Information • Textbooks • Media • Resources edited by
JCE WebWare
William F. Coleman Wellesley College Wellesley, MA 02481
From Our Peer-Reviewed Collection
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Edward W. Fedosky University of Wisconsin–Madison Madison, WI 53715
The JCE WebWare collection continues to evolve and grow. If you have developed resources for teaching and learning chemistry that are readily accessible via the Web, we encourage you to submit them to be considered for publication in JCE WebWare. We have recently reorganized the submission and review processes. Guidelines for preparing and submitting materials are available at http://jchemed.chem.wisc.edu/ JCEWWW/Features/WebWare/submit.html. If you have questions, contact the JCE WebWare assistant editor, Ed Fedosky, at
[email protected]. We are preparing to incorporate JCE WebWare into the National Science Digital Library (NSDL), along with other materials from the JCE Digital Library (JCEDLib). More information on this effort is available online at http:// jchemed.chem.wisc.edu/JCEDLib/. This month we add another program, “SpecScan: A Utility Program for Generating Numerical Data from Printed Forms of Spectra or Other Signals”, to our collection of peerreviewed WebWare. Find this and the entire collection at http:// jchemed.chem.wisc.edu/JCEWWW/Features/WebWare/collection/ reviewed/index.html. SpecScan: A Utility Program for Generating Numerical Data from Printed Forms of Spectra or Other Signals W Constantinos E. Efstathiou, Laboratory of Analytical Chemistry, Department of Chemistry, University of Athens, University Campus, Athens 157 71, Greece;
[email protected] SpecSpan is a utility program for Microsoft Windows that generates numerical data from printed spectra or other plots found as figures in text, chart recordings, or freehand drawings. SpecScan can process bitmap (.BMP) images of such figures and drawings. After a brief interaction with the user, it generates and exports numerical data as Excel (.XLS) or text (.TXT) files. There may be up to 1500 X–Y data points that represent the original signal at the appropriate units. Such data could be obtained manually drawing fine vertical and horizontal auxiliary lines on spectra or on enlarged photocopies. The measured distances are linearly transformed to the respective values of the physical or chemical quantities. This is tedious, prone to error, and can only obtain a limited number of usable X–Y data points. A simple method of digitizing data using a personal computer and a pen plotter (1) requires extensive user input and generates data sets of limited size. More sophisticated methods involving light pens or other X–Y data-tracking devices require special hardware and software. Using SpecScan is convenient and accurate. An image file is first obtained by scanning a printed plot and saving
Figure 1. Processing of a retouched bitmap image originally scanned from a figure in an instrumental analysis textbook (2), containing three absorption spectra (molar absorptivity vs wavelength, in nm) of aqueous solutions of Co2+, Ni2+, and Cu2+. The Ni2+ spectrum is shown being processed, and SpecScan has been instructed to generate an .XLS file containing 501 equidistant spectral points (at 1 nm intervals).
the image in .BMP format. Some retouching may be necessary to remove black pixel smudges, and the orientation of the bitmap image may need adjustment to align the diagram axes as closely as possible to vertical and horizontal. Most image-processing programs can perform this retouching. The image is then imported into SpecScan, which generates and exports a set of data points that corresponds to the imported plot. Alternatively, SpecScan allows the user to select the experimental points to be included by visual inspection of the graph. This manual mode must be applied when the printed signal is represented by isolated points and not by a continuous line, and for graphs depicting cyclic processes (for example, cyclic voltammograms), which cannot be automatically handled by SpecScan. The X–Y data file generated by SpecScan can be imported to any data-analysis program. The original signal then can be reconstructed, rescaled, or subjected to any mathemati-
JChemEd.chem.wisc.edu • Vol. 80 No. 9 September 2003 • Journal of Chemical Education
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Information • Textbooks • Media • Resources
cal transformation or treatment to extract further numerical information, for example a least-squares regression analysis, or combining two or more X–Y data sets to generate a graph of composite signals. Educators may use SpecScan to demonstrate the wealth of numerical information that can be extracted from figures found in texts as well as showing how one graph can be transformed to another—how an absorbance spectrum can be calculated from a transmittance spectrum or how a back-
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ground-corrected absorbance can be obtained by a point-topoint subtraction of two absorbance spectra. Literature Cited 1. Manche, E. P.; Fox, J. T. J. Chem. Educ. 1993, 70, 994. 2. Skoog, D. A.; Holler, F. J.; Nieman, T. A. Principles of Instrumental Analysis, 5th ed.; Saunders College Publishing: Philadelphia, 1998; p 338.
Journal of Chemical Education • Vol. 80 No. 9 September 2003 • JChemEd.chem.wisc.edu
