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Results for “Heterogenous Electron Transfer”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Sources of background current in the ECC ozonesonde - Implications for total ozone measurements

The source of the background current in the usual operation of the electrochemical concentration cell ozonesonde is the reduction of tri-iodide normally present in the cathode solution. The time variations in the background current can be explained by the slow rates of solution mass transport and of heterogeneous electron transfer for tri-iodide. Oxygen does not contribute to the background current through reaction with iodide to produce tri-iodide. Direct reduction of oxygen at the cathode is negligible once the electrodes have been exposed to iodide for 24 hours. The present background current correction is altitude-dependent, since it is based on an assumed sensitivity of the electrochemical concentration cell to oxygen. If the background current is independent of altitude and of oxygen, a constant, uncorrected, background current of 0.1 microamp would produce an error of +5.5% for the total ozone value of the electrochemical concentration cell for a typical midlatitude total ozone value of 0.345 atm-cm.

Thornton, D. C.↗

Oxidation of the Mantle Wedge by H+ in Aqueous Fluids: A New Interdisciplinary Approach

The observation that arc magmas are the most oxidized on Earth have led petrologists to question whether the subduction process might cause oxidation of the sub-arc mantle source. A strong correlation between the input of slab-derived aqueous fluid and Fe3(+)/ΣFe in arc magmas has led to the hypothesis that slab fluids may facilitiate the transfer of redox potential from oxidized slab material to mantle wedge and subsequently to primary arc melts. Despite this intuitive link, identifying an efficient and ubiquitous chemical process to transfer oxidation state in slab fluids has been challenging. Pure H2O alone is an inefficient oxidizer in the mantle, necessitating another oxidant within the fluid. Commonly invoked components include S or C, which are likely heterogeneously distributed within subducting slabs, and direct transfer of Fe3(+), which is only possible in very solute-rich fluids. Here we present a new mechanism to explain the oxidation of the sub-arc mantle by slab-derived aqueous fluid, wherein dissolved H(+)(aq) is reduced to H2(aq). Redox equilibrium is satisfied by electron transfer from Fe2(+)(s), which is oxidized in the rock to Fe3(+)(s) in the reaction: 2Fe2(+)(s) + 2H(+)(aq) = 2Fe3(+)(s) + H2(aq). This simple reaction was previously overlooked due to the assumption that all H must be bound by H2O molecules (i.e., no dissolved H), applicable to a pure H2O fluid, but not one with a solute load as addressed here. The application of thermodynamic modeling tools from aqueous geochemistry (DEW, EQ3/6) to mantle petrology predicts this reaction between mantle rock and slab fluid with our own experimentally constrained chemistry and fO2 (QFM+2). Mass transfer model results show an increase in Fe3(+)/ΣFe in mantle rock from MORB- like (0.15) to arc-like (0.2–0.3) values at reasonable fluid fluxes, co-incident with increasing H2 activity in the fluid. This can explain the stark correlation between slab fluid input into the mantle wedge and the observed fO2 of arc magmas. Moreover, it does not require diffusion of hydrogen out of the system. Instead, H2 remains dissolved in fluid in equilibrium with oxidized mantle rock.

Iacovino, Kayla↗

Pyrite oxidation and reduction - Molecular orbital theory considerations

In this paper, molecular orbital theory is used to explain a heterogeneous reaction mechanism for both pyrite oxidation and reduction. The mechanism demonstrates that the oxidation of FeS2 by Fe(3+) may occur as a result of three important criteria: (1) the presence of a suitable oxidant having a vacant orbital (in case of liquid phase) or site (solid phase) to bind to the FeS2 via sulfur; (2) the initial formation of a persulfido (disulfide) bridge between FeS2 and the oxidant, and (3) an electron transfer from a pi(asterisk) orbital in S2(2-) to a pi or pi(asterisk) orbital of the oxidant.

Luther, George W., III↗

Lifetimes of bacteriochlorophyll fluorescence in Rhodopseudomonas viridis and Heliobacterium chlorum at low temperatures

Fluorescence lifetimes of isolated membranes of Rhodopseudomonas viridis were measured in the temperature range of 77 K to 25 K. At room temperature, the main component of the fluorescence decay of bacteriochlorophyll (BChl) b had a time constant of 50 ps. In contrast to other purple bacteria, the emission at low temperature was spectrally homogeneous and showed essentially single lifetimes of 140 ps at 77 K and 180 ps at 25 K, with the primary electron donor in the oxidized state. Taking into account the relative fluorescence yields with open and closed reaction centers, we arrive at numbers of 125 ps and 215 ps, respectively, for open reaction centers. These numbers are significantly smaller than expected on the basis of measurements of the efficiency of charge separation, perhaps suggesting that the excitation decay in the absence of reaction centers is considerably faster at low temperature than at room temperature. At least four different spectral components with different lifetimes were observed at 25 K in the emission of Heliobacterium chlorum, a short-wavelength component of about 30 ps and three longer-wavelength components of about 100 ps, 300 ps, and 900 ps. This indicates a strong heterogeneity in the emitting pigment, BChl g-808. The component with the shortest lifetime does not appear to be affected by the redox state of the reaction center and might reflect energy transfer to BChl g species which are connected to the reaction center.

NASA Discipline Number 52-30↗

Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.

Liou, Frank↗

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗