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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Interaction between the emerging components of online shopping and in-person activities: insights from a behavioral survey

The rise of technological advancements has led to the commonplace practice of online shopping for retail, grocery, and food. However, little research has been conducted on the interplay of these components in burdened communities (BCs) that face issues of marginalization and limited access to digital resources. Here, this study aims to provide a comprehensive understanding of travel behavior changes by analyzing the interconnectedness of the emerging components of online shopping (retail, grocery, and food) and in-person activities in both BCs and non-BCs. A unique household-level database is created by linking the 2021 Puget Sound Household Travel Survey and the US Department of Transportation’s burdened community databases, and a conditional mixed process model is estimated to account for unobserved endogeneity. The findings suggest households living in BCs are less likely to order online retail goods and groceries compared to non-BC households. Additionally, the probability of making more restaurant trips decreases for households living in BCs. The study highlights the digital divide that exists in BCs and the differences in online and in-person shopping activities across socioeconomic levels. Policymakers may address these disparities to promote better access to goods and services for all. Besides, planners may need to improve the travel demand models by accounting for the emerging components of online shopping and the trip frequencies by purpose in BCs.

Digital Divide↗
DOE OSTI2022

Derivation and assessment of regional electricity generation emission factors in the USA

Electricity production is one of the largest sources of environmental emissions - especially greenhouse gases (GHGs) - in the USA. Emission factors (EFs) vary from region to region, which requires the use of spatially relevant EF data for electricity production while performing life cycle assessments (LCAs). Uncertainty information, which is sought by LCA practitioners, is rarely supplied with available life cycle inventories (LCIs). To address these challenges, we present a method for collecting data from different sources for electricity generation and environmental emissions; discuss the challenges involved in agglomerating such data; provide relevant suggestions and solutions to merge the information; and calculate EFs for electricity generation processes from various fuel sources for different spatial regions and spatial resolutions. The EFs from the US 2016 Electricity Life Cycle Inventory (eLCI) are analyzed and explored in this study. We also explore the method of uncertainty information derivation for the EFs. We explore the EFs from different technologies across Emissions & Generation Resource Integrated Database (eGRID) regions in the USA. We find that for certain eGRID regions, the same electricity production technology may have worse emissions. This may be a result of the age of the plants in the region, the quality of fuel used, or other underlying factors. Region-wise life cycle impact assessment (LCIA) ISO 14040 impacts for total generation mix activities provide an overview of the total sustainability profile of electricity production in a particular region, rather than only global warming potential (GWP). We also find that, for different LCIA impacts, several eGRID regions are consistently worse than the US average LCIA impact for every unit of electricity generated. Here this work describes the development of an electricity production LCI at different spatial resolutions by combining and harmonizing information from several databases. The inventory consists of emissions, fuel inputs, and electricity and steam outputs from different electricity production technologies located across various regions of the USA. This LCI for electricity production in the USA will prove to be an enormous resource for all LCA researchers - considering the detailed sources of the information and the breadth of emissions covered by it.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Thermodynamic Modeling of the Al-Ce-Cu-Mg-Si System and Its Application to Aluminum-Cerium Alloy Design

Recently discovered AlCe alloys have shown promise in a number of applications, but the propensity of Ce to react with Al and other alloying elements can complicate the phase equilibria and design approach. To solve this, the CALPHAD method is used to explore an alloy within the quinary Al-Ce-Cu-Mg-Si system by developing a thermodynamic database with self-consistent parameters. The database includes a description of all 10 binary systems and 8 ternary systems consisting of: (i) 6 Al-containing ternaries (Al-Ce-Cu, Al-Ce-Mg, Al-Ce-Si, Al-Cu-Mg, Al-Cu-Si and Al-Mg-Si); and (ii) 2 additional ternaries that include Mg and Si (i.e., Ce-Mg-Si and Cu-Mg-Si). The thermodynamic description for the Al-Ce-Mg and Al-Mg-Si systems were reassessed to ensure consistency with the binary systems and the Ce-Mg-Si system is presented for the first time and compared to theoretical data from DFT (Density Functional Theory). In addition to the ternary interactions, the quaternary compound Al3Cu2Mg9Si7 and solid solution extending from the ternary Al2CuMg phase (Al,Si)2CuMg are incorporated. The CALPHAD method is employed and leveraged through the use of a Materials Design Simulator (MDS) to accelerate the design of novel aluminum-cerium-based alloys. The combination of a CALPHAD-based framework with experimental efforts and industrial insight permits the development of three new Al-Ce alloys: Al-3.5Ce-0.4Mg-7Si (Ce-modified A356), Al-5Ce-1Cu-0.5Mg-10Si and Al-19Ce-0.9Mg-1.1Si.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Interactive Exploration of High-Dimensional Phase Diagrams

High-dimensional thermodynamic phase stability databases are becoming increasingly common due to the convergence of three recent trends: (i) the widespread interest in so-called “high-entropy” alloys, (ii) the availability of high-throughput computational assessments of phase stability in broad composition spaces and (iii) the ongoing development of ever-increasingly broad, multicomponent, multiphase CALPHAD databases. Although automated computational tools can readily process such high-dimensional data, scientists are often unable to visualize the relevant phase relations, an ability that is crucial to gaining an intuitive understanding of the stability constraints governing materials design. The present work addresses this need by providing algorithms that enable the interactive exploration of phase equilibria in high-dimensional spaces. These algorithms concentrate the complex nonlinear nonsmooth optimization needed into a preprocessing step that generates a large number of high-dimensional yet elementary graphical primitives. Furthermore, these primitives can then be cross-sectioned to yield 3-dimensional views in a computationally efficient manner that enables an interactive exploration of high-dimensional spaces. All of these operations are highly parallelizable, thus facilitating scaling of this method to large data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Deficiency of mismatch repair genes is less frequently observed in signet ring cell compared with non-signet ring cell gastric cancer

Signet ring cell (SRC) gastric cancer at advanced stage has poor prognosis. While a recent study reported nearly one-third of SRC cases contain tumors with deficient mismatch repair (MMR) genes, other studies in SRC have been inconclusive. To re-analyze the results, we performed immunohistochemical staining of MLH1, MSH2, MSH6 and PMS2 proteins in 38 SRC gastric tumors compared with 109 non-SRC (NSRC) tumors from 94 patients. In contrast to the previous study, all SRC gastric tumors normally expressed MMR proteins, whereas 22 of 109 of NSRC (20%) showed deficient MMR proteins. To reinforce our results, we referred to the Cancer Genome Atlas (TCGA) genomic database and found that only 6 (6%) of 99 samples with diffuse gastric tumors showed deficient MMR, whereas 64 (21%) of 304 in intestinal gastric tumors showed deficient MMR. Our results as well as the TCGA database indicated that MMR genes are infrequently inactivated in SRC gastric cancer. These findings indicate that SRC patients may not be the best candidates for immuno-oncology therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Population-based assessment of the national comprehensive cancer network recommendations for baseline imaging of hepatocellular carcinoma

This analysis aims to evaluate the performance characteristics of alternative baseline imaging thresholds in a cohort of hepatocellular carcinoma (HCC) patients from the Surveillance, Epidemiology, and End Results (SEER) database. HCC patients within the SEER database (2010–2015) who had complete information on clinical T and N stages as well as complete information on metastatic sites were eligible for the current study. Various performance characteristics associated with baseline imaging were investigated, including specificity, sensitivity, positive likelihood ratio (LR), negative LR, number needed to investigate (NNI), negative predictive value (NPV), positive predictive value (PPV), and accuracy. A total of 27,201 HCC patients were included. Based on current recommendations that advocate for the use of cross-sectional chest imaging in all newly diagnosed cases of HCC, these recommendations would yield a PPV of 5.0% for the detection of lung metastases. This would translate to an NNI of 20.0. When T1N0 patients were excluded from routine chest or bone imaging, this resulted in a PPV of 6.8% for the identification of lung metastases and an NNI of 14.7. Likewise, this translated to a PPV of 4.6% for the identification of bone metastases and an NNI of 21.7. Similarly, when patients with T1N0 disease and normal alpha-fetoprotein (AFP) were excluded from routine imaging, this resulted in a PPV of 5.6% for the identification of lung metastases and an NNI of 17.8. Also, this translated to a PPV of 3.8% for the identification of bone metastases and an NNI of 26.3. The current study suggests that the omission of routine baseline chest imaging may be considered in selected patients with asymptomatic early-stage HCC and normal AFP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Data-Driven Constitutive Model for the Inelastic Response of Metals: Application to 316H Steel

Here, predictions of the mechanical response of structural elements are conditioned by the accuracy of constitutive models used at the engineering length-scale. In this regard, a prospect of mechanistic crystal-plasticity-based constitutive models is that they could be used for extrapolation beyond regimes in which they are calibrated. However, their use for assessing the performance of a component is computationally onerous. To address this limitation, a new approach is proposed whereby a surrogate constitutive model (SM) of the inelastic response of 316H steel is derived from a mechanistic crystal plasticity-based polycrystal model tracking the evolution of dislocation densities on all slip systems. The latter is used to generate a database of the expected plastic response and dislocation content evolution associated with several instances of creep loading. From the database, a SM is developed. It relies on the use of orthogonal polynomial regression to describe the evolution of the dislocation content. The SM is then validated against predictions of the dead load creep response given by the polycrystal model across a range of temperatures and stresses. When the SM is used to predict the response of 316H during complex non monotonic loading, extrapolating to new loading conditions, it is found that predictions compare particularly well against those from the physics-based polycrystal model.

36 MATERIALS SCIENCE↗
DOE OSTI2018

An Evaluation of “Drug Ineffective” Postmarketing Reports in Drug Safety Surveillance

Introduction: The most commonly reported adverse event, based on frequency of Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs), in the US FDA Adverse Event Reporting System (FAERS) database is ‘‘drug ineffective’’ (DI). This study aimed to describe the DI reports and provide data to support recommendations on how to best evaluate these reports. Methods: We characterized all FAERS reports coded with the MedDRA PT ‘‘drug ineffective’’ received between 1 September 2012 and 31 August 2016 using all other FAERS reports as a comparator. Additionally, we conducted a manual evaluation to identify informative data elements in the report narratives. Results: During the study period, 247,513 (6.4% of all FAERS reports) DI reports were entered in FAERS. Compared with non-DI reports, DI reports were more likely to be reported by consumers (69.8 vs. 48.1%) and less likely to report a serious outcome (26.2 vs. 56.3%). Most DI reports (88%) were from the USA. Manual evaluation of 552 sample US reports identified 43 reports (7.8%) deemed ‘‘useful’’; a higher proportion of ‘‘useful’’ reports provided a batch or lot number (39.5 vs. 17.2%) and were coded with additional PTs beyond ‘‘drug ineffective’’ (83.7 vs. 59.2%), the most frequent of which were ‘‘product quality issue’’ (23.3%) and ‘‘product substitution issue’’ (18.6%). Conclusions: DI was the most frequently reported adverse event in the FAERS database; however, the yield from these reports in terms of usefulness from a pharmacovigilance perspective was low. Efficient strategies are needed to identify which DI reports are more likely to contain useful information.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A Field Survey of Rare Earth Element Concentrations in Process Streams Produced by Coal Preparation Plants in the Eastern USA

I this work, a field study was undertaken to experimentally measure the concentrations of rare earth elements (REEs) contained in the process streams generated by a group of 20 coal preparation plants located in the eastern USA. For each site, representative samples of clean coal product, coarse refuse, and fine refuse were collected. Each sample was then partitioned into preselected size and density classes by wet screening/sieving and float-sink testing. The resultant products were dried and subjected to laboratory analyses to determine ash contents and rare earth element concentrations including Yttrium and Scandium. A detailed analysis of the database generated by this exercise showed that coal-based products from these preparation plants contained significant quantities of rare earth elements. In particular, the coarse refuse streams currently discarded by the 20 plants examined were found to contain a sufficient tonnage of REEs to satisfy the current domestic demand for these important elements. The data also showed a strong positive correlation between ash content and REE concentration, which suggested that the primary association of REEs in eastern USA bituminous coal sources is likely within fractions containing inorganic impurities. This association was well described using a simple power equation relating ash content and REE concentration. The ratio of heavy-to-light rare earth elements was discovered to be significantly higher in organically rich fractions of clean coal, suggesting that mineral impurities intimately associated with carbonaceous matter have elevated concentrations of heavy rare earth elements. A similar trend was observed for a grouping of rare earth elements (Y, Nd, Eu, Tb, and Dy) that are likely subject to near-term supply shortages. Finally, the database showed that a linear correlation existed between La for many REEs of interest, although there were several notable exceptions for some high-value REEs (Lu, Pr, and Tb).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Determination of the five parameter grain boundary character distribution of nanocrystalline alpha-zirconium thin films using transmission electron microscopy

Grain boundary engineering and other fundamental materials science problems (e.g., phase transformations and physical properties) require an improvement in the understanding of the type and population of grain boundaries in a given system – yet, databases are limited in number and spare in detail, including for hcp crystals such as zirconium. One way to rapidly obtain databases to analyze is to use small-grained materials and high spatial resolution orientation microscopy techniques, such as ASTAR™/precession electron diffraction. To demonstrate this, a study of grain boundary character distributions was conducted for α-zirconium deposited at room temperature on fused silica substrates using physical vapor deposition. The orientation maps of the nanocrystalline thin films were acquired by the ASTARα/precession electron diffraction technique, a new transmission electron microscope based orientation microscopy method. The reconstructed grain boundaries were classified as pure tilt, pure twist, 180°-twist and 180°-tilt grain boundaries based on the distribution of grain boundary planes with respect to the angle/axis of misorientation associated with grain boundaries. The results of the current study were compared to the results of a similar study on α-titanium and the molecular dynamics results of grain boundary energy for α-titanium.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solute-vacancy clustering in aluminum

In this study, we present an extensive first-principles database of solute-vacancy, homoatomic, heteroatomic solute-solute, and solute-solute-vacancy binding energies of relevant alloying elements in aluminum. We particularly focus on the systems with major alloying elements in aluminum, i.e., Cu, Mg, and Si. The computed binding energies of solute-vacancy, solute-solute pairs, and solute-solute-vacancy triplets agree with available experiments and theoretical results in literature. We consider physical factors such as solute size and formation energies of intermetallic compounds to correlate with binding energies. Systematic studies of the homoatomic solute-solute-vacancy and heteroatomic (Cu, Mg, or Si)-solute-vacancy complexes reveal the overarching effect of the vacancy in stabilizing solute-solute pairs. The binding energy database presented here elucidates the interaction between solute cluster and vacancy in aluminum, and it is expected to provide insight into the design of advanced Al alloys with tailored properties.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Iso-nuclear tungsten dielectronic recombination rates for use in magnetically-confined fusion plasmas

Under the auspices of the IAEA Atomic and Molecular Data Center and the Korean Atomic Energy Research Institute, our assembled group of authors has reviewed the current state of dielectronic recombination (DR) rate coefficients for various ion stages of tungsten (W). Subsequent recommendations were based upon available experimental data, first-principle calculations carried out in support of this paper and from available recombination data within existing atomic databases. If a recommendation was possible, data were compiled, evaluated and fitted to a functional form with associated uncertainty information retained, where available. This paper also considers the variation of the W fractional abundance due to the underlying atomic data when employing different data sets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

The nth-plant scenario for blended feedstock conversion and preprocessing nationwide: biorefineries and depots

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation’s renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation’s target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. A total delivered feedstock cost that is less than $79.07/dt (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple, and quadruple in size.

09 BIOMASS FUELS↗
DOE OSTI2023

A chemistry-informed hybrid machine learning approach to predict metal adsorption onto mineral surfaces

Historically, surface complexation model (SCM) constants and distribution coefficients (K d ) have been employed to quantify mineral-based retardation effects controlling the fate of metals in subsurface geologic systems. Our recent SCM development workflow, based on the Lawrence Livermore National Laboratory Surface Complexation/Ion Exchange (L-SCIE) database, illustrated a community FAIR data approach to SCM development by predicting uranium(VI)-quartz adsorption for a large number of literature-mined data. Here, we present an alternative hybrid machine learning (ML) approach that shows promise in achieving equivalent high-quality predictions compared to traditional surface complexation models. At its core, the hybrid random forest (RF) ML approach is motivated by the proliferation of incongruent SCMs in the literature that limit their applicability in reactive transport models. Our hybrid ML approach implements PHREEQC-based aqueous speciation calculations; values from these simulations are automatically used as input features for a random forest (RF) algorithm to quantify adsorption and avoid SCM modeling constraints entirely. Named the LLNL Speciation Updated Random Forest (L-SURF) model, this hybrid approach is shown to have applicability to U(VI) sorption cases driven by both ion-exchange and surface complexation, as is shown for quartz and montmorillonite cases. The approach can be applied to reactive transport modeling and may provide an alternative to the costly development of self-consistent SCM reaction databases.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2015

Identification of a PEAK1/ZEB1 signaling axis during TGFβ/fibronectin-induced EMT in breast cancer

Transforming Growth Factor beta (TGFβ) is the archetypal member of the TGFβ superfamily of ligands and has pleiotropic functions during normal development, adult tissue homeostasis and pathophysiological processes such as cancer. In epithelial cancers TGFβ signaling can either suppress tumor growth or promote metastasis via the induction of a well-characterized epithelial–mesenchymal transition (EMT) program. We recently reported that PEAK1 kinase mediates signaling cross talk between TGFβ receptors and integrin/Src/MAPK pathways and functions as a critical molecular regulator of TGFβ-induced breast cancer cell proliferation, migration, EMT and metastasis. Here, we examined the breast cancer cell contexts in which TGFβ induces both EMT and PEAK1, and discovered this event to be unique to oncogene-transformed mammary epithelial cells and triple-negative breast cancer cells. Using the Cancer BioPortal database, we identified PEAK1 co-expressors across multiple malignancies that are also common to the TGFβ response gene signature (TBRS). We then used the ScanSite database to identify predicted protein–protein binding partners of PEAK1 and the PEAK1-TBRS co-expressors. Analysis of the Cytoscape interactome and Babelomics-derived gene ontologies for a novel gene set including PEAK1, CRK, ZEB1, IL11 and COL4A1 enabled us to hypothesize that PEAK1 may be regulating TGFβ-induced EMT via its interaction with or regulation of these other genes. In this regard, we have demonstrated that PEAK1 is necessary for TGFβ to induce ZEB1-mediated EMT in the context of fibronectin/ITGB3 activation. These studies and future mechanistic studies will pave the way toward identifying the context in which TGFβ blockade may significantly improve breast cancer patient outcomes. - Highlights: • PEAK1 is upregulated in mammary epithelial cells during TGFβ-induced EMT. • TGFβ-induced EMT upregulates PEAK1 in triple negative breast cancer. • PEAK1 is necessary for TGFβ/fibronectin-induced ZEB1 expression during EMT. • The PEAK1/CRK/ZEB1 pathway is a novel target for blocking EMT in breast cancer.

60 APPLIED LIFE SCIENCES↗