Teaching 1H NMR Spectrometry Using Computer Modeling - Journal

Use of computer modeling for teaching 1H NMR spectroscopy is described. The direction of the induced magnetic field is clarified by displaying the ele...
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Teaching with Technology

James P. Birk Arizona State University Tempe, AZ 85287

Teaching 1H NMR Spectrometry Using Computer Modeling

W

Yoichi Habata* and Sadatoshi Akabori Department of Chemistry, Faculty of Science, Toho University, Funabashi, Chiba 274-8510, Japan; *[email protected]

Molecular modeling by computer is used not only as a research tool but also as an educational tool for chemistry. A lot of educational software for chemistry is available (1) and some textbooks of organic chemistry provide a CD-ROM that contains molecular modeling data and animation (2). In addition, useful and low-cost molecular modeling software has been marketed (3), enabling one to perform molecular mechanics and high-level semiempirical and ab initio calculations without an extensive knowledge of quantum chemistry and computer programming. Now teachers are able to use not only educational software and molecular modeling data in the CD-ROM included with textbooks, but also modeling data from the low-cost modeling software. Molecular modeling by computer is used to display stereochemistry, molecular orbitals, structure of transition states, progress of reactions and simulated vibrational frequencies. In teaching spectroscopy, display of the simulated vibrational frequencies and molecular orbitals will be very effective when

Figure 1. (a) Ring current effects in benzene; (b) deshielding of ethylenic; and (c) shielding of acetylenic protons.

precise IR and UV–vis spectroscopy are available. Students can view motions of IR vibrations on the personal computer, and UV–vis absorption wavelengths can be estimated from the energy difference between HOMO and LUMO values (2f, 3b, 3c). However, there are few examples of the use of molecular modeling for teaching 1H NMR spectroscopy, which is the most-used spectroscopic tool in organic chemistry (2f, pp 262–264). Here we report new ideas for teaching 1 H NMR spectrometry using the computer modeling. The Electrostatic Potential Surface for Describing Magnetic Anisotropy Effects In textbooks that describe 1H NMR spectroscopy (4 ), ring current effects in benzene, deshielding of ethylenic protons, and shielding of acetylenic protons are explained as shown in Figure 1. Although students can easily understand the ring current effects in benzene, some of them question why the direction of the induced magnetic line of force differs in acetylene and ethylene.1 Figure 1 does not give a clear answer. Figure 2 shows electrostatic potential surfaces for benzene, ethylene, and acetylene. The electrostatic potential is a function describing the energy of interaction of a point positive charge with the nuclei and the fixed charge distribution of a molecule (5). That is to say, the electrostatic potential surface shows the location of the π electrons. In benzene and ethylene, the π electrons lie on the top and bottom of the ring or doublebond planes and the induced magnetic line of force is perpendicular to these planes. On the other hand, the induced magnetic line of force in acetylene is along the molecule, because the π electrons in acetylene surround the C–C triple bond. The electrostatic potential surfaces offer a clear answer to why the induced magnetic line is different in ethylene and acetylene. The electrostatic potential surface can be used to explain the induced magnetic line for more complicated molecules. [18]Annulene (see structure) is a typical example. The electrostatic potential map of the molecule (Fig. 3) shows that a “big hamburger bun“ of π electrons lies on top and bottom of the molecule and covers the inside protons. H

H

H H

H

H

H

H H

Figure 3. Electrostatic potential of [18]annulene.

H

H

H

H

Figure 2. Electrostatic potential of (a) benzene, (b) ethylene, and (c) actylene.

H H

H H

H

[18]annulene

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The Electrostatic Potential Map for Describing of the Electronegativity Effects The chemical shift reflects the magnetic field environment in the neighborhood of the proton. The magnetic field environment is also an electronic environment. Therefore, the chemical shift is affected by the electronegativity of the neighboring groups. The charge distribution of the circumference of the proton can be visualized by an electrostatic potential map, a graph that shows the value of the electrostatic potential on an electron density iso-surface corresponding to a van der Waals surface (6 ). In the map, blue and red mean positively and negatively charged regions, respectively. A darker blue indicates that the proton is more deshielded. Figure 4 shows the electrostatic potential maps for CHCl3, CH2Cl2 and CH3Cl; color versions of this map may be found in the Table of Contents and in JCE Online.W The methine proton of CHCl3 is the darkest blue followed; the methylene protons of CH2Cl2 and methyl protons of CH3Cl are progressively lighter blue, the order corresponding to the chemical shift of these molecules. Electrostatic potential maps can also visualize the difference in the chemical shifts of methyl protons among CH3F, CH3Cl, CH3Br, and CH3I and which of the protons on the α- and β-carbon atoms in α,β-unsaturated ketones and vinyl methyl ether appear in the higher magnetic field.

Figure 4. Electrostatic potential maps of (a) CHCl3, (b) CH2Cl2, and (c) CH3Cl.

H7a 3.5 Hz

Hendo

The Molecular Orbital for Describing the Long-Range Coupling in Bicyclic Systems Long-range coupling between protons arranged in a W in a bicyclo ring system is an interesting phenomenon in NMR spectrometry and is introduced in most textbooks. However, to the best of our knowledge, only two textbooks have described why long-range coupling between protons happens in such systems: large coupling constants result from the overlap between the small posterior lobes of the C–H bonds (4a, p 115; 7 ) and the existence of multiple coupling routes (4g, p 124). Spin–spin interaction occurs through intervening bonding electrons (4f, p 190), and the spin–spin coupling constant can be calculated using molecular orbital wave function (4j, p 139; 8). It is possible to obtain some information for the spin–spin coupling by examining the overlap of the molecular orbital. By displaying the highest occupied molecular orbital on a molecule, students can visually understand the two explanations mentioned above. The coupling constants between H7a and Hendo-2 protons arranged in a W in bicyclo[2.2.1]heptane and between Hendo-5 and Hendo-6 protons arranged in a W in bicyclo[2.1.1]hexane are about 3.5 and 7 Hz, respectively (Fig. 5) (9). As shown in Figures 6a and 6b, the highest occupied molecular orbital (HOMO{᎑4}) between the H7a and Hendo-2 protons arranged in a W in bicyclo[2.2.1]heptane is coupled through one route, whereas the highest occupied molecular orbital (HOMO{᎑2}) between the Hendo-5 and Hendo-6 protons arranged in a W in bicyclo[2.1.1]hexane is coupled through two routes. Longrange coupling constants increase when there are many routes of the molecular orbital with suitable interaction between two protons arranged in a W. Thus, coupling constants in the bicyclo[2.1.1]hexane are larger. In addition, it is possible to understand by the highest occupied molecular orbital why the coupling constant ( J = 18 Hz) between the two methine protons (H1 and H3) in a linear configuration in bicyclo122

bicyclo[2.2.1]heptane

H4a H6a

H3

7 Hz

18 Hz H1 10 Hz

H2a

H5a

bicyclo[2.1.1]hexane

bicyclo[1.1.1]pentane

Figure 5. Structure and long range coupling constants of bicyclo[2.2.1]heptane, bicyclo[2.1.1]hexane, and bicyclo[1.1.1]pentane.

Figure 6. (a) HOMO {᎑4} of bicyclo[2.2.1]heptane, (b) HOMO {᎑2} of bicyclo[2.1.1]hexane, (c) HOMO {᎑2} of bicyclo[1.1.1]pentane, and (d) HOMO {᎑1} of bicyclo[1.1.1]pentane.

Journal of Chemical Education • Vol. 78 No. 1 January 2001 • JChemEd.chem.wisc.edu

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Table 1. Conditions for Calculating Electrostatic Potential, Property Range, and HOMO Level Molecule

Electrostatic Property Property Potential/ Range (᎑)/ Range (+)/ HOMO { } ᎑1 ᎑1 (kcal mol ) (kcal mol ) (kcal mol᎑1)

Benzene

᎑3

default

default



Ethylene

᎑3

default

default



Acetylene

᎑5

default

default



[18]Annulene

᎑4.5

default

default



CHCl3

default

᎑20

52



CH2Cl2

default

᎑20

52



CH3Cl

default

᎑20

52



bicyclo[2.2.1]heptane

default

default

default

᎑4

bicyclo[2.1.1]hexane

default

default

default

᎑2

bicyclo[1.1.1]pentane

default

default

default

᎑1, ᎑2

[1.1.1]pentane is larger than that ( J = 10 Hz) between the bridged methylene protons (H2a and H4a) arranged in a W. Figures 6c and 6d show HOMO{᎑2} and HOMO{᎑1} of bicyclo[1.1.1]pentane, respectively. The highest occupied molecular orbital (HOMO{᎑2}) between the H1 and H3 protons on the bridgehead carbons is coupled through three routes, whereas the highest occupied molecular orbital (HOMO{᎑1}) between the H2a and H4a protons arranged in a W is coupled through two routes. Therefore, the coupling constant between two methine protons on the bridgehead carbons is larger than that of the W-arranged methyl protons. Molecular Modeling Software and Specifications of Personal Computers The ab initio 3-21G(*) calculations (10) using SYBYL (11) or MMFF94 geometry (12) were performed on a Power Macintosh 7600/200 (200-MHz processor and 128 MB memory) or a Dell Optiplex/GX1p (450-MHz processor and 192 MB memory). Mac Spartan Plus (3c) and PC Spartan Pro (3d ) were used as the computer modeling software. Isovalues for the electrostatic potential, the (᎑) and (+) property ranges that correspond to the red and blue parts in the electrostatic potential map and HOMO levels, are summarized in Table 1. The electrostatic potential surface and molecular orbital can be also displayed by Chem 3D and Win MOPAC software (3a, 3b). Acknowledgments We would like to thank T. Takasaki, T. Uchida, and M. Takahashi (CRC Research Institute, Inc., Japan) for technical support. W

Supplemental Material

This article is available with color figures in this issue of JCE Online. Note 1. Teaching by computer modeling was carried out in a onesemester course for junior chemistry majors. Judging from the results

of a questionnaire (56 students), when computer modeling was used the percentage of students who understood the difference in the direction of the induced magnetic line of force between acetylene and ethylene increased from 2% to 95%.

Literature Cited 1. Book Buyers Guide; J. Chem. Educ. 1999, 76 (2 Suppl.), 29. 2. (a) Jones, M. Jr. Organic Chemistry; Norton: New York, 1998. (b) McMurry, J. Organic Chemistry, 4th ed.; Brooks/ITP: Pacific Grove, CA, 1996. (c) Bruice, P. Y. Organic Chemistry, 2nd ed.; Prentice-Hall: Englewood Cliffs, NJ, 1998. (d) Wade, L. G. Organic Chemistry, 4th ed.; Prentice Hall: Englewood Cliffs, NJ, 1998. (e) Carey, F. A. Organic Chemistry, 3rd ed.; McGrawHill: New York, 1995. (f ) Hehre, W. J.; Shusterman, A. J.; Nelson, J. E. The Molecular Modeling Workbook for Organic Chemistry; Wavefunction: Irvine, CA, 1998. 3. (a) CS Chem 3D Pro Ver. 5.0; CambridgeSoft: Cambridge, MA, 1999. (b) Win MOPAC Ver. 2.0, Fujitsu: Chiba, Japan, 1998. (c) Mac Spartan Plus Ver 1.2; Wavefunction: Irvine, CA, 1997. (d) PC Sartan Pro Ver. 1.0; Wavefunction: Irvine, CA, 1999. 4. For example, (a) Bhacca, N. S.; Williams, D. H. Applications of NMR Spectroscopy in Organic Chemistry; Holden-Day: San Francisco, 1964. (b) Dyer, J. R. Applications of Absorption Spectroscopy of Organic Compounds; Prentice-Hall: Englewood Cliffs, NJ, 1965. (c) Rahman, A. Nuclear Magnetic Resonance, Springer: New York, 1986. (d) Abraham, R. J.; Fisher, J.; Loftus, P. Introduction to NMR Spectroscopy; Wiley: Chichester, 1988. (e) Brown, D. W.; Floyd, A. J.; Sainsbury, M. Organic Spectroscopy; Wiley: Chichester, 1988. (f ) Silverstein, R. M.; Bassler, G. C.; Morrill, T. C. Spectrometric Identification of Organic Compounds, 5th ed.; Wiley: Chichester, 1991; (g) Gunther, H. NMR Spectroscopy, 2nd ed.; Wiley: Chichester, 1992. (h) Hore, P. J. Nuclear Magnetic Resonance; Oxford University Press, Oxford, 1995. (i) Becker, E. D. High Resolution NMR, 2nd ed.; Academic: New York, 1980. (j) Dixon. W. T. Theory and Interpretation of Magnetic Resonance Spectra; Plenum: New York, 1972 (Japanese translation). 5. Hehre, W. J. Practical Strategies for Electronic Structure Calculations; Wavefunction: Irvine, CA, 1995; p 231. 6. Hehre, W. J.; Yu, J.; Klunzinger, P. E.; Lou, L. A Brief Guide to Molecular Mechanics and Quantum Chemistry Calculations; Wavefunction: Irvine, CA, 1998; p 159. 7. Marchand, A. P. Stereochemical Applications of NMR Studies in Rigid Bicyclic Systems; Verlag Chemie International: Deerfield Beach, FL, 1982; p 174. 8. McConnell, H. M. J. Chem. Phys. 1955, 23, 760; 1956, 24, 460. 9. Pretsch, E.; Seibl, J.; Simon, W.; Clerc, T. Tabellen zur Strukturaufklarung organischer Verbindungen mit spektroskopischen Methoden; Boschke, F. L.; Fresenius, W.; Huber, J. F. K.; Pungor, E.; Simon, W.; West, T. S., Eds.; Springer: Berlin, 1981; p H190. 10. Pietro, W. J.; Francl, M. M.; Hehre, W. J.; DeFrees, D. J.; Pople, J. A.; Binkley, J. S. J. Am. Chem. Soc. 1982, 104, 5039. 11. Clark, M.; Cramer, R. D. III; van Opdensch, N. J. Comput. Chem. 1989, 10, 982. 12. Halgren, A. J. Comput. Chem. 1996, 17, 490.

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