In the Classroom edited by
Molecular Modeling Exercises and Experiments
Alan J. Shusterman
Predicting the Shifts of Absorption Maxima of Azulene Derivatives Using Molecular Modeling and ZINDO CI Calculations of UV–Vis Spectra
Reed College Portland, OR 97202-8199
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Wyona C. Patalinghug,* Maharlika Chang, and Joanne Solis Chemistry Department, De La Salle University, 2401 Taft Avenue, Manila 1004, Philippines; *
[email protected] One of the striking properties of azulene is its brilliant blue color from which the compound derives its name (azure). The deep blue color is rare for a hydrocarbon. Although azulene, with molecular formula C10H8, is isomeric with naphthalene with five conjugated double bonds each, the two compounds exhibit different properties. Naphthalene is colorless and nonpolar whereas azulene is blue with a significant dipole moment (µ = 1 D).
When substituents are attached to azulene, its S0–S1 absorption band shifts and, at times, its color changes dramatically. Liu and coworkers in their efforts to prepare red-shifted visual pigment analogs have synthesized azulene derivatives having varied colors. For instance, 1-fluoroazulene is blue green; 1,3-difluoroazulene is emerald green; azulene-1carboxaldehyde is magenta; azulene-1,3-dicarboxaldehyde is red; azulene-2-carboxaldehyde and azulene-4-carboxaldehyde are green (1–3). Heilbronner demonstrated the blue or red shift of HOMO–LUMO transitions in a series of methylated azulene derivatives (4). Cyano-azulenes have also been reported to exhibit the shifts in absorption maxima (5, 6). Clearly, the nature and position of the substituents affect the colors of azulene derivatives. Quantum mechanics is a powerful tool that can be used to investigate molecular structure and properties such as those shown by azulene. However, the solution of the Schrödinger equation for multi-electron systems entails approximations and rigorous computational effort. The approximation methods are either ab initio or semiempirical. Semiempirical methods are based on Hartree–Fock formalism; however, they ignore or approximate some of the integrals used in ab initio meth-
ods and introduce parameters based on experimental data to compensate for the neglect of these integrals. As a result, they are less computationally intensive than ab initio methods. Much work has been done to search for functions and parameters that can predict good estimates of different molecular properties. It is assumed that the parameterized functions that fit a known set of molecules are transferable and can be used to predict molecular properties of other molecules. Some semiempirical methods such as INDO (intermediate neglect of differential overlap), MNDO (modified neglect of differential overlap), PM3, and AM1 are used to predict groundstate geometries, heats of formation, or ionization potentials. ZINDO (Zerner’s INDO) is further parameterized to predict UV–vis spectra. An additional improvement in the approximation and calculation of molecular properties is the inclusion of configuration interaction (CI), which takes into account expressions for unoccupied excited-state orbitals. The theories and applications of the various semiempirical methods have been widely discussed (7–9). Molecular Modeling Several theoretical studies of azulene using ab initio and DFT calculations have been published (10, 11). However, we present here the use of computational semiempirical methods to model the UV–vis spectra of azulene and azulene derivatives and to illustrate the absorption band shifts upon addition of substituents to azulene. Specifically we have used ZINDO CI of CAChe v6.1.10 (12) to obtain the UV–vis spectra after initially optimizing the molecules at INDO/1 geometry. Using the shapes of the HOMO, LUMO, and LUMO+1 orbitals of azulene, a qualitative prediction of how the S0–S1 and S0–S2 absorption bands will shift upon the addition of substituents to azulene can also be made. Michl and Thulstrup (13) have put forward a simple explanation for the distinctive color of azulene. The HOMO and LUMO of azulene are concentrated on different regions of the molecule (Figure 1) and produce a small HOMO–
Figure 1. The HOMO, LUMO, and LUMO+1 of azulene.
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In the Classroom A
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Figure 2. The change in the HOMO, LUMO, and LUMO+1 energies with the addition of substituents to azulene (3). (A) Addition of electron-donating groups to odd-numbered and even-numbered carbons in azulene. (B) Addition of electron-withdrawing groups to oddnumbered and even-numbered carbons in azulene.
LUMO overlap density distribution. This leads to a small S0–S1 excitation energy. On the other hand, the HOMO and LUMO of alternant hydrocarbons like naphthalene are concentrated on the same atoms of the molecule and produce relatively large overlap density distributions and correspondingly large excitation energies. Lemal and Goldman (14) used Hückel theory to describe azulene’s molecular orbitals. While the resulting Hückel HOMO–LUMO gap is smaller in azulene than in naphthalene, one should be cautious in using this correlation since Hückel orbital energies do not take into account electron–electron interactions. On the other hand, substituent effects on frontier MO energies, which have been described by Liu (2), may offer a useful tool for predicting color changes. Figure 1 graphically shows the HOMO, LUMO, and LUMO+1 orbitals of azulene calculated with ZINDO CI. The electron distribution of the HOMO is not uniform and is more concentrated in the five-membered ring. Carbons 1, 3, 5, and 7 (the odd-numbered carbons) contribute to the HOMO but carbons 2, 4, 6, and 8 (the even-numbered carbons) do not. When electron-donating substituents are attached to the odd-numbered carbons, they will introduce an antibonding interaction into the HOMO and destabilize the orbital, while electron-withdrawing substituents will have the opposite effect. Substituents of either type will have no effect when attached to the even-numbered carbons (Figure 2). The LUMO, on the other hand, shows an almost completely reversed situation. It is the even-numbered carbons that contribute to the LUMO while the odd-numbered carbons do not. Hence, substituents that perturb the HOMO will not affect the LUMO and vice versa. Electron-donating substituents at odd-numbered carbons destabilize the HOMO but have no effect on the LUMO and so reduce the S0-S1 excitation energy (Figure 2A, left). Attaching these substituents to the even-numbered carbons should have no effect on the HOMO, destabilize the LUMO, and increase the excitation energy resulting in a blue shift of the S0–S1 (Figure 2A, right). Electron-withdrawing substituents at either position should exert the opposite effect (Figure 2B). While the LUMO+1 has a more complicated shape, it can be seen from Figure 1 that the same odd-numbered carbons that contribute to the HOMO also contribute to the LUMO+1. Therefore, substituents attached to these carbons should perturb both orbitals in the same direction and the S0–S2 excitation should not show any major shifts. 1946
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Taken together, these principles suggest that moving a given type of substituent systematically around the ring (odd → even → odd …) should produce large oscillations in S0– S1 transition energies and relatively small changes in S0–S2 energies. Experimental Overview In this activity, students optimize the structure of azulene and calculate its UV–vis spectrum using ZINDO CI. The students note the S0–S1 and S0–S2 peaks and discuss the cause for the blue color of azulene. Using qualitative reasoning and the HOMO, LUMO, and LUMO+1 orbitals of azulene, the students predict the shifts of the absorption peaks when different substituents such as CH3, CHO, and F are placed at various carbon positions of azulene. The electron-donating, electron-withdrawing, inductive, or conjugative properties of the substituents are discussed. The molecules are then modeled and optimized and their UV–vis spectra are calculated using ZINDO CI. The predicted shifts of the absorption peaks are compared with those calculated by ZINDO CI. The HOMO, LUMO, and LUMO+1 energies may be obtained and the variations in the HOMO–LUMO and HOMO–LUMO+1 energy gaps are plotted. Results Some results obtained from molecular modeling investigations of various azulene derivatives using ZINDO CI are shown in Table 1. The trends in the shifts of the absorption maxima for substituted azulenes are shown in Figures 3 and 4. The weakly electron-donating (inductive) methyl groups cause a red shift in the S0–S1 peak when attached to the oddnumbered carbons because of the destabilization of the HOMO and a blue shift when attached to even-numbered carbons because of the destabilization of the LUMO. Conversely, the electron-withdrawing CHO groups show a blue shift in the S0–S1 peak when attached to odd-numbered carbons and a red shift when attached to even-numbered carbons. Fluorine withdraws electrons inductively but donates electrons by resonance. When the lone pairs of fluorine maximally interact with the p orbitals of its neighboring atom, it shows electron releasing via resonance properties. The compatible size of the orbitals make the 2p–π interaction in azulene very efficient and the electron releasing via resonance
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In the Classroom Table 1. Calculated and Experimental S0–S1 and S0–S2 Peaks for Azulene and Azulene Derivatives S0–S1/nm
S0–S2/nm
Compound
Exp Calc (in hexanes)
Azulene
587
2-CH3-azulene
577
Calc
Exp (in hexanes)
a
352
341a
566
b
361
––
b
580
3-CH3-azulene
627
608
364
––
4-CH3-azulene
581
568b
353
––
5-CH3-azulene
604
592
b
356
––
6-CH3-azulene
565
576
b
355
––
2-CHO-azulene
624
664
c
352
360
c
362
385
c
383
354c
c
3-CHO-azulene 4-CHO-azulene
520 672
542 642
c c
5-CHO-azulene
569
571
392
383c
6-CHO-azulene
674
652c
366
351c
614
a
356
343
a
359
342a
c
356
––
1-F-azulene 1,3-F-azulene
637
1,3-(CHO)2-azulene 486
625
670
507
a
a
Data from ref 16. bData from ref 4. cData from ref 3.
property of fluorine dominates (2, 15). Hence when fluorine is attached at the C1 or the C1 and C3 positions, the S0–S1 peak likewise shifts to the red region. The attachment at both C1 and C3 causes a greater perturbation resulting in a change of color from blue to emerald green. Summary This activity enables the students to qualitatively predict whether a substituent will cause a blue or red shift of the absorption peaks of azulene based on frontier molecular orbital shapes, although it does not quantitatively predict the magnitude of the shifts. Moreover, it allows the students to verify their predictions using computational chemistry, specifically ZINDO CI, which calculates the UV–vis spectra of the azulene derivatives. The variations in the HOMO– LUMO and HOMO–LUMO+1 gaps can be plotted to further corroborate the predictions. W
Supplemental Material
The HOMO, LUMO, and LUMO+1 energies, the HOMO–LUMO and HOMO–LUMO+1 energy gaps, and the plots of the variations of the energy gaps for the substituted azulenes are available in this issue of JCE Online. Literature Cited
Figure 3. Trends in shifts of S0–S1 absorption peak of methyl-substituted azulenes. Data from refs 3, 4, and 16.
Figure 4. Shifts of S0–S1 and S0–S2 absorption peaks for CHOsubstituted azulenes. Data from refs 3, 4, and 16.
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1. Liu, Robert S. H.; Asato, Alfred E. J. Photochem. Photobiol. C: Photochem. Rev. 2003, 4, 179–194. 2. Liu, Robert S. H. J. Chem. Educ. 2002, 79, 183–185. 3. Shevyakov, Sergey V.; Li, Hongru; Muthyala, Rajeev; Asato, Alfred E.; Croney, John C.; Jameson, David M.; Liu, Robert S. H. J. Phys. Chem. A 2003, 107, 3295–3299. 4. Heilbronner, E. Tetrahedron 1963, 19 (Suppl. 2), 289. 5. Nozoe, T.; Seto, S.; Matsumura, S. Bull. Chem. Soc. Jpn. 1962, 35, 1990–1998. 6. Stefan, S.; Baumgarten, M.; Simm, J.; Hafner, K. Angew. Chem., Int. Ed. 1998, 37, 1078–1081. 7. Lewars, E. Computational Chemistry: Introduction to the Theory and Applications of Molecular and Quantum Mechanics; Kluwer Academic Publishers: Boston, 2003. 8. Cramer, C. J. Essentials of Computational Chemistry: Theories and Models, 2nd ed.; John Wiley and Sons: Chichester, United Kindgom, 2004. 9. Zerner, M. C. Semiempirical Molecular Orbital Methods. In Reviews in Computational Chemistry; Lipkowitz, K. B., Boyd, D. B., Eds.; VCH Publishers: New York, 1991; Vol. 2, pp 313– 365. 10. Wang, Bo-Cheng; Lin, Yun-Shan; Chang, Jian-Chuang; Wang, Pei-Yu. Can. J. Chem. 2000, 78, 224–232. 11. Kozlowski, P. M.; Rauhut, G.; Pulay, P. J. Chem. Phys. 1995, 103, 5650. 12. CAChe 6.1.10 (Windows); Fujitsu Limited, 2004. 13. Michl, J.; Thulstrup, E. W. Tetrahedron 1976, 32, 205–209. 14. Lemal, David M.; Goldman, Glenn D. J. Chem. Educ. 1988, 65, 923–925. 15. McMurry, J. Organic Chemistry, 6th ed.; Brooks/Cole: South Melbourne, Australia, 2004; p 547. 16. Tetreault, Nicolas; Muthyala, Rajeev; Liu, Robert S. H.; Steer, Ronald P. J. Phys. Chem. A 1999, 103, 2524–2531.
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