In the Classroom
Separation Anxiety: An In-Class Game Designed To Help Students Discover Chromatography Michael J. Samide Department of Chemistry, Butler University, Indianapolis, IN 46208;
[email protected] Discussions of chromatography in the analytical classroom often begin with theory related to partition coefficients and the van Deemter equation and often end with instrumentation and application (1, 2). Peppered throughout these discussions are equations and terms that allow one to characterize, describe, and optimize a separation. While many students can employ an equation, or even perform experimental procedures involving chromatography, some have a difficult time envisioning the actual process producing the separation. Helping students understand chromatographic separations as an equilibrium process can be difficult.
Table 1. Example Set of Partition Coefficients Used To Separate Nickels and Pennies Turn
Number of Nickels (%)
Number of Pennies (%)
Stationary Phase
Mobile Phase
Stationary Phase
Mobile Phase
1–5
30
70
80
20
6–10
20
80
65
35
11–15
10
90
50
50
16–30
0
100
35
65
Note: In this example the partition coefficients increase to reflect a higher affinity of the analytes toward the mobile phase. This gradual change is designed to mimic the process of gradient elution. However, different sets of partition coefficients can be given to different teams and results of various separations can be compared between groups.
injector All items begin here
Stationary Phase
Mobile Phase detector Count items and record
Figure 1. A game board for the separation game. The boxes on the left represent the mobile phase, with direction of flow indicated by the shaded arrow. The boxes on the right represent the stationary phase, with equilibrium being denoted by the equilibrium arrows.
1512
Many experimental procedures exist that describe the application of chromatographic separations in the laboratory (3). These experiments tend to focus on optimization of a separation, quantitative analysis of a mixture, or isolation of a desired product. In addition to laboratory experiments, many computer-based simulations (4–7) have been described that focus on the mathematical aspects of a separation. These exercises allow students to change a particular parameter and monitor the effect on a particular separation. While these types of exercises play an important role in educating students, they often do not provide students an opportunity to discover for themselves the physical basis for separation. Several recommendations regarding this type of discovery or problem-based active learning have resulted from discussions at various National Science Foundation workshops (8, 9). These include direct student exposure to the material using the methods and processes of inquiry, small-group learning, cooperative learning, and project-centered classes. Furthermore, this type of active learning in the classroom often tends to make abstract concepts more concrete (10, 11). Multiple in-class activities can each focus on a different aspect of a similar topic. Bauer (12) describes an in-class exercise where students move through chairs and sit for a predetermined time. This exercise highlights the differences an analyte might have with a stationary phase. Smith and Villaescusa (13) describe an in-class exercise where students become the sample and must separate themselves using provided guidelines. As a result of this activity, students experience and then discuss the role of flow rate, column dimensions, and mobile–stationary phase affinity on a particular separation. Parcher (14) describes a parable used in explaining how affinity to the stationary phase effects separation. While the models used in the classroom may not represent a system with complete accuracy, they serve in helping a student bridge the gap between abstract concepts and reality. I describe a game, developed using plate theory, to assist students in understanding the concepts of partition coefficient, equilibration, retention, resolution, gradient programming, and, ultimately, separation. The game allows students to physically separate coins on the basis of a provided partition coefficient (changed throughout the game by a theoretical gradient program). Students move coins between stationary and mobile phases to establish equilibrium conditions. The goal of the game is to have students understand equilibration as it relates to separation, which can then lead students into a discussion of more complex topics. Because of the simplicity of the exercise, it could be used at any level from a high school AP class to college-level instrumental analysis. Equipment To play this game, a team of students need a calculator, a stop watch (a key component to the anxiety element of the game), 20 pennies, 20 nickels, a gradient program (as shown in Table 1), and game board. A rule sheet and a tally sheet are provided that outline some theory and relate class discussion topics to the activity. As shown in Figure 1, the game board was
Journal of Chemical Education • Vol. 85 No. 11 November 2008 • www.JCE.DivCHED.org • © Division of Chemical Education
In the Classroom
developed with a mobile phase and stationary phase, divided into eight distinct equilibration zones or plates. All game pieces begin in the injector square and are moved onto the “column”. At the end of the board sits a detector, where students count the total number of each item eluting from the board. Playing the Game To add interest and excitement to the game, each group of students is instructed to complete the separation of game pieces within a 10 minute time period. When a team of students begin the game, all 40 game pieces are placed in the injector square of the board and then are immediately moved into the mobile phase. Each “turn” in the game consists of (a) equilibration of items in each cell according to the partition coefficients
Students continue to equilibrate and move game pieces toward the detector until all pieces are removed from the board. As each turn ends, students should check the partition coefficients to be used in each subsequent equilibration. A theoretical gradient program (either temperature or solvent) causes the analyte to have a higher affinity for the mobile phase. Once items have reached the detector square, the items are removed from the board and are considered out-of-play. Scoring As game play progresses, students use a provided tally sheet (Table 2) to record the number of items at the detector as a function of “turn” number. Once all pieces are off the board, students are instructed to plot the results using Excel. Figure 2 depicts an example Excel graph for separation of nickels and pennies using the partition coefficients shown in Table 1.
Table 2. Sample Tally Sheet Generated by Playing the Separation Game Using the Partition Coefficients Found in Table 1 detector
detector
Turn
Number in the Mobile Phase (%) Nickels
beginning configuration before equilibrium
configuration after equilibrium
Game pieces are partitioned between the mobile phase (left set of boxes in each plate) and the stationary phase (right set of boxes in each plate) according to the partition coefficients specified by the instructor. In this example, notice that the pennies (dark circles) are more retained than nickels (light circles). Also note that it is the total number of items in a plate that come to equilibrium; coins can move from the stationary phase to the mobile phase or vice versa. During this step, all plates containing game pieces undergo equilibration to meet the requirements specified by the partition coefficient. Furthermore, when determining the number of game pieces to move (or keep) in the mobile phase, any fractional values of 0.5 or higher are rounded to the next higher whole number. (b) shifting the game pieces one plate down, toward the detector.
detector
detector
Only game pieces in the mobile phase (left set of boxes in each plate) will move toward the detector. Those in the stationary phase stay in place unless promoted into the mobile phase during an equilibration step. (c) counting the number of each item in the detector square. In this example, no items are in the detector square. Therefore we count 0 nickels and 0 pennies.
Number at the Detector
Pennies
Nickels
Pennies
1
70
20
0
0
2
70
20
0
0
3
70
20
0
0
4
70
20
0
0
5
70
20
0
0
6
80
35
0
0
7
80
35
0
0
8
80
35
2
0
9
80
35
5
0
10
80
35
5
0
11
90
50
3
0
12
90
50
3
0
13
90
50
2
1
14
90
50
0
1
15
90
50
0
1
16
100
65
0
2
17
100
65
0
3
18
100
65
0
3
19
100
65
0
3
20
100
65
0
1
21
100
65
0
1
22
100
65
0
1
23
100
65
0
1
24
100
65
0
1
25
100
65
0
1
26
100
65
0
0
27
100
65
0
0
28
100
65
0
0
29
100
65
0
0
30
100
65
0
0
© Division of Chemical Education • www.JCE.DivCHED.org • Vol. 85 No. 11 November 2008 • Journal of Chemical Education
1513
In the Classroom
Once students have completed the exercise and have plotted their results using Excel, a series of topics can be discussed either in small groups or as an entire class. Here, the calculated values can be determined from the data presented in Figure 2.
1) Partition coefficients – Using equilibration as a starting point, students can discuss the differences in retention as a function of partition coefficients.
2) Gradient elution – Students can discuss the need to change the analyte affinity to the stationary or mobile phase in order to optimize a separation.
3) Retention time – Using the graph, students can see and discuss how partition affects retention. Values such as the retention times for the nickels and pennies, tR,nic and tR,pen, respectively, and the time for an unretained species, tm, can be determined. In this case, the retention times are estimated from the plot in Figure 2 and tm is a function of the size of the game board (tm = 8 since it requires 8 moves to have an unretained item travel from injector to detector). In addition, relative retention (α) and capacity factor (k′) can be calculated.
B knic b
kpen b
tR , pen
tR , nic
19 1. 9 10
t R , nic tm 10 8 0. 25 tm 8 t R, pen tm tm
19 8 1. 375 8
The greater the relative retention, the greater the separation between the two components. The greater the capacity factor, the longer a component is retained.
4) Resolution – Using the graph, students can calculate resolution, R, using the retention times and the average of the peak widths, wav, and compare with other students (if other students were given different sets of partition coefficients)
R
% tR wav
19 10 7 14 2
0. 86
Required resolution for product isolation or quantitation can be discussed. In general, a resolution > 1.5 is necessary for quantitation.
5) Peak tailing – In many cases students will notice that the items being separated tend to lag behind once a separation is almost complete.
Modifications Additional modifications can be made to the game to enhance the students’ understanding of separations. For example, to illustrate longitudinal diffusion, students can move items in the mobile phase vertically. Students could also be given a set time to achieve equilibrium before moving the items in the mobile phase (increasing the “anxiety” portion of the game). This would allow students to discover the affect of flow rate on the equilibrium process. 1514
Number of Items at Detector
6
Discussion
nickels
5 4
pennies
3 2 1 0 0
5
10
15
20
25
30
35
Turn Figure 2. An Excel graph depicting the “chromatogram” generated from playing the separation game using the partition coefficients found in Table 1. Estimation of the retention times for the nickels (tR,nic) and for the pennies (tR,pen) are 10 min and 19 min, respectively. Peak widths, w, are estimated to be 7 min and 14 min for the nickels and pennies, respectively.
Literature Cited 1. Harris, D. C. Quantitative Chemical Analysis, 7th ed.; W. H. Freeman and Company: New York, 2007; Chapters 23 and 24. 2. Harvey, D. Modern Analytical Chemistry, 1st ed.; McGraw Hill, Boston, 2000; Chapter 12. 3. JCE Index Search for “Chromatography”. http://www.jce.divched. org/Journal/Search/search.html (accessed Jun 2008). 4. Stone, D. C. J. Chem. Educ. 2007, 84, 1488–1496. 5. Haigh, J.; Lord, J. R. J. Chem. Educ. 2000, 77, 1528. 6. Armitage, D. B. J. Chem. Educ. 1999, 76, 287. 7. Sundheim, B. R. J. Chem. Educ. 1992, 69, 1003–1005. 8. Shaping the Future: New Expectations for Undergraduate Education in Science, Mathematics, Engineering, and Technology; NSF 96-139; National Science Foundation, Directorate for Education and Human Resources, 1996. http://www.nsf.gov/pubs/stis1996/ nsf96139/nsf96139.txt (accessed Jun 2008). 9. Kuwana, T. Curricular Developments in the Analytical Sciences; final report of workshops supported by the National Science Foundation Directorate of Education and Human Resources and Division of Undergraduate Education and Division of Chemistry; Leesburg, VA, Oct 28–39, 1996; Atlanta, GA, March 13–15 1997. http://www.asdlib.org/files/curricularDevelopment_report. pdf (accessed Jun 2008). 10. Spencer, J. N. J. Chem. Educ. 1999, 76, 566–569. 11. Wenzel, T. J. Anal. Chem. 2000, 72, 293A–296A. 12. Bauer, C. F. J. Chem. Educ. 1982, 59, 846. 13. Smith, C. A.; Villaescusa, F. W. J. Chem. Educ. 2003, 80, 1023–1025. 14. Parcher, J. F. J. Chem. Educ. 2000, 77, 176.
Supporting JCE Online Material
http://www.jce.divched.org/Journal/Issues/2008/Nov/abs1512.html Abstract and keywords Full text (PDF) Links to cited URLs and JCE articles
Color figures
Supplement
Student handouts
Score and tally sheet
Game board
Journal of Chemical Education • Vol. 85 No. 11 November 2008 • www.JCE.DivCHED.org • © Division of Chemical Education
