Quantitative Analysis of Potassium Permanganate by Spectrophotometric
Methods
Student Contributors: Andrew Park, Arman Manjikian, Claire Ryu, Courtney Zielke, Diana Abaryan, Danial Albino, Elizabeth Orr, Erick Escalera, Erik Hernandez, Kenneth Robles,
Jason Bonilla, Misty Mills, Samantha Suh, Steve Reyes.
Faculty: Terry Boan
Discussion
Results
Abstract
Absorbance Spectra
Former DI Water - Day 1 vs. Day 7
Possible factors affecting absorbance readings of potassium permanganate
solutions were investigated. Parameters studied include potassium permanganate
precipitate age (as determined at time of purchase), pH, light exposure, and water
sources. Various concentration of potassium permanganate solutions were
prepared to test each parameter. Their absorbance was measured in timed
intervals. While our data points toward water sources as the main culprit in
solutions degradation, further studies are underway to rule out other factors, such
as organics and kinetic effects.
Degradation Curve of 0.00016 M KMnO4
0,3
0,45
0,4
0,25
0,3
0.00016 M Day 1
0,25
0.00016 M Day 7
0.000064 M Day 1
0,2
0.000064 M Day 7
0.000032 M Day 1
0,15
0.000032 M Day 7
Absorbance (at 523 nm)
Absorbance (at 523 nm)
0,35
0,2
Environmental Water
0,15
Ultrapure Water
Deionized Water
0,1
0,1
0,05
0,05
0
400
450
500
550
600
650
700
0
0
50
Wavelength (nm)
100
150
200
Time (hours)
•Figure 2- Absorbance spectra comparison of the first and seventh day of each
solution displays no major shift at the peak absorbance.
Different parameters were tested in order to determine the cause(s) for
the degradation of KMnO4 during an undergraduate chemistry
experiment. The results revealed that variables such as pH, the age of the
KMnO4, and exposure to UV light had minimal effect on the change of
absorbance observed over time, leaving the school’s water source as the
most probable determinant.
Focus of research shifted to comparing the effects of different water
sources on the absorbance readings, with ultrapure and environmental
water used as controls. The environmental water was obtained from a
preserved sample of the Ventura water containing contaminants following
the Thomas fire. As expected and apparent in Figure 3, the absorbance
patterns of the KMnO4 in the ultrapure water displayed the most stability.
However, solutions derived from the environmental and deionized water
showed drastic degradation, with the highest rate occurring in the
beginning hours.
•Figure 4 - It is evident from the comparison of the degradation curves of the
different water sources used that the solution derived from deionized water did not
display the same stability as ultrapure water.
Methods
Conclusion
•Results imply that the school’s deionized water contains impurities that
affect the stability of the KMnO4 solutions. Future experimentation will
attempt to identify these impurities and explore associated kinetic
properties.
Degradation Curve of KMnO4 with Deionized Water
0,3
0,25
Absorbance (at 523 nm)
Average % Increase in Transmission
0,2
0.00016 M
0,15
0.000064 M
0.000032 M
0,1
0,05
Water Source
0.00016 M
0.000064 M
0.000032 M
Ultrapure
7.7
7.0
4.7
Environmental
86.0
26.2
8.5
Former DI
59.0
20.0
6.7
Current DI
88.0
36.2
13.2
Acknowledgements
0
0
50
100
150
200
Time (hours)
Figure 1: Degradation via light exposure and pH were documented in
previous experiments; degradation via 𝐾𝑀𝑛𝑂4 age and water source were
examined in the experiment. Three different spectrophotometers were used
in the analysis of absorbance readings.
•Figure 3 - The absorbance curves of the three concentrations of potassium
permanganate solutions using the school's deionized water all show significant
degradation over time. The fastest rate of degradation appear to occur in the
beginning hours.
•Table 1- In comparison, the average percent increase in transmittance for each
water source showed the solutions with ultrapure water experienced the smallest
change over time. Both, the current school DI water and the contaminated
environmental water solutions experienced the largest change.
We would like to thank Professor Terry Boan and Glen
Baghdasarian, PhD, for supporting and guiding us throughout our
research experience.
Also, thank you to the Director of the LACC STEM Pathways,
Jayesh Bhakta, Ph. D. for supporting and funding our science research.