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22 records · Page 2

Hydroxylpyromorphite, a mineral important to lead remediation: Modern description and characterization

Abstract Hydroxylpyromorphite, Pb5(PO4)3(OH), has been documented in the literature as a synthetic and naturally occurring phase for some time but has not previously been formally described as a mineral. It is fully described here for the first time using crystals collected underground in the Copps mine, Gogebic County, Michigan. Hydroxylpyromorphite occurs as aggregates of randomly oriented hexagonal prisms, primarily between about 20–35 μm in length and 6–10 μm in diameter. The mineral is colorless and translucent with vitreous luster and white streak. The Mohs hardness is ~3½–4; the tenacity is brittle, the fracture is irregular, and indistinct cleavage was observed on {001}. Electron microprobe analyses provided the empirical formula Pb4.97(PO4)3(OH0.69F0.33Cl0.06)Σ1.08. The calculated density using the measured composition is 7.32 g/cm3. Powder X-ray diffraction data for the type material is compared to data previously reported for hydroxylpyromorphite from the talc mine at Rabenwald, Austria, and from Whytes Cleuch, Wanlockhead, Scotland. Hydroxylpyromorphite is hexagonal, P63/m, at 100 K, a = 9.7872(14), c = 7.3070(10) Å, V = 606.16(19) Å3, and Z = 2. The structure [R1 = 0.0181 for 494 F>4σ(F) reflections] reveals that hydroxylpyromorphite adopts a column anion arrangement distinct from other members of the apatite supergroup due to the presence of fluorine and steric constraints imposed by stereoactive lone-pair electrons of Pb2+ cations. The F– anion sites are displaced slightly from hydroxyl oxygen anions, which allows for stronger hydrogen-bonding interactions that may in turn stabilize the observed column-anion arrangement and overall structure. Our modern characterization of hydroxylpyromorphite provides deeper understanding to a mineral useful for remediation of lead-contaminated water.

Geochemistry & Geophysics↗

Trebiskyite, the First Titanium-Decavanadate Mineral

Abstract Trebiskyite, Na3Mg2[TiV9O28]·22H2O, from the Pickett Corral mine, Bull Canyon, Montrose County, Colorado, USA, is the first mineral containing essential Ti as a component of a decavanadate polyanion. Crystals are thin prisms or needles up to ∼0.3 mm in length, occurring as individuals and in divergent sprays. Trebiskyite crystals are translucent yellow with vitreous luster and pale-yellow streak and are non-fluorescent under both longwave and shortwave ultraviolet illumination. The crystals exhibit elongation on [001] and are modified by several 0kl prism forms, possibly corresponding to {010}, {011}, and {012}. The Mohs hardness is ca. 2 based on scratch tests. Crystals have brittle tenacity with irregular fracture. No apparent cleavage, nor twinning, was evident, and the mineral is readily soluble in H2O. The density measured by flotation in methylene iodide-toluene mixture is 2.38(2) g/cm3. The calculated density is 2.352 g/cm3 for the empirical formula and 2.343 g/cm3 for the ideal formula. Electron microprobe analyses provided the empirical formula Na3.39Mg1.87V8.75Ti1.25O50H44.00, based on Ti + V = 10 apfu, O = 50 apfu, with the Na content having been determined from the refined crystal structure. Trebiskyite is monoclinic, space group P21/c, a = 9.478(4), b = 21.426(11), c = 11.267(5) Å, β = 114.572(7)°, V = 2080.8(13) Å3, Z = 2. The structure was refined from 6642 reflections to a final R1 = 0.0517 for reflections I > 2σ(I). The structural unit of trebiskyite, (TiV9O28)7−, is built from a Ti-substituted decavanadate polyanion, (V10O28)6−, found in other members of the pascoite family. Chemically, trebiskyite is closely related to lasalite, Na2Mg2[V10O28]·20H2O, and huemulite, Na4Mg[V10O28]·24H2O; however, trebiskyite contains a novel structural arrangement that is unique among the decavanadate minerals. The interstitial complex in trebiskyite has the ideal formula {[Na3Mg2(H2O)19](H2O)3} and consists of chains of distorted octahedrally coordinated Na+ and regular Mg[O(H2O)5] octahedra. The observed low incident bond valence to the V1 site (4.45 vu) and marked deviation in vanadyl and V–Oeq bond lengths indicate that this site is host to the essential Ti4+ identified during chemical analyses.

Mineralogy↗

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗

Microscopic and Macroscopic Characterization of Grain Boundary Energy and Strength in Silicon Carbide via Machine-Learning Techniques

Predicting the properties of grain boundaries poses a challenge because of the complex relationships between structural and chemical attributes both at the atomic and continuum scales. Grain boundary systems are typically characterized by parameters used to classify local atomic arrangements in order to extract features such as grain boundary energy or grain boundary strength. The present work utilizes a combination of high-throughput atomistic simulations, macroscopic and microscopic descriptors, and machine-learning techniques to characterize the energy and strength of silicon carbide grain boundaries. Additionally, a diverse data set of symmetric tilt and twist grain boundaries are described using macroscopic metrics such as misorientation, the alignment of critical low-index planes, and the Schmid factor, but also in terms of microscopic metrics, by quantifying the local atomic structure and chemistry at the interface. These descriptors are used to create random-forest regression models, allowing for their relative importance to the grain boundary energy and decohesion stress to be better understood. Results show that while the energetics of the grain boundary were best described using the microscopic descriptors, the ability of the macroscopic descriptors to reasonably predict grain boundaries with low energy suggests a link between the crystallographic orientation and the resultant atomic structure that forms at the grain boundary within this regime. For grain boundary strength, neither microscopic nor macroscopic descriptors were able to fully capture the response individually. However, when both descriptor sets were utilized, the decohesion stress of the grain boundary could be accurately predicted. These results highlight the importance of considering both macroscopic and microscopic factors when constructing constitutive models for grain boundary systems, which has significant implications for both understanding the fundamental mechanisms at work and the ability to bridge length scales.

36 MATERIALS SCIENCE↗