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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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At least 109 records · Page 6

Rock weathering controls the potential for soil carbon storage at a continental scale

Abstract As rock-derived primary minerals weather to form soil, they create reactive, poorly crystalline minerals that bind and store organic carbon. By implication, the abundance of primary minerals in soil might influence the abundance of poorly crystalline minerals, and hence soil organic carbon storage. However, the link between primary mineral weathering, poorly crystalline minerals, and soil carbon has not been fully tested, particularly at large spatial scales. To close this knowledge gap, we designed a model that links primary mineral weathering rates to the geographic distribution of poorly crystalline minerals across the USA, and then used this model to evaluate the effect of rock weathering on soil organic carbon. We found that poorly crystalline minerals are most abundant and most strongly correlated with organic carbon in geographically limited zones that sustain enhanced weathering rates, where humid climate and abundant primary minerals co-occur. This finding confirms that rock weathering alters soil mineralogy to enhance soil organic carbon storage at continental scales, but also indicates that the influence of active weathering on soil carbon storage is limited by low weathering rates across vast areas.

54 ENVIRONMENTAL SCIENCES↗

Reduced accrual of mineral-associated organic matter after two years of enhanced rock weathering in cropland soils, though no net losses of soil organic carbon

Abstract Enhanced rock weathering (ERW), the application of crushed silicate rock to soil, can remove atmospheric carbon dioxide by converting it to (bi) carbonate ions or solid carbonate minerals. However, few studies have empirically evaluated ERW in field settings. A critical question remains as to whether additions of crushed rock might positively or negatively affect soil organic matter (SOM)—Earth’s largest terrestrial organic carbon (C) pool and a massive reservoir of organic nitrogen (N). Here, in three irrigated cropland field trials in California, USA, we investigated the effect of crushed meta-basalt rock additions on different pools of soil organic carbon and nitrogen (i.e., mineral-associated organic matter, MAOM, and particulate organic matter, POM), active microbial biomass, and microbial community composition. After 2 years of crushed rock additions, MAOM stocks were lower in the upper surface soil (0–10 cm) of plots with crushed rock compared to unamended control plots. At the 2 sites where baseline pre-treatment data were available, neither total SOC nor SON decreased over the 2 years of study in plots with crushed rock or unamended control plots. However, the accrual rate of MAOM-C and MAOM-N at 0–10 cm was lower in plots with crushed rock vs. unamended controls. Before ERW is deployed at large scales, our results suggest that field trials should assess the effects of crushed rock on SOM pools, especially over multi-year time scales and in different environmental contexts, to accurately assess changes in net C and understand the mechanisms driving interactions between ERW and SOM cycling.

58 GEOSCIENCES↗

Manganese exposure from spring and well waters in the Shenandoah Valley: interplay of aquifer lithology, soil composition, and redox conditions

Manganese (Mn) is of particular concern in groundwater, as low-level chronic exposure to aqueous Mn concentrations in drinking water can result in a variety of health and neurodevelopmental effects. Much of the global population relies on drinking water sourced from karst aquifers. Thus, we seek to assess the relative risk of Mn contamination in karst by investigating the Shenandoah Valley, VA region, as it is underlain by both karst and non-karst aquifers and much of the population relies on water wells and spring water. Water and soil samples were collected throughout the Shenandoah Valley, to supplement pre-existing well water and spring data from the National Water Information System and the Virginia Household Water Quality Program, totaling 1815 wells and 119 springs. Soils were analyzed using X-ray fluorescence and Mn K-Edge X-ray absorption near-edge structure spectroscopy. Factors such as soil type, soil geochemistry, and aquifer lithology were linked with each location to determine if correlations exist with aqueous Mn concentrations. Analyzing the distribution of Mn in drinking water sources suggests that water wells and springs within karst aquifers are preferable with respect to chronic Mn exposure, with < 4.9% of wells and springs in dolostone and limestone aquifers exceeding 100 ppb Mn, while sandstone and shale aquifers have a heightened risk, with > 20% of wells exceeding 100 ppb Mn. The geochemistry of associated soils and spatial relationships to various hydrologic and geologic features indicates that water interactions with aquifer lithology and soils contribute to aqueous Mn concentrations. Relationships between aqueous Mn in spring waters and Mn in soils indicate that increasing aqueous Mn is correlated with decreasing soil Mn(IV). These results point to redox conditions exerting a dominant control on Mn in this region.

54 ENVIRONMENTAL SCIENCES↗

Two-Stage Cryogenic HEMT-Based Amplifier for Low-Temperature Detectors

To search for dark matter candidates with masses below $\mathcal{O}$ (MeV), the SPLENDOR (Search for Particles of Light dark mattEr with Narrow-gap semiconDuctORs) experiment is developing novel narrow-bandgap semiconductors with electronic bandgaps on the order of 1–100 meV. In order to detect the charge signal produced by scattering or absorption events, SPLENDOR has designed a two-stage cryogenic HEMT-based amplifier with an estimated charge resolution approaching the single-electron level. A low-capacitance (~ 1.6 pF) HEMT is used as a buffer stage at T = 10 mK to mitigate effects of stray capacitance at the input. The buffered signal is then amplified by a higher-capacitance (~ 200 pF) HEMT amplifier stage at T = 4 K. Importantly, the design of this amplifier makes it usable with any insulating material—allowing for rapid prototyping of a variety of novel detector materials. Here, we present the two-stage cryogenic amplifier design, preliminary voltage noise performance, and estimated charge resolution of 7.2 electrons.

47 OTHER INSTRUMENTATION↗

Diamond and SiC Detectors for Rare Event Searches

In recent years, there has been increasing interest in developing detectors which are sensitive to sub-GeV dark matter and low-energy events from coherent neutrino scattering. Due to carbon’s light atomic weight and its tendency to form crystals with high-energy, long-lived phonon modes, carbon-based crystals (including diamond and silicon carbide (SiC)) present themselves as natural target materials for scattering-based searches in this regime. Here, we present our preliminary results in adapting our TES-based detectors to these substrates, specifically 4-H SiC and polycrystalline diamond. We focus on our fabrication efforts, specifically tuning the transition temperature (T C ) of tungsten films sputtered on these materials, as well as our advancement toward fabricating and testing devices on these substrates.

47 OTHER INSTRUMENTATION↗

Evaluation of dried blood spot sampling for verification of exposure to chemical threat agents

Abstract Purpose Exposure to chemical threat agents (CTAs), including nerve agents, the vesicating agent sulfur mustard, and opioids, remains a significant threat to warfighter and civilian populations. Definitive analytical methods to verify exposure to CTAs require shipping refrigerated or frozen biomedical samples to reference laboratories for analysis. Logistical and financial burdens arise as the transport of biomedical samples is subject to strict restrictions and complex packaging, which, if done incorrectly, can lead to sample deterioration. The use of dried blood spot (DBS) sampling could provide operational improvements for collecting, storing, and shipping important forensic samples. Therefore, this effort focuses on developing DBS techniques with Mitra® 30-µL volumetric absorptive microsampling (VAMS®) devices for use in CTA exposure verification. Methods VAMS® devices were loaded and dried with human whole blood that was exposed to the metabolites pinacolyl methylphosphonic acid (PMPA), ethyl methylphosphonic acid (EMPA), 1,1’sulfonylbis[2-(methylsulfinyl)ethane] (SBMSE), norfentanyl, norcarfentanil, norsufentanil, and norlofentanil. Following extraction from the VAMS® devices, metabolites were detected using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The methods were validated for performance by assessing sensitivity, precision, accuracy, and recovery. Results These methods were sensitive to 1 ng/mL for SBMSE, 0.5 ng/mL for PMPA, EMPA, and norfentanyl; 0.1 ng/mL for norlofentanil, and 0.05 ng/mL for norsufentanil and norcarfentanil. All methods met acceptable precision and accuracy criteria with favorable recovery. Conclusions These results demonstrated the utility of VAMS® in stabilizing human whole blood and show promise as an improved collection method for verification of exposure to various CTAs.

Toxicology↗

A Technique for the Quantitative Characterization of Weld Microstructure and Application to Mo Welds

The choice of weld parameters determines the size, shape, and curvature of grains in the fusion zone (FZ) and heat-affected zone (HAZ) of welds while the mechanical properties of the welds are correlated to this microstructure. Here, a new technique to quantitatively evaluate these microstructural characteristics in both zones of welds has been applied to molybdenum gas tungsten arc welds fabricated using different weld parameters. Trends in microstructural characteristics in the FZ and HAZ were evaluated and correlated with changes to heat input, weld speed, and weld technique. The use of this approach showed that a 20 pct decrease in heat input caused a 20 pct decrease in the number of FZ grains with aspect ratios ≥ 4. The orientations of the FZ grain segments as a function of distance from the FZ centerline were significantly affected by the weld speed and its effect on weld pool shape. A 50 pct increase in weld speed caused a 20 pct decrease in grain segments orientated 60 to 90 deg from the normal to the direction of welding. This technique also captured differences in grain sizes and grain size anisotropy in the FZ between welds made with a constant current, pulsed current, and use of a 4-pole-magnetic oscillator.

36 MATERIALS SCIENCE↗

Uncertainty Quantification in Atomistic Modeling of Metals and Its Effect on Mesoscale and Continuum Modeling: A Review

The design of next-generation alloys through the integrated computational materials engineering (ICME) approach relies on multiscale computer simulations to provide thermodynamic properties when experiments are difficult to conduct. Atomistic methods such as density functional theory (DFT) and molecular dynamics (MD) have been successful in predicting properties of never before studied compounds or phases. However, uncertainty quantification (UQ) of DFT and MD results is rarely reported due to computational and UQ methodology challenges. Over the past decade, studies that mitigate this gap have emerged. These advances are reviewed in the context of thermodynamic modeling and information exchange with mesoscale methods such as the phase-field method (PFM) and calculation of phase diagrams (CALPHAD). The importance of UQ is illustrated using properties of metals, with aluminum as an example, and highlighting deterministic, frequentist, and Bayesian methodologies. Finally, challenges facing routine uncertainty quantification and an outlook on addressing them are also presented.

36 MATERIALS SCIENCE↗

Active and passive cooling approaches for a Southern California residential community

This study assesses cooling strategies in a low-income community in Southern California that lacks air conditioning and struggles with heat and air pollution. We used an urban building energy model and an electric distribution system model to evaluate active and passive cooling measures. The most effective space cooling measures were high-performance air-source heat pumps, cool coatings, window films, and harnessing the space cooling effect from heat pump water heaters. The results show that combining heat pump water heaters with window films and cool coatings reduces heat index hazard hours within buildings by 95 % to 99 % but increases total energy costs (equipment costs plus changes in utility bills) by 20 % to 60 % where the higher end includes building electrical upgrades. These measures also led to increased space heater use during colder months to avoid overcooling. Replacing conventional heaters with air source heat pumps eliminated unsafe indoor temperatures and reduced total energy use, but increased cost by 125 % to 150 %. In total, using heat pumps for space and water heating could reduce primary energy use by up to 57 %. The higher cost of active and passive cooling measures can be mitigated by existing and emerging incentive programs, especially those that support heat pumps. Electric distribution upgrades to support community electrification are estimated to increase utility costs by $\$$25 to $\$$40 per ratepayer per year. The results underscore the potential and challenges of adapting building infrastructure in communities at risk from climate and environmental stressors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Correlations between thermal history and keyhole porosity in laser powder bed fusion

Additive manufacturing has the potential to revolutionize the production of metallic components as it yields near net shape parts with complex geometries and minimizes waste. At the present day, additively manufactured components face qualification and certification challenges due to the difficulty in controlling defects. This has driven a significant research effort aimed at better understanding and improving processing controls – yielding a plethora of in-situ measurements aimed at correlating defects with material quality metrics of interest. In this work, we develop machine-learning methods to learn correlations between thermal history and subsurface porosity for a variety of print conditions in laser powder bed fusion. Un-normalized surface temperatures (in the form of black-body radiances) are obtained using high-speed infrared imaging and porosity formation is observed in the sample cross-section through synchrotron x-ray imaging. To demonstrate the predictive power of these features, we present four statistical machine-learning models that correlate temperature histories to subsurface porosity formation in laser fused Ti-6Al4V powder.

36 MATERIALS SCIENCE↗

Utilization of ACE nuclear data file toolkit ACEtk to calculate relative sensitivity coefficients of point-kinetics parameters

Sensitivity and uncertainty methods are quintessential for nuclear criticality safety and experiment design. This type of analysis relies on calculations of sensitivity coefficients; sensitivity coefficients of the effective neutron multiplication factor with respect to some nuclear data are predominantly calculated and used. As a part of the Laboratory Directed Research & Development project EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) at Los Alamos National Laboratory, sensitivity coefficients of many radiation detector measurement responses with respect to nuclear data were investigated. Specifically, this paper outlines a method to calculate point-kinetics parameters relative sensitivity coefficients with respect to nuclear data. Point-kinetics parameters such as the prompt neutron decay constant, effective delayed neutron fraction, and neutron generation time are especially important to experimenters and reactor operators designing systems with dynamic neutron populations. This method couples capabilities of the ACE (A Compact ENDF) nuclear data file toolkit, ACEtk, with the ability to load cross sections into the radiation transport code Monte Carlo N-Particle (MCNP). In conclusion, key aspects of optimizing this method for a particular application and sensitivity profiles of the Jezebel criticality experiment are examined and discussed.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Validating automated resonance evaluation with synthetic data

The integrity and precision of nuclear data are crucial for a broad spectrum of applications, from national security and nuclear reactor design to medical diagnostics, where the associated uncertainties can significantly impact outcomes. A substantial portion of uncertainty in nuclear data originates from the subjective biases in the evaluation process, a crucial phase in the nuclear data production pipeline. Recent advancements indicate that automation of certain routines can mitigate these biases, thereby standardizing the evaluation process and enhancing reproducibility. This research aims to provide a methodology, framework, and metrics for the validation of automated nuclear data evaluation software leveraging high-quality synthetic data that closely mimic real experimental observables. An introduced error metric provides a scale and intuitive measure of the evaluation quality by quantifying the estimate’s accuracy and performance across the specified energy range. Synthetic data provides access to experimental observables and underlying resonance parameters, enabling comparison of different evaluations. The methodology is demonstrated using Ta-181 isotope data in the resolved resonance region. The Automated Resonance Identification Subroutine (ARIS), which operates without prior resonance information, was used to test and showcase the framework’s capabilities utilizing the proposed error metrics. The results demonstrate the effectiveness of the proposed approach and framework for optimizing software parameters and testing hypotheses through “what-if” controlled experiments, such as modifying assumptions about experimental conditions or average resonance parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗