In the Laboratory
Quantitation of Phenol Levels in Oil of Wintergreen Using Gas Chromatography–Mass Spectrometry with Selected Ion Monitoring
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A Quantitative Analysis Laboratory Experiment Robert M. Sobel, David S. Ballantine, and Victor Ryzhov* Department of Chemistry and Biochemistry, Northern Illinois University, De Kalb, IL 60115; *
[email protected] Industrial application of gas chromatography–mass spectrometry (GC–MS) analysis has grown in popularity since the advent of GC–MS instrumentation in the late 1970s (1– 4). This powerful technique can be used to elucidate components of a complex mixture while offering the benefits of high-precision quantitative analysis. Techniques and instrumentation have become commonplace within many academic and industrial settings necessitating the introduction of GC– MS techniques within the undergraduate curriculum. The scope of representative undergraduate laboratories involving GC–MS analysis includes: instrumental analysis (5), forensics (6), component identification for aroma and flavoring (7), environmental monitoring (8), biochemical (9, 10), and organic or physical organic (11, 12). A review of the listed undergraduate experiments in this Journal reveals only two laboratory experiments exploiting the quantitative or qualitative advantages of selected ion monitoring (SIM) (5, 10). The undergraduate laboratory outlined here examines the quantitative aspects of SIM and how this technique relates to natural-products chemistry. Natural products used for industrial applications have a wide variance in their chemical composition. Many factors can affect the concentration of certain components found in natural products. These factors include climate, soil conditions, and species type. Certain components, such as phenol, are sometimes found in relatively high concentrations such that the natural product is not suitable for certain applications based upon the smell, palatability, and toxicity of this compound. While there seems to be a concern with phenol, it should be noted that trace levels of phenol commonly found in many raw materials pose little health risk to the consumer and that most natural products are generally tested because phenol imparts an undesirable medicinal flavor to foodstuffs (13). The level of phenol is particularly relevant to the natural product oil of wintergreen, used to flavor many consumer food products. This creates the need for analysis of phenol content in natural oil of wintergreen before it can be used for a specific application. Raw methyl salicylate oil, or oil of wintergreen, can be obtained from various natural sources. Methyl salicylate was first isolated from the leaves of the wintergreen plant Gaultheria procumbens (14). Another source of the methyl salicylate that produces a higher yield is the bark of certain birch trees (Betula alleghanenis and Betula lenta). The leaves or bark are steam-distilled allowing for the extraction of the raw wintergreen oil. This classical separation technique produces crude methyl salicylate oil containing considerable quanti-
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ties of natural contaminants (i.e., phenols, menthols, and salicylates). While natural wintergreen oil is readily used in many food industry applications, it is commonly examined for its phenol concentration to determine the level of refining necessary to maximize methyl salicylate concentration and minimizing the content of phenol and other contaminants. The chromatographic method provided here takes advantage of selected ion monitoring. SIM is a process where a predetermined m兾z is monitored by the quadrupole mass filter (15). If one selects the primary ion (base peak ion) of the component of interest (i.e., m兾z 94 for phenol), the analysis can be limited to components that contain this ion. This greatly reduces analysis time and concern for co-eluting species. Co-elution is no longer problematic for analysis because eluates of different m兾z will not be detected unless they, too, contain the ion of with m兾z 94 in their fragmentation pattern. This means that chromatographic separation times can be substantially shortened and fine-tuned to components with this specific m兾z. Separations that would normally take an hour or more can now be completed in minutes (by using shorter columns, faster temperature gradient, or higher head pressures in conjunction with SIM). Other merits of SIM include: lower detection limits, better chromatographic resolution, and enhanced precision. A typical spectrum scan rate for a mass window of 30–500 m兾z is 2.0 scans兾s. Decreasing the size of the mass window can significantly increase the scan rate of the instrument. Lower detection limits are possible because signal-to-noise (S兾N) ratios are increased. The S兾N is substantially increased because more scans are performed for the ion of interest. The increased number of scans directly relates to signal averaging, which effectively reduces responses from interfering compounds and noise. Overall, the SIM process fulfills the industry’s ever-growing requirement for speed, high precision, and efficiency of analysis. This experiment is suitable for chemistry or biochemistry majors enrolled in a quantitative analysis (or instrumental analysis) course. To keep this experiment within a typical laboratory time frame, multiple runs of standards and unknowns were not performed. The authors stress that quantitative applications, such as this one, should use multiple analyses for proper calibration of data if laboratory time permits. This experiment was performed on an HP (Agilent) GC–MS; it can be easily adapted to any available GC–MS system. A typical laboratory group can acquire calibration data and measure the concentration of phenol within a 1.5– 2 hour time frame.
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In the Laboratory
Experimental
Overview A common approach for calibrating concentrations is through the use of an internal standard. The internal standard method offers high precision because it alleviates uncertainties introduced by sample injection and variations in detector response. Students obtain SIM data for their phenol standards and unknown using the procedure outlined in the laboratory handout (see the Supplemental MaterialW). HP ChemStation software is used to integrate peaks and determine the peak areas of the dodecane internal standard and of phenol. A calibration plot can be created from the relative peak area (phenol兾dodecane). The unknown phenol concentration is determined using the linear regression obtained from calibration data. Finally, students compare the SIM results with a chromatogram obtained through the use of scanning a larger m兾z range. Silanization of Glassware It is highly recommended that all glassware be silanized to prevent phenol from adsorbing to the glassware surfaces. Silanization can be done beforehand and is stable for about six months. First, glassware (i.e., flask, sample vials) are rinsed with absolute methanol and allowed to dry. Next, all glassware is filled with a 3% (v兾v) solution of hexamethyldisilazine in hexane and allowed to stand for one hour. Finally, the glassware is rinsed again with absolute methanol and are ready for use. Standards and Unknown Solutions A 60 µg兾mL dodecane internal standard (ISTD) stock solution of solvent was prepared by combining 40 mL of dodecane with dichloromethane (DCM) in a 500-mL volumetric flask. About 0.1 g of phenol, recorded to the nearest tenth of a milligram, is dissolved in a silanized 250-mL volumetric flask with ISTD, creating a 400 µg兾mL phenol standard stock solution. A 2-mL aliquot is pulled from the 400 µg兾mL phenol stock solution and is used to create the first of the four standards. This aliquot is combined in a 5-mL silanized volumetric flask with ISTD solution filled to the mark creating a 160 µg兾mL phenol solution. A serial dilution is performed starting with the 160 µg兾mL solution by using 2-mL aliquots of each successive standard into 5-mL silanized volumetric flasks. Each standard is filled to the mark with ISTD stock solution before the next aliquot is taken. Standards with the following concentrations were produced: 160, 64, 26, and 10 µg兾mL. A 100-mL sample of natural methyl salicylate was combined with 8 µL of pure n-dodecane creating a natural sample spiked with 60 µg兾mL of dodecane. Instrumentation The chromatographic system used was a Hewlett Packard 6980 Series II gas chromatograph outfitted with a HP-Wax capillary column (30-m length; 250-mm i.d.; 0.50-mm film). The GC was connected inline with a Hewlett Packard 5973 Mass Selective Detector (MSD) operated by HP Enhanced ChemStation Software Version B.01.00. Sample volumes of 1 µL were injected at a column-head pressure of 4.15 psi with a split ratio of 15:1 at a flow rate of 9.3 cm3兾min. The GC
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Figure 1. SIM of natural wintergreen oil. Phenol elutes at 8.84 min.
oven was set to an initial temperature of 75 ⬚C and held for 2.00 min. The oven temperature was increased to a final temperature of 230 ⬚C using a ramp of 28 ⬚C兾min and held for 3.00 min for a total analysis time of 10.54 min. The ion source potential was set to 70 eV with a source and transfer line temperature of 250 ⬚C. The MSD was programmed with a 3.00 min solvent delay after which the m兾z 57 was monitored until 8.00 min for detection of dodecane internal standard. After 8.00 min the m兾z 94 ion was monitored for the remainder of the run. Both SIM were scanned at a rate of 42.6 scans兾s with a m兾z window of +1 m兾z. The natural sample’s primary constituent, methyl salicylate, elutes from the column from 8.00 to 8.50 min. During this elution period, to extend filament and detector life, it is highly recommended that the MSD filament and detector be turned off (i.e., latent solvent delay). Hazards Skin and eye contact of the standards and unknowns should be avoided owing to the presence of phenol and dichloromethane. Dichloromethane is harmful by inhalation. The liquid irritates the eyes. Phenol is toxic in contact with skin and if swallowed. It also causes burns. The vapors of both compounds irritate the eyes and respiratory system. It is recommended that the laboratory instructor or students performing this procedure wear gloves while preparing the glassware (silanization), creating the standards, and injecting the sample on the GC. Standards should be prepared in a fume hood to minimize exposure of phenol and chlorinated solvent vapors. Results A linear regression of the phenol standards was performed and aided in determining the concentration of phenol in natural wintergreen oil. The data exhibit a good dynamic linear range for phenol concentration with an r 2 value of 0.9991. The sample of natural wintergreen oil containing 63 µg兾mL of dodecane was injected and analyzed using the SIM approach (Figure 1 shows natural wintergreen oil SIM). A value of 1.145 was obtained as the relative peak
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In the Laboratory
area in the unknown relating to a phenol concentration of 66.0 µg兾mL in the unknown. An optional step, further illustrating the benefits of SIM, is to perform another measurement of the wintergreen sample without using the SIM mode. W
Supplemental Material
Detailed instructor notes, including the SIM plots of the standard phenol solutions, the calibration plot, and the SIM plot of natural oil of wintergreen, and step-by-step instructions for students are available in this issue of JCE Online. Acknowledgments This work was supported by the Northern Illinois University Department of Chemistry and Biochemistry. The authors thank Flavors of North America Inc. for supplying the specialty chemicals (natural oil of wintergreen and pure methyl salicylate) used for this experiment. Literature Cited 1. Hirschfeld, T. Anal. Chem. 1980, 52, 297A. 2. Wilkins, C. L. Science 1983, 222, 291.
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3. Wilkins, C. L. Anal. Chem. 1987, 59, 571A. 4. Fuoco, R.; Shafer, K. H.; Griffths, P. R. Anal. Chem. 1986, 58, 3249–3254. 5. Brush, R. C.; Rice, G. W. J. Chem. Educ. 1994, 71, A293– A296. 6. Sodeman, D. A.; Lillard, S. J. J. Chem. Educ. 2001, 78, 1228– 1230. 7. Knupp, G.; Kusch, P.; Neugebauer, M. J. Chem. Educ. 2002, 79, 98–100. 8. Quach, D. T.; Ciszkowski, N. A.; Finalyson-Pitts, B. J. J. Chem. Educ. 1998, 75, 1595. 9. Bender, J. D.; Catino, A. J.; Hess, K. R.; Lassman, M. E.; Leber, P. A.; Reinard, M. D.; Strotman, N. A. J. Chem. Educ. 2000, 77, 1466–1468. 10. Hamann, C. S.; Myers, D. P.; Rittle, K. J.; Wirth, E. F.; Moe, O. A. J. Chem. Educ. 1991, 68, 438–442. 11. Schildcrout, S. M. J. Chem. Educ. 2000, 77, 501–502. 12. Pelter, M. W.; Macudzinski, R. M. J. Chem. Educ. 1999, 76, 826. 13. Gyorik, M.; Herpai, Z.; Szecsenyi, L.; Varga, L.; Szigeti, J. J. Agric. Food Chem. 2003, 51, 5222–5225. 14. Lehman, J. W. Operational Organic Chemistry, 2nd ed.; Prentice-Hall, Inc.: Upper Saddle River, NJ, 1988. 15. Siuzdak, G. Mass Spectrometry for Biotechnology; Academic Press: San Diego, CA, 1996.
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