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MINERAL ECOLOGY AND NETWORK ANALYSIS OF CHROMIUM, PLATINUM, GOLD AND PALLADIUM A THESIS IN ENVIRONMENTAL AND URBAN GEOSCIENCES Presented to the Faculty of the University Of Missouri-Kansas City in partial fulfillment of The requirements for the degree MASTER OF SCIENCE By CHARLES ANDENGENIE MWAIPOPO B.S., University of Missouri-Kansas City, 2018 Kansas City, Missouri 2020 MINERAL ECOLOGY AND NETWORK ANALYSIS OF CHROMIUM, PLATINUM, GOLD AND PALLADIUM Charles Andengenie Mwaipopo, Candidate for the Master of Science Degree University of Missouri-Kansas City, 2020 ABSTRACT Data collected on the location of mineral species and related minerals from the field have many great uses from mineral exploration to mineral analysis. Such data is useful for further exploration and discovery of other minerals as well as exploring relationships that were not as obvious even to a trained mineralogist. Two fields of mineral analysis are examined in the paper, namely mineral ecology and mineral network analysis through mineral co-existence. Mineral ecology explores spatial distribution and diversity of the earth’s minerals. Mineral network analysis uses mathematical functions to visualize and graph mineral relationships. Several functions such as the finite Zipf-Mandelbrot (fZM), chord diagrams and mineral network diagrams, processed data and provided information on the estimation of minerals at different localities and interrelationships between chromium, platinum, gold and palladium-bearing minerals. The results obtained are important in highlighting several connections that could prove useful in mineral exploration. The main objective of the study is to provide any insight into the relationship among chromium, platinum, palladium and gold that could prove useful in mapping out potential locations of either mineral in the future. With more open data repositories available, more research could be done to further highlight the importance of mineral ecology and network iii analysis in mineral exploration. Such a research is important in paving the way for data driven discovery on the field of geology by making use of the vast amount of data currently available. Mineral ecology and network analysis currently face a hindrance, because of more crucial data being held for proprietary reasons that tend to profit from its exclusivity. iv APPROVAL PAGE The faculty listed below, appointed by the Dean of the College of Arts and Sciences, have examined a thesis titled “Mineral Ecology and Network Analysis of Chromium, Platinum, Gold and Palladium” , presented by Charles Andengenie Mwaipopo, candidate for the Master of Science degree, and certify that in their opinion it is worthy of acceptance. Supervisory Committee Alison Graettinger, Ph.D., Committee Chair Department of Geosciences James Murowchick, Ph.D. Department of Geosciences Fengpeng Sun, Ph.D. Department of Geosciences v CONTENTS ABSTRACT ..................................................................................................................... iii LIST OF TABLES .......................................................................................................... vii LIST OF ILLUSTRATIONS ......................................................................................... viii ACKNOWLEDGEMENTS ............................................................................................. ix Chapter 1. INTRODUCTION ................................................................................................ 1 2. PREVIOUS WORKS............................................................................................ 5 3. DATA COLLECTION AND METHODOLOGY ................................................ 8 4. MINERAL ECOLOGY ANALYSIS OF SELECTED MINERALS ................. 12 5. MINERAL NETWORK ANALYSIS OF SELECTED MINERALS ................ 37 6. DISCUSSION ..................................................................................................... 51 7. CONCLUSION ................................................................................................... 57 REFERENCE LIST ........................................................................................................ 59 VITA ............................................................................................................................... 64 vi TABLES Table Page 4.1 Chromium minerals and locality counts ............................................................ 14 4.2 Chromium fZM model parameters .................................................................... 19 4.3 Platinum minerals and locality counts ............................................................... 22 4.4 Platinum fZM model parameters ....................................................................... 24 4.5 Palladium minerals and locality counts ............................................................. 27 4.6 Gold minerals and locality counts...................................................................... 32 4.7 Gold fZM model parameters .............................................................................. 34 5.1 Probabilities of mineral cooccurrence ............................................................... 38 5.2 Mineral occurrences locality values ................................................................... 38 5.3 Mineral node attributes ...................................................................................... 43 5.4 Mineral edge attributes ...................................................................................... 44 5.5 Total mineral locality and association count ..................................................... 48 5.6 Example pathfinder elements used in mineral exploration ................................ 54 vii ILLUSTRATIONS Figure Page 4.1 Example of a network model ............................................................................. 13 4.2 Chromium frequency spectrum .......................................................................... 20 4.3 Platinum frequency spectrum ............................................................................ 25 4.4 Gold frequency spectrum ................................................................................... 35 5.1 Chord diagram of selected minerals in terms of percentages ............................ 40 5.2 Chord diagram of selected minerals in terms of locality count ......................... 41 5.3 Network diagram displaying weight of relationships ........................................ 45 5.4 Network diagram displaying weight and association count .............................. 46 5.5 Difference in node sizes between minerals ........................................................ 49 viii ACKNOWLEDGEMENTS I would like to thank Dr Alison Graettinger for having the patience to work with me during the period of my master’s program. This project has been a challenge for all of us including the other members of my approval committee, namely, Dr James Murowchick and Fengpeng Sun. Dr James Murowchick has been an incredible promoter and supporter of my research by being informative, supportive, and very instrumental in helping me succeed. Without the guidance of Drs. Graettinger, Murowchick and Sun, I feel I might not have made it. People behind the scenes are usually forgotten when it comes to providing the necessary acknowledgement. Much of what the geosciences department accomplishes is due to Megan Medley always working at peak efficiency. Joseph Nolan, a colleague of mine was also very supportive during my research, who often times took time off of his schedule to review my work. To both Megan and Joseph, I thank you very much for all your help. Last but not the least, my wife deserves the credit for this degree as much, if not more than I do. She has been very supportive and understanding during this chaotic time period and I would not have been able to do it without her. ix CHAPTER 1 INTRODUCTION Data collection is a practice quite widespread in science and other art forms of study that serve the purpose of advancing the knowledge of the subject in question. The advancement usually comes in the form of observing the data collected over time and noticing patterns that do not happen by accident but are rather a result of a certain factor or factors. The subject in question is the geology of certain minerals. Analysis of minerals and mineralogical systems data could lead to more discoveries in their respective fields. Prior knowledge in mineralogy is essential for even more groundbreaking discoveries in the field. In this case, physical and chemical principles of minerals as well as their locality information all play a significant role in a better understanding of network like relationships among minerals. This paper will explore relationships between chromium and the selected precious minerals and by observing the data attempt to see if chromium can be a key identifier of precious metals close by. If successful it will support arguments of more resources being diverted into analyzing big bulks of data to aid in the exploration of precious metals thereby saving costs. Network analysis compiles a powerful collection of mathematical and graphical methods that have proved quite useful in the presentation and clarification of data collected over the years (Morrison et al., 2017). Such methods have been employed in various fields such as in technological networks that comprise of physical infrastructures of power grids, roads and water supply systems (Morrison et al., 2017).
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