LC Innovative Approaches to Data Analysis and Presentation MATLAB Class Test 2022
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LC Innovative Approaches to Data Analysis and Presentation
MATLAB Class Test 2022
Data for answering Question 1
All students analyse the same dataset for Question 1. While the data is shown in the question, it is also provided in a text file:
Qu1_Data.txt
which can be downloaded from the Assessment link in Canvas, and from which you can copy/paste the relevant parts for your MATLAB input file.
Data for answering Questions 2, 3 and 4.
Each student will receive their own bespoke dataset to enable them to answer Questions 2, 3 and 4.
The data can be obtained as follows:
Download the Microsoft Excel file entitled:
LC Data Analysis Summer 22 – Student Data.xlsx which is linked from the Assessment link in Canvas.
Open this file in Microsoft Excel.
Enter your Student ID Number in the highlighted (yellow) box and press the
enter/return key on your keyboard.
Your dataset will be presented in the Excel Spreadsheet.
[Note that you can copy the data from a cell within the spreadsheet by right-clicking with your mouse button and selecting Copy, then pasting the list of numbers into another program to manipulate into the format you require.]Use the data provided below (also available electronically in the Qu1_Data.txt file) to create a 2×2 composite figure to display the following plots:
(Top left) (Top right) (Bottom left)
(Top right)
absorbance versus concentration of iron complex at 396 nm (scatter plot, blue squares);
absorbance versus concentration of iron complex at 550 nm (scatter plot, blue circles);
absorbance versus concentration of copper complex at 396 nm (scatter plot, red squares);
absorbance versus concentration of copper complex at 550 nm (scatter plot, red circles);
Each plot should be titled, axis labels marked with units, and have grid lines displayed. Axis limits should be set to avoid markers extending out of the diagram area.
% Column 1: concentration of iron complex (µM); Column 2: concentration of copper complex (mM); Column 3: Absorbance of iron complex at 396 nm; Column 4: Absorbance of iron complex at 550 nm; Column 5: Absorbance of copper complex at 396 nm; Column 6: Absorbance of copper complex at 550 nm;
data = [10 0.12 0.00084 0.0997 0.10272 0.00408; 20 0.24 0.00168 0.1994 0.20544 0.00816;
30 0.36 0.00252 0.2991 0.30816 0.01224; 40 0.48 0.00336 0.3988 0.41088 0.01632; 50 0.60 0.00420 0.4985 0.51360 0.0204;];
Checklist of components required to be uploaded for Question 1:
Single composite figure.
MATLAB script.
(20 marks)
A solution containing iron and copper ions was mixed with a colorimetric reagent to obtain purple-blue and pale-green iron and copper complexes, respectively. The absorbance of the solution was measured using 1 cm path length cuvette.
Using absorbance and molar extinction coefficient data provided in the Excel data file, determine the concentrations of iron and copper ions in the solution. The symbols used in the Excel data file are defined in the table below.
Symbol |
Description |
396,Fe |
Molar extinction coefficient of iron complex at 396 nm |
550,Fe |
Molar extinction coefficient of iron complex at 550 nm |
396,Cu |
Molar extinction coefficient of copper complex at 396 nm |
550,Cu |
Molar extinction coefficient of copper complex at 550 nm |
A396 |
Total absorbance of solution at 396 nm |
A550 |
Total absorbance of solution at 550 nm |
Recall, at each wavelength
Absorbance = (molar extinction coefficient) × (concentration) × (path length)
For a solution containing species 1 and 2, at each wavelength
Total absorbance = (absorbance of species 1) + (absorbance of species 2)
Checklist of components required to be uploaded for Question 2:
Concentration of iron and copper ions.
MATLAB script.
(30 marks)
Given an analyte solution with molar extinction coefficient of 100,000 M−1cm−1 and a cuvette of path length of 1 cm, calculate the absorbance of solutions of the analyte concentrations provided in the Excel data file.
If absorbance > 1, signal to noise ratio decreases. Determine how many concentrations resulted in absorbance > 1. Create a MATLAB script that generates a list of concentrations that resulted in absorbance ≤ 1.
Recall,
Absorbance = (molar extinction coefficient) × (concentration) × (path length)
Checklist of components required to be uploaded for Question 3:
Number of concentrations that resulted in absorbance of > 1 List of concentrations that resulted in absorbance ≤ 1. MATLAB script.
(30 marks)
The output of an immunosensor and analyte concentration may follow the Langmuir relationship, which is given by the expression below.
c |
c + Kd |
where y is immunosensor output, c is analyte concentration and Kd is dissociation constant.
Use the data provided in the Excel data file and create a semi-log scatter plot by displaying concentrations on a logarithmic x axis. The plot should be titled and axis labels should be marked with units.
Estimate the dissociation constant and the uncertainty in the best estimate.
Checklist of components required to be uploaded for Question 4:
Semi-log scatter plot.
Estimated dissociation constant and the uncertainty
MATLAB script.
(20 marks)
2022-08-20