Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

Distribution of major, minor, and trace metals in lake environments of Antarctica

The concentrations of major, minor and trace metals were measured in water samples collected from five shallow Antarctic lakes (Carezza, Edmonson Point (No 14 and 15a), Inexpressible Island and Tarn Flat) found in Terra Nova Bay (northern Victoria Land, Antarctica) during the Italian Expeditions of 1993-2001. The total concentrations of a large suite of elements (Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Gd, K, La, Li, Mg, Mn, Mo, Na, Nd, Ni, Pb, Pr, Rb, Sc, Si, Sr, Ta, Ti, U, V, Y, W, Zn and Zr) were determined using spectroscopic techniques (ICP-AES, GF-AAS and ICP-MS). The results are similar to those obtained for the freshwater lakes of the Larsemann Hills, East Antarctica, and for the McMurdo Dry Valleys. Principal Component Analysis (PCA) and Cluster Analysis (CA) were performed to identify groups of samples with similar characteristics and to find correlations between the variables. The variability observed within the water samples is closely connected to the sea spray input; hence, it is primarily a consequence of geographical and meteorological factors, such as distance from the ocean and time of year. The trace element levels, in particular those of heavy metals, are very low, suggesting an origin from natural sources rather than from anthropogenic contamination.

Evaluation of extractants for estimation of the phytoavailable trace metals in soils

Despite its environmental (and financial) importance, there is no agreement in the literature as to which extractant most accurately estimates the phytoavailability of trace metals in soils. A large dataset was taken from the literature, and the effectiveness of various extractants to predict the phytoavailability of Cd, Zn, Ni, Cu, and Pb examined across a range of soil types and contamination levels. The data suggest that generally, the total soil trace metal content, and trace metal concentrations determined by complexing agents (such as the widely used DTPA and EDTA extractants) or acid extractants (such as 0.1 M HCl and the Mehlich 1 extractant) are only poorly correlated to plant phytoavailability. Whilst there is no consensus, it would appear that neutral salt extractants (such as 0.01 M CaCl2 and 0.1 M NaNO3) provide the most useful indication of metal phytoavailability across a range of metals of interest, although further research is required.

Sedimentologic, petrographic, and sulfur isotope constraints on fine-grained pyrite formation at Mount Isa Mine and environs, Northwest Queensland, Australia

Fine-grained pyrite is the earliest generation of pyrite and the most abundant sulfide within the Urquhart Shale at Mount Isa, northwest Queensland. The pyrite is intimately interbanded with ore-grade Pb-Zn miner alization at the Mount Isa mine but is also abundant north and south of the mine at several stratigraphic horizons within the Urquhart Shale. Detailed sedimentologic, petrographic, and sulfur isotope studies of the Urquhart Shale, mostly north of the mine, reveal that the fine-grained pyrite (delta(34)S = -3.3 to +26.3 parts per thousand) formed by thermochemical sulfate reduction during diagenesis. The sulfate source was local sulfate evaporites, pseudo morphs of which are present throughout the Urquhart Shale (i.e., gypsum, anhydrite, and barite). Deep-burial diagenetic replacement of these evaporites resulted in sulfate-bearing ground waters which migrated parallel to bedding. Fine-grained pyrite formed where these fluids infiltrated and then interacted with carbon-rich laminated siltstones. Comparison of the sulfur isotope systematics of fine-grained pyrite and spatially associated base metal sulfides from the Mount Isa Pb-Zn and Cu orebodies indicates a common sulfur source of ultimately marine origin for all sulfide types. Different sulfur isotope ratio distributions for the various sulfides are the result of contrasting formation mechanisms and/or depositional conditions rather than differing sulfur sources. The sulfur isotope systematics of the base metal and associated iron sulfide generations are consistent with mineralization by reduced hydrothermal fluids, perhaps generated by bulk reduction of evaporite-sourced sulfate-bearing waters generated deeper in the Mount Isa Group, the sedimentary sequence which contains the Urquhart Shale. The available sulfur isotope data from the Mount Isa orebodies are consistent with either a chemically and thermally zoned, evolving Cu-Pb-Zn system, or discrete Cu and Pb-Zn mineralizing events linked by a common sulfur source.

Complexes of 1-thia-4,7,10-triazacyclododecane ([12]aneN(3)S) - Synthesis, structure and stability constants

The 12-membered macrocyclic ligand 1-thia-4,7, 10-triazacyclododecane ([12]aneN(3)S) has been synthesised, although upon crystallization from acetonitrile a product in which carbon dioxide had added to one secondary amine in the macrocyclic ring (H[12]aneN(3)SCO(2). H2O) was isolated and subsequently characterised by X-ray crystallography. The protonation constants for [12]aneN(3)S and stability constants with Zn(II), Pb(II), Cd(II) and Cu(II) have been determined either potentiometrically or spectrophotometrically in aqueous solution, and compared with those measured or reported for the ligands 1-oxa-4,7,10-triazacyclododecane ([12]aneN(3)O) and 1,4,7,10-tetraazacyclododecane ([12]aneN(4)). The magnitudes of the stability constants are consistent with trends observed previously for macrocyclic ligands as secondary amine donors are replaced with oxygen and thioether donors although the stability constant for the [Hg([12]aneN(4))](2+) complex has been estimated from an NMR experiment to be at least three orders of magnitude larger than reported previously. Zinc(II), mercury(II), lead(II), copper(II) and nickel(II) complexes of [12]aneN(3)S have been isolated and characterised by X-ray crystallography. In the case of copper(II), two complexes [Cu([12]aneN(3)S)(H2O)](ClO4)(2) and [Cu-2([12]aneN(3)S)(2)(OH)(2)](ClO4)(2) were isolated, depending on the conditions employed. Molecular mechanics calculations have been employed to investigate the relative metal ion size preferences of the [3333], asym-[2424] and sym-[2424] conformation isomers. The calculations predict that the asym-[2424] conformer is most stable for M-N bond lengths in the range 2.00-2.25 Angstrom whilst for the larger metal ions the [3333] conformer is dominant. The disorder seen in the structure of the [Zn([12]aneN(3)S)(NO3)](+) complex is also explained by the calculations. (C) 1999 Elsevier Science Ltd. All rights reserved.

Ni-II and Zn-II complexes of the hexadentate macrocyclic ligand cis-6,13-dimethyl-1,4,8,11-tetraazacyclotetra- decane-6,13-diamine

The title pendent-arm macrocyclic hexaamine ligand binds stereospecifically in a hexadentate manner, and we report here its isomorphous Ni-II and Zn-II complexes (both as perchlorate salts), namely (cis-6,13-dimethyl-1,4,8,11-tetraazacyclotetradecane-6,13-diamine-kappa(6)N)nickel(II) diperchlorate, [Ni(C12H30N6)](ClO4)(2), and (cis-6,13-dimethyl-1,4,8,11-tetraazacyclotetradecane-6,13-diamine-kappa(6)N)zinc(II) diperchlorate, [Zn(C-12 H30N6)](ClO4)(2). Distortion of the N-M-N valence angles from their ideal octahedral values becomes more pronounced with increasing metal-ion size and the present results are compared with other structures of this ligand.

Experimental study of phase equilibria in the systems Fe-Zn-O and Fe-Zn-Si-O at metallic iron saturation

The reported experimental work on the systems Fe-Zn-O and Fe-Zn-Si-O in equilibrium with metallic iron is part of a wider research program that combines experimental and thermodynamic computer modeling techniques to characterize zinc/lead industrial slags and sinters in the system PbO-ZnO-SiO2-CaO-FeO-Fe2O3. Extensive experimental,investigations using high-temperature equilibration and quenching techniques followed by electron probe X-ray microanalysis (EPMA) were carried out. Special experimental; procedures were developed to enable accurate measurements in these ZnO-containing systems to be performed in equilibrium with metallic iron; The systems Fe-Zn-O and FeZn-Si-O were experimentally investigated in equilibrium with metallic iron in the temperature ranges 900 degreesC to 1200 degreesC (1173 to 1473 K) and from 1000 degreesC to 1350 degreesC (1273 to 1623 K), respectively. The liquidus surface in the system Fe-Zn-Si-O in equilibrium with metallic iron was characterized in the composition ranges 0 to 33 wt pet ZnO and 0 to 40 wt pet SiO2. The wustite (Fe,Zn)O, zincite (Zn,Fe)O, willemite (Zn,Fe)(2)SiO4, arid fayalite: (Fe,Zn)(2)SiO4 solid solutions in equilibrium with metallic iron were measured.