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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fluid inertia controls mineral precipitation and clogging in pore to network-scale flows

Mineral precipitation caused by fluid mixing presents complex control and predictability challenges in a variety of natural and engineering processes, including carbon mineralization, geothermal energy, and microfluidics. Precipitation dynamics, particularly under the influence of fluid flow, remain poorly understood. Combining microfluidic experiments and three-dimensional reactive transport simulations, we demonstrate that fluid inertia controls mineral precipitation and clogging at flow intersections, even in laminar flows. We observe distinct precipitation regimes as a function of Reynolds number (Re). At low Reynolds numbers (Re < 10), precipitates form a thin, dense layer along the mixing interface, which shuts precipitation off, while at high Reynolds numbers (Re > 50), strong three-dimensional flows significantly enhance precipitation over the entire intersection, resulting in rapid clogging. When injection rates from two inlets are uneven, flow symmetry-breaking leads to unexpected flow bifurcation phenomena, which result in enhanced concurrent precipitation in both downstream channels. Finally, we extend our findings to rough channel networks and demonstrate that the identified inertial effects on precipitation at the intersection scale are also present and even more dramatic at the network scale. This study sheds light on the fundamental mechanisms underlying mixing-induced mineral precipitation and provides a framework for designing and optimizing processes involving mineral precipitation.

Science & Technology - Other Topics↗
DOE OSTI2026

Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-June 2024. (DE-SC0021139)

This dataset contains raw data from four tripod stations along an elevation gradient on Snodgrass Mountain in the East River Watershed, CO, USA. Each station contains a datalogger connected to 3 soil Carbon Dioxide CO2 gas probes, 3 soil temperature/moisture sensors and a micrometeorological station. Sensors are scanned every minute, and the 30 minute average is reported. The file snodgrass_soil_ESS.csv contains raw data, a row of column descriptors, and units of measurements. some data processing and QA/QC was done to filter out data from sensors that went bad and extreme outliers. CO2 sensors that went bad were replaced with new sensors as soon as possible. This research was performed to investigate the ecohydrological linkages of belowground carbon processes in the East River watershed forested communities to better understand how these ecosystems will respond to a changing cold-season moisture input. This is the second version of this data set and was modified on 10/01/2024. The primary change in the data was the addition of data from the fall of 2022 to June of 2024. In addition, minor QA/QC was done to filter out data from sensors that went bad and extreme outliers. THe filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. This is now the third version of the data set, and was modified 03/25/2026. The primary change in the data was the addition of data from the June of 2024 to December 2025. Further r QA/QC was done with the new data to filter out bad data from faulty sensors and extreme outliers. The filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. ##This additional data was funded under DE-SC0024218( Responses of Plant and Microbial Respiration Sources to Changing Cold Season Climate Drivers in the East River Watershed)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A solid-state extrusion pathway extensible to upcycling aluminum scrap and end-of-life permanent magnets into ductile Al-6061/SmCo 5 structural magnetic composites

Permanent magnets offer strong potential for multifunctional structural components, but their inherent brittleness limits direct integration. Here, SolidStir® Extrusion (SSE) is used to embed SmCo5 powder into AA6061 in the solid state, and the resulting microstructure, interfacial chemistry, mechanical properties, and magnetic response are systematically characterized. SSE fragments the initial SmCo 5 powder into predominantly fine particles dispersed within an ultrafine Al matrix, with a volume fraction of ∼ 4–6 % in this proof-of-concept study. Interfacial reactions form a continuous Al–Co reaction layer, with local atomic-resolution indexing consistent with Al 13 Co 4 , together with Sm–Si-rich reaction products, while the matrix contains Sm–Co–Si-rich precipitates and Mg 2 Si, producing features from nanometers to micrometers. Compared with an Al extrudate, this architecture increases yield strength by ∼ 42 % and tensile strength by ∼ 31 %, while preserving uniform elongation, and it sustains work hardening in compression from 150 to 400 °C. The composite retained hard-magnetic behavior, with axial magnetization of 12.7 A·m 2 kg −1 at 6 T and intrinsic coercivity of 9.6 kOe. These findings demonstrate that SSE can produce Al-based load-bearing magnetic composites while preserving useful SmCo5 functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Moisture Recycling through Pumping by Mesoscale Convective Systems

Abstract Moisture recycling, the contribution of local evapotranspiration (ET) to precipitation, has been studied using bulk models assuming a well-mixed atmosphere. The latter is inconsistent with a climatologically stratified atmosphere that slants across latitudes. Reconciling the two views requires an understanding of overturning associated with different weather systems. In this study, we aim to better understand moisture recycling associated with mesoscale convective systems (MCSs). Using a convection-permitting WRF simulation equipped with water vapor tracers (WRF-WVT), we tag moisture from terrestrial ET in the U.S. Southern Great Plains during May 2015, when more than 20 MCS events occurred and produced significant precipitation and flooding. Water budget analysis reveals that approximately 76% of terrestrial ET is advected away from the region while the remaining 24% of terrestrial ET is “pumped” upward within the region, accounting for 12% of precipitation. Moisture recycling peaks during early night hours (1800–2400 LT) due to the mixing of the daytime accumulated ET by active convection. By focusing on five “diurnally driven” MCSs with less large-scale circulation influence than other MCSs during the same period, we find an upright pumping of terrestrial ET at the MCS initiation and development stages, which diverges into two branches during the MCS mature and decaying stages. One branch in the upper level advects the ET-sourced moisture downstream, while the other branch in the mid-to-upper level contributes to the trailing precipitation upstream. Overall, our analysis depicts a pumping mechanism associated with MCSs that mixes local ET vertically, highlighting its specific contributions to enhancing convective precipitation processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Areal-Averaged Surface Albedo (ArealAveAlb) Value-Added Product

The surface albedo plays an important role in the Earth's radiation balance. This report provides information on how to estimate areal-averaged surface albedo from ground-based measurements of solar radiation at five wavelengths (415,500,615,675, and 870 nm). The report first explains why this estimation is important and challenging. Then the report defines both the required and complimentary inputs for the corresponding Areal-Averaged Surface Albedo (ArealAveAlb) Value-Added Product (VAP) and highlights the major outputs of this VAP. The following section explains how estimation of the areal-averaged surface albedo at four wavelengths (500,615,675, and 870 nm) can be performed for different surface types, including those partly covered by snow. The final section provides three examples that illustrate the VAP’s performance and emphasizes the benefits of complementary inputs, such as distinct cloud types and precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advancing Organized Convection Representation in the Unified Model: Implementing and Enhancing Multiscale Coherent Structure Parameterization

To address the effect of stratiform latent heating on meso- to large-scale circulations, an enhanced implementation of the Multiscale Coherent Structure Parameterization (MCSP) is developed for the Met Office Unified Model. MCSP represents the top-heavy stratiform latent heating from under-resolved organized convection in general circulation models. We couple the MCSP with a mass-flux convection scheme (CoMorph-A) to improve storm lifecycle continuity. The improved MCSP trigger is specifically designed for mixed-phase deep convective cloud, combined with a background vertical wind shear, both known to be crucial for stratiform development. We also test a cloud top temperature dependent convective-stratiform heating partitioning, in contrast to the earlier fixed partitioning. Assessments from ensemble weather forecasts and decadal simulations demonstrate that MCSP directly reduces cloud deepening and precipitation areas by moderating mesoscale circulations. Indirectly, it amends tropical precipitation biases, notably correcting dry and wet biases over India and the Indian Ocean, respectively. Remarkably, the scheme outperforms a climate model ensemble by improving seasonal precipitation cycle predictions in these regions. The scheme also improves Madden-Julian Oscillation (MJO) spectra, achieving better alignment with observational and reanalysis data by intensifying the simulated MJO over the Indian Ocean during phases 4 to 5. However, the scheme increases precipitation overestimation over the Western Pacific. Shifting from fixed to temperature-dependent convective-stratiform partitioning reduces the Pacific precipitation overestimation and further improves the seasonal cycle in India. Spatially correlated biases highlight the necessity for advances beyond deterministic approaches to align MCSP with environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CROCUS Dual Polarization Ceilometer Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, CROCUS Urban Integrated Field Laboratory (https://crocus-urban.org/). The dual-polarization ceilometer (Vaisala CL61) is an autonomous lidar system operating at 910 nm wavelength, providing valuable measurements for understanding atmospheric boundary layer evolution, air quality, and cloud-aerosol interactions. The CL61 measures the backscattered signal intensity alternating between parallel- and cross-polarization signals. The unique depolarization measurement capability improves discrimination between different particle types, such as liquid droplets, ice crystals, and aerosols. The depolarization is highly dependent on the scatterer shape and orientation (spherical vs non-spherical particles), with the linear depolarization ratio providing a measure of dominant backscatter signal component from atmospheric particles at various heights, essentially allowing discrimination between liquid and solid particles. With its efficient optical system, CL61’s improved signal-to-noise ratio compared to traditional ceilometers allows studying detailed vertical profiles of aerosols and clouds up to 15 km height.Datasets are stored in a netCDF data format, and we we encourage users to make use of the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

EPCAPE-Partitioning Thrust-Los Alamos National Laboratory (EPCAPE-PT-LANL) Field Campaign Report

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on aerosol and cloud properties. As part of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM)’s Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted to complement the science goals of EPCAPE and add additional in-depth measurements of aerosols and clouds at Mt. Soledad. Our campaign focused on measuring the physical, optical, and chemical properties of aerosols, trace gases, and their interactions within marine stratocumulus clouds in La Jolla, California (see Figure 1).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

New insights on the effects of chemistry and temperature on α’ precipitation during aging of FeCrAl alloys

Here, the effect of Al on α' precipitation in FeCrAl alloys was studied through thermal aging of several model binary FeCr and FeCrAl alloys with Cr content of 13 wt.%, 17 wt.%, and 25 wt.% with and without 5.5 wt.% Al. Aging was performed up to 1,000h at varying temperatures from 400-500°C. At 400°C no age hardening was observed due to slow kinetics at this temperature. For both the 17Cr and 25Cr alloys, the addition of Al shows a lowering of the miscibility gap, consistent with other reports in literature. Interestingly, however, for the 25Cr alloys the addition of Al in the FeCrAl ternary alloy accelerated α' precipitation below the miscibility gap. Such enhanced precipitation has also been predicted by our atomistic kinetic Monte Carlo (AKMC) simulations. While previous literature has often focused on Al suppressing α', here we show that while Al can lower the miscibility gap in the Fe-Cr ferritic system thermodynamically, it may also enhance the kinetics of precipitation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Idaho National Laboratory Site Environmental Surveillance Program Report: Second Quarter 2023

This report for the second quarter of 2023 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s onsite, boundary and offsite location environment, April 1 through June 30, 2023. All sample types (media) and the sampling schedule followed during 2023 are listed in Appendix A. This report contains results for the following sample types: (1) Air, including particulate air filters, charcoal cartridges, and atmospheric moisture; (2) Precipitation; (3) Drinking/surface water; (4) Milk; (5) OSLDs; and (6) Large Game Animal Sampling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The effects of environmental conditions on eggshell thickness of two North American secondary cavity-nesting birds

Egg hatchability in birds is a critical component of individual reproductive success and is associated with eggshell integrity. Contaminants, such as DDT, can influence eggshell thickness and are known to cause population declines. Moisture content and temperature can also impact eggshell thickness, but the influence of environmental conditions on the natural variation in eggshell thickness in wild populations is not well understood. Our goal was to investigate the relationship between environmental conditions and eggshell thickness of Western Bluebird (Sialia mexicana) and Ash-throated Flycatcher (Myiarchus cinerascens) eggs from 1997 to 2013 on the Pajarito Plateau in northern New Mexico. We tested whether nesting elevation, temperature, precipitation, and drought conditions influenced eggshell thickness in these two secondary cavity-nesting species, while also looking at eggshell thickness over time. Over the 16 years, nonviable or abandoned eggs were collected, and the analyzed dataset included 330 bluebird eggs and 113 flycatcher eggs. There was a significant increase in eggshell thickness over time for both species. Flycatcher eggshells were correlated with higher temperatures, whereas bluebird eggshells were influenced by an interaction between temperature and drought severity. In drought conditions, bluebird eggshell thickness was positively correlated with temperature, whereas in wet conditions, eggshell thickness was negatively correlated with temperature. Thicker eggshells in drought conditions may be a way of reducing water loss from eggs, which occurs faster at higher temperatures. In the southwestern United States, frequent and severe drought, higher temperatures, and decreases in precipitation are all expected to continue. In conclusion, the structure of eggs will be important to consider regarding how species may or may not adapt to novel conditions or persist in new environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Predicting the Evolution of Shallow Cumulus Clouds With a Lotka‐Volterra Like Model

Abstract In numerical weather prediction and climate models, boundary‐layer clouds are controlled by a wide range of subgrid‐scale processes. However, understanding the nature of these processes and their role in the evolution of the cloud size distribution as a whole has been elusive. To address this issue, we adopt a novel empirical framework from the field of population dynamics to model the evolution of cloud size statistics by using the shallow cumulus properties obtained from a large‐eddy simulation (LES). Our approach involves representing the cloud size distribution and the total cloud area using a revised Lotka‐Volterra model and ridge linear model, respectively. The physical interpretation of the total cloud area and coefficients obtained from the optimization of the models reveals three stages probably interpreted by dominant processes: the formation of new clouds, the growth of single clouds, and a steady state with organized transitions involving the growth and decay of multiple clouds. Furthermore, we showcase the potential of this framework to serve as a component of scale‐aware parameterizations of shallow‐convective clouds in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Microbial community data from throughfall exclusion experiment: Metadata, SI, community composition, LefSe, and FunGuilR data tables from PARCHED Panama tropical forest soils, 2024-2025

Soil contains more carbon (C) than terrestrial vegetation and the atmosphere combined, with some of the largest terrestrial C stocks in tropical rainforests. Soil microbes decompose organic matter, playing a vital role in the storage or loss of soil C. With climate change, drought conditions are predicted to increase in many tropical regions, including both chronic drying and extended drought, potentially influencing these processes. This project explored the effects of chronic and seasonal drying on soil microbial communities across four distinct tropical forests in a long-term drying experiment. We investigated the effects of a chronic drying manipulation on soil microbial community abundance and variation across different forests and seasons. We also compared findings with previously published data from these forests after short-term drying. This project used soils from a long-term drying experiment established in 2018 across four seasonal lowland forests in Panama. Soils were collected from 0 – 10 cm depths during three seasonal periods in control and drying plots in 2024 and 2025 from a total of 32 plots (n = 4 per forest per treatment). The forests varied in baseline rainfall and soil fertility. We calculated alpha and beta diversity indices and compared taxonomic community composition. We found significant biogeographic variation in microbial diversity and taxonomy, with significant differences across the forests and significant effects of the drying treatment. Metadata and sample IDs are within Metadata_16S.csv and Metadata_ITS.csv. Relative abundance tables of every sample at every season are shown in the Excel workbooks 16S Relative Abundance.xlsx and ITS Relative Abundance.xlsx. They are then also shown in CSV files by each taxonomic level. Linear discriminant analysis effect size (LefSe) tables are shown for the full 16S and ITS datasets (n = 96), subsets for every site at every season (n = 8), and then for the forests with each plot merged by season (n = 8). FunGuildR data table of ITS data is uploaded.

Bacteria↗