Kaolinite deposition from moving suspensions: The roles of flocculation,salinity, suspended sediment concentration and flow velocity/bed shear

Understanding how mud moves and deposits is essential for conceptualizing the dynamic nature of surface environments and their ancient counterparts. Experimental study has largely been pursued by civil engineers, using kaolinite as an active ingredient. Yet, applying their data to the physical comprehension of mudstone sedimentology is hampered by multiple flume configurations between labs, and data sets tailored to specific engineering needs. The need for a better grasp of underlying processes is acute, given recent flume studies that show that moving suspensions form large bedload floccules, migrating floccule ripples and bed accretion under currents capable of moving sand grains. To advance mudstone sedimentology, integrated study of suspended sediment concentration, salinity and bed shear stress on the deposition of floccules is crucial. Described here is a set of tightly controlled experiments that explored suspended sediment concentrations from 70 to 900 mg/l, freshwater, brackish and marine salinities, flow velocities in the 5 to 50 cm/s range (equivalent to 0.01 to 0.58 Pa bed shear), measured the size of in-flow and bedload floccules, and the critical velocity of sedimentation that marks the onset of sustained bedload accumulation. The critical velocity of sedimentation of kaolinite clays is in the 26 to 28 cm/s flow velocity range (0.22 to 0.25 Pa), appears insensitive to a wide range of suspended sediment concentrations and salinities, and coincides with the formation of sand-size bedload floccules. Further decrease of flow velocity/bed shear stress is accompanied by a steady increase in the size of bedload floccules. Large bedload floccules appear to form in the high-shear basal part of the flow, a phenomenon requiring further investigation. Better understanding of the mechanisms that facilitate mud deposition from moving suspensions is critical for more realistic assessments of the depositional conditions of mud and mudstones, as well as for refining predictive models for the flux of fine-grained sediments across the Earth's surface.     

Compositional and lithological diversity among brecciated lunar meteorites of intermediate iron concentration

Abstract— We present new compositional data for 30 lunar stones representing about 19 meteorites. Most have iron concentrations intermediate to those of the numerous feldspathic lunar meteorites (3–7% FeO) and the basaltic lunar meteorites (17–23% FeO). All but one are polymict breccias. Some, as implied by their intermediate composition, are mainly mixtures of brecciated anorthosite and mare basalt, with low concentrations of incompatible elements such as Sm (1–3 μg/g). These breccias likely originate from points on the Moon where mare basalt has mixed with material of the FHT (Feldspathic Highlands Terrane). Others, however, are not anorthosite‐basalt mixtures. Three (17–75 μ/g Sm) consist mainly of nonmare mafic material from the nearside PKT (Procellarum KREEP Terrane) and a few are ternary mixtures of material from the FHT, PKT, and maria. Some contain mafic, nonmare lithologies like anorthositic norites, norites, gabbronorites, and troctolite. These breccias are largely unlike breccias of the Apollo collection in that they are poor in Sm as well as highly feldspathic anorthosite such as that common at the Apollo 16 site. Several have high Th/Sm compared to Apollo breccias. Dhofar 961, which is olivine gabbronoritic and moderately rich in Sm, has lower Eu/Sm than Apollo samples of similar Sm concentration. This difference indicates that the carrier of rare earth elements is not KREEP, as known from the Apollo missions. On the basis of our present knowledge from remote sensing, among lunar meteorites Dhofar 961 is the one most likely to have originated from South Pole‐Aitken basin on the lunar far side.     

The influence of multivariate analysis methods and target grain size on the accuracy of remote quantitative chemical analysis of rocks using laser induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) was used to quantitatively analyze 195 rock slab samples with known bulk chemical compositions, 90 pressed-powder samples derived from a subset of those rocks, and 31 pressed-powder geostandards under conditions that simulate the ChemCam instrument on the Mars Science Laboratory Rover (MSL), Curiosity. The low-volatile (<2 wt.%) silicate samples (90 rock slabs, corresponding powders, and 22 geostandards) were split into training, validation, and test sets. The LIBS spectra and chemical compositions of the training set were used with three multivariate methods to predict the chemical compositions of the test set. The methods were partial least squares (PLS), multilayer perceptron artificial neural networks (MLP ANNs) and cascade correlation (CC) ANNs. Both the full LIBS spectrum and the intensity at five pre-selected spectral channels per major element (feature selection) were used as input data for the multivariate calculations. The training spectra were supplied to the algorithms without averaging (i.e. five spectra per target) and with averaging (i.e. all spectra from the same target averaged and treated as one spectrum). In most cases neural networks did not perform better than PLS for our samples. PLS2 without spectral averaging outperformed all other procedures on the basis of lowest quadrature root mean squared error (RMSE) for both the full test set and the igneous rocks test set. The RMSE for PLS2 using the igneous rock slab test set is: 3.07 wt.% SiO₂, 0.87 wt.% TiO₂, 2.36 wt.% Al₂O₃, 2.20 wt.% Fe₂O₃, 0.08 wt.% MnO, 1.74 wt.% MgO, 1.14 wt.% CaO, 0.85 wt.% Na₂O, 0.81 wt.% K₂O. PLS1 with feature selection and averaging had a higher quadrature RMSE than PLS2, but merits further investigation as a method of reducing data volume and computation time and potentially improving prediction accuracy, particularly for samples that differ significantly from the training set. Precision and accuracy were influenced by the ratio of laser beam diameter (∼490 μm) to grain size, with coarse-grained rocks often resulting in lower accuracy and precision than analyses of fine-grained rocks and powders. The number of analysis spots that were normally required to produce a chemical analysis within one standard deviation of the true bulk composition ranged from ∼10 for fine-grained rocks to >20 for some coarse-grained rocks.