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At least 235 records · Page 13

Soil physical and thermal properties from soil samples at multiple locations at Teller Road Site, Seward Peninsula, Alaska, 2019

This dataset contains results of the laboratory analysis of soil samples collected across the watershed located at miles #27 along the Teller road, near Nome, AK. The dataset includes 124 soil samples retrieved from 52 locations during the first week of August 2019. The soil samples were collected in the top 1.2 m of soil with volume known samples, analyzed with a thermal analyser to infer thermal parameters (thermal conductivity, volumetric heat capacity and thermal diffusivity), and then processed in a lab for estimation of their bulk density, water content, carbon and nitrogen content, soil texture, and elemental fractions. This dataset has one csv file and one pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States.

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation System. The fundamental fire intensity algorithms in these systems require surface fire behavior fuel models and canopy cover to model surface fire behavior. Canopy base height, stand height, and canopy bulk density are required in addition to surface fire behavior fuel models and canopy cover to model crown fire activity. Several surface fuel and canopy classification efforts have used various remote sensing and ecological relationships as core methods to develop the spatial layers. All of these methods depend upon consistent and temporally constant interpretations of crown attributes and their ecological conditions to estimate surface fuel conditions. This study evaluates modeled fire behavior for an 80,000 ha tract of land in the Atlantic Coastal Plain of the southeastern US using three different data sources. The Fuel Characteristic Classification System (FCCS) was used to build fuelbeds from intensive field sampling of 629 plots. Custom fire behavior fuel models were derived from these fuelbeds. LANDFIRE developed surface fire behavior fuel models and canopy attributes for the US using satellite imagery informed by field data. The Southern Wildfire Risk Assessment (SWRA) developed surface fire behavior fuel models and canopy cover for the southeastern US using satellite imagery. Differences in modeled fire behavior, data development, and data utility are summarized to assist in determining which data source may be most applicable for various land management activities and required analyses. Characterizing fire behavior under different fuel relationships provides insights for natural ecological processes, management strategies for fire mitigation, and positive and negative features of different modeling systems. A comparison of flame length, rate of spread, crown fire activity, and burn probabilities modeled with FlamMap shows some similar patterns across the landscape from all three data sources, but there are potentially important differences. All data sources showed an expected range of fire behavior. Average flame lengths ranged between 1 and 1.4 m. Rate of spread varied the greatest with a range of 2.4-5.7 m min{sup -1}. Passive crown fire was predicted for 5% of the study area using FCCS and LANDFIRE while passive crown fire was not predicted using SWRA data. No active crown fire was predicted regardless of the data source. Burn probability patterns across the landscape were similar but probability was highest using SWRA and lowest using FCCS.

60 APPLIED LIFE SCIENCES↗

Soil Water Retention and Hydraulic Conductivity Data and Model at Trail Creek in Taylor River Watershed, Colorado 2024-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Trail Creek. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format TR-X-Y, where TR refers to Trail Creek, X is the treatment block identifier, and Y is the location identifier. Specifically, TR-ASCC1 is the control treatment block under the Adaptive Silviculture for Climate Change (ASCC) project, and TR-ASCC2 is the clear-cut treatment block. TR-ASCC-EHSn is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and TR-ASCC-ERTn (upslope n=1) are ecohydrology sites along the electrical resistivity tomography transects. The sample and location information can be found in metadata.csv, and the data from the soil sensors will be included in a future data version when the observation period becomes sufficiently long for data analysis. Sampling and Measurements Each sample falls into one of the two sampling methods – (1) intact cores or (2) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. The intact cores were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗

THE EFFECT OF TEMPERATURE AND UNIAXIAL PRESSURE ON THE DENSIFICATION BEHAVIOR OF SILICA AEROGEL GRANULES

Materials are being developed in U.S. for the removal and immobilization of iodine from gaseous products of nuclear fuel reprocessing in support of the Fuel Cycle Technology Separations and Waste Forms Campaign. The silver-functionalized silica aerogel proved to be an excellent candidate for this treatment because of its high selectivity and sorption capacity for radioiodine and its possible conversion to a durable silica-based waste form. The present study investigated with nitrogen sorption and helium pycnometry the effect of pressureless isothermal sintering at temperatures of 900-1400°C for 2.5-90 min or isothermal hot-pressing at 1200°C for 2.5 min on densification of raw and silver-functionalized silica aerogel granules. Rapid sintering was observed at 1050 and 1200°C. Only 15 min of pressureless sintering at 1200°C resulted in almost complete densification. The macropores disappeared, surface area decreased from 1114 m2/g to 25 m2/g, pore volume from 7.41 cm3/g to 0.09 cm3/g, and adsorption pore size from 18.7 to 7 nm. The skeletal density of sintered granules was similar to the bulk density of amorphous silica (2.2 g/cm3). The hot-pressing accelerated the sintering process, decreasing significantly the pore size and volume.

BET↗

Water Uptake by Silica Nanopores: Impacts of Surface Hydrophilicity and Pore Size

Water uptake at 298 K by two mesoporous silicas with different pore sizes was studied using volumetric vapor sorption. Here, through variation of sample pretreatment temperature and time, the number of surface hydroxyl groups was varied, leading to marked changes in the water sorption behavior. With increasing surface hydroxyl density, the adsorption of water to the pore surfaces increases, leading to formation of a thicker and denser water sorption layer. The BET model was used to measure surface hydroxyl density from low pressure parts of water adsorption isotherms. Adsorption of water molecules scales with the number density of surface hydroxyl groups, and monolayer coverage is reached at reduced pressure of ca. 0.3. The onset of adsorption pore condensation of water shifts to lower reduced pressure with increasing surface hydroxyl density, indicating growing thickness of adsorption layers. However, the water pore condensation step of the desorption branch shifts to smaller reduced pressure with increasing surface hydroxylation, reducing the adsorption-desorption hysteresis width. An adsorbed phase model is utilized to calculate the distribution of pore water molecules between adsorbed and pore condensation phases, and characterize the density and thickness of the water sorption phase. In the smaller pores, the adsorbed phase forms a sparse monolayer, while approximately a bilayer is formed in the wider pores. The previously reported silica nanopore underfilling by water is confirmed and rationalized by a significantly reduced water density in the adsorbed phase with respect to bulk, while the pore core is filled with water of approximately bulk density.

36 MATERIALS SCIENCE↗

Ultrasonic characterization of structural ceramics

Ultrasonic velocity and attenuation measurements were used to characterize density and microstructure in monolithic silicon nitride and silicon carbide. Research samples of these structural ceramics exhibited a wide range of density and microstructural variations. It was shown that bulk density variations correlate with and can be estimated by velocity measurements. Variations in microstructural features such as grain size or shape and pore morphology had a minor effect on velocity. However, these features had a pronounced effect on ultrasonic attenuation. The ultrasonic results are supplemented by low-energy radiography and scanning laser acoustic microscopy.

Klima, S. J.↗

Nondestructive characterization of structural ceramics

Ultrasonic velocity and attenuation measurements were used to characterize density and microstructure in monolithic silicon nitride and silicon carbide. Research samples of these structural ceramics exhibited a wide range of density and microstructural variations. It was shown that bulk density variations correlate with and can be estimated by velocity measurements. Variations in microstructural features such as grain size or shape and pore morphology had a minor effect on velocity. However, these features had a pronounced effect on ultrasonic attenuation. The ultrasonic results are supplemented by low-energy radiography and scanning laser acoustic microscopy.

Klima, S. J.↗

An extension of the localized artificial diffusivity method for immiscible and high density ratio flows

The localized artificial diffusivity (LAD) method is widely regarded as the preferred multi-material regularization scheme for the compact finite difference method, because it is conservative, easy to implement, and generally robust for a wide range of multi-material problems. However, traditional LAD methods face significant challenges when applied to flows with large density ratios and when maintaining thermodynamic equilibrium across material interfaces. These limitations arise from the formulation of the artificial diffusivity flux and the reliance on enthalpy diffusion for interface regularization. Additionally, traditional LAD methods struggle to ensure stability under large density ratio conditions, fail to maintain a finite interface thickness, and are therefore unsuitable for modeling immiscible interfaces. Here, in this work, we discuss the origins of these issues in traditional LAD methods and propose modifications which enable the simulation of large density ratio and immiscible flows. The proposed method targets the artificial diffusion fluxes at gradients and ringing in the volume fraction, rather than the mass fraction in traditional methods, to consistently regularize large density ratio interfaces. Furthermore, the proposed method introduces an artificial bulk density diffusion term to enforce equilibrium conditions across interfaces. To address the challenge of modeling immiscible flows, a conservative diffuse interface term is incorporated into the formulation to ensure a finite interface thickness. Specific consideration is taken in the design of the method to ensure that these crucial properties are maintained for N -material flows. The effectiveness of the proposed method is demonstrated through a series of canonical test cases, and its accuracy is validated by comparison with experimental data on micro-bubble collapse in water. These results highlight the method’s robustness and its ability to overcome the limitations of traditional LAD approaches.

Artificial diffusivity↗

Modeling of SAR returns from a red pine stand

Bright P-band radar returns from red pine forests have been observed on synthetic aperture radar (SAR) images in Bangor, Maine. A plot of red pine trees was selected for the characterization and modeling to understand the cause of the high P-band returns. The red pine stand under study consisted of mature trees. Diameter at breast height (DBH) measurements were made to determine stand density as a function of tree diameter. Soil moisture and bulk density measurements were taken along with ground rough surface profiles. Detailed biomass measurements of the needles, shoots, branches, and trunks were also taken. These site statistics have been used in a distorted Born approximation model of the forest. Computations indicate that the direct-reflected or the double-bounce contributions from the ground are responsible for the high observed P-band returns for HH polarization.

Lang, R. H.↗

Direct Measure of the Dense Methane Phase in Gas Shale Organic Porosity by Neutron Scattering

Here, we report the first direct measurements of methane density in shale gas using small-angle neutron scattering. At a constant pressure, the density of methane in the inorganic pores is similar to the gas bulk density of the system conditions. Conversely, the methane density is 2.1 ± 0.2 times greater in the organic mesopores. Furthermore, classical density functional theory calculations show that this excess density in the organic pores persists to elevated temperatures, typical of shale gas reservoir conditions, providing new insight into the hydrocarbon storage mechanisms within these reservoirs.

04 OIL SHALES AND TAR SANDS↗

Physical Properties of Moist, Fermented Corn Kernels

A novel approach to producing corn stover biomass feedstock has been investigated. In this approach, corn grain and stover are co-harvested at moisture contents much less than typical corn silage. The grain and stover are conserved together by anaerobic storage and fermentation and then separated before end use. When separated from the stover, the moist, fermented grain had physical characteristics that differ from typical low-moisture, unfermented grain. A comprehensive study was conducted to quantify the physical properties of this moist, fermented grain. Six corn kernel treatments, either fermented or unfermented, having different moisture contents, were used. Moist, fermented kernels (26 and 36% w.b. moisture content) increased in size during storage. The fermented kernels’ widths and thicknesses were 10% and 15% greater, respectively, and their volume was 28% greater than the dry kernels (15% w.b.). Dry basis particle density was 9% less for moist, fermented kernels. Additionally, the dry basis bulk density was 29% less, and the dry basis hopper-discharged mass flow rate was 36% less. Moist, fermented grain had significantly greater kernel-to-kernel coefficients of friction and angles of repose compared to relatively dry grain. The friction coefficient on four different surfaces was also significantly greater for fermented kernels. Fermented corn kernels had lower individual kernel rupture strengths than unfermented kernels. These physical differences must be considered when designing material handling and processing systems for moist, fermented corn grain.

09 BIOMASS FUELS↗

Microwave dielectric properties of dry rocks

A combination of techniques was used to measure the dielectric properties of 80 rock samples in the microwave region. The real part (RP) of the relative dielectric constant was measured in 0.1-GHz steps from 0.5 to 18 GHz, and the imaginary part (IP) was measured at five frequencies between 1.6 and 16 GHz. The bulk density rho(b) was also measured for all the samples, and the bulk chemical composition (BCC) was determined for 56 of the samples. RP is found to be frequency-independent at 0.5-18 GHz for all samples, and rho(b) accounts for about 50 percent of the observed variance. For silicate rocks, as much as 78 percent of the variance is explained by the combination of rho(b) and the fractional contents of oxides when the silicates are subgrouped by genesis. In contrast, IP decreases with increasing frequency for most rock samples, and no statistically significant relationships are found between IP and rho(b). For subgrouped silicate rocks, 60 percent of the variance in IP can be explained by BCC.

Ulaby, Fawwaz T.↗

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Ulaby, F. T.↗

Thermoelectric transport properties of polycrystalline titanium diselenide co-intercalated with nickel and titanium using spark plasma sintering

Polycrystalline samples of nickel intercalated (0-5%) TiSe{sub 2} were attempted via solid-state reaction in evacuated quartz tubes followed by densification using a spark plasma sintering process. X-ray diffraction data indicated that mixed NiSe{sub 2} and TiSe{sub 2} phases were present after initial synthesis by solid-state reaction, but a pure TiSe{sub 2} phase was present after the spark plasma sintering. While EPMA data reveals the stoichiometry to be near 1:1.8 (Ti:Se) for all samples, comparisons of the measured bulk densities to the theoretical densities suggest that the off stoichiometry is a result of the co-intercalation of both Ni and Ti rather than Se vacancies. Due to the presence of excess Ti (0.085-0.130 per formula) in the van der Waals gap of all the samples, the sensitive electron-hole balance is offset by the additional Ti-3d electrons, leading to an increase in the thermopower (n-type) over pristine, stoichiometric TiSe{sub 2}. The effects of the co-intercalation of both Ni and Ti in TiSe{sub 2} on the structural, thermal, and electrical properties are discussed herein. - Graphical abstract: Co-intercalation of nickel and excess titanium into the van der Waals gap of TiSe{sub 2} via solid state synthesis followed by spark plasma sintering results in a systematic shift in the ratio of hole and electron carrier concentration, which is close to unity for pristine TiSe{sub 2}. This directly affects the electrical transport properties, and as the structural disorder induced by intercalation suppresses the lattice thermal conductivity, co-intercalation is an effective route to enhance the thermoelectric properties of transition metal diselenides. Highlights: Black-Right-Pointing-Pointer Single phase bulk Ni and Ti co-intercalated TiSe{sub 2} samples prepared by spark plasma sintering. Black-Right-Pointing-Pointer Density and X-ray diffraction suggest that the Ni and excess Ti are ordered in the Van der Waals gap. Black-Right-Pointing-Pointer Co-intercalation of Ni and Ti can be used to control electron-hole ratio and structural disorder.

36 MATERIALS SCIENCE↗

Structure and hydrogen adsorption properties in low density nanoporous carbons from simulations

We systematically model the hydrogen adsorption in nanoporous carbons over a wide range of carbon bulk densities (0.6 - 2.4 g/cm3) by using tight binding molecular dynamics simulations for the carbon structures and thermodynamics calculations of the hydrogen adsorption. The resulting structures are in good agreement with the experimental data of ultra-microporous carbon (UMC), a wood-based activated carbon, as indicated by comparisons of the microstructure at atomic level, pair distribution function, and pore size distribution. The hydrogen adsorption calculations in carbon structures demonstrate both a promising hydrogen storage capacity (excess uptake of 1.33 wt% at 298K and 5 MPa, for carbon structures at the lower range of densities) and a reasonable heat of adsorption (12-22 kJ/mol). This work demonstrates that increasing the heat of adsorption does not necessarily increase the hydrogen uptake. In fact, the available adsorption volume is as important as the isosteric heat of adsorption for hydrogen storage in nanoporous carbons.

08 HYDROGEN↗

Exploring Alternative Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. The combination of reliable cloud microphysics and radar reflectivity may constrain radiative transfer models used in satellite simulators during future missions, including EarthCARE and the NASA Global Precipitation Measurement. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a mid latitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗

Method for providing a low density high strength polyurethane foam

Disclosed is a method for making a polyurethane closed-cell foam material exhibiting a bulk density below 4 lbs/ft.sup.3 and high strength. The present embodiment uses the reaction product of a modified MDI and a sucrose/glycerine based polyether polyol resin wherein a small measured quantity of the polyol resin is "pre-reacted" with a larger quantity of the isocyanate in a defined ratio such that when the necessary remaining quantity of the polyol resin is added to the "pre-reacted" resin together with a tertiary amine catalyst and water as a blowing agent, the polymerization proceeds slowly enough to provide a stable foam body.

36 MATERIALS SCIENCE↗

A Near-infrared Chemical Inventory of the Atmosphere of 55 Cancri e

We present high-resolution near-infrared spectra taken during eight transits of 55 Cancri e, a nearby low-density super-Earth with a short orbital period (<18 hr). While this exoplanet’s bulk density indicates a possible atmosphere, one has not been detected definitively. Our analysis relies on the Doppler cross-correlation technique, which takes advantage of the high spectral resolution and broad wavelength coverage of our data, to search for the thousands of absorption features from hydrogen-, carbon-, and nitrogen-rich molecular species in the planetary atmosphere. Although we are unable to detect an atmosphere around 55 Cancri e, we do place strong constraints on the levels of HCN, NH{sub 3}, and C{sub 2}H{sub 2} that may be present. In particular, at a mean molecular weight of 5 amu, we can rule out the presence of HCN in the atmosphere down to a volume mixing ratio (VMR) of 0.02%, NH{sub 3} down to a VMR of 0.08%, and C{sub 2}H{sub 2} down to a VMR of 1.0%. If the mean molecular weight is relaxed to 2 amu, we can rule out the presence of HCN, NH{sub 3}, and C{sub 2}H{sub 2} down to VMRs of 0.001%, 0.0025%, and 0.08%, respectively. Our results reduce the parameter space of possible atmospheres consistent with the analysis of Hubble Space Telescope/WFC3 observations by Tsiaras et al. and indicate that if 55 Cancri e harbors an atmosphere, it must have a high mean molecular weight or clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗