In the Laboratory edited by
The Microscale Laboratory
R. David Crouch Dickinson College Carlisle, PA 17013-2896
W
Microscale Quantitative Analysis of Hard Water Samples Using an Indirect Potassium Permanganate Redox Titration John N. Richardson,* Mark T. Stauffer, and Jennifer L. Henry Department of Chemistry, Shippensburg University, Shippensburg, PA 17257; *
[email protected] In recent years, there has been a great deal of interest among instructors of high school, college, and university laboratories in reducing traditional laboratory experiments to microscale (1–3). These changes have been made in response to the need to cut costs of materials and waste disposal, as well as to make these experiments safer and more environmentally friendly. Microscale experiments have been shown to be particularly effective in wet analytical chemistry techniques such as titration. In fact, accounts of microscale analytical titration experiments may be found in the literature and in commercially available laboratory manuals (4, 5). However, there has been little mention in the literature of use of microscaled techniques in the traditional quantitative analysis laboratory, and only one citation involving comparison of accuracy and precision data between comparable microscale and macroscale titration techniques (6). The work presented in this paper includes a procedure for a microscale quantitative analysis of hard water using an indirect potassium permanganate redox titration. This technique is a traditional method (7) of determining calcium ion concentration in an aqueous sample, and it lends itself particularly well to an introductory quantitative analysis laboratory course because it exposes students to several fundamental quantitative principles in a single laboratory exercise. These include: (a) redox titration, (b) indirect titration, (c) use of a primary standard, (d) use of a self-indicator, and (e) quantitative precipitation, digestion, and filtration. In fact, this experiment (run as a macroscale analysis) has been a staple in our quantitative analysis laboratory for many years. As an abbreviated introduction, Ca2+ from a prepared hard water solution is precipitated in basic solution as CaC2O4, the precipitate is recovered, and then redissolved in dilute acid, whereupon the liberated C2O42- is titrated according to the reaction 5 C2O42᎑ + 2 MnO4᎑ + 16 H+
This paper focuses on an analysis of the quality of the data obtained using microscale techniques, as well as a comparison of actual student data from our instructional laboratories in which accuracy and precision of both microscale and traditional macroscale data are compared. The microscaled experiment employed may be found in the Lab Documentation.W Results and Discussion The first objective of this work was to determine whether or not the analysis could be effectively microscaled. To accomplish this task, the entire microscaled experiment was run repeatedly by a test student who had taken our quantitative analysis course previously, and was thus familiar with the chemistry and techniques required. We began by investigating the standardization process. Here, the student performed 20 titrations using the traditional macroscale approach and a 50.00-mL buret, followed by 20 more trials using the microscale procedure and a 2.000-mL microburet. A summary of the data acquired is found in Table 1. Here, the average molarities differed by only 0.0001 M, and the standard deviations in both cases were acceptably small. In fact, the student obtained identical standard deviations using both techniques. These results suggest that there is no quantitative disadvantage to conducting the standardization of the KMnO4 titrant using microscale titration. Our next objective was to have the test student use the standardized titrant to complete three full sets of microscale analysis on different unknown hard water samples. These samples were prepared by the instructor and introduced to the student as would be done in the instructional laboratory.
Table 2. Summary of Test Student's Results for Microscale Analysis of Calcium in Three Unknown Hard Water Samples
10 CO2 + 2 Mn2+ + 8 H2O
using a previously standardized KMnO4 titrant.
Unknown Sample #
Table 1. Test Student Standardization of KMnO4 Titrant Techniques
Molar Concentration /mol L᎑1
Standard Deviation /mol L᎑1
Microscale
0.0218
0.0006
0.0219
0.0006
∆a (ppm)
Standard Deviationb (ppm)
1
391
401
᎑10
13
2
476
481
᎑5
15
642
᎑6
13
3 a
Macroscale
Reported Ca2+ Actual Ca2+ concentration concentration (ppm) (ppm)
636
∆ = [Ca ]Reported − [Ca ]Actual 2+
2+
b
Based on three trials for each unknown sample.
JChemEd.chem.wisc.edu • Vol. 80 No. 1 January 2003 • Journal of Chemical Education
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In the Laboratory
were used to calculate the section average. The reason for this is that in many cases, the raw average ∆ looks deceptively small because large individual values both above and below the actual values tend to cancel one another out. By analyzing the absolute averages, one can appreciate the large deviations that seem intrinsic to this technique. The raw average differences are given as a means of identifying and evaluating possible determinate error. The statistical analysis of these data is given in Table 4. Some interesting trends come out of the data in Tables 3 and 4. First, comparing accuracy, the average of the microscale ∆ values is 61 ppm, compared to 52 ppm for the macroscale ∆ values. Assuming all error to be random, a comparison of these means using Student’s t test (at the 95% confidence level) clearly indicates that there is no statistical difference between the macroscale and microscale data sets. However, a closer comparison of the raw ∆ values in Table 3 indicates that all microscale section averages were low; in the macroscale experiment three sections turned in low average values while the remaining three section turned in high average values. These data indicate that there is likely a source of determinate error in the microscale technique that does not appear to be present in the macroscale technique. Since all microscale averages are below the expected values, the error must result from either undertitration or loss of analyte. As a means of evaluating the source of this apparent determinate error, both the test student and quantitative analysis students were polled as to what they felt the most error-prone aspect of the experiment might be. While some students felt
Therefore, the student had no previous knowledge of the actual concentration of calcium in each sample. The quantitative results obtained are shown in Table 2. The largest difference between the actual and reported ppm calcium values (∆) was 10 ppm, which is quite acceptable based on past student results (macroscale). Likewise, standard deviations, based on three trials per unknown sample, were also quite impressive compared to past student results. It is also notable that in all cases the magnitude of the difference falls within one standard deviation on either side of the mean. These results indicate that with proper and careful experimental technique, the microscale procedure can be just as accurate and precise as the traditional macroscale experiment. Our final goal of this work was to demonstrate that the microscale procedure could be introduced to the instructional laboratory and be carried out effectively by inexperienced students, some of whom had not yet been exposed to microscale techniques. To accomplish this, laboratory data from the past four years of our quantitative analysis course were collected and condensed. These data are illustrated in Table 3. Note that there are two years of macroscale data, 1998 and 1999, and two years of microscale data, 2000 and 2001. The data are broken down by individual sections, and the number of students per section is included. We have chosen to categorize the average section ∆ values two ways: first as a raw average that accounts for data both higher and lower than the actual values (i.e., we account for the sign of the deviation), and secondly, as an absolute average in which the absolute values of the individual differences within a section
Table 3. Summary of Students' Quantitative Analysis Results # Students per Section
Year
Section's Raw Average ∆ (ppm)
Section's Absolute Average ∆ (ppm)
Average Section Standard Deviation (ppm)
7
’98 (macro)
33
’98 (macro)
1 ᎑16
40
12
23
31
17
’98 (macro)
5
26
20
8
’99 (macro)
131
39
17
’99 (macro)
80 ᎑52
55
20
16
’99 (macro)
᎑50
59
16
10
’00 (micro)
᎑71
74
52
16
’00 (micro)
᎑71
73
32
14
’00 (micro)
᎑67
82
44
18
’01 (micro)
᎑28
50
19
21
’01 (micro)
41
35
14
’01 (micro)
᎑8 ᎑51
63
25
Table 4. Statistical Analysis of Macroscale and Microscale ∆ Values
66
Statistic
Raw Microscale ∆ (ppm)
Absolute Microscale ∆ (ppm)
Raw Macroscale ∆ (ppm)
Absolute Macroscale ∆ (ppm)
Average
᎑46
61
᎑16
52
Standard Deviation
62
47
74
55
Journal of Chemical Education • Vol. 80 No. 1 January 2003 • JChemEd.chem.wisc.edu
In the Laboratory
intimidated by the microburet, the vast majority pointed toward the quantitative filtration step. This step is accomplished using a ca. 4-cm filter paper folded into a cone and placed into the bottom of a large long-stemmed filter funnel. As one can imagine, a great deal of manual dexterity is required to decant and rinse only a few milliliters of supernatant and a nearly undetectable amount of precipitate into the relatively small filter paper. Indeed, the instructors noted a great deal of overfilling and “creeping” which ultimately led to loss of analyte. We feel that future purchase of micro-filter funnels will go a long way toward alleviating this problem. Another means of mitigating this problem might be to perform the digestion in a test tube, spin the precipitate down in a centrifuge, and rinse with water prior to performing the final titration. Comparing student precision, the average of all microscale standard deviations (raw) was 62 ppm, whereas the macroscale value (raw) was 74 ppm. Again, assuming error to be random, there appears to be no significant difference between the macroscale and microscale procedures. However, given knowledge of the probable loss of precipitated calcium oxalate, it seems sensible that a larger standard deviation might be expected in the case of the microscale analysis. Hazards Students should follow customary safe laboratory procedures, especially while handling strong acids. Students should also be aware that 0.02 M KMnO4 is an oxidizing agent and can cause discoloration of skin and clothing. With the exception of student preparation and degassing of 1:20 (v:v) and 1:10 (v:v) aqueous H2SO4 (both of which could be prepared and degassed in advance by a trained technician, if the instructor wished), all strong acids needed in the lab are provided to the students in dropper bottles, which lessens the chance of spillage and subsequent injury.
Note that the procedure always calls for addition of acids by counting drops. Conclusions We have compared data from both traditional macroscale and a new microscale determination of calcium in an unknown hard water sample via titration using standardized permanganate solution. Our data indicate that the microscale technique yields data of comparable accuracy and precision to the macroscale technique. However, potential users of the microscale approach should be aware that loss of calcium oxalate precipitate during the filtration step could be a potential source of determinate error. This error should be easily mitigated through careful technique and use of appropriate microscale glassware. W
Supplemental Material
Detailed information about the microscaled experiment is available in this issue of JCE Online. Literature Cited 1. Belletire, J. L.; Mahmoodi, N. O. J. Chem. Educ. 1989, 66, 964. 2. McGuire, P.; Ealy, J.; Pickering, M. J. Chem. Educ. 1991, 68, 869. 3. Craig, E. R.; Kaufman, K. K. J. Chem. Educ. 1995, 72, A102. 4. Kumar, V.; Courie, P.; Haley, S. J. Chem. Educ. 1992, 69, A213. 5. Singh, M. M.; Pike, R. M.; Szafran, Z. Microscale and Selected Macroscale Experiments for General and Advanced General Chemistry: An Innovative Approach; Wiley: New York, 1995. 6. Singh, M. M.; McGowan, C. B.; Szafran, Z.; Pike, R. M. J. Chem. Educ. 2000, 77, 625. 7. Ayres, G. H. Quantitative Chemical Analysis, 2nd ed.; Harper and Row: New York, 1968; pp 590–593.
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