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.