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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A numerical framework for simulating the atmospheric variability of supermicron marine biogenic ice nucleating particles

Abstract. We present a framework for estimating concentrations of episodically elevated high-temperature marine ice nucleating particles (INPs) in the sea surface microlayer and their subsequent emission into the atmospheric boundary layer. These episodic INPs have been observed in multiple ship-based and coastal field campaigns, but the processes controlling their ocean concentrations and transfer to the atmosphere are not yet fully understood. We use a combination of empirical constraints and simulation outputs from an Earth system model to explore different hypotheses for explaining the variability of INP concentrations, and the occurrence of episodic INPs, in the marine atmosphere. In our calculations, we examine the following two proposed oceanic sources of high-temperature INPs: heterotrophic bacteria and marine biopolymer aggregates (MBPAs). Furthermore, we assume that the emission of these INPs is determined by the production of supermicron sea spray aerosol formed from jet drops, with an entrainment probability that is described by Poisson statistics. The concentration of jet drops is derived from the number concentration of supermicron sea spray aerosol calculated from model runs. We then derive the resulting number concentrations of marine high-temperature INPs (at 253 K) in the atmospheric boundary layer and compare their variability to atmospheric observations of INP variability. Specifically, we compare against concentrations of episodically occurring high-temperature INPs observed during field campaigns in the Southern Ocean, the Equatorial Pacific, and the North Atlantic. In this case study, we evaluate our framework at 253 K because reliable observational data at this temperature are available across three different ocean regions, but suitable data are sparse at higher temperatures. We find that heterotrophic bacteria and MBPAs acting as INPs provide only a partial explanation for the observed high INP concentrations. We note, however, that there are still substantial knowledge gaps, particularly concerning the identity of the oceanic INPs contributing most frequently to episodic high-temperature INPs, their specific ice nucleation activity, and the enrichment of their concentrations during the sea–air transfer process. Therefore, targeted measurements investigating the composition of these marine INPs and drivers for their emissions are needed, ideally in combination with modeling studies focused on the potential cloud impacts of these high-temperature INPs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below $5\%$ MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗
DOE OSTI2023

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM: Preprint

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗
DOE OSTI2025

PSTN-056: Survey Cadence Optimization Committee's Phase 3 Recommendations

We present the final planned comprehensive recommendation for Rubin Observatory the Legacy Survey of Space and Time (LSST) survey strategy ahead of the start of LSST. This recommendation is the product of a many-years-long iterative process where community recommendations to maximize the scientific impact of LSST across domains of astrophysics were reviewed, synthesized, aggregated, and merged to define the overall plan for 10 years of LSST observations. The current recommendation builds on Phase 1 (PSTN-053) and Phase 2 recommendations (PSTN-055) and, together, they define a 10-year plan for observing. Here we answer questions left open in PSTN-055, refine additional survey details, and describe the scope of future activities of the SCOC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A framework for testing soil carbon dynamics post land-use transition in a multisector dynamics model

Soil carbon plays a crucial role in the global carbon cycle. Changes in land use can determine whether carbon is stored or is emitted into the atmosphere as carbon dioxide, which has broad implications for the human and Earth systems. These feedbacks to the carbon cycle and their socio-economic drivers are modelled by many global multisector dynamics models to project future possibilities for the human-Earth system. One notable model of this class is the Global Change Analysis Model (GCAM), which uses a simplified process to model soil organic carbon (SOC) content after land-use transition across 384 land units. While the current GCAM soil carbon framework is based on scientific principles, it has not been tested against experimental data. This work examines rates of SOC change from GCAM input data. Specifically, first order rate constants derived from model inputs were compared to values from two syntheses to assess GCAM’s accuracy. Welch’s t-tests and linear models were used to determine if rate constants were consistent across all tested geographical areas and land-use transition types. While we found that there was general agreement on the direction and magnitude (i.e., rate) of SOC change, the rate constant derived from GCAM and empirical values differed strongly in a subset of specific instances. These results indicate that GCAM’s current SOC dynamics during land use transition successfully capture broad patterns of change in this critical carbon pool, but should be interpreted with caution at finer spatial scales. One potential cause of these discrepancies is our highly aggregated variable, soil timescale, which could be made more granular to improve accuracy. When using economically rooted multisector dynamics models, such as GCAM, it is critical to understand such model limitations for representing specific Earth system processes.

carbon↗
DOE OSTI2024

Clustering Interval Load with Weather to Create Scenarios of Behind-the-Meter Solar Penetration

Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation is only visible to the utility as aggregated net-load. This work proposes a methodology for creation of scenarios of solar penetration at the feeder level for use by forecasters to test the robustness of their algorithm to progressively higher penetrations of solar. The algorithm draws on publicly available observations of weather condition (e.g., rainy/cloudy/fair) for use as proxies to sky clearness. These observations are used to mask and weight the interval deviations of similar native usage profiles from which average interval usage is calculated and subsequently added to interval net generation to reconstruct interval total generation. This approach improves the estimate of annual energy generation by 23%; where the net generation signal currently reflects 52% of total annual gener- ation, now 75% is captured. This methodology for creation of forecast testing scenarios is data driven and extensible to service territories which lack information on irradiance measurements and geocoordinates.

solar, load↗
DOE OSTI2023

Geographically Dependent Sustainability Indicators for Comparison of Conventional Vegetable Production to Controlled-Environment Agriculture

Many food system lifecycle analyses distill agricultural production and supply chain impacts into single-value sustainability metrics for various food categories. These studies provide an overview of the food supply system that highlight striking results such as the GHG impacts of meat production. The supply chain impacts of vegetable production occupy the middle ground; higher than average food loss and waste, lower than average overall energy use, etc. However, aggregated results obscure the sustainability implications of the location of food production, especially for vegetables. Moreover, the increasing instability of food production systems are not captured, as illustrated by a recent Washington Post article. According to a UC Merced study conducted for the state, California farmers left nearly 400,000 acres of agricultural land unplanted last year because of a lack of water. The result, the study found, was a direct economic cost to farmers of $1.1 billion and the loss of nearly 9,000 agricultural jobs. (The Washington Post, March 21, 2022.) Previous work quantified the food-energy-water nexus implications of transitioning vegetable production from large, centralized agricultural operations to smaller distributed production in controlled-environment farms (CEA). The importance of location-specific data is especially evident for water use. Water impacts of the food system are primarily local to the region where food is produced, water impacts vary significantly between locations, and water stress is a major concern in locations that currently host large agricultural operations. Location-specific data is needed to accurately assess the water impacts of transitioning to CEA. The location of farms in relation to consumers impacts transportation energy use, food loss and waste, and requirements for food processing (e.g., to reduce weight, preserve foods for long storage, and package foods to reduce damage and loss) Reducing transport is particularly relevant for agricultural products that could be grown in CEAs (fruits, vegetables, protein). Access to nutritious food is not evenly distributed in the population. Remote communities, communities in harsh environments, and economically-disadvantaged communities often have poor access to healthy foods. CEA is ideally suited to these environments. However, the energy and water use of CEA, while in many respects lower overall than conventional supply chains, are concentrated within communities and could have significant local impacts. This paper reports on development of sustainability metrics that seek to capture the tradeoffs between the current supply chain and a CEA supply chain for vegetables; focusing on the location-dependent implications of water use, the transition from largely fossil fuel based energy use to electricity, and the food access, resilience and wellbeing implications of urban versus rural food production.

controlled-environment agriculture↗
DOE OSTI2015

Highly sensitive nonlinear luminescent ceramics for volumetric and multilayer data carriers

The interaction of optical ceramics based on wide-bandgap crystals with near-IR femtosecond laser radiation is studied experimentally. The formation of luminescent centres in LiF and MgF{sub 2} ceramics under the action of single laser pulses is considered. Two interaction regimes are used. In the regime of low-aperture focusing of laser radiation (800 nm, 30 fs, 0.3 mJ), multiple selffocusing and filamentation in the samples are observed. The luminescent centres are formed in thin channels induced by light filaments. The average effective self-focusing length is ∼100 μm; the formation of luminescent centres begins at this length and ceases at a wavelength of about 380 mm. The luminescent trace (spur) induced by a single laser filament was ∼30 μm long and 1.3 μm in diameter. The second regime of light interaction with the sample was based on high-aperture focusing with a simultaneous decrease in the laser pulse energy. This led to the formation of single pits with a diameter smaller than the optical diffraction limit. The luminescent centres induced by the laser radiation were aggregated colour centres. The mechanism of their creation included the highly-nonlinear generation of electron – hole pairs in the filamentation region, their recombination with the formation of anion excitons and the decay of excitons into Fresnel defects by the Lushchik – Vitol – Hersh – Pooley mechanism, as well as their recharging, migration and aggregation. (laser applications and other topics in quantum electronics)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2011

Characterization of the intragranular water regime within subsurface sediments: Pore volume, surface area, and mass transfer limitations

Although 'intragranular' pore space within grain aggregates, grain fractures, and mineral 24 surface coatings may contain a relatively small fraction of the total porosity within a porous 25 medium, it often contains a significant fraction of the reactive surface area, and can thus strongly 26 affect the transport of sorbing solutes. In this work, we demonstrate a batch experiment 27 procedure using tritium and bromide as high-resolution diffusive tracers to characterize the 28 intragranular pore space. The method was tested using uranium-contaminated sediments from 29 the vadose and capillary fringe zones beneath the former 300A process ponds at the Hanford site 30 (Washington State, USA). Sediments were contacted with tracers in artificial groundwater, 31 followed by replacement of bulk solution with tracer-free groundwater and monitoring of tracer 32 release. From these data, intragranular pore volumes were calculated and mass transfer rates 33 were quantified using a multirate first-order mass transfer model. Tritium-hydrogen exchange 34 on surface hydroxyls was accounted for by conducting additional tracer experiments on sediment 35 that was vacuum dried after reaction. The complementary ('wet' and 'dry') techniques allowed 36 for the simultaneous determination of intragranular porosity and surface area using tritium. The 37 Hanford 300A samples exhibited intragranular pore volumes of {approx}1% of the solid volume and 38 intragranular surface areas of {approx}20-30% of the total surface area. Comparison with N2 gas 39 adsorption suggests that this pore space includes both 'micropores' (< 2 nm diameter) and 40 'mesopores' (> 2 nm). Intragranular porosity estimates obtained using bromide were 41 significantly smaller, likely due to anion exclusion of Br- from pores with negatively charged 42 surfaces.

300A↗
DOE OSTI2015

Variability of interconnected wind plants: correlation length and its dependence on variability time scale

The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. However, how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer 'how far is far enough,' we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25–2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high-pass filter time constants shorter than about τ = 38 h, all datasets exhibit a correlation length $\xi $ that falls at least as fast as ${{\tau }^{-1}}$ . Since the inter-site separation needed for statistical independence falls for shorter time scales, higher-rate fluctuations can be effectively smoothed by aggregating wind plants over areas smaller than otherwise estimated.

17 WIND ENERGY↗
DOE OSTI2019

Structure of lipoprotein lipase in complex with GPIHBP1

Lipoprotein lipase (LPL) plays a central role in triglyceride (TG) metabolism. By catalyzing the hydrolysis of TGs present in TG-rich lipoproteins (TRLs), LPL facilitates TG utilization and regulates circulating TG and TRL concentrations. Until very recently, structural information for LPL was limited to homology models, presumably due to the propensity of LPL to unfold and aggregate. By coexpressing LPL with a soluble variant of its accessory protein glycosylphosphatidylinositol-anchored high-density lipoprotein binding protein 1 (GPIHBP1) and with its chaperone protein lipase maturation factor 1 (LMF1), we obtained a stable and homogenous LPL/GPIHBP1 complex that was suitable for structure determination. We report here X-ray crystal structures of human LPL in complex with human GPIHBP1 at 2.5–3.0 Å resolution, including a structure with a novel inhibitor bound to LPL. Binding of the inhibitor resulted in ordering of the LPL lid and lipid-binding regions and thus enabled determination of the first crystal structure of LPL that includes these important regions of the protein. It was assumed for many years that LPL was only active as a homodimer. The structures and additional biochemical data reported here are consistent with a new report that LPL, in complex with GPIHBP1, can be active as a monomeric 1:1 complex. The crystal structures illuminate the structural basis for LPL-mediated TRL lipolysis as well as LPL stabilization and transport by GPIHBP1.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Mixing and Transport of Dust in the Early Solar Nebula as Inferred from Titanium Isotope Variations among Chondrules

Chondrules formed by the melting of dust aggregates in the solar protoplanetary disk and as such provide unique insights into how solid material was transported and mixed within the disk. Here, we show that chondrules from enstatite and ordinary chondrites show only small {sup 50}Ti variations and scatter closely around the {sup 50}Ti composition of their host chondrites. By contrast, chondrules from carbonaceous chondrites have highly variable {sup 50}Ti compositions, which, relative to the terrestrial standard, range from the small {sup 50}Ti deficits measured for enstatite and ordinary chondrite chondrules to the large {sup 50}Ti excesses known from Ca–Al-rich inclusions (CAIs). These {sup 50}Ti variations can be attributed to the addition of isotopically heterogeneous CAI-like material to enstatite and ordinary chondrite-like chondrule precursors. The new Ti isotopic data demonstrate that isotopic variations among carbonaceous chondrite chondrules do not require formation over a wide range of orbital distances, but can instead be fully accounted for by the incorporation of isotopically anomalous “nuggets” into chondrule precursors. As such, these data obviate the need for disk-wide transport of chondrules prior to chondrite parent body accretion and are consistent with formation of chondrules from a given chondrite group in localized regions of the disk. Finally, the ubiquitous presence of {sup 50}Ti-enriched material in carbonaceous chondrites and the lack of this material in the non-carbonaceous chondrites support the idea that these two meteorite groups derive from areas of the disk that remained isolated from each other, probably through the formation of Jupiter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

GPM IMERG V07B and V06B: Evaluation Using Ground-Based Radar Observations and Application in Global Mesoscale Convective System Tracking

This study evaluates the latest Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07B) against its predecessor V06B, for studying mesoscale convective systems (MCSs). Both versions are compared using ground-based radar and rain gauge data from five meteorologically diverse regions: the contiguous United States (including eastern coastlines), Amazon rainforest, central Argentina mountains, equatorial Indian Ocean, and northern Australia across multiple temporal (0.5–6 hours) and spatial scales (0.1°–0.25°). An updated global MCS tracking dataset is developed by integrating satellite-observed infrared brightness temperature with IMERG V07B. Comparation of IMERG against radar observations reveals that IMERG demonstrates better performance in capturing the probability distribution and quantitative contributions of rainfall (from no-rain to intense-rain conditions) over tropical oceans than over land, with marked improvements in IMERG V07B for heavy-to-intense rain (> 10 mm h-1). Over land, systematic biases persist: IMERG tends to overestimate light-to-moderate rain (1–10 mm h-1) while underestimating heavy-to-intense rain. Additionally, aggregating IMERG to coarser resolutions (3-hourly or 0.25°) improves consistency with radar observations, outperforming the 1-hourly/0.1° resolution. The new IMERG V07B-based global MCS dataset exhibits consistent statistical characteristics with the V06B-based dataset, despite lower mean rain rates and reduced heavy precipitation contributions. These findings offer valuable insights for utilizing IMERG V07B in global precipitation studies, MCS characterization, and model evaluation.

Zhang, Sihan↗
DOE OSTI2018

Performance study of atomic tally methods for GPU-accelerated Monte Carlo dose calculation - 25352

Over the past several years, the graphics processing unit (GPU) technology has rapidly gained ground in scientific computing due to its outstanding performance and programmability. GPU implementation of Monte Carlo radiation transport for dose calculations has been reported by many investigators. The majority of these studies adopted single-precision floating point format because of the higher peak floating point operations per second (FLOPS) the GPUs can deliver than double-precision. It has been known that calculation using single-precision is more prone to numerical round-off errors, especially when a single tally data is accumulated 'atomically' and repeatedly by thousands of GPU threads. To mitigate this problem, the least intrusive solution in theory is to replace the single-precision atomic-add tally function with a double-precision version. However, the complexity lies in the fact that some GPUs (Nvidia GPUs prior to the Pascal generation; all current AMD GPUs) do not readily offer such double-precision function at hardware level, and that software emulation is too slow to use if not optimized properly. This paper discusses several atomic-add tally methods with reduced numerical errors used throughout ARCHER development. The original software-based compare-and-swap method (CAS) was shown to be inefficient due to high intra-warp thread contention, whereas the improved software-based warp-aggregated method (WAG) and Kahan summation method (KAS) eliminated the thread contention and performed very well on Kepler and Maxwell GPUs, being more than 13 times faster than CAS in our tests. The hardware-based (HB) double-precision atomic-add feature available on Pascal and Volta GPUs exceeded software emulation and offered the best performance universally, so did WIB, a combination of WAG and HB methods. It was also shown that in a single-precision dose engine, KAS managed to maintain high reliability when the single-precision atomic-add tally underestimated the dose by 25%. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Review of the Current State of Knowledge on the Effects of Radiation on Concrete

A review of the current state of knowledge on the effects of radiation on concrete in nuclear applications is presented. Emphasis is placed on the effects of radiation damage as reflected by changes in engineering properties of concrete in the evaluation of the long-term operation (LTO) and for Plant Life or Aging Management of nuclear power plants (NPPs) in Japan, Spain, and the United States. National issues and concerns are described for Japan and the US followed by a discussion of the fundamental understanding of the effects radiation on concrete. Specifically, the effects of temperature, moisture content, and irradiation on ordinary Portland cement paste and the role of temperature and neutron energy spectra on radiation induced volumetric expansion (RIVE) of aggregate-forming minerals are described. This is followed by a discussion of the bounding conditions for extended operation, the significance of accelerated irradiation conditions, the role of temperature, creep, and how these issues are being incorporated into numerical and meso-scale models. From these insights on radiation damage, analyses of these effects on concrete structures are reviewed and the current status of work in Japan and the US are described. Also discussed is the recent formation of a new international scientific and technical organization, the International Committee on Irradiated Concrete (ICIC), to provide a forum for timely information exchanges among organizations pursuing the identification, quantification, and modeling of the effects of radiation on concrete in commercial nuclear applications. Lastly, the paper concludes with a discussion of research gaps including: 1) interpreting test-reactor data, 2) evaluating service-irradiated concrete for aging management and to inform radiation damage models with the Zorita NPP (Spain) serving as the first comprehensive test case, 3) irradiated-assisted alkali-silica reactions, and 4) RIVE under constrained conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Radiation-Induced Changes in Single Crystal Calcite and Dolomite: Mineral Analogues of Light Water Reactor, Nuclear Power Plant Concrete Aggregates

Two analogues of aggregates (calcite and dolomite) found in nuclear power plant (NPP) concrete have been neutron irradiated to fluences up to 2 × 10 20 n/cm 2 at 52 °C and 4 × 10 19 n/cm 2 at 95 °C (E > 0.1 MeV). X-ray diffraction studies showed that these aging conditions affected crystallography of both calcite and dolomite, with both showing a growth in their unit cells compared to that of the unirradiated samples. Only dolomite samples showed a continuous increase of its lattice parameters with the increase in irradiation. In calcites, the lattice growth with irradiation dissipated after a fluence of 5 × 10 18 n/cm 2 . Radiation-induced disordering of the crystal structure was observed in both materials, while a healing effect of irradiation temperature was mainly observed in calcites. Dislocation densities calculated by using XRD data also supported these observations. Insights made into the unit cells of both minerals by using Fourier synthesis showed that the Mg sites are more prone to the neutron irradiation than the Ca sites, resulting in larger radiation effects and higher disruption in the crystal structure of dolomite than that of calcite. Furthermore, other than the polycrystalline characteristics observed by using TEM, these minerals did not show complete amorphization or significant structural decomposition at the studied irradiation fluences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Erosional redistribution of topsoil controls soil nitrogen dynamics

In recent years, the role of soil erosion on terrestrial carbon sequestration had been the focus of a growing number of studies. However, relatively little attention has been paid so far to the role of erosion on the lateral distribution of soil nitrogen (N) and the role of geomorphic processes on soil N dynamics. We present primary data on the stock of nitrogen in soil and its rate of erosion at a relatively undisturbed, zero-order watershed in northern California. Erosion transports 0.26–0.47 g N m -2 year -1 from eroding slope positions (Summit and Slope), and about two-thirds of the eroded N enters depositional landform positions (Hollow and Plain). Our results show that depositional-position soil profiles contain up to 3 times more N than soil profiles in the eroding positions. More than 92% of all soil nitrogen was chemically bound to soil minerals in all the landform positions, compared to 2–4% each found in the free light and occluded light fractions. Nitrogen associated with the free light fraction in topsoil is particularly susceptible to loss by soil erosion. By comparison, soil N associated with the aggregate-protected occluded light fractions and the mineral-associated dense fractions is likely to be protected from gaseous and dissolved losses. On average, we found that soil N has mean residence time of 694 years in eroding landform positions, compared to 2951 years in depositional landform positions. Our results also show that microbial processing of organic matter exerts strong control on overall soil N storage and N stabilized through sorptive interactions with soil minerals only in poorly drained depositional landform positions. Finally, soil erosion exerts important control on stock, distribution, and long-term fate of soil N in dynamic landscapes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Structural differences between single crystal and polycrystalline UBe 13

Here, we report on observations of structural and chemical differences between samples of UBe 13 that were synthesised using two different methods. Unexplained discrepancies in properties between samples with differing synthesis had previously been found in this heavy fermion superconductor. A polycrystalline UBe 13 sample was made by arc-melting the constituents. Single crystals were grown using an aluminium flux and had a consistently slightly larger lattice parameter than the polycrystals, which merited further study. Neutron diffraction data were collected at the Lujan Center at LANSCE on the HIPPO diffractometer. Aluminium was detected by inductively coupled plasma mass spectrometry (ICP-MS) in the flux-grown single crystal (0.803 wt%), and small amounts (~0.2 wt%) of thorium were detected in the UBe 13 polycrystalline sample. In order to probe the implications of the presence of Al, calculations by spin-polarised DFT-GGA+U show that the incorporation of Al onto the 96i site (the lowest symmetry site in the structure) is energetically more favourable than on other sites. In general, the trends calculated by DFT for bond lengths and lattice parameter increases are consistent with bond lengths experimentally observed by neutron diffraction, but specific percentage changes with aluminium incorporation may be obscured by the unexpected thorium in the polycrystalline sample. The aggregate of our initial observations suggests that incorporation of aluminium from the flux into single crystal UBe 13 is significant.

36 MATERIALS SCIENCE↗