7 resultados para Soil physical chemistry
em Université de Lausanne, Switzerland
Resumo:
Six gases (N((CH3)3), NH2OH, CF3COOH, HCl, NO2, O3) were selected to probe the surface of seven combustion aerosol (amorphous carbon, flame soot) and three types of TiO2 nanoparticles using heterogeneous, that is gas-surface reactions. The gas uptake to saturation of the probes was measured under molecular flow conditions in a Knudsen flow reactor and expressed as a density of surface functional groups on a particular aerosol, namely acidic (carboxylic) and basic (conjugated oxides such as pyrones, N-heterocycles) sites, carbonyl (R1-C(O)-R2) and oxidizable (olefinic, -OH) groups. The limit of detection was generally well below 1% of a formal monolayer of adsorbed probe gas. With few exceptions most investigated aerosol samples interacted with all probe gases which points to the coexistence of different functional groups on the same aerosol surface such as acidic and basic groups. Generally, the carbonaceous particles displayed significant differences in surface group density: Printex 60 amorphous carbon had the lowest density of surface functional groups throughout, whereas Diesel soot recovered from a Diesel particulate filter had the largest. The presence of basic oxides on carbonaceous aerosol particles was inferred from the ratio of uptakes of CF3COOH and HCl owing to the larger stability of the acetate compared to the chloride counterion in the resulting pyrylium salt. Both soots generated from a rich and a lean hexane diffusion flame had a large density of oxidizable groups similar to amorphous carbon FS 101. TiO2 15 had the lowest density of functional groups among the three studied TiO2 nanoparticles for all probe gases despite the smallest size of its primary particles. The used technique enabled the measurement of the uptake probability of the probe gases on the various supported aerosol samples. The initial uptake probability, g0, of the probe gas onto the supported nanoparticles differed significantly among the various investigated aerosol samples but was roughly correlated with the density of surface groups, as expected. [Authors]
Resumo:
A continuum of carbon, from atmospheric CO2 to secondary calcium carbonate, has been studied in a soil associ- ated with scree slope deposits in the Jura Mountains of Switzerland. This approach is based on former studies conducted in other environments. This C continuum includes atmospheric CO2, soil organic matter (SOM), soil CO2, dissolved inorganic carbon (DIC) in soil solutions, and secondary pedogenic carbonate. Soil parameters (pCO2, temperature, pH, Cmin and Corg contents), soil solution chemistry, and isotopic compositions of soil CO2, DIC, carbonate and soil organic matter (δ13CCO2, δ13CDIC, δ13Ccar and δ13CSOM values) have been monitored at different depths (from 20 to 140 cm) over one year. Results demonstrated that the carbon source in secondary carbonate (mainly needle fiber calcite) is related to the dissolved inorganic carbon, which is strongly dependent on soil respiration. The heterotrophic respiration, rather than the limestone parent material, seems to control the pedogenic carbon cycle. The correlation of δ13Corg values with Rock-Eval HI and OI indices demonstrates that, in a soil associated to scree slope deposits, the main process responsible for 13C-enrichment in SOM is related to bac- terial oxidative decarboxylation. Finally, precipitation of secondary calcium carbonate is enhanced by changes in soil pCO2 associated to the convective movement of air masses induced by temperature gradients (heat pump effect) in the highly porous scree slope deposits. The exportation of soil C-leachates from systems such as the one studied in this paper could partially explain the "gap in the European carbon budget" reported by recent studies.
Resumo:
The increase of total choline in tumors has become an important biomarker in cancer diagnosis. Choline and choline metabolites can be measured in vivo and in vitro using multinuclear MRS. Recent in vivo(13)C MRS studies using labeled substrates enhanced via dynamic nuclear polarization demonstrated the tremendous potential of hyperpolarization for real-time metabolic studies. The present study demonstrates the feasibility of detecting hyperpolarized (15)N labeled choline in vivo in a rat head at 9.4 T. We furthermore report the in vitro (172 +/- 16 s) and in vivo (126 +/- 15 s) longitudinal relaxation times. We conclude that with appropriate infusion protocols it is feasible to detect hyperpolarized (15)N labeled choline in live animals.
Resumo:
Explicitly correlated coupled-cluster calculations of intermolecular interaction energies for the S22 benchmark set of Jurecka, Sponer, Cerny, and Hobza (Chem. Phys. Phys. Chem. 2006, 8, 1985) are presented. Results obtained with the recently proposed CCSD(T)-F12a method and augmented double-zeta basis sets are found to be in very close agreement with basis set extrapolated conventional CCSD(T) results. Furthermore, we propose a dispersion-weighted MP2 (DW-MP2) approximation that combines the good accuracy of MP2 for complexes with predominately electrostatic bonding and SCS-MP2 for dispersion-dominated ones. The MP2-F12 and SCS-MP2-F12 correlation energies are weighted by a switching function that depends on the relative HF and correlation contributions to the interaction energy. For the S22 set, this yields a mean absolute deviation of 0.2 kcal/mol from the CCSD(T)-F12a results. The method, which allows obtaining accurate results at low cost, is also tested for a number of dimers that are not in the training set.
Resumo:
This paper reports molar heat capacities of Ru50SixGe(50-x) and Ru40SiyGe(60-y) ternary solid solutions determined by differential scanning calorimetry. A second order transition has been characterised for alloys ranging from Ru40Ge60 to Ru40Si10Ge50 at temperatures ranging from 850 to 1040 K, respectively. Tie lines have been established at 1000-900-800-700-600 degrees C by electron microprobe measurements on annealed alloys of the two phase domains: Ru50SixGe(50-x)-Ru40SiyGe(60-y) and Ru40SiyGe(60-y)-SizGe(100-z).
Resumo:
Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.
Resumo:
We investigate nuclear magnetic resonance (NMR) parameters of the rhodopsin chromophore in the dark state of the protein and in the early photointermediate bathorhodopsin via first-principles molecular dynamics simulations and NMR chemical shift calculations in a hybrid quantum/classical (QM/MM) framework. NMR parameters are particularly sensitive to structural properties and to the chemical environment, which allows us to address different questions about the retinal chromophore in situ. Our calculations show that both the 13C and the 1H NMR chemical shifts are rather insensitive to the protonation state of Glu181, an ionizable amino acid side chain located in the vicinity of the isomerizing 11-cis bond. Thus, other techniques should be better suited to establish its protonation state. The calculated chemical shifts for bathorhodopsin further support our previously published theoretical structure, which is in very good agreement with more recent X-ray data.