In the Laboratory
Rotational Analysis of FTIR Spectra from Cigarette Smoke
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An Application of Chem Spec II Software in the Undergraduate Laboratory Alan R. Ford, William A. Burns, and Scott W. Reeve* Department of Chemistry, Arkansas State University, State University, AR 72467; *
[email protected] The infrared spectroscopic study of a gas phase molecule at rotational resolution is a common laboratory experience for the undergraduate physical chemistry student. Indeed, this particular experiment is such a staple of the undergraduate chemistry curriculum that numerous descriptions of the experiment have appeared in this Journal and elsewhere over the years (1). For practical reasons, 9 of the 16 laboratory descriptions in reference (1) involve HCl and just four species (HCl, C2H2, HBr, CO) are utilized in 15 of the 16 experiments listed. Based on our own experience and conversations with colleagues at other institutions, we note there are still a few shortcomings with the rotationally-resolved infrared experiment, specifically: 1. Each student typically analyzes the same species. While this may simplify the lab preparation, it presents the opportunity for inappropriate student collaboration. 2. The experiment and the sample lack a real-world connection. The typical physical chemistry laboratory experiment is approached from a purely pedagogical standpoint (i.e., an application of quantum mechanics). 3. Data analysis ultimately results in the determination of molecular structure. Rotation and rotation–vibration spectroscopy are among the most accurate methods of structure determination available for gas phase systems. Unfortunately highlighting the structure determination overlooks the significant role rotationally resolved spectroscopic methods play in the identification of compounds. For example, nearly half of the species observed in interstellar space were initially studied and identified in the laboratory (2)! 4. Assigning rotational quantum numbers to the individual rovibrational transitions is a tedious, often confusing, step in the data analysis procedure.
A version of the classic gas phase infrared experiment was developed for students at Arkansas State University that addresses several of these shortcomings. The experiment essentially combines a novel sample source with Chem Spec II
analysis software. Chem Spec II is a noncommercial Windows-based software package developed to aid in the potentially complicated problem of assigning quantum numbers to observed spectral lines (3). Designed originally to tackle high-resolution infrared diode laser spectroscopic research problems, the potential to use this in-house software package in the teaching laboratories was quickly recognized. The gas phase infrared experiment is described and the capability of the Chem Spec II software is demonstrated. Cigarette Smoke as a Sample Cigarette smoke is a sample source that, until recently (one of the authors introduced the use of cigarette smoke as a novel sample source at the 218th Meeting of the American Chemical Society in August of 1999), has been largely ignored (4). A representative spectrum for cigarette smoke at one atmosphere total pressure is shown in Figure 1. As a gas sample, cigarette smoke has several advantages: • Cigarette smoke is a real-world sample that is of current interest both from health and pollution aspects. • Cigarettes are inexpensive and readily available. There is essentially no sample preparation, thus students can concentrate on the spectroscopy and data analysis as opposed to the sample preparation. • Compared to pure HCl, HBr, CO, and C2H2, cigarette smoke is relatively safe (HCl and HBr are corrosive, CO is a flammable poison, and C2H2 is explosive). • Cigarette smoke contains three components, CO, CH4, and HCN, that are rotationally resolved at an instrumental resolution of 2 cm᎑1. Students can verify the presence of these components by analyzing the fundamental vibration of CO at 2143.7 cm᎑1, the ν3 mode of CH4 at 3020.3 cm᎑1 (a triply degenerate vibration), and the ν3 mode of HCN at 3311.47 cm᎑1 (the C⫺H stretch) (5). In addition, there are two infrared active bands of CO2 that can be observed with an instrumental resolution of 0.5 cm᎑1 (the asymmetric C⫽O stretch at 2349.3 cm᎑1 and the degenerate bending mode at 667.3 cm᎑1) (5). • The multicomponent nature of cigarette smoke provides flexibility in the manner in which the instructor sets up the experiment. For example, a traditional approach could be taken in which students are asked to analyze the spectra of the known components. In this scenario each student could be required to analyze each component, or students could be given different components. Alternatively, the sample could be treated as an unknown and each student could be required to identify or analyze a single component or all the components.
Figure 1. Infrared spectrum of cigarette smoke acquired at 0.5 cm᎑1 spectral resolution.
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• The experiment presents the opportunity for students to apply aspects of chemistry discussed throughout their undergraduate career (see Supplemental MaterialW for explanation and discussion).
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In the Laboratory
Spectral Analysis Using Chem Spec II Software Assigning the appropriate J quantum number to observed rotation–vibration transitions is typically a trial-anderror process mastered only through practice. Generally the process requires the observed data be fit several times with varying J quantum number assignments to determine the correct assignments. Because intuition is required with such an approach, it is certainly understandable why this process might prove difficult or confusing for students. To streamline the laboratory experience and minimize the confusion an alternative, perhaps more pedagogical, method of assigning quantum numbers to transitions would be helpful. A relatively transparent alternative is provided by the infrared simulation program, Chem Spec II. The infrared simulation code, written in C++ and equipped with a Visual Basic GUI, has been specifically designed to emulate a spreadsheet program. Chem Spec II is Windows based, completely menu driven, and allows students to:
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1. Generate a simulated rovibrational spectrum given an input set of spectroscopic constants. 2. Overlay the simulated spectrum on an observed spectrum. 3. Make changes to the simulated spectrum by changing the values of the input constants. 4. Obtain the quantum numbers associated with any rotation– vibration transition.
What makes Chem Spec II novel is that it emulates spreadsheet programs such as Excel or Quattro Pro. For students who can cut, paste, plot data, and perform calculations in a spreadsheet, Chem Spec II represents a straightforward application of their computer skills and allows them to focus on the spectroscopy of the problem. As carbon monoxide is a prominent feature in the cigarette smoke spectra (Figure 1), the capability of Chem Spec II is demonstrated by examining the absorption region for the CO fundamental vibration in some detail. To initiate the simulation, the Predict IR Spectrum option is chosen from a pull-down menu in Chem Spec II (Figure 2A). Selecting this option opens a Predict IR Spectrum Wizard dialog box (Figure 2B). Here the user selects the appropriate parameters to generate the calculated spectrum. For CO, the linear rotor type is selected. (Chem Spec II has the capability to generate spectra for all rotor types.) Other parameters are entered by highlighting various categories and supplying the requested information. Once the necessary information has been entered, the Output Spectrum option in the Predict IR Spectrum Wizard dialog box will write the calculated spectrum, complete with calculated intensities and quantum number assignments, to the Chem Spec II spreadsheet. The Predict IR Spectrum Wizard also allows experimental spectra to be imported with the Input Spectrum option in the parameter box (see Figure 2B). Plotting the simulated and experimental spectra is accomplished using the built in Chart option located in the Tools pull-down menu (see Figure 2A). These plots are constructed following essentially the same sort of procedure for graphing data in Excel or Quattro Pro. If the predicted stick spectra does not line up with the experimental data, the spectroscopic constants can be varied, perhaps through several iterations, until the predicted stick spectrum “matches” the observed 866
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Figure 2. (A) The infrared prediction routines are accessed via the Tools menu of Chem Spec II. (B) All of the parameters required for the spectral simulation are inputted using the IR Prediction Wizard. Here the rotor type is being selected.
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Figure 3. Rovibrational lines in the infrared spectrum are assigned by right clicking on any line in the stick spectrum: (A) selecting Get Point Info in the Point menu and (B) recording the quantum number assignments from the Info for Series X dialog box.
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In the Laboratory
spectrum. This step is actually instructive for students, as they can observe the effect changing various molecular parameters has on the position of spectral lines. Students can also change the value of other parameters, such as the temperature, that will of course change the intensity and appearance of the rotational contours. Although it is not demonstrated here, both the x and y axes can be scaled to zoom in or zoom out on any spectral feature of interest, again using a set of keystrokes similar to that found in the popular spreadsheet programs. When the predicted stick spectrum matches the observed spectrum, quantum number assignments are obtained by right clicking on the appropriate stick in the predicted spectrum. The right click causes a menu box to appear (Figure 3A). By selecting the Get Point Info under the Point menu, a dialog box pops up that contains the quantum number information (Figure 3B). Thus, the rotation–vibration transition highlighted in Figure 3A involves a change in rotational quantum number of J″ = 12 → J′ = 11. Accordingly, this transition is assigned as P(12) of the fundamental vibration of CO. Chem Spec II is well equipped to handle more complicated molecular systems and the infrared spectrum of cigarette smoke provides a ready source of additional species to analyze. As indicated previously, rotationally resolved spectra for CH4, CO, CO2, HCN, and H2O can be obtained from a cigarette smoke sample. The rotational energy analysis for the spherical rotor CH4 for example, is quite similar to that of the linear rotor. However, coriolis effects must be included in the simulation for the ν3 band of CH4. Coriolis effects are included by choosing the Coriolis Effects parameter in the Predict IR Spectrum Wizard (Figure 2B). A plot of the simulated stick spectrum together with the CH4 absorption spectrum near 3020 cm᎑1 is shown in Figure 4. Quantum number assignments for these rotation–vibration lines can be obtained following the procedure outlined previously (see Table II in Supplemental MaterialW for a complete listing of spectral assignments). Hazards The hazards associated with this experiment are similar to those associated with exposure to secondhand tobacco smoke. Distribution of Software Chem Spec II is available and can be obtained, free of charge, by contacting the authors or at the following Web site, http://pulaylab.uark.edu/downloads/chemspec2.zip (accessed Mar 2004). The software has been optimized and tested and performs well on the Windows XP platform. We have also recently developed an Excel plug-in version of the program that will allow students to generate and plot infrared spectra within the Excel spreadsheet. The Chem Spec II Excel plugin is also available free of charge from the authors. Acknowledgments The Chem Spec II code was developed as part of an ongoing externally funded research program at Arkansas State University. Therefore, we would like to acknowledge Research www.JCE.DivCHED.org
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Figure 4. Chem Spec II generated plot containing the simulated spectrum for methane superimposed on the observed infrared spectrum.
Corporation, the Arkansas Biosciences Institute, as well as the Donors of The Petroleum Research Fund, administered by the American Chemical Society, for partial support of this project. W
Supplemental Material
A detailed description of the laboratory, including tables of rotational constants and rotation–vibration transition frequencies, available in this issue of JCE Online. Literature Cited 1. See for example, (a) Stafford, F. E.; Holt, C. W.; Paulson, G. L. J. Chem. Educ. 1963, 40, 245. (b) Richards, L. W. J. Chem. Educ. 1966, 43, 552. (c) Richards, L. W. J. Chem. Educ. 1966, 43, 644. (d) Ford, T. A. J. Chem. Educ. 1979, 56, 57. (e) Henderson, G.; Ko, C.; Huang, T. J. Chem. Educ. 1982, 59, 683. (f ) McNaught, I. J. J. Chem. Educ. 1982, 59, 879. (g) Devore, T. C.; Gallaher, T. N. J. Chem. Educ. 1983, 60, 522. (h) Keedy, C. R. J. Chem. Educ. 1992, 69, A296. (i) Ganapathisubramanian, N. J. Chem. Educ. 1993, 70, 1035. (j) David, C. W. J. Chem. Educ. 1996, 73, 46. (k) Lawrence, B. A.; Zanella, A. W. J. Chem. Educ. 1996, 73, 367. (l) MinaCamilde, N.; Manzanares, I. C.; Caballero, J. F. J. Chem. Educ. 1996, 73, 804. (m) Pattacini, S. C. J. Chem. Educ. 1996, 73, 822. (n) Shoemaker, D. P.; Garland, C. W.; Nibler, J. W. Experiments in Physical Chemistry; McGraw Hill: New York, 1996. (o) Halpern, A. M. Experimental Physical Chemistry: A Laboratory Textbook; Prentice Hall: New Jersey, 1997. (p) Sime, R. J. Physical Chemistry: Methods, Techniques, and Experiments; Harcourt Brace: Philadelphia, PA, 1997. 2. Hirota, E. J. Phys. Chem. 1983, 87, 3375. 3. (a) Ford, A. R.; Reeve, S. W. J. Ark. Acad. Sci. 2001, 55, 172. (b) Ford, A. R. Rotationally Resolved Infrared Spectrum and DFT Study of Jet Cooled Iron Pentacarbonyl. M.S. Thesis, Arkansas State University, State University, AR, April 2001. 4. Garizi, N.; Macias, A.; Furch, T.; Fan, R.; Wagenknecht, P.; Singmaster, K. A. J. Chem. Educ. 2001, 78, 1665. 5. (a) Herzberg, G. Molecular Spectra and Molecular Structure II: Infrared and Raman Spectra of Polyatomic Molecules; D. Van Norstrand Company, Inc.: New York, 1945. (b) Herzberg, G. Molecular Spectra and Molecular Structure I: Spectra of Diatomic Molecules; D. Van Norstrand Company, Inc.: New York, 1950.
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