503 resultados para 1149


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"Notes and illustrations" at end of v. 1-4; "Proofs and illustrationsfrom manuscripts ... hitherto unprinted" at end of v. 5-7.

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The subduction of oceanic plates regulates crustal growth, influences arc volcanism, and refertilizes the mantle. Continental growth occurs by subduction of crustal material (seawater components, marine sediments, and basaltic crust). The geochemical and physical evolution of the Earth's crust depends, in large part, on the fate of subducted material at convergent margins (Armstrong, 1968, doi:10.1029/RG006i002p00175; Karig and Kay, 1981, 10.1098/rsta.1981.0108). The crustal material on the downgoing plate is recycled to various levels in the subduction zone. The recycling process that takes place in the "Subduction Factory" is difficult to observe directly but is clearly illuminated using chemical tracers. Von Huene and Scholl (1991, doi:10.1029/91RG00969) and Plank and Langmuir (1993, doi:10.1038/362739a0) preliminarily calculated a large flux of subducted materials. By mass balancing the chemical tracers and measuring the fractionations that occur between them, the Subduction Factory work and the effect on the Earth's evolution can be estimated. In order to elucidate this mass balance, Ocean Drilling Program Leg 185 drilled two deepwater shales into the oceanic crust situated in the Mariana-Izu Trenches and recovered core samples of incoming oceanic crust. The calculations of mass circulation in the subduction zone, however, did not take into account the mass transfer properties within subducted oceanic crust, although the dewatering fluid and diffused ions may play an important role in various activities such as seismogeneity, serpentine diapiring, and arc volcanism. Thus, this paper focuses on the quantitative measurements of the physical and mass transfer properties of subducted oceanic crust.

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A mathematical model for the galvanostatic discharge and recovery of porous, electrolytic manganese dioxide cathodes, similar to those found within primary alkaline batteries is presented. The phenomena associated with discharge are modeled over three distinct size scales, a cathodic (or macroscopic) scale, a porous manganese oxide particle (or microscopic) scale, and a manganese oxide crystal (or submicroscopic) scale. The physical and chemical coupling between these size scales is included in the model. In addition, the model explicitly accounts for the graphite phase within the cathode. The effects that manganese oxide particle size and proton diffusion have on cathodic discharge and the effects of intraparticle voids and microporous electrode structure are predicted using the model.

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A mathematical model is developed to simulate the discharge of a LiFePO4 cathode. This model contains 3 size scales, which match with experimental observations present in the literature on the multi-scale nature of LiFePO4 material. A shrinking-core is used on the smallest scale to represent the phase-transition of LiFePO4 during discharge. The model is then validated against existing experimental data and this validated model is then used to investigate parameters that influence active material utilisation. Specifically the size and composition of agglomerates of LiFePO4 crystals is discussed, and we investigate and quantify the relative effects that the ionic and electronic conductivities within the oxide have on oxide utilisation. We find that agglomerates of crystals can be tolerated under low discharge rates. The role of the electrolyte in limiting (cathodic) discharge is also discussed, and we show that electrolyte transport does limit performance at high discharge rates, confirming the conclusions of recent literature.

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In this paper, we present a ∑GIi/D/1/∞ queue with heterogeneous input/output slot times. This queueing model can be regarded as an extension of the ordinary GI/D/1/∞ model. For this ∑GIi/D/1/∞ queue, we assume that several input streams arrive at the system according to different slot times. In other words, there are different slot times for different input/output processes in the queueing model. The queueing model can therefore be used for an ATM multiplexer with heterogeneous input/output link capacities. Several cases of the queueing model are discussed to reflect different relationships among the input/output link capacities of an ATM multiplexer. In the queueing analysis, two approaches: the Markov model and the probability generating function technique, are adopted to develop the queue length distributions observed at different epochs. This model is particularly useful in the performance analysis of ATM multiplexers with heterogeneous input/output link capacities.

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A novel model for the potentiostatic discharge of primary alkaline battery cathodes is presented. The model is used to simulate discharges resulting from the stepped potential electrochemical spectroscopy (SPECS) of primary alkaline battery cathodes cathodes, and the results are validated with experimental data. We show that a model based on a single (or mean) reaction framework can be used to simulate multi-reaction discharge behaviour and we develop a consistent functional modification to the kinetic equation of the model that allows for this to occur. The model is used to investigate the effects that the initial exchange current density, i00, and the diffusion coefficient for protons in electrolytic manganese dioxide (EMD), DH+, have on SPECS discharge. The behaviour observed is consistent with the idea that individual reduction reactions, within the multi-reaction, reduction behaviour of EMD, have distinct i00 and DH+ values.

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In this work, we investigate and compare the Maxwell–Stefan and Nernst–Planck equations for modeling multicomponent charge transport in liquid electrolytes. Specifically, we consider charge transport in the Li+/I−/I3−/ACN ternary electrolyte originally found in dye-sensitized solar cells. We employ molecular dynamics simulations to obtain the Maxwell–Stefan diffusivities for this electrolyte. These simulated diffusion coefficients are used in a multicomponent charge transport model based on the Maxwell– Stefan equations, and this is compared to a Nernst–Planck based model which employs binary diffusion coefficients sourced from the literature. We show that significant differences between the electrolyte concentrations at electrode interfaces, as predicted by the Maxwell–Stefan and Nernst–Planck models, can occur. We find that these differences are driven by a pressure term that appears in the Maxwell–Stefan equations. We also investigate what effects the Maxwell–Stefan diffusivities have on the simulated charge transport. By incorporating binary diffusivities found in the literature into the Maxwell–Stefan framework, we show that the simulated transient concentration profiles depend on the diffusivities; however, the simulated equilibrium profiles remain unaffected.

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Newberyite Mg(PO3OH)•3H2O is a mineral found in caves such as from Moorba cave, Jurien Bay, Western Australia, the Skipton Lava tubes (SW of Ballarat, Victoria, Australia) and in the Petrogale Cave (Madura , Eucla, Western Australia). Because these minerals contain oxyanions, hydroxyl units and water, the minerals lend themselves to spectroscopic analysis. Raman spectroscopy can investigate the complex paragenetic relationships existing between a number of ‘cave’ minerals. The intense sharp band at 982 cm-1 is assigned to the PO43- ν1 symmetric stretching mode. Low intensity Raman bands at 1152, 1263 and 1277 cm-1 are assigned to the PO43- ν3 antisymmetric stretching vibrations. Raman bands at 497 and 552 cm-1 are attributed to the PO43- ν4 bending modes. An intense Raman band for newberyite at 398 cm-1 with a shoulder band at 413 cm-1 is assigned to the PO43- ν2 bending modes. The values for the OH stretching vibrations provide hydrogen bond distances of 2.728Å (3267 cm-1), 2.781Å (3374cm-1), 2.868Å (3479 cm-1), and 2.918Å (3515 cm-1). Such hydrogen bond distances are typical of secondary minerals. Estimates of the hydrogen-bond distances have been made from the position of the OH stretching vibrations and show a wide range in both strong and weak bonds.