In the Classroom edited by
Applications and Analogies
Ron DeLorenzo Middle Georgia College Cochran, GA 31014
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Fingerprinting: Commercial Products and Elements DeeDee Allen and Maria T. Oliver-Hoyo* Department of Chemistry, North Carolina State University, Raleigh, NC 27695-8204; *
[email protected] Background
Learning Objectives
Analogies between disparate domains can be used effectively as a guide in problem solving and consequently can enhance the learning process (1). Conceptual understanding can be promoted by the use of analogies as well (2, 3). “Fingerprinting” is an analogical activity developed for a new program called “concept Advancements through chemistry Laboratory– Lecture”, cAcL2. This program constitutes the chemistry portion of the Student Centered Activities for Large Enrollment Undergraduate Programs, SCALE-UP, developed at North Carolina State University (4 ). It combines lecture and laboratory into one class, thereby providing an active learning environment for classes of up to 99 students. Small-scale activities, known as probes and investigations, take center stage in leading students to a better conceptual understanding of chemistry. Probes are short activities in which the students explore specific chemistry concepts through discovery-based learning. Investigations are more involved activities that require students to design experiments and implement specific skills to solve a given problem. “Fingerprinting” is an example of a probe activity developed for cAcL2. Each probe developed for cAcL2 follows a standard format that includes a title, overview, suggested hardware, software and supplies, learning objectives, skills developed, student misconceptions and difficulties, prerequisites, activity table, references, discussion, and supplementary material. The framework of every activity is the activity table, which describes all tasks to be completed and the reason for accomplishing each one. Fingerprinting in its entirety, standard format and complete activity table, is included as supplemental material for this article.W Only background information and an overview are presented in this article.
In this activity students will see how an element can be identified by its emission spectrum just as a consumer product can be identified by its bar code. The specific objectives for this activity are:
Figure 1. Symbols and corresponding scanned signals (5).
1. Students will relate emission spectra to bar codes. 2. Students will be able to interpret bar code patterns. 3. Students will use bar code properties (line widths, positions, reflectance patterns) to identify the properties of an emission spectrum. 4. Students will discover that simple lines can be used to identify elements. 5. Students will relate the gaps in absorption spectra to emission lines.
The analogy between bar codes found in everyday items and absorption–emission spectra emerges from the fact that both contain information in the form of lines and those lines identify a specific product or element. Each set of lines is unique to the item or element to which it corresponds and therefore can be used as a method for identification just as fingerprinting. The fingerprinting activity uses bar codes to develop a basis for how information can be extracted from a line. Among the different types of bar codes that exist, the Universal Product Codes, or UPC symbols, are probably the most common. Examples of UPC symbols are used in this activity in two levels: to show how the information is read from a line and how the reading leads to identification. The connection to line information from absorption–emission spectra follows this presentation. Scanning Bar Codes (5) Bar codes are most commonly read by computerized scanners, which read light patterns reflected from the bar code. The dark lines in the bar code absorb light, whereas the white spaces reflect the light. A reflectance pattern is then detected and interpreted into numbers by distinguishing between different line widths. The shape of the wave form in the reflectance pattern depends upon the diameter of the laser beam being used. A very narrow beam would produce the optimum wave pattern, thus allowing for direct width measurement. However, the typical laser beams found in commercial scanners are Gaussian, which causes attenuation in the fine details of the wave form (see Fig. 1). Therefore, the wave form must be input into an analog-to-digital converter, or wave shaper, that converts the wave form into a more readable form. This is shown in Figure 2. The output wave form is converted into binary code, which can be read by a computer. It is difficult to determine an exact bar width from the reflectance pattern. Therefore, thresholds are set for each bar
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In the Classroom
Figure 2. Signal generation from scanning devices (5).
a
Figure 4. Encoding pattern for UPC-A bar codes.3
Figure 5. Diagram of the parts of a UPC-A symbol.
b
Figure 3. Bar codes with corresponding reflectance patterns. a: Reflectance pattern and bar code obtained from the literature (5). b: A reflectance pattern and (*) the bar code generated from it by a student. The gray area shows how the bar width is approximated from the reflectance pattern.
width in order to determine the best match. These thresholds vary with scanner and available technology. One component of the fingerprinting activity asks students to generate a bar code from a reflectance plot. It is interesting to observe how students choose the widths of bars on the basis of the given reflectance pattern, since there is no specific standard. The reflectance pattern is the key link to the line emission spectra generated by atoms. Discussion of how the scanner obtains the reflectance pattern is later related to how absorption and emission spectra are obtained. 460
In this activity students are asked to draw both an absorption pattern for a bar code and a predicted bar code from a reflectance pattern. This exercise is necessary to test understanding of whether light is reflected or absorbed. Reflectance patterns are always generated from the bar codes, but students are asked to generate the bar code from the pattern to reinforce the idea that information is contained in the peaks or “lines”. Figure 3 shows examples of reflectance patterns obtained from scanners and the corresponding bar codes. Figure 3a shows a reflectance pattern and bar code obtained from the literature (5) and Figure 3b shows a bar code generated by a student from a given reflectance pattern. Decoding bar codes for purposes of product identification leads the discussion into spectral identification. For these exercises, students have access to Internet resources that allow them to decode bar codes and determine a products’ manufacturer.1 Figures 4 and 5 show the encoding pattern for UPC-A bar codes and a diagram of the components of the UPC-A symbol, respectively. A parallel exercise compares emission and absorption spectra for different elements.2 Students are able to see that the gaps in absorption spectra correspond to the lines in emission spectra. The activity is concluded with a discussion of the hydrogen emission spectrum and energy-level diagram followed by questions to assess the students’ comprehension. Understanding the Bar Code (6) The following information is provided for the instructor’s benefit in understanding bar codes. The 12 positions of the characters in a UPC-A symbol are numbered from right to left. In the sample UPC symbol (Fig. 5), 0 is the Number
Journal of Chemical Education • Vol. 79 No. 4 April 2002 • JChemEd.chem.wisc.edu
In the Classroom
System Character found at position 12. This character denotes UPC product type, such as meat or produce, drug and health-related items, coupons, etc. Position 1 (to the far right) contains the check digit, which is 7 for this sample symbol. The check digit validates the UPC symbol and is the result of a mathematical computation of the characters in the bar code. The numbers 028000 (positions 7–12) correspond to the manufacturer, which in this case is Nestlé Food Company. The rest of the characters (positions 2–6) identify the specific product of the manufacturer. The first two lines in a UPC-A bar code are called the left guard pattern. The last two lines are the right guard pattern and there is also a two-line center guard pattern. Guard patterns are of specific widths to indicate to a scanner that a bar code is being scanned. Numbers to the left of the center guard pattern are referred to as “left digits” and those to the right as “right digits”. Every number is encoded by two lines of varying width with relative spacing. The pattern for each number differs depending on its location (see Fig. 4). The line widths and spacing are used to identify an item. Note that other bar codes may use more complex encoding patterns, but all bar codes are identified by line widths and spacing. Relationship Overview Line emission spectra are characteristic of atoms or atomic ions that, once excited, emit energy in the form of light of definite wavelengths as they return to the ground state. Definite energy states give rise to specific transitions, which in turn show up as specific wavelengths in the emission spectrum. Therefore, line spectra consist of irregularly spaced lines whose positions correspond to specific wavelengths. The corresponding wavelengths of the lines are characteristic of the atom being excited and, like a fingerprint, can be used to identify the atoms. Lines corresponding to wavelengths in the visible portion of the hydrogen spectrum are shown in Figure 6. Emission spectra not only contain information in lines, as do bar codes, but they physically resemble bar codes as well. The emission lines would correspond to gaps in a bar code and the dark background resembles the black bars on codes. A hypothetical pattern and bar code generated in Figure 6 show the relationship between the emission spectrum, reflectance
pattern, and bar codes. When a reflectance pattern is overlaid with its respective bar code, the peaks fill in the white gaps creating one continuous peak (see Fig. 3b). The same relationship is observed with line emission spectra and absorption spectra. The lines of emission spectra fill in the gaps found in absorption spectra, yielding the complete, continuous visible spectrum. This connection concludes the learning objectives of the activity. Concluding Remarks This activity offers students the opportunity to relate emission spectra to bar codes on common objects. Students interpret bar code patterns and relate bar code properties to emission spectra. Correlation between commercial bar codes and line emission spectra emerges from the fact that both contain information in the form of lines that identify a specific product or element. Simple lines in a bar code identify a product, and emission lines identify elements. In this activity students generate bar codes from reflectance patterns, which in turn are related to line emission spectra. Overlays of reflectance patterns and their corresponding bar codes are parallel to overlays of absorption and emission spectra. “Fingerprinting” is designed to help both high school and college instructors motivate their students when discussing emission spectra and to increase the students’ level of conceptual understanding. Most probes and investigations developed for cAcL2 are intended to relate everyday life experiences to the wonders of chemical phenomena. Supplemental Material A detailed instructional plan of the activity and further discussion can be found in this issue of JCE Online. W
Acknowledgments Financial support for the development of this new SCALE-UP program, cAcL2, has come from The Fund for the Improvement of Postsecondary Education, FIPSE, Department of Education. We would like to thank the Physics Department Education Research and Development group for their support to launch this program in the Chemistry Department at North Carolina State University. Notes 1. http://www.deBarcode.com/deBarcode/html/index.html. 2. http://javalab.uoregon.edu/dcaley/elements/Elements.html. 3. http://educ.queensu.ca/~compsci/units/encoding/barcodes/ undrstnd.html.
Literature Cited
Figure 6. Relationship between line emission spectrum, reflectance pattern, and bar code.
1. Gick, M. L.; Holyoak, K. L. Cognit. Psychol. 1980, 12, 306– 355. 2. Venville G. J.; Treagust, D. F. Instruct. Sci. 1996, 24, 295–320. 3. Brown, D. E. Int. J. Sci. Educ. 1994, 16, 201–214. 4. Beichner, R. J. Student-Centered Activities for Large-Enrollment University Physics (SCALE-UP); ftp://ftp.ncsu.edu/pub/ncsu/ beichner/RB/SigmaXi.pdf (accessed Jan 2002). 5. Palmer, R. C. The Bar Code Book: Reading, Printing, Specification, and Applications of Bar Code and Other Machine Readable Symbols; Helmers: Peterborough, NH, 1995; pp 168–179. 6. Erdei, W. H. Bar Codes: Design, Printing & Quality Control; McGraw-Hill: New York, 1993.
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