1. A mixture of Benzene and Toluene in solution gave the following chromatography results:
|
Compound |
Concentration (µg/mL in mixture) |
Peak area (cm2) |
|
Benzene |
236 |
4.42 |
|
Toluene |
337 |
5.52 |
A solution was prepared by mixing 1.23 mg of Toluene in 5.00 mL, with 10.00 mL of a solution containing only an unknown concentration of Benzene, and then diluting the mixture to 25.00 mL. Peak areas of 3.33 and 2.22 cm2 were observed for Benzene and Toluene respectively. Find the concentration of (µg/mL) in the unknown Benzene solution.
2. The US Department of Defense is in the process of disposing of all VX nerve agent chemical warfare stocks to meet Chemical Disarmament Treaty requirements. Chemical neutralization and incineration are the technologies being used for disposal. Prior to operations, one of the on-site laboratories had developed and validated internal standard methodology to verify the effectiveness of the neutralization process in destroying VX. To prepare the laboratory to analyze an incoming set of plant reaction batch samples, the laboratory chemists conducted a calibration of their VX GC/MS/MS internal standard quantitative method and obtained the following set of calibration data:
|
VX Spike (pg/ml) |
IS Peak Area |
VX Peak Area |
|
0 |
28,028 |
1,170 |
|
5 |
29,149 |
3,888 |
|
10 |
28,449 |
10,732 |
|
15 |
29,412 |
16,589 |
|
20 |
28,972 |
21,049 |
|
30 |
29,186 |
33,457 |
The lab then used these internal standard calibration data to analyze a plant sample prepared with the same amount of added internal standard. The analysis of this plant sample yielded a VX peak area of 25,345 and an internal standard peak area of 28,523. Set up an internal standard calibration curve, plot it, show all regression calculations, and determine the amount of VX in the plant sample.
3. Curvilinear Regression Problem: The table below lists data obtained from the calibration of an atomic emission spectrometer's response for a range of alkali ion concentrations. These data are nonlinear above 5.0 ppm.
Concentration
(ppm)
|
Counts/msec
|
0.2
|
0.8
|
0.5
|
1.3
|
1.0
|
2.2
|
2.0
|
3.7
|
3.0
|
5.1
|
4.0
|
6.5
|
5.0
|
7.8
|
6.0
|
8.9
|
7.0
|
9.9
|
8.0
|
10.5
|
9.0
|
10.8
|
10.0
|
11.0
|
Using all points, conduct a 2nd order fit of these data; plot the predicted curve, the data points, and write the equation for the predicted curve that includes appropriate units.
For an unknown analysis that gave a reading of 10.6 counts/msec, determine the unknown's concentration. Show all calculations on a labeled separate worksheet; graphically illustrate this on your calibration plot.
Using all points, conduct a 1st order fit of the data, show the equation, and compare the Coefficients of Determination for the 1st and 2nd order fits. State what percent of the overall variability is accounted for in each of these fits
4. Injection Variability:
The purpose of this exercise is to characterize the variability associated with GC injection techniques. In Room Sims 310 is a GC syringe (in a box), two small beakers and two analytical balances. Working with a lab partner, each person should make 10 separate 5 microliter syringe injections into the tared beaker. Prepare a spreadsheet that determines the following:
The volume of each injection (remember to measure the temperature)
The average volume injected for each lab partner
The average volume for the overall group
The standard deviation for each person
The standard deviation for the overall group
The Coefficient of Variation (CV) for each person and the overall CV. CV is the standard deviation divided by the average, represented in %.
Internal standard quantification is designed to minimize injection errors. Generally, IS techniques are found to be quantitative within 1%. Compare this 1% standard with the CV's you each obtained for your 10 injections.