Question

the student designs the following procedure to produce a calibration curve.
step 1: prepare several standard solutions that have known mno₄⁻(aq) concentrations by dilution of the stock solution.
step 2: rinse the cuvette with distilled water.
step 3: rinse the cuvette with the standard solution and fill the cuvette with the standard solution.
step 4: measure the absorbance of the standard solution with the colorimeter.
step 5: repeat steps 2 - 4 for each of the standard solutions.
the data are plotted in the calibration curve shown. one of the data points (indicated with an arrow) on the calibration curve is below the line of best fit.
(c) assuming that all lab equipment is functioning properly, identify which one of the procedural steps the student could have executed incorrectly that would explain why the marked data point is below the line of best fit. justify your answer.

Explanation:

Step1: Analyze each step

• Step 1: Preparing standard solutions by dilution is a valid method if done correctly.
• Step 2: Rinsing with distilled water is a normal pre - step.
• Step 3: If the cuvette is not rinsed properly with the standard solution (e.g., there is still some water or a previous solution residue), the concentration of the solution in the cuvette for measurement will be lower than the actual standard solution concentration. According to the Beer - Lambert law \(A=\epsilon lc\) (where \(A\) is absorbance, \(\epsilon\) is the molar absorptivity, \(l\) is the path length, and \(c\) is the concentration), a lower concentration \(c\) will lead to a lower absorbance \(A\).
• Step 4: Measuring with a properly functioning colorimeter (as per the problem assumption) is okay.
• Step 5: Repeating is a correct procedure.

Answer:

The student most likely executed Step 3 incorrectly. If the cuvette was not rinsed thoroughly with the standard solution (e.g., there was residual water or a less - concentrated solution from a previous rinse), the actual concentration of \(MnO_4^-(aq)\) in the cuvette for measurement would be lower than the known concentration of the standard solution. Since absorbance (\(A\)) is directly proportional to concentration (\(c\)) according to the Beer - Lambert law (\(A = \epsilon lc\), where \(\epsilon\) is the molar absorptivity and \(l\) is the path length), a lower \(c\) would result in a lower \(A\), which explains why the marked data point is below the line of best fit.