- Email: [email protected]
ATIRS package: A program suite for the rovibrational analysis of infrared spectra of asymmetric top molecules
Journal of Molecular Spectroscopy 243 (2007) 148–154 www.elsevier.com/locate/jms
ATIRS package: A program suite for the rovibrational analysis of infrared spectra of asymmetric top molecules N. Tasinato, A. Pietropolli Charmet *, P. Stoppa Dipartimento di Chimica Fisica, Universita` Ca’ Foscari di Venezia D.D. 2137, I-30123 Venezia, Italy Received 19 December 2006; in revised form 9 February 2007 Available online 20 February 2007
Abstract Nowadays high-resolution infrared spectra can be recorded quite easily and therefore it has become important to assist the rovibrational analysis, especially the assignment step, that is still fraught with many problems in the presence of perturbation effects. In this article we provide a description of ATIRS, a complete software suite developed for assisting in the rotational investigation of vibrational bands of asymmetric top molecules. This package uses the Pickett’s CALPGM suite for fitting transitions and predicting line positions and is composed by three stand-alone applications: (1) Visual Loomis–Wood for the assignment of spectral lines based on Loomis–Wood type diagrams; (2) Visual CALPGM, a new graphical interface to Pickett’s programs SPFIT and SPCAT; (3) Visual Spectra Simulator for the simulation of spectra. The graphical interface to the CALPGM suite is developed for asymmetric rotors. The main feature of this application is to avoid the use of the parameter codes that are here replaced employing the well known parameter names or symbols. Highlighting the regular transition sequences, Visual Loomis–Wood assists in the assignment of the spectral lines. It visualizes the description of a transition and the assignment can be simply done by mouse-clicking on the diagram; moreover its display mode feature lets to check the experimental spectrum in which all the assigned lines together with their description are reported. Visual Spectra Simulator provides a simple and functionally application that, using the calculated frequencies and intensities given by SPCAT, simulates the high-resolution infrared spectrum and compare it to the experimental one. ATIRS, freely available to the spectroscopic community, is designed to be easy to use and presents a standard graphical interface; being based on the CALPGM package it can handle forbidden transitions and perturbations among many states. Ó 2007 Elsevier Inc. All rights reserved. Keywords: Interactive Loomis–Wood assignment scheme; Computer assisted rovibrational analysis; CALPGM graphical interface; IR spectra simulation software
1. Introduction The last decades have seen an exciting progress in the ability to obtain high resolution, rotationally resolved, infrared spectra employing TDL and/or FTIR spectrometers. Such measurements contain a wealth of information about rovibrational parameters not accessible in any other way. Conversely, the time-consuming task of inverting the spectra observables to extract these data (i.e. the assignment of lines within the theoretical model of a given
*
Corresponding author. Fax: +39 041 234 8594. E-mail address: [email protected] (A. Pietropolli Charmet).
0022-2852/$ - see front matter Ó 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jms.2007.02.016
Hamiltonian) still remains tedious and prone to errors. The difficulty increases when working with molecules that have a large mass and several low-energy vibrational modes, which leads to a high density of lines. Finally, perturbation effects arising from resonances may add additional complexity to the analysis. Even though approaches based on genetic algorithms have been applied with success in some cases (see Ref. [1] and references therein) and Moruzzi et al. have presented a software able to determine transition assignments automatically under proper conditions [2,3], nowadays the mostly followed and effective procedure of analysing a high-resolution spectra still relies on an interactive method. This procedure basically involves computing the transition frequencies
N. Tasinato et al. / Journal of Molecular Spectroscopy 243 (2007) 148–154
from a set of parameters, comparing them with the experimental ones to search for recognizable patterns and to make an initial assignment in term of quantum numbers. Subsequently, the parameters are refined by some fitting program to reproduce the assigned transitions, the spectrum is recalculated and so on iteratively until a close match between the experimental and the computed spectra is reached. Among these steps, the assignment is the most critical one and requires a lot of experience, hence many efforts have been made to simplify it. The most widely used approach is based on the method first suggested by Loomis and Wood [4]. Basically, it consists of mapping the wavenumbers of all the lines in the spectrum onto a two-dimensional diagram from which is much easier to assign the branches of the band. In a series of subsequent works Narahari Rao and his collaborators [5] demonstrated the utility of this procedure and with a pioneering work adapted it to a computer calculation. During the last decade the availability of always more powerful computer resources has strongly stimulated the implementation of this assignment scheme in form of interactive Loomis– Wood programs (see for example Refs. [6–11]). Many of them however still need some additional (often homemade) software tools to submit their results to a general fitting program, like SPFIT [12], ASFIT [13] or WANG [14] to determine/refine the desired parameters. Furthermore some prediction program, like SPCAT [12] must be employed to compute new transition frequencies and intensities; other tools to plot the resulting synthetic spectra must be used. Using separate softwares (sometimes still using a DOSbased interface) for assignment, parameter fitting, prediction and plotting inevitably leads to the boring problem of the data exchange. A great deal of research attempts has been focused to develop computer-aided integrated approach to speed up this time-consuming sequence of steps. Recently, some softwares have been presented [15–22], which have proven to be powerful tools in the hands of a spectroscopist. Here, we report on Asymmetric Top Infrared Spectra (ATIRS), a complete suite of programs (written in Visual Basic 2005) developed to assist and speed up the spectral analysis of the infrared rovibrational bands of an asymmetric rotor. Combining a mouse-interactive approach to assign transitions (Visual Loomis–Wood) with a graphical interface to both SPFIT and SPCAT (Visual CALPGM) and a fast plotting program to generate the theoretical spectrum and to compare it with the experimental one (Visual Spectra Simulator), it allows an efficient transfer of data from a program module to another. 2. Structure and description of ATIRS package ATIRS is a suite composed by three stand-alone programs developed to help the spectroscopist in every steps of the rovibrational analysis of the infrared spectra of an
149
asymmetric rotor, from the assignment of the spectral lines to the computing of the overall synthetic spectrum. Its integration with the mostly employed predictive/fitting programs (SPCAT and SPFIT, respectively) makes it very effective in handling also perturbed bands. Moreover, its graphical interface offers clear procedures to import/export data formatted in any desired formats and some additional features to handle spectroscopic data. Basically, ATIRS is composed of: – Visual Loomis–Wood (VLW), to assist the assignment of the spectral lines; – Visual CALPGM (VCALPGM), to fit the experimental data and to predict the transition frequencies and their intensities employing SPFIT and SPCAT, respectively; – Visual Spectra Simulator (VSS), to build up the theoretical spectrum from the predicted transition frequencies (and intensities) and to compare it with the experimental one. These three programs can run simultaneously in separate windows, so that the user can switch from one to another seamlessly. By now, the programs are designed to deal with asymmetric rotor infrared spectra and they handle data only in wavenumbers: future developments will include symmetric top molecules and MHz data. 3. Visual Loomis–Wood The Visual Loomis–Wood program (VLW) requires the following input files: – observed transition file (peak list of line positions and intensities); – calculated transition file (computed transition wavenumbers and intensities); – experimental spectrum file. The last one is an optional file required by the ‘‘display’’ mode. By making clearly recognizable the regular pattern of rovibrational transitions in the spectra, Visual Loomis– Wood allows the assignment of spectral lines. It follows the procedure suggested by Nakagawa and Overend [6], which introduced into the Loomis–Wood type diagram the method of Ground State Combination Differences (GSCDs) to check the consistency of P-, Q- and R-branch assignments. In VLW the assignment strategy, which requires an accurate knowledge of the ground state spectroscopic constants, consists of grouping the calculated transitions according to their K 0a (or K 0c ) values; each of these sets is arranged with ascending J 0 values and then further sorted with ascending wavenumbers. In this way the computed transitions belonging to the P, Q, R branches and reaching the same upper level are grouped together. For each transition, the diagram plots the observed wavenumbers nearby the calculated value.
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On a correlation plot designed in this way, the observed transitions to be assigned to a set of P, Q, R lines for the same J 0 should lie on a vertical line if they satisfy the GSCDs and so the consistency of the P, Q, R assignments could be checked. If the upper state spectroscopic parameters employed to compute the transitions are not close enough to the true values, the diagram shows a deviation of the observed line from the corresponding predicted wavenumber. Nevertheless, these displacements have regular patterns leading to state the following criteria of assignment [6]: – transitions with a common level should exhibit equal deviation; and, in absence of local interactions: – this deviation plotted against the rotational quantum number J 0 should follow a smooth continuous trend; – the intensities of the lines should vary in a reasonably manner. Fig. 1 displays an example of the diagram built by VLW: each observed spectral line is here represented as a small box whose colour stands for its relative intensity while its position in the diagram row with respect to the centre (the zero column displacement) is equal to the difference between its experimental and predicted wavenumber.
Transitions mutually linked by GSCDs appear highlighted by a yellow frame thus enabling an efficient visual recognition of regular sequences. The assignment of a spectral line together with the definition of its weight, here defined as 1/(estimated error squared), is carried out with a simple mouse click on it. At any time it is possible to scroll the diagram in the horizontal as well as vertical direction. Having all the P, Q, R transitions displayed simultaneously in the same plot facilitates the assignment step even if some spectral region is congested. Furthermore, the GSCDs checking assists the analysis especially in the presence of anomalous structure caused by resonances. Transitions with a common upper level show equal deviations even if that level is affected by resonance and therefore the perturbed region becomes easily recognizable thus helping to interpret the resonance model. The analysis of spectra with a high density of peaks always presents the risk of erroneous assignments and the Loomis– Wood diagram alone may be not well suited to handle complex overlapping peak systems. In these cases it is necessary to carefully examine these spectral features in search of reasonable possibilities for the assignment. This program increases the reliability of the analysis in such difficult conditions. Once the mouse cursor is placed on a single line, the user can switch to the ‘‘display’’ mode: as shown by Fig. 2,
Fig. 1. Example of a Loomis–Wood type diagram built up by Visual Loomis–Wood. A frame groups the sets of transitions related by a common upper level. A regular sequence of assigned transitions is clearly recognizable. Below the plot more detailed information regarding the mouse-pointed line is reported: quantum numbers, experimental and computed wavenumbers together with their difference, relative intensity and some details about the correlation diagram.
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Fig. 2. Example of the ‘‘display’’ mode (VLW). This feature plots the spectral region centred on a selected polyad. Assigned transitions are labelled by markers (rectangles): when the mouse cursor is above one of them, information about the selected line is reported (line number, quantum numbers and its wavenumber).
Visual Loomis–Wood will plot three different spectral traces showing the spectral region centred on the selected line and the transitions linked to it by GSCDs. By placing the mouse over a given marker above the spectra, the quantum numbers and the wavenumber of the chosen transition are reported. Combined with the Loomis–Wood view, this feature helps to confirm correct assignments. Besides being very effective in assisting the analysis of a-, b- and c-type bands, this program can be used also in the assignment of so-called pseudo-parallel component (selection rule DKa = DKc = 0) of a c-type band. This component may arise due to strong perturbative effects. Another useful feature of Visual Loomis–Wood is its ability in handling automatically the transition file created by the prediction program SPCAT. Upon completion of a set of assignments, by a mouse click the assigned transition file is generated and it is ready to be submitted (without further modifications) to SPFIT. 4. Visual CALPGM ATIRS uses the CALPGM suite developed by Pickett [12] offering a graphical interface to simplify the use of both SPFIT and SPCAT, i.e. the fitting and the prediction program, respectively. This interface, called Visual CALPGM
(VCALPGM), basically consists of two distinct programs, Visual SPFIT (VSPFIT) and Visual SPCAT (VSPCAT): a mouse-click on a button placed in the tool bar lets the user to switch between them. The only input data required by VCALPGM is the <filename>.lin file, i.e. a list of the assigned transitions in the original SPFIT format (for more information see Ref. [12]). VCALPGM allows the user to import the assigned transition files as required by SPFIT, to read, convert and extract the desired data from the output files of SPFIT/SPCAT. This approach makes possible to do both the steps of refining the parameters by the fitting of the assigned transitions and of computing the new rovibrational transitions without the need of exiting VCALPGM. One of the most relevant feature of VCALPGM relies in that the user does not have to code the parameters following the format employed by SPFIT and SPCAT (spectroscopic constants and data about the dipole moments, respectively). As shown by Fig. 3, VSPFIT employs the more common symbols for the rotational constants as well as for the various centrifugal distortion constants and the interaction parameters. Once the number of vibrational states has been specified, the user clicks a specific tab control to display the page relative to the corresponding vibrational state where easily enter or edit the spectroscopic constants. In addition, by opening
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Fig. 3. Example of the Visual SPFIT window during the execution of SPFIT. The program replaces the original Pickett’s parameter codes with the corresponding spectroscopic symbols (referring to the Watson’s A-reduction Hamiltonian in the Ir representation: D = D, d = d, F = U, f = u). Many options have been implemented to import files, to add interaction parameters and to handle data from the SPFIT output file. In the lower panel the output of SPFIT is displayed.
the ‘‘interaction parameter’’ page the user can specify the parameters describing the perturbation effects by choosing among a pre-defined list containing the mostly common ones (i.e. anharmonic and Coriolis resonances). Of course, there exists the possibility of defining a new coupling term by writing the corresponding code following the original Pickett’s notation. As soon as a new interaction parameter has been defined, it appears as a new entry in the list and it will be available in all the subsequent runs of the program. A similar graphical approach to the creation of the input file is adopted by VSPCAT. When the parameter set has been saved, VCALPGM creates the input files for SPFIT or SPCAT (.par or .int file) converting the symbols into the corresponding codes. It is worth to note that this program employs the Watson’s A-reduction Hamiltonian in the Ir representation [23]; nevertheless a simple mouse-click on a button allows the user to edit the input files also by using a text-editor (future developments including other representation and higher order distortion terms have been already planned). After entering all the data sets, by a simple mouse-click the SPFIT/SPCAT program is executed as a hidden process and its output detailing the progress of the computation is displayed in the lower panel of the main window, thus allowing the user to check the correct execution.
VCALPGM provides various tools to handle the output files of SPFIT/SPCAT; in addition, general interfaces have been developed to easily import/export these data according to a user-defined format scheme. 5. Visual Spectra Simulator Visual Spectra Simulator (VSS) is the application which generates and plots the synthetic spectra employing the frequencies and the intensities predicted by VSPCAT. This module requires the following input data: – calculated transition file (computed transition wavenumbers and intensities); – experimental spectrum file. The last one is an optional file required if the user wants to compare the experimental spectrum to the synthetic one. The user has to specify the desired line profile (and its FWHM) choosing among Gaussian, Lorentzian or pseudo-Voigt functions. Once the synthetic spectrum has been plotted, it is possible to change the line profile simply by mouse-clicking: the plotting algorithm developed is fast enough that the spectrum is redrawn immediately.
N. Tasinato et al. / Journal of Molecular Spectroscopy 243 (2007) 148–154
153
Fig. 4. Example of the Visual Spectra Simulator window. This program generates the synthetic spectra from the output files of VSPCAT and can also load the experimental spectra (many options to make easy the comparison between them have been implemented). The plot of the synthetic spectra is mousesensitive: moving the cursor around a peak, in the upper panel the quantum numbers of the corresponding transition are shown, while in the status bar information about its wavenumber and intensity is reported.
Fig. 4 shows an example of the spectrum displayed by VSS: the spectrum can be scrolled left/right by using the scroll bar. By moving the cursor around the peak, the user gets information about its wavenumber, intensity and the values of upper and lower quantum numbers. In the status bar of the window, the wavenumber range of the computed spectrum together with the current position of the cursor (expressed as wavenumber—intensity), the FWHM values and the sampling frequency, are shown. The simulation can be saved into a text file using any kind of format the user wants. Additionally, the software can load the experimental spectrum and display it together with the computed one: several features have been implemented to facilitate the comparison between them. 6. Getting and installing ATIRS ATIRS and its documentation are freely downloadable from http://venus.unive.it/molspectragroup. They consist of a self-extractive archive that contains all the executable files for Windows 2000/XP. The programs have been tested with the current release of SPFIT/SPCAT (October 2006); as soon as a new version will be available, we will check our software package for compatibility. Please refer to the web
site for complete installation and running instructions, for future developments and for giving us suggestions and/or bug notices. 7. Conclusions Extracting the rovibrational parameters from a highresolution infrared spectra still remains a tedious work and very often one has to deal with the additional complexity arising by resonance effects and strongly overlapped peak systems. A new spectrum analysis software called ATIRS is presented in this article. Featuring a Loomis–Wood type diagram interactively linked to a spectra viewer it provides a total access to the full spectral information. The correlation plot displays the P, Q, R branches simultaneously, highlighting the polyad of transitions related by GSCDs, and this organizing scheme aids the check of consistency in the assignments in all the branches even in the presence of irregular pattern. Its graphical interfaces to SPFIT and SPCAT allow the user to fit the assigned transitions and to predict line positions and intensities. Together with its plotting module, this software package aids the overall process of spectral analysis freeing the spectroscopist from many time-consuming
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steps and reducing the danger of misassignment. Its integration with SPFIT/SPCAT routine makes possible to determine the set of spectroscopic rovibronic parameters that describes the measured spectrum also taking into account perturbation features. Acknowledgments The ATIRS package, apart from some revisions, was presented at the Praha 2006 19th International Conference [24]. At that meeting we were informed about the program by Lodyga et al. [25] (a powerful improvement of their previous work [11]); their suggestions are here gratefully acknowledged. The authors thank Prof. H.M. Pickett for his helpful explanations concerning the distribution of SPFIT and SPCAT. This work was financially supported by MIUR, Rome. References [1] W. Leo Meerts, M. Schmitt, Int. Rev. Phys. Chem. 25 (2006) 353–406. [2] G. Moruzzi, L.H. Xu, R.M. Lees, B.P. Winnewisser, M. Winnewisser, J. Mol. Spectrosc. 167 (1994) 156–175. [3] G. Moruzzi, W. Jabs, B.P. Winnewisser, M. Winnewisser, J. Mol. Spectrosc. 190 (1998) 353–364. [4] F.W. Loomis, R.W. Wood, Phys. Rev. 32 (1928) 223–236. [5] J.F. Scott, K. Narahari Rao, J. Mol. Spectrosc. 20 (1966) 461–463; S. Ghersetti, K. Narahari Rao, J. Mol. Spectrosc. 28 (1968) 27–43; A.W. Mantz, K. Narahari Rao, J. Mol. Spectrosc. 30 (1969) 513–530. [6] T. Nakagawa, J. Overend, J. Mol. Spectrosc. 50 (1974) 333–348. [7] B.P. Winnewisser, J. Reinsta¨dtler, K.M.T. Yamada, J. Behrend, J. Mol. Spectrosc. 132 (1989) 12–16.
[8] D. McNaughton, D. McGilvery, F. Shanks, J. Mol. Spectrosc. 149 (1991) 458–473. [9] F. Winther, M. Schoenhoff, R. LePrince, A. Guarnieri, J. Mol. Spectrosc. 152 (1992) 205–212. [10] R. Brotherus, J. Comput. Chem. 20 (1999) 610–622. [11] Sˇ. Urban, J. Behrend, P. Pracna, J. Mol. Struct. 690 (2004) 105–114. [12] H.M. Pickett, J. Mol. Spectrosc. 148 (1991) 371–377,
ATIRS package: A program suite for the rovibrational analysis of infrared spectra of asymmetric top molecules N. Tasinato, A. Pietropolli Charmet *, P. Stoppa Dipartimento di Chimica Fisica, Universita` Ca’ Foscari di Venezia D.D. 2137, I-30123 Venezia, Italy Received 19 December 2006; in revised form 9 February 2007 Available online 20 February 2007
Abstract Nowadays high-resolution infrared spectra can be recorded quite easily and therefore it has become important to assist the rovibrational analysis, especially the assignment step, that is still fraught with many problems in the presence of perturbation effects. In this article we provide a description of ATIRS, a complete software suite developed for assisting in the rotational investigation of vibrational bands of asymmetric top molecules. This package uses the Pickett’s CALPGM suite for fitting transitions and predicting line positions and is composed by three stand-alone applications: (1) Visual Loomis–Wood for the assignment of spectral lines based on Loomis–Wood type diagrams; (2) Visual CALPGM, a new graphical interface to Pickett’s programs SPFIT and SPCAT; (3) Visual Spectra Simulator for the simulation of spectra. The graphical interface to the CALPGM suite is developed for asymmetric rotors. The main feature of this application is to avoid the use of the parameter codes that are here replaced employing the well known parameter names or symbols. Highlighting the regular transition sequences, Visual Loomis–Wood assists in the assignment of the spectral lines. It visualizes the description of a transition and the assignment can be simply done by mouse-clicking on the diagram; moreover its display mode feature lets to check the experimental spectrum in which all the assigned lines together with their description are reported. Visual Spectra Simulator provides a simple and functionally application that, using the calculated frequencies and intensities given by SPCAT, simulates the high-resolution infrared spectrum and compare it to the experimental one. ATIRS, freely available to the spectroscopic community, is designed to be easy to use and presents a standard graphical interface; being based on the CALPGM package it can handle forbidden transitions and perturbations among many states. Ó 2007 Elsevier Inc. All rights reserved. Keywords: Interactive Loomis–Wood assignment scheme; Computer assisted rovibrational analysis; CALPGM graphical interface; IR spectra simulation software
1. Introduction The last decades have seen an exciting progress in the ability to obtain high resolution, rotationally resolved, infrared spectra employing TDL and/or FTIR spectrometers. Such measurements contain a wealth of information about rovibrational parameters not accessible in any other way. Conversely, the time-consuming task of inverting the spectra observables to extract these data (i.e. the assignment of lines within the theoretical model of a given
*
Corresponding author. Fax: +39 041 234 8594. E-mail address: [email protected] (A. Pietropolli Charmet).
0022-2852/$ - see front matter Ó 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jms.2007.02.016
Hamiltonian) still remains tedious and prone to errors. The difficulty increases when working with molecules that have a large mass and several low-energy vibrational modes, which leads to a high density of lines. Finally, perturbation effects arising from resonances may add additional complexity to the analysis. Even though approaches based on genetic algorithms have been applied with success in some cases (see Ref. [1] and references therein) and Moruzzi et al. have presented a software able to determine transition assignments automatically under proper conditions [2,3], nowadays the mostly followed and effective procedure of analysing a high-resolution spectra still relies on an interactive method. This procedure basically involves computing the transition frequencies
N. Tasinato et al. / Journal of Molecular Spectroscopy 243 (2007) 148–154
from a set of parameters, comparing them with the experimental ones to search for recognizable patterns and to make an initial assignment in term of quantum numbers. Subsequently, the parameters are refined by some fitting program to reproduce the assigned transitions, the spectrum is recalculated and so on iteratively until a close match between the experimental and the computed spectra is reached. Among these steps, the assignment is the most critical one and requires a lot of experience, hence many efforts have been made to simplify it. The most widely used approach is based on the method first suggested by Loomis and Wood [4]. Basically, it consists of mapping the wavenumbers of all the lines in the spectrum onto a two-dimensional diagram from which is much easier to assign the branches of the band. In a series of subsequent works Narahari Rao and his collaborators [5] demonstrated the utility of this procedure and with a pioneering work adapted it to a computer calculation. During the last decade the availability of always more powerful computer resources has strongly stimulated the implementation of this assignment scheme in form of interactive Loomis– Wood programs (see for example Refs. [6–11]). Many of them however still need some additional (often homemade) software tools to submit their results to a general fitting program, like SPFIT [12], ASFIT [13] or WANG [14] to determine/refine the desired parameters. Furthermore some prediction program, like SPCAT [12] must be employed to compute new transition frequencies and intensities; other tools to plot the resulting synthetic spectra must be used. Using separate softwares (sometimes still using a DOSbased interface) for assignment, parameter fitting, prediction and plotting inevitably leads to the boring problem of the data exchange. A great deal of research attempts has been focused to develop computer-aided integrated approach to speed up this time-consuming sequence of steps. Recently, some softwares have been presented [15–22], which have proven to be powerful tools in the hands of a spectroscopist. Here, we report on Asymmetric Top Infrared Spectra (ATIRS), a complete suite of programs (written in Visual Basic 2005) developed to assist and speed up the spectral analysis of the infrared rovibrational bands of an asymmetric rotor. Combining a mouse-interactive approach to assign transitions (Visual Loomis–Wood) with a graphical interface to both SPFIT and SPCAT (Visual CALPGM) and a fast plotting program to generate the theoretical spectrum and to compare it with the experimental one (Visual Spectra Simulator), it allows an efficient transfer of data from a program module to another. 2. Structure and description of ATIRS package ATIRS is a suite composed by three stand-alone programs developed to help the spectroscopist in every steps of the rovibrational analysis of the infrared spectra of an
149
asymmetric rotor, from the assignment of the spectral lines to the computing of the overall synthetic spectrum. Its integration with the mostly employed predictive/fitting programs (SPCAT and SPFIT, respectively) makes it very effective in handling also perturbed bands. Moreover, its graphical interface offers clear procedures to import/export data formatted in any desired formats and some additional features to handle spectroscopic data. Basically, ATIRS is composed of: – Visual Loomis–Wood (VLW), to assist the assignment of the spectral lines; – Visual CALPGM (VCALPGM), to fit the experimental data and to predict the transition frequencies and their intensities employing SPFIT and SPCAT, respectively; – Visual Spectra Simulator (VSS), to build up the theoretical spectrum from the predicted transition frequencies (and intensities) and to compare it with the experimental one. These three programs can run simultaneously in separate windows, so that the user can switch from one to another seamlessly. By now, the programs are designed to deal with asymmetric rotor infrared spectra and they handle data only in wavenumbers: future developments will include symmetric top molecules and MHz data. 3. Visual Loomis–Wood The Visual Loomis–Wood program (VLW) requires the following input files: – observed transition file (peak list of line positions and intensities); – calculated transition file (computed transition wavenumbers and intensities); – experimental spectrum file. The last one is an optional file required by the ‘‘display’’ mode. By making clearly recognizable the regular pattern of rovibrational transitions in the spectra, Visual Loomis– Wood allows the assignment of spectral lines. It follows the procedure suggested by Nakagawa and Overend [6], which introduced into the Loomis–Wood type diagram the method of Ground State Combination Differences (GSCDs) to check the consistency of P-, Q- and R-branch assignments. In VLW the assignment strategy, which requires an accurate knowledge of the ground state spectroscopic constants, consists of grouping the calculated transitions according to their K 0a (or K 0c ) values; each of these sets is arranged with ascending J 0 values and then further sorted with ascending wavenumbers. In this way the computed transitions belonging to the P, Q, R branches and reaching the same upper level are grouped together. For each transition, the diagram plots the observed wavenumbers nearby the calculated value.
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On a correlation plot designed in this way, the observed transitions to be assigned to a set of P, Q, R lines for the same J 0 should lie on a vertical line if they satisfy the GSCDs and so the consistency of the P, Q, R assignments could be checked. If the upper state spectroscopic parameters employed to compute the transitions are not close enough to the true values, the diagram shows a deviation of the observed line from the corresponding predicted wavenumber. Nevertheless, these displacements have regular patterns leading to state the following criteria of assignment [6]: – transitions with a common level should exhibit equal deviation; and, in absence of local interactions: – this deviation plotted against the rotational quantum number J 0 should follow a smooth continuous trend; – the intensities of the lines should vary in a reasonably manner. Fig. 1 displays an example of the diagram built by VLW: each observed spectral line is here represented as a small box whose colour stands for its relative intensity while its position in the diagram row with respect to the centre (the zero column displacement) is equal to the difference between its experimental and predicted wavenumber.
Transitions mutually linked by GSCDs appear highlighted by a yellow frame thus enabling an efficient visual recognition of regular sequences. The assignment of a spectral line together with the definition of its weight, here defined as 1/(estimated error squared), is carried out with a simple mouse click on it. At any time it is possible to scroll the diagram in the horizontal as well as vertical direction. Having all the P, Q, R transitions displayed simultaneously in the same plot facilitates the assignment step even if some spectral region is congested. Furthermore, the GSCDs checking assists the analysis especially in the presence of anomalous structure caused by resonances. Transitions with a common upper level show equal deviations even if that level is affected by resonance and therefore the perturbed region becomes easily recognizable thus helping to interpret the resonance model. The analysis of spectra with a high density of peaks always presents the risk of erroneous assignments and the Loomis– Wood diagram alone may be not well suited to handle complex overlapping peak systems. In these cases it is necessary to carefully examine these spectral features in search of reasonable possibilities for the assignment. This program increases the reliability of the analysis in such difficult conditions. Once the mouse cursor is placed on a single line, the user can switch to the ‘‘display’’ mode: as shown by Fig. 2,
Fig. 1. Example of a Loomis–Wood type diagram built up by Visual Loomis–Wood. A frame groups the sets of transitions related by a common upper level. A regular sequence of assigned transitions is clearly recognizable. Below the plot more detailed information regarding the mouse-pointed line is reported: quantum numbers, experimental and computed wavenumbers together with their difference, relative intensity and some details about the correlation diagram.
N. Tasinato et al. / Journal of Molecular Spectroscopy 243 (2007) 148–154
151
Fig. 2. Example of the ‘‘display’’ mode (VLW). This feature plots the spectral region centred on a selected polyad. Assigned transitions are labelled by markers (rectangles): when the mouse cursor is above one of them, information about the selected line is reported (line number, quantum numbers and its wavenumber).
Visual Loomis–Wood will plot three different spectral traces showing the spectral region centred on the selected line and the transitions linked to it by GSCDs. By placing the mouse over a given marker above the spectra, the quantum numbers and the wavenumber of the chosen transition are reported. Combined with the Loomis–Wood view, this feature helps to confirm correct assignments. Besides being very effective in assisting the analysis of a-, b- and c-type bands, this program can be used also in the assignment of so-called pseudo-parallel component (selection rule DKa = DKc = 0) of a c-type band. This component may arise due to strong perturbative effects. Another useful feature of Visual Loomis–Wood is its ability in handling automatically the transition file created by the prediction program SPCAT. Upon completion of a set of assignments, by a mouse click the assigned transition file is generated and it is ready to be submitted (without further modifications) to SPFIT. 4. Visual CALPGM ATIRS uses the CALPGM suite developed by Pickett [12] offering a graphical interface to simplify the use of both SPFIT and SPCAT, i.e. the fitting and the prediction program, respectively. This interface, called Visual CALPGM
(VCALPGM), basically consists of two distinct programs, Visual SPFIT (VSPFIT) and Visual SPCAT (VSPCAT): a mouse-click on a button placed in the tool bar lets the user to switch between them. The only input data required by VCALPGM is the <filename>.lin file, i.e. a list of the assigned transitions in the original SPFIT format (for more information see Ref. [12]). VCALPGM allows the user to import the assigned transition files as required by SPFIT, to read, convert and extract the desired data from the output files of SPFIT/SPCAT. This approach makes possible to do both the steps of refining the parameters by the fitting of the assigned transitions and of computing the new rovibrational transitions without the need of exiting VCALPGM. One of the most relevant feature of VCALPGM relies in that the user does not have to code the parameters following the format employed by SPFIT and SPCAT (spectroscopic constants and data about the dipole moments, respectively). As shown by Fig. 3, VSPFIT employs the more common symbols for the rotational constants as well as for the various centrifugal distortion constants and the interaction parameters. Once the number of vibrational states has been specified, the user clicks a specific tab control to display the page relative to the corresponding vibrational state where easily enter or edit the spectroscopic constants. In addition, by opening
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Fig. 3. Example of the Visual SPFIT window during the execution of SPFIT. The program replaces the original Pickett’s parameter codes with the corresponding spectroscopic symbols (referring to the Watson’s A-reduction Hamiltonian in the Ir representation: D = D, d = d, F = U, f = u). Many options have been implemented to import files, to add interaction parameters and to handle data from the SPFIT output file. In the lower panel the output of SPFIT is displayed.
the ‘‘interaction parameter’’ page the user can specify the parameters describing the perturbation effects by choosing among a pre-defined list containing the mostly common ones (i.e. anharmonic and Coriolis resonances). Of course, there exists the possibility of defining a new coupling term by writing the corresponding code following the original Pickett’s notation. As soon as a new interaction parameter has been defined, it appears as a new entry in the list and it will be available in all the subsequent runs of the program. A similar graphical approach to the creation of the input file is adopted by VSPCAT. When the parameter set has been saved, VCALPGM creates the input files for SPFIT or SPCAT (.par or .int file) converting the symbols into the corresponding codes. It is worth to note that this program employs the Watson’s A-reduction Hamiltonian in the Ir representation [23]; nevertheless a simple mouse-click on a button allows the user to edit the input files also by using a text-editor (future developments including other representation and higher order distortion terms have been already planned). After entering all the data sets, by a simple mouse-click the SPFIT/SPCAT program is executed as a hidden process and its output detailing the progress of the computation is displayed in the lower panel of the main window, thus allowing the user to check the correct execution.
VCALPGM provides various tools to handle the output files of SPFIT/SPCAT; in addition, general interfaces have been developed to easily import/export these data according to a user-defined format scheme. 5. Visual Spectra Simulator Visual Spectra Simulator (VSS) is the application which generates and plots the synthetic spectra employing the frequencies and the intensities predicted by VSPCAT. This module requires the following input data: – calculated transition file (computed transition wavenumbers and intensities); – experimental spectrum file. The last one is an optional file required if the user wants to compare the experimental spectrum to the synthetic one. The user has to specify the desired line profile (and its FWHM) choosing among Gaussian, Lorentzian or pseudo-Voigt functions. Once the synthetic spectrum has been plotted, it is possible to change the line profile simply by mouse-clicking: the plotting algorithm developed is fast enough that the spectrum is redrawn immediately.
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Fig. 4. Example of the Visual Spectra Simulator window. This program generates the synthetic spectra from the output files of VSPCAT and can also load the experimental spectra (many options to make easy the comparison between them have been implemented). The plot of the synthetic spectra is mousesensitive: moving the cursor around a peak, in the upper panel the quantum numbers of the corresponding transition are shown, while in the status bar information about its wavenumber and intensity is reported.
Fig. 4 shows an example of the spectrum displayed by VSS: the spectrum can be scrolled left/right by using the scroll bar. By moving the cursor around the peak, the user gets information about its wavenumber, intensity and the values of upper and lower quantum numbers. In the status bar of the window, the wavenumber range of the computed spectrum together with the current position of the cursor (expressed as wavenumber—intensity), the FWHM values and the sampling frequency, are shown. The simulation can be saved into a text file using any kind of format the user wants. Additionally, the software can load the experimental spectrum and display it together with the computed one: several features have been implemented to facilitate the comparison between them. 6. Getting and installing ATIRS ATIRS and its documentation are freely downloadable from http://venus.unive.it/molspectragroup. They consist of a self-extractive archive that contains all the executable files for Windows 2000/XP. The programs have been tested with the current release of SPFIT/SPCAT (October 2006); as soon as a new version will be available, we will check our software package for compatibility. Please refer to the web
site for complete installation and running instructions, for future developments and for giving us suggestions and/or bug notices. 7. Conclusions Extracting the rovibrational parameters from a highresolution infrared spectra still remains a tedious work and very often one has to deal with the additional complexity arising by resonance effects and strongly overlapped peak systems. A new spectrum analysis software called ATIRS is presented in this article. Featuring a Loomis–Wood type diagram interactively linked to a spectra viewer it provides a total access to the full spectral information. The correlation plot displays the P, Q, R branches simultaneously, highlighting the polyad of transitions related by GSCDs, and this organizing scheme aids the check of consistency in the assignments in all the branches even in the presence of irregular pattern. Its graphical interfaces to SPFIT and SPCAT allow the user to fit the assigned transitions and to predict line positions and intensities. Together with its plotting module, this software package aids the overall process of spectral analysis freeing the spectroscopist from many time-consuming
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steps and reducing the danger of misassignment. Its integration with SPFIT/SPCAT routine makes possible to determine the set of spectroscopic rovibronic parameters that describes the measured spectrum also taking into account perturbation features. Acknowledgments The ATIRS package, apart from some revisions, was presented at the Praha 2006 19th International Conference [24]. At that meeting we were informed about the program by Lodyga et al. [25] (a powerful improvement of their previous work [11]); their suggestions are here gratefully acknowledged. The authors thank Prof. H.M. Pickett for his helpful explanations concerning the distribution of SPFIT and SPCAT. This work was financially supported by MIUR, Rome. References [1] W. Leo Meerts, M. Schmitt, Int. Rev. Phys. Chem. 25 (2006) 353–406. [2] G. Moruzzi, L.H. Xu, R.M. Lees, B.P. Winnewisser, M. Winnewisser, J. Mol. Spectrosc. 167 (1994) 156–175. [3] G. Moruzzi, W. Jabs, B.P. Winnewisser, M. Winnewisser, J. Mol. Spectrosc. 190 (1998) 353–364. [4] F.W. Loomis, R.W. Wood, Phys. Rev. 32 (1928) 223–236. [5] J.F. Scott, K. Narahari Rao, J. Mol. Spectrosc. 20 (1966) 461–463; S. Ghersetti, K. Narahari Rao, J. Mol. Spectrosc. 28 (1968) 27–43; A.W. Mantz, K. Narahari Rao, J. Mol. Spectrosc. 30 (1969) 513–530. [6] T. Nakagawa, J. Overend, J. Mol. Spectrosc. 50 (1974) 333–348. [7] B.P. Winnewisser, J. Reinsta¨dtler, K.M.T. Yamada, J. Behrend, J. Mol. Spectrosc. 132 (1989) 12–16.
[8] D. McNaughton, D. McGilvery, F. Shanks, J. Mol. Spectrosc. 149 (1991) 458–473. [9] F. Winther, M. Schoenhoff, R. LePrince, A. Guarnieri, J. Mol. Spectrosc. 152 (1992) 205–212. [10] R. Brotherus, J. Comput. Chem. 20 (1999) 610–622. [11] Sˇ. Urban, J. Behrend, P. Pracna, J. Mol. Struct. 690 (2004) 105–114. [12] H.M. Pickett, J. Mol. Spectrosc. 148 (1991) 371–377,