UV-Vis Spectrophotometry
UV-Vis spectrophotometry is a type of quantitative absorption spectrophotometry in the ultra-violet-visible spectral region. This means that light in the visible and adjacent (near UV) ranges is used. This analytical method is used in this experiment because it is suitable for the analysis of organic compounds, especially those with a high degree of conjugation, such as tartrazine (www2.chemistry.msu.edu).
Figure 4. Visible Spectrum (www2.chemistry.msu.edu).
Quantitative spectrophotometry is based on the concept of transmittance and absorbance, illustrated in fig. 5 and fig. 6. The lighter dye solution (right) is less concentrated, allowing more light to penetrate the sample. The darker dye solution (left), however, is more concentrated thus less light is permitted through. If the solution on the left is two times more concentrated than the one on the right, then it has twice the amount of dye molecules, which absorb more light or transmit (pass through) less light. Thus, it appears darker (www.microspectroanalysis.com)
In spectrophotometry, Transmittance is the fraction of light at a specified wavelength passing through a sample. It is also described as the ratio of transmitted light intensity (I) to the incident intensity (I0) (www.microspectroanalysis.com).
T = I/I0
Absorbance, on the other hand, is the inverse log of Transmittance; its usefulness arises from the fact that it is directly proportional to concentration, which makes it ideal for quantitative purposes (www.microspectroanalysis.com).
A = -log(T) A α concentration
The Beer-Lambert Law or Beer’s Law characterises this relationship:
A = εbc
A and c represent absorbance and concentration respectively. The molar absorptivity or extinction coefficient (ε) (M-1cm-1), is a constant value for a certain compound at a given wavelength. The pathlength (b) is where light travels past the sample and is also a constant, usually a 1.0 cm cuvette for a standard spectrophotometer (www.microspectroanalysis.com).
A Beer’s Law plot (or calibration curve), can be generated by graphing absorbance against concentration demonstrating a direct linear relationship. A series of standard solutions must first be prepared to be able to construct such a curve. The standards will consist of a known and specific quantity of the analyte (tartrazine). Each standard’s absorbance is typically measured at the wavelength of maximum peak height (λmax) such as Fig. 7, since it is the wavelength to which the analyte is most sensitive and provides the most accurate results (www.microspectroanalysis.com).
Figure 7. Absorbance with concentration, and maximum peak height
The readings will be used to plot a calibration curve. The absorbance of the sample, which has an unknown concentration of the analyte, s measured. The measured absorbance (y-value) is used in the equation of the line from the calibration curve to calculate the concentration of the analyte in the sample (x-value).
As a rule, a sample (unknown) contains not only the analyte but also further constituents. Mountain Dew does not solely contain tartrazine but also consists of several other ingredients (e.g. carbonated water, concentrated orange juice, high fructose corn syrup, sodium benzoate, citric acid, caffeine). Matrix effects occur when the matrix (components of the unknown other than the analyte) falsely increases or decreases the analytical signal. A compound in the unknown’s matrix may interact with the analyte to change the instrumental response. The result would be a falsely elevated or reduced absorbance reading for the unknown, thus giving an incorrect determination (may appear to have more or less analyte than there actually is) (www.microspectroanalysis.com).
To offset matrix effects, an alternative calibration technique known as standard addition is used. This method is helpful when the analyte is present in a complicated matrix and no ideal blank is available. In standard addition, known quantities of the analyte are added to an unknown (spiking). Equal amounts of the unknown are split into flasks then mixed with correspondingly increasing volumes of the analyte. By spiking we are increasing the analytical signal above the level of noise. We can now generate a standard addition curve from which a more accurate determination of the analyte can be calculated. This is done by extending the line of best fit to its intersection with the concentration axis (x axis) (www.sepscience.com)
Figure 8. Standard Addition Plot