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At least 1,711 records · Page 95

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DOE OSTI2024

Enhancing Mechanical Properties of Carbon–Silicon Steel through Two–Stage Quenching and Partitioning with Bainitic Transformation: Ultimate Tensile Strength of 1875 MPa and Total Elongation of 8.03%

To achieve the desired microstructural properties, the ongoing development and innovation in new structural steels require novel thermal processing. This study aims to improve the mechanical properties of a commercial spring carbon–silicon steel by tailoring its microstructure through a process involving quenching and partitioning (Q&P) followed by bainitic transformation. A two–stage Q&P process is proposed to generate a nanoscale dispersion of stable retained austenite and carbides within the tempered martensite and bainite microstructure. The resulting tensile properties demonstrate a yield strength of 1280 MPa, an ultimate tensile strength of 1875 MPa, and a total elongation of 8.03%. These values surpass those of conventional spring 9254 steel, highlighting the effectiveness of the thermal treatment design. Microstructure analysis reveals the presence of tempered martensite, bainite sheaves, nanoscale carbides, and aggregates of retained austenite. Moreover, the resulting body–centered cubic matrix exhibits minimal lattice tetragonality of ≈1.0051, coupled with stable retained austenite featuring a carbon concentration of ≈3.42 ± 0.5 wt%, resulting in outstanding strength–ductility properties. In conclusion, these findings indicate that the proposed two–stage Q&P process, followed by bainitic transformation, significantly enhances the mechanical properties of carbon–silicon steels, making it a promising candidate for high–performance spring applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Recycling Perspectives of Electric Arc Furnace Slag in the United States: A Review

This article presents a comprehensive review of electric arc furnace (EAF) slag recycling in the United States, examining its classification and the associated challenges and opportunities of its industrial use. The study affirms EAF slag's nonhazardous status. Here, the main challenges identified in EAF slag applications include substantial variations in composition and volume instability during/after hydration. Analysis of the U.S. recycling practices reveals that EAF slag is predominantly reused, with minimal landfill disposal. However, its prevalent use as a low value-added aggregate in construction applications underscores the industry's ongoing challenge to get additional value from EAF slag recycling. Despite these challenges, the study highlights a great potential for increased value extraction from EAF slag recycling. Beyond conventional applications as a clinker material for the cement industry, the review explores modern technologies for steelmaking slag recycling, revealing options for recovering valuable metals such as Cr, V, Mo, and Fe through methods such as leaching, reduction, and oxidation.

42 ENGINEERING↗

DOE OSTI2024

Synthesis of Red, Green, and Blue Carbon Quantum Dots and Construction of Multicolor Cellulose-Based Light-Emitting Diodes

Light-emitting diodes (LEDs) are widely used in lighting and display applications. Carbon quantum dots (CQDs), which have high biocompatibility, high resistance to photobleaching, and full-spectrum luminescence, have inherent advantages as fluorescent materials for LED devices. Herein, multicolor CQDs are prepared by a new reagent engineering strategy due to the difference of effective conjugate length and the surface electron-withdrawing groups of CQDs. White CQDs are realized by mixing blue, green, and red CQDs proportionally. Then, the aggregation-caused quenching phenomenon of CQDs is suppressed through the hydrogen-bonding network of cellulose nanofibrils (CNFs). Multicolor fluorescent films are prepared from CQDs and CNFs by simple mixing and casting methods. Finally, thin-film encapsulation based on the photosensitive resin ABPE-10 coating can be realized and rapidly assembles into fluorescent films with different light-emitting colors into LED devices, leading to have superior thermal performance compared with conventional LEDs. White LEDs have excellent white-light illumination performance, with Commission Internationale de L’Eclairage color coordinates of (0.33, 0.37), a correlated color temperature of 5688 K, and a color rendering index of 86. This strategy provides a convenient and scalable pathway for low-cost, environmentally friendly, and high-performance CQDs-based LEDs.

42 ENGINEERING↗

DOE OSTI2022

Limitations of reanalysis data for wind power applications

Wind energy resource estimates commonly depend on simulated wind speed profiles generated by reanalysis or weather models due to the lack of long time series measurements with sufficient coverage at relevant heights (roughly 90 m above ground). However, modeled data, including reanalyses, can be noisy and display a wide range of biases and errors, variously attributed to terrain effects, poor coverage of assimilated inputs, and model resolution. Wind generation records, if available at high temporal and geographical resolution, can provide a proxy for wind measurements and allow for evaluation of reanalyses and weather model wind time series. We use a 7-year-long data set of hourly, plant-level generation records from over 100 wind plants across Texas to evaluate two commonly used reanalysis data sets (MERRA2 and ERA5). Additionally, we use 1-year of records (2019) to evaluate an operational, high-resolution regional weather modeling product (HRRR v3). We find that across the region, and across all modeling products, the modeled representation of wind generation (i.e., wind speeds at hub heights passed through a power curve) has relatively small mean errors when aggregated daily, but that accuracy and hourly correlation have a strong diurnal sensitivity. Accuracy and correlation systematically decline through the evening and markedly improve after sunrise. These diurnal patterns persist even in the highest resolution model tested (HRRR v3). We hypothesize the nighttime decline in accuracy is mostly due to poorly represented boundary layer conditions, perhaps related to model representation of stability, while other uncertainties (such as wake effects) play a secondary role.

17 WIND ENERGY↗

DOE OSTI2023

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗

DOE OSTI2024

A practical approach to using the Genomic Standards Consortium MIxS reporting standard for comparative genomics and metagenomics

Comparative analysis of (meta)genomes necessitates aggregation, integration, and synthesis of well-annotated data using standards. The Genomic Standards Consortium (GSC) collaborates with the research community to develop and maintain the Minimal Information about any (x) Sequence (MIxS) reporting standard for genomic data. To facilitate use of the GSC’s MIxS reporting standard, we provide a description of the structure and terminology, how to navigate ontologies for required terms in MIxS, and demonstrate practical usage through a soil metagenome example.

standards, metadata, genome, metagenome, schema, v↗

DOE OSTI2020

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗

DOE OSTI2022

Proximity Portability and in Transit , M-to-N Data Partitioning and Movement in SENSEI [Book Chapter]

In high-performance parallel in situ processing, the term in transit processing refers to those configurations where data must move from a producer to a consumer that runs on separate resources. In the context of parallel and distributed computing on an HPC platform one of the central challenges is to determine a mapping of data from producer ranks to consumer ranks. This problem is complicated by the heterogeneity that arises in producer-consumer pairs, such as when producer and consumer codes have different levels of concurrency, different scaling characteristics, or different data models. The resulting mapping and movement of data from M producer to N consumer ranks can have a significant impact on aggregate application performance, particularly when the data consumer requires only a subset of the overall data for its task. This chapter focuses on the design considerations that underlie SENSEI’s implementation to this challenging problem. These design considerations extend the core SENSEI architecture and include ideas like the need to accommodate flexibility in the choice of different partitioning methods, the ability for a data consumer to request and receive only the subset of data needed for its particular operation, and the ability to leverage any of several different data transport tools. The idea of proximity portability, being able to use different data transport methods as part of an in transit workflow, is illustrated through the use of three different transport layers where switching from one transport tool to another is accomplished with only a configuration file change. Here, the chapter also includes a performance analysis summary showing the performance gains that are possible in terms of multiple metrics, such as memory footprint, time to solution, and amount of data moved, when using optimized partitioners in an in transit setting, gains that are made possible by the implementation shaped by specific design considerations.

Bethel, E. Wes↗

DOE OSTI2023

U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies

The COVID-19 pandemic highlights the importance of improving building indoor air quality to reduce occupants' chances of contracting airborne illness. The ASHRAE Epidemic Task Force (ASHRAE-ETF) released several COVID-19 mitigation strategies at the onset of the pandemic. This study explores four of those recommendations for reducing transmission of COVID-19 inside buildings: (1) 100% outdoor air ventilation, (2) MERV-13 or better filters, (3) demand control ventilation removal, and (4) HVAC flushing mode. These recommendations were simulated and assessed using ComStock, a model of the U.S. commercial building stock. The study showed the 100% outdoor air ventilation recommendation had the largest impact on energy consumption, noncoincident peak demand, and thermostat violations. Removing demand control ventilation had the smallest national aggregate impact, installing MERV-13 filters led to slight increases in energy use and peak demand, and HVAC outdoor air flushing led to modest energy use and peak demand increases.

building energy modelling↗

DOE OSTI2021

Correlated gravitational wave and microlensing signals of macroscopic dark matter

Fermion dark matter particles can aggregate to form extended dark matter structures via a first-order phase transition in which the particles get trapped in the false vacuum. We study Fermi balls created in a phase transition induced by a generic quartic thermal effective potential. We show that for Fermi balls of mass, 3 x 10 -12 M ⊙ ≲ M FB ≲ 10 -5 M ⊙ , correlated observations of gravitational waves produced during the phase transition (at SKA/THEIA/μAres), and gravitational microlensing caused by Fermi balls (at Subaru-HSC), can be made.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Quantitation of amiodarone and N-desethylamiodarone in single HepG2 cells by single-cell printing-liquid vortex capture-mass spectrometry

Quantitative measure of a drug and its associated metabolite(s) with single-cell resolution is often limited by sampling throughput or other compromises that limit broad use. Here, we demonstrate the use of single-cell printing-liquid vortex capture-mass spectrometry (SCP-LVC-MS) to quantitatively measure the intracellular concentrations of amiodarone (AMIO) and its metabolite, N-desethylamiodarone (NDEA), from thousands of single cells across several AMIO incubation concentrations ranging from 0 to 10 μM. Concentrations obtained by SCP-LVC-MS were validated through comparison with average assays and traditional measurement of cells in bulk. Average of SCP-LVC-MS measurements and aggregate vial collection assay the concentrations differed by < 5%. Both AMIO and NDEA had clear log-normal distributions with similar standard deviation of concentrations in the cell population. The mean of both AMIO and NDEA intracellular concentrations were positively correlated with AMIO incubation concentration, increasing from 0.026 to 0.520 and 0.0055 to 0.048 mM for AMIO and NDEA, respectively. The standard deviation of AMIO and NDEA log-normal distribution fits were relatively similar in value across incubation concentrations, 0.15–0.19 log 10 (mM), and exhibited a linear trend with respect to each other. The single cell-resolved conversion ratio of AMIO to NDEA increased with decreasing incubation concentration, 7 ± 2%, 18 ± 3%, and 20 ± 7% for 10.0, 1.0, and 0.1 μM AMIO incubation concentrations, respectively. Finally, association with simultaneously measured lipids had several ions with statistically significant difference in intensity but no clear correlations with AMIO intracellular content was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Lattice dynamics, sound velocities, and atomic environments of szomolnokite at high pressure

Complex mixtures of sulfates, silicates, and ice have been observed in a variety of planetary environments on Earth, Mars and the icy satellites of the solar system. Characterizing the properties of the corresponding compositional endmembers is important for understanding the interiors of a range of planetary bodies in which these phases are observed. To measure the electronic and vibrational properties of the pure ferrous iron endmember of the kieserite group, szomolnokite, (FeSO 4 ∙H 2 O), we have performed synchrotron 57 Fe nuclear resonant inelastic and forward scattering experiments in the diamond-anvil cell up to 14.5 GPa. This pressure range covers depths within Earth’s interior relevant to sulfur cycling in subduction zones and the range of pressures expected within icy satellite interiors. We find evidence of crystal lattice softening, changes in elastic properties, and changes in the electric field gradients of iron atoms associated with two structural transitions occurring within the experimental pressure range. Here we apply these findings to icy satellite interiors, including discussion of elastic properties, modeling of ice-sulfate aggregates, and implications for tidal observations.

58 GEOSCIENCES↗

DOE OSTI2022

Assessing the large-scale drivers of precipitation in the northeastern United States via linear orthogonal decomposition

This study examines the linear orthogonal modes associated with monthly precipitation in the northeastern United States, from CESM1 LENS (35 ensemble members, 1979–2005) and two reanalysis datasets (ERA5, 1950–2018 and NOAA-CIRES-DOE 20CRv3, 1950–2015). Calendar months are aggregated together, and any linear trends in data are removed. Using region-averaged precipitation anomaly time series and monthly anomalies for several global 2D atmospheric fields, a linear orthogonal decomposition method is implemented to iteratively extract time series (based on field and geographic location) of absolute maximum correlation. Linear modes associated with this method are then projected onto the full set of 2D fields to provide physical insight into the mechanisms involved in generating precipitation. In this region, the first mode is associated with vapor transport from the Atlantic seaboard, the second mode is characterized by westward vapor transport associated with extratropical cyclones, and the third mode captures vapor transport from the Gulf of Mexico during the fall and winter. However, the third mode is less robust in the spring and summer. Results are generally consistent across the datasets, and applying multiple linear regression with the linear modes to predict the precipitation anomalies produces R-squared values of around 0.54–0.65 for CESM1 LENS, and around 0.58–0.88 for reanalysis, with the lowest values generally in the spring and late summer. The influence of low-frequency climate variability on the modes is considered for CESM1 LENS, and the modes in late winter can be predicted with some success via a combination of several, prominent large-scale teleconnection patterns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Association of small vessel disease with tau pathology

Emerging evidence suggests that small vessel disease (SVD) is a risk factor for clinical dementia and may contribute to AD neuropathological changes. Watershed brain regions are located at the most distal areas between arterial territories, making them vulnerable to SVD-related changes. We examined the association of pathologic markers of SVD, specifically arteriolosclerosis in watershed brain regions, with AD pathologic changes. Participants (N= 982; mean age-at-death = 90; 69% women) were enrolled as part of one of two cohort studies of aging and dementia. At autopsy, neuropathological evaluation included semi-quantitative grading of arteriolosclerosis pathology from 2 cortical watershed regions: the anterior watershed (AWS) and posterior watershed (PWS), densities for cortical β-amyloid and tau-tangle pathology, and other common age-related pathologies. Linear regression models examined the association of watershed arteriolosclerosis pathology with β-amyloid and tau-tangle burden. In follow-up analyses, available ex-vivo MRI and proteomics data in a subset of decedents were leveraged to examine the association of whole brain measure of WMH, as a presumed MRI marker of SVD, with β-amyloid and tau-tangle burden, as well as to examine the association of watershed arteriolosclerosis with proteomic tau. Watershed arteriolosclerosis was common, with 45% of older persons having moderate-to-severe arteriolosclerosis pathology in the AWS region, and 35% in the PWS. In fully adjusted models that controlled for demographics and common age-related pathologies, an increase in severity of PWS arteriolosclerosis was associated with a higher burden of tau-tangle burden, specifically neocortical tau burden, but not with β-amyloid. AWS arteriolosclerosis was not associated with β-amyloid or tau pathology. Ex-vivo WMH was associated with greater tau-tangle pathology burden but not β-amyloid. Furthermore, PWS arteriolosclerosis was associated with higher abundance of tau phosphopeptides, that promote formation of tau aggregates. These data provide compelling evidence that SVD, specifically posterior watershed arteriolosclerosis pathology, is linked with tau pathological changes in the aging brain.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Evidence linking calcium to increased organo-mineral association in soils

Geochemical indicators are emerging as important predictors of soil organic carbon (SOC) dynamics, but evidence concerning the role of calcium (Ca) is scarce. This study investigates the role of Ca prevalence in SOC accumulation by comparing otherwise similar sites with (CaCO 3 -bearing) or without carbonates (CaCO 3 -free). We measured the SOC content and indicators of organic matter quality (C stable isotope composition, expressed as δ 13 C values, and thermal stability) in bulk soil samples. We then used sequential sonication and density fractionation (DF) to separate two occluded pools from free and mineral-associated SOC. The SOC content, mass, and δ 13 C values were determined in all the fractions. X-ray photoelectron spectroscopy was used to investigate the surface chemistry of selected fractions. Our hypothesis was that occlusion would be more prevalent at the CaCO 3 -bearing site due to the influence of Ca on aggregation, inhibiting oxidative transformation, and preserving lower δ 13 C values. Bulk SOC content was twice as high in the CaCO 3 -bearing profiles, which also had lower bulk δ 13 C values, and more occluded SOC. Yet, contrary to our hypothesis, occlusion only accounted for a small proportion of total SOC (< 10%). Instead, it was the heavy fraction (HF), containing mineral-associated organic C, which accounted for the majority of total SOC and for the lower bulk δ 13 C values. Overall, an increased Ca prevalence was associated with a near-doubling of mineral-associated SOC content. Future investigations should now aim to isolate Ca-mediated complexation processes that increase organo-mineral association and preserve organic matter with lower δ 13 C values.

58 GEOSCIENCES↗

DOE OSTI2021

Quantifying microbial control of soil organic matter dynamics at macrosystem scales

Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Microscale mechanical modeling of deformable geomaterials with dynamic contacts based on the numerical manifold method

Abstract Micromechanical modeling of geomaterials is challenging because of the complex geometry of discontinuities and potentially large number of deformable material bodies that contact each other dynamically. In this study, we have developed a numerical approach for micromechanical analysis of deformable geomaterials with dynamic contacts. In our approach, we detect contacts among multiple blocks with arbitrary shapes, enforce different contact constraints for three different contact states of separated, bonded, and sliding, and iterate within each time step to ensure convergence of contact states. With these features, we are able to simulate the dynamic contact evolution at the microscale for realistic geomaterials having arbitrary shapes of grains and interfaces. We demonstrate the capability with several examples, including a rough fracture with different geometric surface asperity characteristics, settling of clay aggregates, compaction of a loosely packed sand, and failure of an intact marble sample. With our model, we are able to accurately analyze (1) large displacements and/or deformation, (2) the process of high stress accumulated at contact areas, (3) the failure of a mineral cemented rock samples under high stress, and (4) post-failure fragmentation. The analysis highlights the importance of accurately capturing (1) the sequential evolution of geomaterials responding to stress as motion, deformation, and high stress; (2) large geometric features outside the norms (such as large asperities and sharp corners) as such features can dominate the micromechanical behavior; and (3) different mechanical behavior between loosely packed and tightly packed granular systems.

58 GEOSCIENCES↗

DOE OSTI2020

Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗