−1)
literature11 (cm−1)
assignment
632 708 840 1058 1128 1200 1304 1449 1776
636 708 846 1060 1128 1198 1296 1454 1776
NH2 wagging, NH out of plane bending NH out of plane bending NH2 wagging, NH out of plane bending NO3 sym. stretching CH aromatic in plane bending NH2 rocking, NH in plane bending SO asym. stretching NH in plane bending, C−N stretching NH2 scissoring
Figure 8. Raman spectrum of DMC.
identify the peaks. When identifying hidden shoulders and peaks, reasonable initial guesses were applied. A table of halfwidth at half-maximum, w1/2, and band maximum (maximum intensity, Amax, and wavenumber, υ̃max ) of the peaks was developed. Half width, w1/2, was estimated by using a peak that was not overlapping with the others. The band profile, therefore, was calculated using
Figure 9. Raman spectra (collected in situ) of the reaction.
⎡ (υ ̃ − υ ̃ )2 ⎤ max ⎥ A = A max exp⎢ 2 ⎢⎣ 2w1/2 ⎥⎦
minimize the SSR by changing band max and half width of the peaks. After deconvolution, the height of the peak was measured from the baseline to band maximum. Figure 11 shows the
Band profiles summation and sum of square of residuals (SSR) were calculated in different columns. Solver was used to 4115
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Figure 12. Plot of externally studentized residuals versus fitted intensity.
Figure 10. (A) Raman spectra of standard mixtures with (B) the corresponding calibration curve using peak height.
Figure 13. Comparison of raw and fitted absorbance values based on transformed X.
dynamic behavior of the peak height at 1656 cm−1 over 1 h. The height of the CC stretching peak decreases with the production of biofuel.
optimized values is close to the raw data’s trend line, indicating minimization of the residuals. That is to say, the Gaussian model adequately describes the spectrum. As previously mentioned, when conversion increases in the calibration curve, the intensity and height of the peak decreases. In other words, the fatty acid detachment from oil and production of FAME changes the molecular environment of CC. Formation of FAMEs (i.e., molecules smaller than triglycerides) contributes to a decrease in intensity and height of the CC stretching peak. Comparatively, the Raman method was in agreement with the results obtained by the GC (Figure 14). Note that error bars in Figure 14 are from the standard deviations of duplicate runs using the online Raman procedure where an aliquot was removed from the reactor for GC analysis (as described above). As mentioned previously, the substantial costs associated with refining crude vegetable oils prior to biofuel conversion limits economic viability of the biofuel industry. Our lab has
Figure 11. Behavior of the CC peak of the reaction over 1 h.
Externally studentized residual, ti, was calculated using diagonal elements of hat matrix, H, to check the model adequacy. Residual plot of fitted values for one of the reaction spectra is shown in Figure 12. The model shows linearity at low intensities. However, nonlinearity of the model was observed when the intensity was greater than 500 indicating the model adequacy. A statistical method was developed to check the functionality of the Gaussian distribution for Raman spectra of the reaction. A new X was introduced as follows ⎡ (υ ̃ − υ ̃ )2 ⎤ max ⎥ X = exp⎢ 2 ⎢⎣ 2w1/2 ⎥⎦
X′ was also obtained using optimized values of w1/2 and υ̃max . Plots of A/Amax versus X and fitted A/Amax versus X′ were compared as is shown in Figure 13. The line obtained from the
Figure 14. Concentration of triglyceride oil over 1 h of reaction with DMC using TBD-LDH catalyst (Temp. = 70 °C). 4116
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(4) Gharat, N.; Rathod, V. K. Ultrason. Sonochem. 2013, 20, 900−905. (5) Fabbri, D.; Bevoni, V.; Notari, M.; Rivetti, F. Fuel 2007, 86, 690− 697. (6) Min, J. Y.; Lee, E. Y. Biotechnol. Lett. 2011, 33, 1789−1796. (7) Lai, E. P. C. Pet. Environ. Biotechnol. 2014, 5, e122. (8) Jiang, Y.; Li, D.; Li, Y.; Gao, J.; Zhou, L.; He, Y. Bioresour. Technol. 2013, 150, 50−54. (9) Ma, F.; Hanna, M. A. Bioresour. Technol. 1999, 70, 1−15. (10) Islam, M. R.; Kurle, Y. M.; Gossage, J. L.; Benson, T. J. Energy Fuels 2013, 27, 1564−1569. (11) Islam, M. R.; Guo, Z.; Rutman, D.; Benson, T. J. RSC Adv. 2013, 3, 24247−24255. (12) Kurle, Y. M.; Islam, M. R.; Benson, T. J. Fuel Process. Technol. 2013, 114, 49−57. (13) Lee, M.; Kim, H.; Rhee, H.; Choo, J. Bull. Korean Chem. Soc. 2003, 24, 205−208. (14) Zhao, J.; McCreery, R. L.; Frankel, G. J. Electrochem. Soc. 1998, 145, 2258−2264. (15) Osswald, S.; Havel, M.; Gogotsi, Y. J. Raman Spectrosc. 2007, 38, 728−736. (16) Bell, W. C.; Booksh, K. S.; Myrick, M. L. Anal. Chem. 1998, 70, 332−339. (17) Burrueco, M. I.; Mora, M.; Jiḿ enez-Sanchidrían, C.; Ruiz, J. R. J. Mol. Struct. 2013, 1034, 38−42. (18) Bradley, M. Curve Fitting in Raman and IR Spectroscopy: Basic Theory of Line Shapes and Applications; Application Note: 50733; Thermo Fisher Scientific: Madison, WI, 2007.
tested the conversion of crude corn oil to biofuel using DMC and TBD-LDH catalyst. The crude corn oil used in this experiment was a black, tarry liquid having a similar appearance to that of crude petroleum. Figure 15 illustrates the utility of
Figure 15. Raman comparison of reacted versus unreacted crude corn oil (4.5 wt% FFA, Trxn = 70 °C).
the online Raman analytical technique to monitor the conversion of the crude corn oil without degumming or acid esterification of the FFAs prior to the transesterification reaction.
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CONCLUSION An in situ Raman method has been developed for monitoring the transesterification of triglyceride oils with dimethyl carbonate (DMC) using a heterogeneous catalyst. A DMC/ oil molar ratio of 6:1 and a 3 wt% triazabicyclodecene modified layered double hydroxide (TBD-LDH) was used to produce a biofuel containing FAMEs and FAGCs. When fatty acids of the oil are detached from the glycerol backbone, the height of the CC stretching peak decreases, indicating conversion of the oil. Raman spectra were deconvoluted with Gaussian distribution for quantification. Model adequacy was checked with statistical method tools indicating that Gaussian is well fitting for the reaction spectra. Raman results show that the conversion of the oil is 62% over 1h. Interestingly enough, 55% conversion was obtained over 5 min signifying that most of the oil was converted in the beginning of the reaction. Reactions using a crude corn oil validate that Raman is a powerful tool for in situ monitoring of heterogeneous reactions for a broad range of triglyceride-type oils.
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AUTHOR INFORMATION
Corresponding Author
*Telephone: +1-(409)-880-7536; Fax: +1-(409)-880-2197; Email:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS The authors acknowledge the financial support from the Texas Hazardous Waste Research Center (513LUB0022H). The authors also gratefully thank Dan Rutman for performing XRD analyses.
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REFERENCES
(1) Corma, A.; Garcia, H. J. Catal. 2013, 308, 168−175. (2) Ilham, Z.; Saka, S. Bioresour. Technol. 2009, 100, 1793−1796. (3) Song, C. Catal. Today 2006, 115, 2−32. 4117
DOI: 10.1021/acs.energyfuels.6b00313 Energy Fuels 2016, 30, 4112−4117
