the computer bulletin board Modified Gran Plots of Very Weak Acids on A Spreadsheet F. T. Chau, H. K. Tse, and F. L. Cheng Department of Applied Biology and Chemical Technology Hong Kong Polytechnic Hung Hom, Hong Kong
The Gran plot methodology has been utilized very often for analyses of acid-base titration curves. For the titration of a weak acid HA with a strong base M+OH-, the variation in the hydrogen ion concentration of the resulting solution with the volume of titrant added v can be expressed by (7,8)
values. What students need to do is to input the volumes of the acidic solution, the volumes of sodium hydroxide added, and the corresponding pH readings in specified ranges of cells. The outputs from the program are the optimal value of pKw, the corresponding correlation coefficient, UE, and pKa. Students can also make use of the graphics feature provided by the spreadsheet to visualize the fitting between the optimized Gran plot and the experimental data. The program MODGRAN was applied to titrations of phenol with calculated values pKa, agreeing well with the literature value (7). We have a listing of the program and a description of the experiments. (Send requests to FTC.)
with VE and Ka being the equivalence volume and the dissociation constant of the acid, respectively. A plot of the product vlO-pH against v gives the Gran plot. However, for very weak acids with pKa > 6, vc instead of v should be used in eq 1with
to give linear plots (9).In the expression, CB, Kw, and VT denote the concentration of the base, the autoprotolysis constant of water, and the total acid volume, respectively. As part of our Chemical Technolgy Laboratory course, we require the second-year students to determine concentrations and dissociation constants of weak acids. The experiment involves titrations of ethanoic acid and phenol with sodium hydroxide solution. For ethanoic acid, values of vlOpH are plotted against the volume parameter v. The equivalence volume as well as the dissociation constant can be determined respectively from the intercept and the slope of the plot. The calculation can further be facilitated with the use of a linear regression analysis by employing a calculator or a computer program package such as Lotus 1-2-3. As for the phenol titration, the parameter KWas given in the modified Gran plot formula (eq 2) varies with experimental conditions and enters in the equation in a nonlinear way. The figure shows modified Gran plots of a phenol titration with different pKw values. To interpret data obtained, students have to use different pKw values to deduce UE and pKa for the titration. It is tedious and time-consuming in so doing. Thus a computer program MODGRAN was written in the Lotus 1-2-3 environment to assist students in this type of calculation. The correlation coefficient of a set of titration data, vc and uclOpH, in a modified Gran plot varies monotonically with pKw around the value of 14. Hence, the dichotomous search (10) was employed by varying pKw systematically within a search interval. The one that gives the highest correlation coefficient is considered to give the optimal pKw value from which the quantities UE and pKa are deduced. In the program, the search interval, the tolerance for pKw, and the numbers of cycles are all set to have certain Journal of Chemical Education
Modified Gran plots of a phenol titration with pKw valuesof 13.25, 13.75, 13.89, 14.00, and 14.45 for curves A-E, respectively.
Computerizinga Stockroom Inventory Martha M. Vestling SUNY College at Brockport Brockport, NY 14420
We have acquired, like many schools, rather more chemicals and supplies than any one of us knew about. Furthermore, our collection is spread over multiple rooms, several buildings, and many different-sized containers. When we decided to computerize our holdings, our goals were to find out what we owned, to save money, to improve storage conditions, to promote safety, and to eliminate unnecessary holdings. This report contains a series of recommendations for others starting the same task. Unlike Feliu ( l l ) , we strongly suggest using commercial database software. There is no reason to reinvent the wheel. The data-
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A. Identifying 1. Organic chemicals a) Chemical Abstracts Service Registry Number i $ , b) Prefix c) Name (usually the, name on the container) 1 2. Inorganic Chemicals a) Chemical Abstracts Service Registry Number b) Name (usually the name of the container) c) Formula 3. Glassware -, a) Glassware number (for the computer to use, locally generated) b) Name c) Size and other specifications 4. Notions a) Notion number (for the computer to use, locally generated) +i b) Name (description given here) ' B. Specific 1. Quantity * , 2. Unit i3. NewIOpened t 4. Manufacturer ' 5. Catalog Number it 6. Building + Y 7. Room 8. Cabinet 9. Shelf 10. Department * ' 11. Unit price 12. Date 1 13. Reorder level
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Select Database to Work On: 1. Organics 2. Inorganics 3. Glass 4. Notions Enter your choice: 2
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You may specify the record you want by entering 1. The CAS Number 2. The Chemical's Name 3. Its Location Enter your choice: 2
