Surface complexation at mineral interfaces: Multisite and Charge Distribution approach

cum laude graduation (with distinction

Inner-sphere complexation of cations at the rutile-water interface: A concise surface structural interpretation with the CD and MUSIC model

Acid–base reactivity and ion-interaction between mineral surfaces and aqueous solutions is most frequently investigated at the macroscopic scale as a function of pH. Experimental data are then rationalized by a variety of surface complexation models. These models are thermodynamically based which in principle does not require a molecular picture. The models are typically calibrated to relatively simple solid-electrolyte solution pairs and may provide poor descriptions of complex multi-component mineral–aqueous solutions, including those found in natural environments. Surface complexation models may be improved by incorporating molecular-scale surface structural information to constrain the modeling efforts. Here, we apply a concise, molecularly-constrained surface complexation model to a diverse suite of surface titration data for rutile and thereby begin to address the complexity of multi-component systems. Primary surface charging curves in NaCl, KCl, and RbCl electrolyte media were fit simultaneously using a charge distribution (CD) and multisite complexation (MUSIC) model [Hiemstra T. and Van Riemsdijk W. H. (1996) A surface structural approach to ion adsorption: the charge distribution (CD) model. J. Colloid Interf. Sci. 179, 488–508], coupled with a Basic Stern layer description of the electric double layer. In addition, data for the specific interaction of Ca2+ and Sr2+ with rutile, in NaCl and RbCl media, were modeled. In recent developments, spectroscopy, quantum calculations, and molecular simulations have shown that electrolyte and divalent cations are principally adsorbed in various inner-sphere configurations on the rutile 1 1 0 surface [Zhang Z., Fenter P., Cheng L., Sturchio N. C., Bedzyk M. J., Predota M., Bandura A., Kubicki J., Lvov S. N., Cummings P. T., Chialvo A. A., Ridley M. K., Bénézeth P., Anovitz L., Palmer D. A., Machesky M. L. and Wesolowski D. J. (2004) Ion adsorption at the rutile–water interface: linking molecular and macroscopic properties. Langmuir 20, 4954–4969]. Our CD modeling results are consistent with these adsorbed configurations provided adsorbed cation charge is allowed to be distributed between the surface (0-plane) and Stern plane (1-plane). Additionally, a complete description of our titration data required inclusion of outer-sphere binding, principally for Cl- which was common to all solutions, but also for Rb+ and K+. These outer-sphere species were treated as point charges positioned at the Stern layer, and hence determined the Stern layer capacitance value. The modeling results demonstrate that a multi-component suite of experimental data can be successfully rationalized within a CD and MUSIC model using a Stern-based description of the EDL. Furthermore, the fitted CD values of the various inner-sphere complexes of the mono- and divalent ions can be linked to the microscopic structure of the surface complexes and other data found by spectroscopy as well as molecular dynamics (MD). For the Na+ ion, the fitted CD value points to the presence of bidenate inner-sphere complexation as suggested by a recent MD study. Moreover, its MD dominance quantitatively agrees with the CD model prediction. For Rb+, the presence of a tetradentate complex, as found by spectroscopy, agreed well with the fitted CD and its predicted presence was quantitatively in very good agreement with the amount found by spectroscopy

Recognition of micro-scale deformation structures in glacial sediments - pattern perception, observer bias and the influence of experience

It is a scientist's mission to try to remain unbiased. However, certain factors play a role in scientific analyses that are not controlled by conscious thought. These factors are potentially very important in areas of science where interpretations are based on a scientist's ability to identify patterns or structures. One such area is the micromorphology of glacial sediments. In this paper we investigate the role of an analyst's experience in relation to pattern perception with specific reference to turbate microstructures in glacial diamictons. An experiment was conducted on 52 participants, which demonstrated that, as may be expected, more experienced (glacial) micromorphologists tend to exhibit a higher sensitivity-to-signal, but that complete novices, if given clear instructions, can reach levels of sensitivity similar to those of experts. It also showed, perhaps more surprisingly, that response bias does not decrease with experience. We discuss psychological factors, such as the drive for success and consistency, that may have contributed to these results and investigate their possible implications in the micromorphological analysis and interpretation of glacial sediments

The integrated stress response in lung disease.

Lungs are repeatedly exposed to inhaled toxic insults, such as smoke, diesel exhaust, and microbes, which elicit cellular stress responses. The phosphorylation of eukaryotic translation initiation factor 2α by one of four stress-sensing kinases triggers a pathway called the integrated stress response that helps protect cellular reserves of nutrients and prevents the accumulation of toxic proteins. In this review, we discuss how activation of the integrated stress response has been shown to play an important role in pulmonary pathology, and how its study may help in the development of novel therapies for diverse conditions, from hypoxia to cancer

Broad iron line in the fast spinning neutron-star system 4U 1636-53

We analysed the X-ray spectra of six observations, simultaneously taken with XMM-Newton and Rossi X-ray Timing Explorer (RXTE), of the neutron-star low-mass X-ray binary 4U 1636-53. The observations cover several states of the source, and therefore a large range of inferred mass accretion rate. These six observations show a broad emission line in the spectrum at around 6.5 keV, likely due to iron. We fitted this line with a set of phenomenological models of a relativistically broadened line, plus a model that accounts for relativistically smeared and ionized reflection from the accretion disc. The latter model includes the incident emission from both the neutron-star surface or boundary layer and the corona that is responsible for the high-energy emission in these systems. From the fits with the reflection model we found that in four out of the six observations the main contribution to the reflected spectrum comes from the neutron-star surface or boundary layer, whereas in the other two observations the main contribution to the reflected spectrum comes from the corona. We found that the relative contribution of these two components is not correlated to the state of the source. From the phenomenological models, we found that the iron line profile is better described by a symmetric, albeit broad, profile. The width of the line cannot be explained only by Compton broadening, and we therefore explored the case of relativistic broadening. We further found that the direct emission from the disc, boundary layer and corona generally evolved in a manner consistent with the standard accretion disc model, with the disc and boundary layer becoming hotter and the disc moving inwards as the source changed from the hard to the soft state. The iron line, however, did not appear to follow the same trend

Lidar and Deep Learning Reveal Forest Structural Controls on Snowpack

Forest structure has a strong relationship with abiotic components of the environment. For example, canopy morphology controls snow depth through interception and modifies incoming thermal radiation. In turn, snow water availability affects forest growth, carbon sequestration, and nutrient cycling. We investigated how structural diversity and topography affect snow depth patterns across scales. The study site, Grand Mesa, Colorado, is representative of many areas worldwide where declining snowpack and its consequences for forest ecosystems are increasingly an environmental concern. On the basis of a convolution neural network model (R2 of 0.64; root mean squared error of 0.13 m), we found that forest structural and topographic metrics from airborne light detection and ranging (lidar) at fine scales significantly influence snow depth during the accumulation season. Moreover, complex vertically arranged foliage intercepts more snow and results in shallower snow depths below the canopy. Assessing forest structural controls on snow distribution and depth will aid efforts to improve understanding of the ecological and hydrological impacts of changing snow patterns