In the Laboratory edited by
Molecular Modeling Exercises and Experiments
Alan J. Shusterman
Assigning the NMR Spectrum of Glycidol: An Advanced Organic Chemistry Exercise
Reed College Portland, OR 97202-8199
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Eric Helms,* Nicholas Arpaia, and Melissa Widener Department of Chemistry, State University of New York College at Geneseo, Geneseo, NY 14454; *
[email protected] FT-NMR spectrometers are finding their way into more undergraduate departments, making their use widespread in undergraduate laboratories as evidenced by a number of articles in recent issues of this Journal (1–3). In one article, Alonso and Warren note that it is not necessary to give students extensive theoretical background to teach them how to interpret 2-D NMR spectra and that having students exposed to various NMR techniques earlier rather than later has facilitated research at their institution (1). Desktop molecular modeling software has become accessible to undergraduate departments and is finding more use in undergraduate laboratories (4–7). In this exercise, we make use of Spartan ES (8) to model the conformations of a small molecule. This modeling serves two purposes: First, it functions as a practical tool that allows students to determine dihedral angles for each conformation. Second, the modeling gives students a visual tool to understand the effects of electron density on the conformations of small molecules. This exercise is designed to be part of a course in advanced organic chemistry laboratory techniques and is presented early in the course. The objective of the exercise is to combine 1-D NMR, 2-D NMR, and conformational modeling to assign all of the proton and carbon resonances of a deceptively simple compound, providing a foundation upon which more rigorous experiments involving more complex molecules can be introduced. Because of the limited number of atoms and its apparent molecular simplicity, we find 2,3-epoxy-1-propanol (glycidol) is well suited for this purpose. The exercise shows the logical progression of how each NMR technique provides a specific piece of information aiding in the complete assignment of the peaks. In the process, experience is gained using coupling constants and computation to correctly assign two sets of diastereotopic protons. Organization The exercise is designed for one laboratory period. Since the exercise is for an advanced organic chemistry course, it is assumed that the students have had an introduction to NMR in their previous coursework as well as prior experience using modeling programs. As each new topic or spectrum is encountered, a short lecture is used to provide the necessary background and tools to continue the analysis. We feel that doing so helps avoid “information overload” that results from presenting all of the material at once. Students are first shown the line-bond structure of glycidol and asked to construct a handheld molecular model. A consensus prediction for the 1H and 13C spectrum is produced. The experimental spectra are then provided at the
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appropriate time, starting with the proton and carbon spectra. Alternatively, one could have the students acquire the proton and carbon spectra or process the FIDs. However, owing to the toxicity of glycidol, we do not recommend this unless strict supervision of sample preparation and disposal can be provided. The next spectrum introduced is the DEPT135 followed by the HETCOR spectrum, and ending with the COSY spectrum. The exercise concludes with conformational modeling that allows complete assignment of all the protons. The primary computational package used is Spartan ES (8). Students work individually or in pairs on a Dell Latitude D600 laptop with a 1.6 GHz Pentium M processor and 256 MB of RAM running Windows XP. Hartree–Fock ab initio calculations are run using the 6-31G* basis set. The conformer distribution calculation takes approximately 45 minutes at this level of theory and gives satisfactory results. The spectra supplied to the students were run on a Bruker Avance DPX 300 using a sample that contained 25 µL of glycidol in 0.75 mL CDCl3 with 0.1% tetramethylsilane (TMS) as a reference. Hazards There are no significant hazards for this exercise as described. Results Students note that the experimental proton spectrum is much more complex than predicted (Figure 1). Students find the assignment of the peaks with confidence in both spectra (1H and 13C) problematic at this point. The DEPT-135 spectrum allows the methine carbon at C2 (52.8 ppm) to be distinguished from the methylene carbons at C1 and C3 whose signals have been inverted (62.5 and 44.9 ppm, respectively). Having determined the position of C2, the methine proton D is easily assigned to the signal at 3.16 ppm using the HETCOR spectrum. Also using the HETCOR spectrum, students note that the apparent triplet at 2.53 ppm is not correlated with a signal in the carbon spectrum and can therefore be assigned to the hydroxyl proton A. To distinguish the two methylene groups, one can use the 2-D homonuclear shift correlation spectroscopy (COSY) spectrum to trace the proton connectivity in the molecule. By observing the offaxis contours, one is able to ascertain which protons are coupled. By using the hydroxyl proton resonance, one is able to distinguish the non-oxirane methylene protons at C1 from the oxirane methylene protons at C3 by the off-axis contours.
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In the Laboratory
Figure 1. The lowest energy conformation of glycidol shown with hydrogen atoms labeled A–F, carbon atoms numbered 1–3, and oxygen atoms unlabeled. The 300 MHz proton NMR spectrum is shown; the small peaks result from impurities (mainly diglycidyl ether) in the sample as purchased. These peaks generally do not interfere with the analysis.
This information leads to the assignment of the two ddd at 3.60 and 3.95 ppm to protons B and C on C1. The remaining two resonances at 2.76 and 2.82 ppm are protons E and F on C3. At this point in the exercise, the assignment of the carbon spectrum can be completed and protons A and D can be assigned to individual signals in the proton spectrum. Next, the diastereotopic protons at C3 and then C1 are assigned to their peaks. Vicinal coupling constants are dependent upon the dihedral angles, which for proton E is ∼0⬚ and for proton F ∼150⬚. Students can find these values by looking at their handheld molecular models or by building a model of glycidol on the computer. Looking at the Karplus curve, proton E should have a larger vicinal coupling constant than proton F. After obtaining the coupling constants from the actual proton spectrum, students assign the apparent triplet at 2.82 ppm (2J = 5 Hz, 3Jcis = 5 Hz) to proton E and the dd at 2.76 ppm (2J = 5 Hz, 3Jtrans = 2.7 Hz) to proton F. These assignments and coupling constants match well with literature values (9). The assignment of protons B and C to their individual resonances begins with a Monte Carlo conformational search using a RHF兾6-31G* calculation. The results can be represented in a plot of relative energy versus conformation as shown in Figure 2. Viewing the electron density map of the lowest and highest energy conformations (Figure 3) suggests a reason for the differences in energy—the lowest energy conformation shows an electrostatic interaction of the hydroxyl proton and the oxirane oxygen atom that has been suggested to be a weak hydrogen bond (10). For a molecule in which conformational exchange is fast on the NMR time scale, the observed signal width, Jobs, is simply the summation of each conformation’s mole fraction,
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Figure 2. Plot of the relative energy (in kJ/mol) versus conformation for glycidol. The graph was made using a RHF/6-31G* Monte Carlo conformational search in Spartan ES that found nine conformations for glycidol. The structure of each conformation is shown below the graph, numbered in order of increasing relative energy. Before running the calculation, most students predict that the fourth conformation, which places the hydroxyl anti to the oxirane oxygen atom, is the most stable based on their hand-held molecular model.
Figure 3. The electrostatic potential maps for the lowest (left) and highest (right) energy conformations of glycidol: numbers 1 and 9, respectively, from Figure 2. (This image is shown in color on p 1235.)
ni, multiplied by its coupling constant. A simple expression of this is Jobs = ∑ ni Ji i
(1)
The mole fraction of each conformation is obtained from Spartan ES. Using the dihedral angles for the two lowest energy conformations, the vicinal coupling constants are calculated using the Haasnoot equation (11) and a Web-based coupling constant calculator (12). The contribution to the signal width from the CHOH vicinal coupling can be found similarly from the modeling and a Web-based coupling constant calculator (13) based on the work of Fraser et al. (14). Lastly, the geminal coupling constant can be extracted from the ddd by following the methods outlined by Hoye (15) or Mann (16). The largest coupling constant is the geminal cou-
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formations. This experiment provides a wealth of experience on a simple molecule and sets the stage for more challenging problems. Acknowledgments This work was supported by a Merck/AAAS Undergraduate Research Award and by the Geneseo Foundation. W
Supplemental Material
Detailed instructor notes, all spectra, and additional details are available in this issue of JCE Online. Literature Cited
Figure 4. The final assignments for the protons of glycidol.
pling constant. Using this method, one finds the geminal coupling constant to be ∼12.7 Hz, matching the literature value. This value is now used in conjunction with the other two vicinal coupling constants to find the signal widths. Students produce a spreadsheet with the dihedral angle and coupling constant data, use eq 1, and predict that proton B has a signal width of 24.5 Hz and that proton C has a signal width of 18.4 Hz. Looking at the actual proton spectrum, the ddd at 3.6 ppm has a width of ∼24 Hz and the ddd at 3.95 ppm has a width of ∼21 Hz. With these data, students are able to assign proton B to the signal at 3.6 ppm and proton C to the ddd at 3.95 ppm. Putting all of this information together, students assign the proton NMR spectrum as shown in Figure 4. Conclusions The interpretation of 1-D and 2-D NMR experiments has provided specific pieces of information needed to assign the proton and carbon NMR spectra of glycidol. Students learn about diastereotopicity and its consequences in proton NMR spectra. Geminal and vicinal coupling constants have been obtained from experimental spectra. The consequences of conformational flexibility in NMR spectra are seen and experience gained in molecular modeling of con-
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1. Alonso, David E.; Warren, Steven E. J. Chem. Educ. 2005, 82, 1385–1386. 2. Alty, Lisa T. J. Chem. Educ. 2005, 82, 1387–1389. 3. Glagovich, Neil M.; Shine, Timothy D. J. Chem. Educ. 2005, 82, 1382–1384. 4. Kutateladze, A. G.; Hornback, J. M. J. Chem. Educ. 2001, 78, 81–82. 5. LeFevre, J. W.; McNeill, K. I.; Moore, J. L. J. Chem. Educ. 2001, 78, 535–537. 6. Brown, K. C.; Tyson, R. L.; Weil, J. A. J. Chem. Educ. 1998, 75, 1632–1635. 7. Streit, Bennett R.; Geiger, David K. J. Chem. Educ. 2005, 82, 111–115. 8. Spartan ES, version 2.0.1; Wavefunction, Inc: Irving, CA. See http://www.wavefun.com for more information about this program (accessed Apr 2007). 9. Leifer, A.; Goldstein, H. L. Applied Spectroscopy 1968, 22, 773– 776. 10. Brooks, W. V. F.; Sastry, K. V. L. N. Can. J. Chem. 1975, 53, 2247–2251. 11. Haasnoot, C. A. G.; DeLeeuw, F. A. A. M.; Altona, C. Tetrahedron 1980, 36, 2783–2792. 12. Vicinal Proton–Proton Coupling Constants. http:// www.casper.organ.su.se/ke3690/jhh.html (accessed Apr 2007). 13. Karplus Calculator. http://www.casper.organ.su.se/ke3690/ karplus.html (accessed Apr 2007). 14. Fraser, R. R.; Kaufman, M.; Morand, P.; Govil, G. Can. J. Chem. 1969, 47, 403–409. 15. (a) Hoye, Thomas R.; Zhao, Hongyu. J. Org. Chem. 2002, 67, 4014–4016. (b) Hoye, Thomas R.; Hanson, Paul R.; Vyvyan, James R. J. Org. Chem. 1994, 59, 4096–4103. 16. Mann, Brian E. J. Chem. Educ. 1995, 72, 614–615.
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