Applications of Laser Ablation Inductively Coupled Plasma Mass Spectrometry to Problems in Mineral Resource Geology

Abstract

Mining has been a defining driver of human progress since the beginning of organized civilization. Minerals extracted from the Earth not only gave humans the means to create tools and weapons, but ornamental gemstones and metals add to the rich culture we share as a species. Today, the need and desire for mining precious resources has never been higher. This demand results in an undeniable need to focus time, energy, and resources in the exploration of new deposits, and to better understand those deposits we currently rely on. This is the aim of mineral resource geochemistry: to better understand where, why, and how economically important mineral deposits form. This can be done via the analysis of the chemistry found within individual minerals from these deposits. Understanding the trace elements and specific isotopes that comprises a mineral—like a unique fingerprint—allow us to gain tremendous insights and draw broad conclusions on resource formation from microscopic amounts of sample material. It can be argued that no instrument more profoundly transformed the field of geochemical research than the laser ablation inductively coupled plasma mass spectrometer (LA-ICP-MS). Its ease of use, moderate cost, relatively rapid data collection compared to other geochemical techniques, ability to maintain spatial context within samples, and minimal sample preparation needed makes the LA-ICP-MS one of the most powerful tools in the geochemist’s arsenal. This dissertation investigates distinct applications of LA-ICP-MS to mineral resource and gemological research, the results of which add to our understanding of geologic resource formation and mineral provenance determination. Chapter 2 highlights the power of LA- ICP-MS in situ U–Pb dating for elucidating the geochronology of the Candelaria iron oxide-copper- gold deposit in Northern Chile. This is coupled with other geochronological techniques for a comprehensive study of the temporal evolution of one of the most important copper mines in the world. Chapters 3 and 4 utilize a comprehensive suite of LA-ICP-MS collected trace element data and a random forest machine learning algorithm to effectively determine the provenance of different gemstone material to a hyper-specific degree: Colombian emeralds and euclase in chapter 2, and Montana, USA, sapphires in chapter 4. The results of this dissertation highlight the effectiveness, broad-reaching application, and versatility of LA-ICP-MS as a tool in mineral resource geology.