The redox state of Earth's convecting mantle, masked by the lithospheric plates and basaltic magmatism of plate tectonics, is a key unknown in the evolutionary history of our planet. Here we report that large, exceptional gem diamonds like the Cullinan, Constellation, and Koh-i-Noor carry direct evidence of crystallization from a redox-sensitive metallic liquid phase in the deep mantle. These sublithospheric diamonds contain inclusions of solidified iron-nickel-carbon-sulfur melt, accompanied by a thin fluid layer of methane +/- hydrogen, and sometimes majoritic garnet or former calcium silicate perovskite. The metal-dominated mineral assemblages and reduced volatiles in large gem diamonds indicate formation under metal-saturated conditions. We verify previous predictions that Earth has highly reducing deep mantle regions capable of precipitating a metallic iron phase that contains dissolved carbon and hydrogen.

Recently, statistical distributions have been explored to provide estimates of the mineralogical diversity of Earth, and Earth-like planets. In this paper, a Bayesian approach is introduced to estimate Earth's undiscovered mineralogical diversity. Samples are generated from a posterior distribution of the model parameters using Markov chain Monte Carlo simulations such that estimates and inference are directly obtained. It was previously shown that the mineral species frequency distribution conforms to a generalized inverse Gauss-Poisson (GIGP) large number of rare events model. Even though the model fit was good, the population size estimate obtained by using this model was found to be unreasonably low by mineralogists. In this paper, several zero-truncated, mixed Poisson distributions are fitted and compared, where the Poisson-lognormal distribution is found to provide the best fit. Subsequently, the population size estimates obtained by Bayesian methods are compared to the empirical Bayes estimates. Species accumulation curves are constructed and employed to estimate the population size as a function of sampling size. Finally, the relative abundances, and hence the occurrence probabilities of species in a random sample, are calculated numerically for all mineral species in Earth's crust using the Poisson-lognormal distribution. These calculations are connected and compared to the calculations obtained in a previous paper using the GIGP model for which mineralogical criteria of an Earth-like planet were given.

Curiosity investigated active eolian sands near linear dunes during Phase 2 of the Bagnold Dunes campaign in Gale crater, Mars. Ogunquit Beach, a sample scooped from a large-ripple trough within the Mount Desert Island ripple field and delivered to the Chemistry and Mineralogy (CheMin) X-ray diffraction instrument, is dominated by basaltic igneous minerals and X-ray amorphous materials. CheMin mineralogy of the Gobabeb sample acquired at a large-ripple crest on the Namib barchan dune during Phase 1 is similar to Ogunquit Beach. Ogunquit Beach, however, contains more plagioclase and Gobabeb contains more olivine. Compact Reconnaissance Imaging Spectrometer for Mars (CRISM)-based estimates of mineralogy at the optical surface of Namib Dune and Mount Desert Island demonstrate that surface sands are enriched in olivine and depleted in plagioclase over Mount Desert Island relative to Namib Dune. Differences between CheMin-derived and CRISM-derived mineralogies suggest sorting by grain size on bedform to dune field scales. Crystal chemistry from CheMin suggests contributions from multiple igneous sources and the local bedrock.

Ten sulphide inclusions in three diamonds from the Zimmi (West Africa) alluvial diamond locality were analysed for their bulk Fe-Cu-Ni-Co contents and Re-Os isotopic compositions. The host diamonds are exceptionally rare, lb types that still preserve isolated nitrogen (C centres), rather than more common nitrogen pairs (A centres) and nitrogen aggregates (B centres). C centres in Zimmi diamonds require that they did not experience temperatures above 850 degrees C for any extended period. Such diamonds make up less than 0.1% of natural gem diamonds and have never before been dated. The sulphides are pyrrhotite-rich, have low Ni and Os contents, and radiogenic Os-187/Os-188, all features characteristic of eclogitic sulphides. Each diamond has 3-4 individual inclusions. Re-187/Os-188 and Os-187/Os-188 data fall along three individual similar to 650 Ma age arrays that represent essentially 3-point or 4-point mineral isochrons for each diamond unambiguously dating the time of diamond formation. The similar to 650 Ma age correlates with the timing of Neoproterozoic assembly of Gondwana, recorded in the Rokelide orogen along the SW margin of the West African craton. The initial Os-187/Os-188 of the three age arrays fall between 1.6 and 2.2 and are highly radiogenic compared to chondritic mantle at 650 Ma. Along with low Re/Os ratios, this data suggests that sulphides were not derived from Neoproterozoic subducting slabs, but rather from older eclogitic material already present in the West African lithospheric mantle. The age of the diamonds and their nitrogen substitutional characteristics, along with their residence in a lithospheric mantle with a normal cratonic geotherm (determined here from Koidu clinopyroxene xenocrysts) suggests that after diamond formation they were rapidly exhumed to shallower depths in the lithosphere. This likely occurred through tectonic uplift following Neoproterozoic continental collision. (C) 2016 Elsevier B.V. All rights reserved.

A preliminary list of plausible near-surface minerals present during Earth's Hadean Eon (>4.0 Ga) should be expanded to include: (1) phases that might have formed by precipitation of organic crystals prior to the rise of predation by cellular life; (2) minerals associated with large bolide impacts, especially through the generation of hydrothermal systems in circumferential fracture zones; and (3) local formation of minerals with relatively oxidized transition metals through abiological redox processes, such as photo-oxidation. Additional mineral diversity arises from the occurrence of some mineral species that form more than one 'natural kind', each with distinct chemical and morphological characteristics that arise by different paragenetic processes. Rare minerals, for example those containing essential B, Mo, or P, are not necessary for the origins of life. Rather, many common minerals incorporate those and other elements as trace and minor constituents. A rich variety of chemically reactive sites were thus available at the exposed surfaces of common Hadean rock-forming minerals.

Large and growing data resources on the diversity, distribution, and properties of minerals are ushering in a new era of data-driven discovery in mineralogy. The most comprehensive international mineral database is the IMA database, which includes information on more than 5400 approved mineral species and their properties, and the mindat.org data source, which contains more than 1 million species/locality data on minerals found at more than 300 000 localities. Analysis and visualization of these data with diverse techniques-including chord diagrams, cluster diagrams, Klee diagrams, skyline diagrams, and varied methods of network analysis-are leading to a greater understanding of the co-evolving geosphere and biosphere. New data-driven approaches include mineral evolution, mineral ecology, and mineral network analysis-methods that collectively consider the distribution and diversity of minerals through space and time. These strategies are fostering a deeper understanding of mineral co-occurrences and, for the first time, facilitating predictions of mineral species that occur on Earth but have yet to be discovered and described. (C) 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Exogenic contamination is of primary concern for geochemical and biological clean laboratories working with sample sizes at the nanogram or even subpicogram level. Here, we determined sixty trace elements in fifteen different types of gloves from major suppliers world-wide to evaluate whether gloves could be potential sources of contamination for routine trace element and isotope measurements. We found that all gloves contain some trace elements that can be easily mobilised in significant amounts. In weak acid at room temperature, the tested gloves released up to 17 mg of Zn, more than 1 mu g of Mg, Ti, Mn, Fe, Rb, Sr, Zr, Sn, Hf and Pb and between 100 and 1000 ng of Li, Sc, V, Cr, Ni, Cu, Ga, As, Se, Y, Ag, Ba, La, Ce, Nd, Tl and Th. Vinyl gloves released lower quantities of biologically and geologically important elements, with the exception of In and Sn. Isotopic analyses indicate that all gloves share roughly the same Zn isotopic composition (average delta Zn-66= +0.10 +/- 0.32 parts per thousand (2s)). A single contact between glove and labware releases an average of similar to 6 ng of Zn and hence can significantly shift delta Zn-66 above the precision level when the amount of Zn determined is below 500 ng.

As exploration for new resources increasingly relies upon deeper and deeper drilling to investigate through overburden, exploration projects will encounter significantly higher drilling costs to sample target areas and to open new areas to exploration. Therefore, as much information as possible must be extracted from every drill hole. One tool that can be used is the in situ trace element analysis of individual mineral phases using LA-ICPMS. In this study, we investigate the use of pyrite trace element chemistry to fingerprint different ore deposit types so that appropriate geologic models can be employed at an early stage of exploration in new greenfields areas. While this data is effective at identifying ore deposit type, variability within the raw data leads to inherent complications for manual analysis. One way to deconvolute this data is to employ machine learning algorithms to aid in the classification. Here we develop a classifier using supervised classification (Random Forests) and further test non-supervised classification (cluster analysis) algorithms. The results of using Random Forests and cluster analysis to identify ore deposit type are then compared.

Eighteen diamond samples from the A154 South kimberlite pipe (Diavik Mine), Slave Craton, Northwest Territories (Canada); sixteen diamond samples from the Lynx kimberlite dyke, Superior Craton, Quebec (Canada) and twelve diamond samples from the Kelsey Lake kimberlite pipe, Wyoming Craton, Colorado (USA), were cut through the core-zones, polished, imaged by cathodoluminescence (CL), and analyzed by secondary ion mass spectrometry (SIMS) for carbon isotope composition and nitrogen abundance. Twenty Kelsey Lake diamond plates, including the twelve crystals analyzed by SIMS, were analyzed by Fourier transform infrared spectrometry (FTIR) for nitrogen concentration and aggregation state.