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71.
Christian Ruby Mustapha Abdelmoula Aurélien Renard Georges Ona-Nguema Jean-Marie R. Génin 《Geochimica et cosmochimica acta》2010,74(3):953-966
FeII-III hydroxycarbonate green rust GR(CO32−), FeII4 FeIII2 (OH)12 CO3·3H2O, is oxidized in aqueous solutions with varying reaction kinetics. Rapid oxidation with either H2O2 or dissolved oxygen under neutral and alkaline conditions leads to the formation of ferric oxyhydroxycarbonate GR(CO32−)∗, FeIII6 O12 H8 CO3·3H2O, via a solid-state reaction. By decreasing the flow of oxygen bubbled in the solution, goethite α-FeOOH forms by dissolution-precipitation mechanism whereas a mixture of non-stoichiometric magnetite Fe(3−x)O4 and goethite is observed for lower oxidation rates. The intermediate FeII-III oxyhydroxycarbonate of formula FeII6(1−x) FeIII6x O12 H2(7−3x) CO3·3H2O, i.e. GR(x)∗ for which x ? [1/3, 1], is the synthetic compound that is homologous to the fougerite mineral present in hydromorphic gleysol; in situ oxidation accounts for the variation of ferric molar fraction x = [FeIII]/{[FeII]+[FeIII]} observed in the field as a function of depth and season but limited to the range [1/3, 2/3]. The domain of stability for partially oxidized green rust is observed in the Eh-pH Pourbaix diagrams if thermodynamic properties of GR(x)∗ is compared with those of lepidocrocite, γ-FeOOH, and goethite, α-FeOOH. Electrochemical equilibrium between GR(x)∗ and FeII in solution corresponds to Eh-pH conditions close to those measured in the field. Therefore, the reductive dissolution of GR(x)∗ can explain the relatively large concentration of FeII measured in aqueous medium of hydromorphic soils containing fougerite. 相似文献
72.
High-order Statistics of Spatial Random Fields: Exploring Spatial Cumulants for Modeling Complex Non-Gaussian and Non-linear Phenomena 总被引:9,自引:7,他引:2
The spatial distributions of earth science and engineering phenomena under study are currently predicted from finite measurements
and second-order geostatistical models. The latter models can be limiting, as geological systems are highly complex, non-Gaussian,
and exhibit non-linear patterns of spatial connectivity. Non-linear and non-Gaussian high-order geostatistics based on spatial
connectivity measures, namely spatial cumulants, are proposed as a new alternative modeling framework for spatial data. This
framework has two parts. The first part is the definition, properties, and inference of spatial cumulants—including understanding
the interrelation of cumulant characteristics with the in-situ behavior of geological entities or processes, as examined in
this paper. The second part is the research on a random field model for simulation based on its high-order spatial cumulants.
Mathematical definitions of non-Gaussian spatial random functions and their high-order spatial statistics are presented herein,
stressing the notion of spatial cumulants. The calculation of spatial cumulants with spatial templates follows, including
anisotropic experimental cumulants. Several examples of two- and three-dimensional images, including a diamond bearing kimberlite
pipe from the Ekati Mine in Canada, are analyzed to assess the relations between cumulants and the spatial behavior of geological
processes. Spatial cumulants of orders three to five are shown to capture directional multiple-point periodicity, connectivity
including connectivity of extreme values, and spatial architecture. In addition, they provide substantial information on geometric
characteristics and anisotropy of geological patterns. It is further shown that effects of complex spatial patterns are seen
even if only subsets of all cumulant templates are computed. Compared to second-order statistics, cumulant maps are found
to include a wealth of additional information from underlying geological patterns. Further work seeks to integrate this information
in the predictive capabilities of a random field model. 相似文献