Inaug.-diss.--Leipzig. / Lebenslauf.

No description available.

Machine learning algorithms can be used to analyze large datasets and to identify relationships and patterns that otherwise might be missed by more traditional scientific and statistical approaches. The aim of this study is to evaluate the ability of machine learning algorithms to classify mineral systems and provide insights into the geological processes operating on Earth. This study examines the potential of machine learning algorithms as interpretive tools for the identification of geological processes and additional approaches are implemented to predict how geological processes may have evolved at tourmaline-bearing localities in the United States. Tourmaline mineral occurrence data for localities in the United States were retrieved from mineral databases and exploratory machine learning algorithms, such as market basket analysis and hierarchical clustering, were used to identify geological and geochemical processes. Common geological processes operating in sedimentary, igneous, metamorphic, and hydrothermal systems were all identified based on the presence of diagnostic mineral assemblages such as actinolite-wollastonite-dravite in metamorphic rocks or microcline-schorl-beryl in igneous deposits. Several different iterations of supervised machine learning algorithms were used with models incorporating different combinations of mineral occurrence data, environmental data, and geological process labels in order to learn how to predict the geologic evolution of tourmaline-bearing localities. A test dataset was generated by selecting different locations within the United States randomly and mineralogy was assigned to each site by using interpolation methods. Decision tree and random forest algorithms were both then used to classify the randomly generated test dataset. Cross-validation approaches show that the decision trees likely performed better when classifying the test dataset. The results discussed throughout this study highlight how machine learning algorithms can be very effective and accurate supplementary tools when characterizing tourmaline-bearing deposits. The models discussed in this paper were able to classify different geological processes with over ~90% accuracy and they were able to predict how geological processes evolved at different tourmaline-bearing localities with an estimated ~70% accuracy. The most accurate classification of tourmaline-bearing localities occurred when analyzing deposits that were subjected to higher temperatures and pressures which in turn generates more distinct mineralogies that allow machine learning algorithms to identify patterns with greater confidence. The analysis of tourmaline localities associated with low-temperature hydrothermal and sedimentary environments results in much more error-prone classifiers which can be attributed to a lack of tourmaline-bearing sedimentary deposits in mineral databases and because sedimentary deposits can have a record of processes from multiple geologic environments that may or may not be related. The strengths and limitations of the models trained are detailed throughout this paper.

No description available.

The O and H isotopic composition of minerals can provide valuable information on the source of the fluids and temperature of mineral precipitation. To obtain accurate isotopic measurements using SIMS, it is important to select chemically similar standards and samples to correct for both matrix effects and instrumental mass fractionation (IMF), collectively termed instrumental mass bias (IMB). For certain mineral groups (e.g. tourmalines), there are large variations in major element composition between species. This study uses three of these tourmaline species (schorl, dravite, and elbaite) to construct calibration curves to correct for IMB during SIMS analysis of O and H isotopes. I have applied my technique to analyses of tourmalines from the Wollaston Group, Athabasca region, Saskatchewan to test my method, and I have calculated the O and H isotopic composition of the fluids that formed these tourmalines. / October 2016

The Usakos pegmatite, Namibia, is a highly evolved, rare-element LCT-type pegmatite. The pegmatite is emplaced in metasedimentary rocks of the Kuiseb formation. Ca and Al enrichment at the contact, B mineralization in the country rock and Sr mineralization in the core of the pegmatite are all evidence of interaction of the pegmatite melt and hosting country rock. K/Rb ratios within mica and feldspar are very low indicating a highly evolved melt. Tourmaline has a fractionation trend from Fe-rich at contact and intermediate areas to Fe-depleted in core regions and pockets. Columbite tantalite group minerals show a similar trend in fractionation, with columbite-(Fe) found near the pegmatite country rock contact and tantalite-(Mn) found in the core region. Trace element geochemistry from samples of pegmatite-country rock contact is enriched in light rare earth elements. Whole rock geochemistry provides evidence of the geochemically evolved nature of the pegmatite forming melt.

Thesis (M.S.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on October 30, 2007) Includes bibliographical references.

Part I. The Boron Content of British Columbia Soils British Columbia soils were analyzed for total and available boron. Peace River soils showed significantly higher total contents than did soils from the rest of the province. Lower Fraser Valley soils were low in total boron. One hundred and twenty-four surface soils showed available boron contents ranging from 0.0 to 22.0 p.p.m. Lime additions seemed to lower the available boron content of certain Fraser Valley Soils. Part II. Investigations Concerning the Possibility of Using Tourmaline Rock as a Boron Fertilizer. A Tourmaline rock supplied by the Consolidated Mining and Smelting Company seemed to offer little value as a boron fertllizer. / Land and Food Systems, Faculty of / Graduate

Suites of gem-quality faceted tourmaline, slices and fragments from Nigeria Namibia, Mali, Tanzania, Congo and Mozambique were quantitatively analyzed to determine mineralogy and minor elementChemistry. The specimens range in color from colorless to pink, red, yellowish-brown, green, bluish-gray, blue, brown and black. The results show that these tourmalines are elbaite, liddicoatite, rossmanite and schorl. Fe, Mn and Ti are the principal chromophores of the studied tourmaline. Fe is the most dominant and causes green, blue, dark-brown and black colors. Mn imparts pink and red hues. Correlations between Mn content and pink color intensity were not found. The Mn2+¡êTi4+ charge transfer causes yellowish-brown colors. A positive correlation of Na+ with transition element content was found. Limited relationships betweenChemistry and locality were deciphered for Nigeria, Namibia and Tanzania on the basis of endmember content and Congo based on Mn, Mg and Ti content.

The P2 reverse fault in the metasedimentary basement rocks of the eastern Athabasca Basin is the main structural control of the world-class McArthur River uranium deposit. The earliest preserved assemblage along the fault is oxy-dravite, rutile, quartz, pyrite and graphite. This assemblage formed at temperatures of up to 890 °C, during regional metamorphism or a thermal event at ~1.75 Ga. The exhumation and surface exposure of the rocks was accompanied by paleo-weathering, and the deposition of the Athabasca sandstones. Diagenetic fluids of the sandstones altered the basement rocks to form Sr-Ca-SO42- rich aluminum phosphate sulfate (APS) minerals + hematite ± kaolin. The onset of hydrothermal activity along the basement and the P2 fault is recorded by local anatase at 1569 ± 31 Ma. Uraniferous fluid formed an assemblage of sudoite illite, magnesio-foitite and LREE+P rich APS minerals (rims earlier diagenetic-type APS minerals) along the entire P2 fault. Magnesio-foitite exhibits a high X-site vacancy (0.70 – 0.85 apfu) and contains high Al in its Y-site (0.70 – 1.12 apfu), suggesting that magnesio-foitite likely replaced kaolin. The REE pattern of magnesio-foitite is similar to that of uraninite (CeN<YN), likely due to their co-crystallization with LREE-rich APS minerals. APS minerals show variably high S/P ratios (0.05 - 0.21) in proximity to the deposit and low ratios (0.11 - 0.13) far from the deposit along the P2 fault, indicating reducing conditions in the ore zone. Low values of δD (-41 to -98 ‰) and high values of δ11B (+13.1 to +23.2 ‰) for magnesio-foitite suggest that groundwater interacted with carbonates or evaporites and was progressively enriched in 11B through interaction with illite and kaolin minerals. This work demonstrates that i) the P2 fault was a site of extensive fluid-rock interaction, ii) mineralizing fluids travelled along the entire P2 fault in the basement, iii) the deposition of the McArthur River deposit was controlled by the availability of a reducing fluid through the P2 fault, and iv) mineral chemistry (tourmaline and APS minerals) may help identify fertile faults in exploration for uranium deposits.