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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

A study of IMRT planning parameters on planning efficiency, delivery efficiency, and plan quality

Purpose: To improve planning and delivery efficiency of head and neck IMRT without compromising planning quality through the evaluation of inverse planning parameters.Methods: Eleven head and neck patients with pre-existing IMRT treatment plans were selected for this retrospective study. The Pinnacle treatment planning system (TPS) was used to compute new treatment plans for each patient by varying the individual or the combined parameters of dose/fluence grid resolution, minimum MU per segment, and minimum segment area. Forty-five plans per patient were generated with the following variations: 4 dose/fluence grid resolution plans, 12 minimum segment area plans, 9 minimum MU plans, and 20 combined minimum segment area/minimum MU plans. Each plan was evaluated and compared to others based on dose volume histograms (DVHs) (i.e., plan quality), planning time, and delivery time. To evaluate delivery efficiency, a model was developed that estimated the delivery time of a treatment plan, and validated through measurements on an Elekta Synergy linear accelerator. Results: The uncertainty (i.e., variation) of the dose-volume index due to dose calculation grid variation was as high as 8.2% (5.5 Gy in absolute dose) for planning target volumes (PTVs) and 13.3% (2.1 Gy in absolute dose) for planning at risk volumes (PRVs). Comparison results of dose distributions indicated that smaller volumes were more susceptible to uncertainties. The grid resolution of a 4 mm dose grid with a 2 mm fluence grid was recommended, since it can reduce the final dose calculation time by 63% compared to the accepted standard (2 mm dose grid with a 2 mm fluence grid resolution) while maintaining a similar level of dose-volume index variation. Threshold values that maintained adequate plan quality (DVH results of the PTVs and PRVs remained satisfied for their dose objectives) were 5 cm{sup 2} for minimum segment area and 5 MU for minimum MU. As the minimum MU parameter was increased, the number of segments and delivery time were decreased. Increasing the minimum segment area parameter decreased the plan MU, but had less of an effect on the number of segments and delivery time. Our delivery time model predicted delivery time to within 1.8%. Conclusions: Increasing the dose grid while maintaining a small fluence grid allows for improved planning efficiency without compromising plan quality. Delivery efficiency can be improved by increasing the minimum MU, but not the minimum segment area. However, increasing the respective minimum MU and/or the minimum segment area to any value greater than 5 MU and 5 cm{sup 2} is not recommended because it degrades plan quality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Fabrication of core-shell Fe{sub 3}O{sub 4}@MIL-100(Fe) magnetic microspheres for the removal of Cr(VI) in aqueous solution

Facile regeneration of an adsorbent is very important for commercial feasibility. One typical highly porous metal-organic framework (MOF) materials based on MIL-100(Fe) and magnetic iron oxide particles (denoted as MMCs) with diameter about of 350 nm were successfully synthesized. The growth of MIL-100(Fe) shell on the surface of Fe{sub 3}O{sub 4} was utilized precursor as crystal seed via in-situ step hydrothermal reaction. It is a simple way to obtain well organized core-shell MOF composites, compared to the step-by-step method. MMCs were firstly used to uptake of Cr(VI) anions in aqueous solution. Adsorption experiments were carried out in batch sorption mode investigating with the factors of contact time (0–1000 min), pH (from 2 to 12), dose of adsorbent (4–25 mg), and initial Cr(VI) concentration (range from 10 to 100 ppm). - Graphical abstract: One typical highly porous metal-organic framework (MOF) materials based on MIL-100(Fe) and magnetic iron oxide particles (denoted as MMCs) were successfully synthesized. Utilizing Fe{sub 3}O{sub 4} precursor as crystal seed to grow MIL-100(Fe) shell by in-situ step hydrothermal reaction. It is a simple way to obtain core-shell MOF composites. MMCs could effectively uptake of Cr(VI) anions in aqueous solution. - Highlights: • Fe{sub 3}O{sub 4}@MIL-100(Fe) composites with core-shell structure were successfully prepared through a simple method. • The influence factors on Cr(VI) adsorption by Fe{sub 3}O{sub 4}@MIL-100(Fe) were investigated. • Cr(VI) can efficiently adsorbed by Fe{sub 3}O{sub 4}@MIL-100(Fe) composites from aqueous solution.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Recovering network topologies via Taylor expansion and compressive sensing

Gaining knowledge of the intrinsic topology of a complex dynamical network is the precondition to understand its evolutionary mechanisms and to control its dynamical and functional behaviors. In this article, a general framework is developed to recover topologies of complex networks with completely unknown node dynamics based on Taylor expansion and compressive sensing. Numerical simulations illustrate the feasibility and effectiveness of the proposed method. Moreover, this method is found to have good robustness to weak stochastic perturbations. Finally, the impact of two major factors on the topology identification performance is evaluated. This method provides a natural and direct point to reconstruct network topologies from measurable data, which is likely to have potential applicability in a wide range of fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Growth and defect structure of CdF{sub 2} crystal and nonstoichiometric Cd{sub 1-x}R{sub x}F{sub 2+x} phases (R are rare earth elements and in): 6. Growth and ionic conductivity of Cd{sub 0.904}In{sub 0.096}F{sub 2.096} single crystal

Cd{sub 0.904}In{sub 0.096}F{sub 2.096} crystals with fluorite-type defect structures have been grown from melt in a fluorinating atmosphere by the Bridgman method, and their ionic conductivity is investigated. The fluorine-ion transport activation enthalpy in Cd{sub 0.904}In{sub 0.096}F{sub 2.096} ({Delta}H = 0.68 eV) is much smaller than the corresponding characteristic of the crystals belonging to the isoconcentration series Cd{sub 0.9}R{sub 0.1}F{sub 2.1}, R = La-Lu, Y ({Delta}H = 0.8-0.9 eV). The ionic conductivity of Cd{sub 0.904}In{sub 0.096}F{sub 2.096} is {sigma} = 2 Multiplication-Sign 10{sup -4} S/cm (at 467 K); this value exceeds the conductivity of the CdF{sub 2} crystal matrix and the highest conductivity Cd{sub 0.9}R{sub 0.1}F{sub 2.1} crystals with rare earth elements by factors of 3 Multiplication-Sign 10{sup 3} and {approx}10, respectively. Nonstoichiometric crystals of solid electrolyte Cd{sub 1-x}In{sub x}F{sub 2+x} have the highest conductivity out of all studied electrolytes based on the CdF{sub 2} matrix.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Explainable machine learning for hydrogen diffusion in metals and random binary alloys

Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen diffusion, they often lack accuracy when making quantitative predictions. Machine learning models are capable of making accurate predictions, but their inner workings are obscured, rendering it unclear which physical features are truly important. To develop interpretable machine learning models to predict the activation energies of hydrogen diffusion in metals and random binary alloys, we create a database for physical and chemical properties of the species and use it to fit six machine learning models. Our models achieve root-mean-squared errors between 98–119 meV on the testing data and accurately predict that elemental Ru has a large activation energy, while elemental Cr and Fe have small activation energies. By analyzing the feature importances of these fitted models, we identify relevant physical properties for predicting hydrogen diffusivity. While metrics for measuring the individual feature importances for machine learning models exist, correlations between the features lead to disagreement between models and limit the conclusions that can be drawn. Instead grouped feature importance, formed by combining the features via their correlations, agree across the six models and reveal that the two groups containing the packing factor and electronic specific heat are particularly significant for predicting hydrogen diffusion in metals and random binary alloys. In conclusion, this framework allows us to interpret machine learning models and enables rapid screening of new materials with the desired rates of hydrogen diffusion.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The roles of hypoxia-inducible Factor-1 and iron regulatory protein 1 in iron uptake induced by acute hypoxia

Divalent metal transporter 1 (DMT1) and transferrin receptor (TfR1) are vital proteins for cellular iron uptake. These proteins have hypoxia-responsive elements (HREs) in their 5‘-regulatory region, and they are regulated by hypoxia-inducible factor 1α (HIF-1α) transcriptionally under hypoxic condition. Besides, iron regulatory protein 1 (IRP1) regulates DMT1 and TfR1 by binding to iron-responsive elements (IREs) present in their mRNAs to control cellular iron homeostasis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Association between body mass index and arsenic methylation efficiency in adult women from southwest U.S. and northwest Mexico

Human arsenic methylation efficiency has been consistently associated with arsenic-induced disease risk. Interindividual variation in arsenic methylation profiles is commonly observed in exposed populations, and great effort has been put into the study of potential determinants of this variability. Among the factors that have been evaluated, body mass index (BMI) has not been consistently associated with arsenic methylation efficiency; however, an underrepresentation of the upper BMI distribution was commonly observed in these studies. This study investigated potential factors contributing to variations in the metabolism of arsenic, with specific interest in the effect of BMI where more than half of the population was overweight or obese. We studied 624 adult women exposed to arsenic in drinking water from three independent populations. Multivariate regression models showed that higher BMI, arsenic (+ 3 oxidation state) methyltransferase (AS3MT) genetic variant 7388, and higher total urinary arsenic were significantly associated with low percentage of urinary arsenic excreted as monomethylarsonic acid (%uMMA) or high ratio between urinary dimethylarsinic acid and uMMA (uDMA/uMMA), while AS3MT genetic variant M287T was associated with high %uMMA and low uDMA/uMMA. The association between BMI and arsenic methylation efficiency was also evident in each of the three populations when studied separately. This strong association observed between high BMI and low %uMMA and high uDMA/uMMA underscores the importance of BMI as a potential arsenic-associated disease risk factor, and should be carefully considered in future studies associating human arsenic metabolism and toxicity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Molecular Glue Discovery: Current and Future Approaches

The intracellular interactions of biomolecules can be maneuvered to redirect signaling, reprogram the cell cycle, or decrease infectivity using only a few dozen atoms. Such "molecular glues," which can drive both novel and known interactions between protein partners, represent an enticing therapeutic strategy. Here, we review the methods and approaches that have led to the identification of small-molecule molecular glues. We first classify current FDA-approved molecular glues to facilitate the selection of discovery methods. We then survey two broad discovery method strategies, where we highlight the importance of factors such as experimental conditions, software packages, and genetic tools for success. In conclusion, we hope that this curation of methodologies for directed discovery will inspire diverse research efforts targeting a multitude of human diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

How to Obtain Reproducible Results for Lithium Sulfur Batteries

The basic requirements for getting reliable Li-S battery data have been discussed in this work. Unlike Li-ion batteries, electrolyte-rich environment significantly affects the cycling stability of Li-S batteries prepared and tested under the same conditions. The reason has been assigned to the different concentrations of polysulfide-containing electrolytes in the cells, which have profound influences on both sulfur cathode and lithium anode. At optimized S/E ratio of 50 g L-1, a good balance among electrolyte viscosity, wetting ability, diffusion rate dissolved polysulfide and nucleation/growth of short-chain Li2S/Li2S2 has been built along with largely reduced contamination on the lithium anode side. Accordingly, good cyclability, high reversible capacity and Coulombic efficiency are achieved in Li-S cell with controlled S/E ratio without any additive. Other factors such as sulfur content in the composite and sulfur loading on the electrode also need careful concern in Li-S system in order to generate reproducible results and gauge the various methods used to improve Li-S battery technology.

Cycling stability↗
DOE OSTI2021

How Does the COVID-19 Pandemic Affect Transport-Related Diesel Consumption in the U.S.?

Understanding how energy usage reacts to the COVID-19 pandemic is essential to making strategic policy decisions. This study aims to quantify the pandemic’s influences on diesel consumption and explore the potential causes of the differences across regions. We found various levels of reduction in diesel consumption at the state level during the pandemic in the U.S. Many factors, including COVID-19 cases and commodities being moved, are associated with these reductions. In particular, at the state level, more truck/train shipping of minerals, coal, and forest products associates with fewer truck activities and greater decreases in diesel consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Preparation and upconversion properties of rare earth doped core-shell Y(OH)3 and β-NaYF4 hybrid nanorods

Highlights: • Er{sup 3+}/Yb{sup 3+}-doped Y(OH)3@β-NaYF4@β-NaYF4 hybrid nanorods swere synthesized. • Upconversion intensity increases dramatically by ion exchange reaction, and it can be further enhanced through coating inert shells. • Formation mechanisms of the core-shell nanorods are discussed, as well as their upconversion properties. - Abstract: Er{sup 3+}/Yb{sup 3+}-doped Y(OH){sub 3}@β-NaYF{sub 4} core-shell nanorods are synthesized through in situ ion exchange reaction using Y(OH){sub 3} nanorods as templates. Further, inert shells of β-NaYF{sub 4} without activated dopants are coated by a facile hydrothermal method. Upconversion intensity increases dramatically by ion exchange reaction, and it can be further enhanced through coating inert shells. The maximal enhanced factor of inert coating reaches 6.58. On the basis of the structural tests and spectral data, formation mechanisms of the core-shell nanorods are discussed, as well as their upconversion properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Critical Practices in Rigorously Assessing the Inherent Activity of Nanoparticle Electrocatalysts

Accurate activity measurements for electrocatalytic materials are the backbone of impactful electrocatalyst research. Inherent to accurate measurements is the correct accounting of the active catalyst sites and the design of experiments to ensure that these sites are participating in the measured reaction. Improvements in electrocatalyst activity for fuel cell reactions (hydrogen oxidation and oxygen reduction) are essential for the widespread adoption of this carbon-neutral energy source. Activities for these half-reactions can be reported in a variety of ways including specific activities, mass activities, volumetric activities, and half-wave potentials. These values are traditionally measured with a rotating disk electrode (RDE) in which the electrocatalyst is supported on a porous active layer film attached to the RDE. To accurately measure electrocatalyst activity with an RDE, two major sources of errors must be addressed: (i) accurate electrochemical surface area (ECSA) quantification and (ii) fast diffusion of reactants through the active layer film. In this contribution, we first aim to detail through RDE experiments and mass transport modeling the potential errors that can be observed when these factors are not properly addressed. We then present recommendations and discuss techniques for properly constructing electrocatalyst thin films and characterizing the ECSA on monometallic and novel alloy electrocatalysts. These practices, when adopted, ensure greater confidence and reliability in reports of electrocatalyst activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Transition form factors: γ * + p → Δ ( 1232 ) , Δ ( 1600 )

We report that electroproduction form factors describing the γ * p → Δ + ( 1232 ) , Δ + ( 1600 ) transitions are computed using a fully dynamical diquark-quark approximation to the Poincaré-covariant three-body bound-state problem in relativistic quantum field theory. In this approach, the Δ ( 1600 ) is an analogue of the Roper resonance in the nucleon sector, appearing as the simplest radial excitation of the Δ ( 1232 ) . Precise measurements of the γ * p → Δ + ( 1232 ) transition already exist on 0 ≤ Q 2 ≲ 8 GeV 2 , and the calculated results compare favorably with the data outside the meson-cloud domain. The predictions for the γ * p → Δ + ( 1600 ) magnetic dipole and electric quadrupole transition form factors are consistent with the empirical values at the real photon point, and extend to Q 2 ≈ 6 m p 2 , enabling a meaningful direct comparison with experiment once analysis of existing data is completed. In both cases, the electric quadrupole form factor is particularly sensitive to deformation of the Δ -baryons. Interestingly, while the γ * p → Δ + ( 1232 ) transition form factors are larger in magnitude than those for γ * p → Δ + ( 1600 ) in some neighborhood of the real photon point, this ordering is reversed on Q 2 ≳ 2 m p 2 , suggesting that the γ * p → Δ + ( 1600 ) transition is more localized in configuration space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A data mining approach to investigate food groups related to incidence of bladder cancer in the BLadder cancer Epidemiology and Nutritional Determinants International Study

Abstract At present, analysis of diet and bladder cancer (BC) is mostly based on the intake of individual foods. The examination of food combinations provides a scope to deal with the complexity and unpredictability of the diet and aims to overcome the limitations of the study of nutrients and foods in isolation. This article aims to demonstrate the usability of supervised data mining methods to extract the food groups related to BC. In order to derive key food groups associated with BC risk, we applied the data mining technique C5.0 with 10-fold cross-validation in the BLadder cancer Epidemiology and Nutritional Determinants study, including data from eighteen case–control and one nested case–cohort study, compromising 8320 BC cases out of 31 551 participants. Dietary data, on the eleven main food groups of the Eurocode 2 Core classification codebook, and relevant non-diet data (i.e. sex, age and smoking status) were available. Primarily, five key food groups were extracted; in order of importance, beverages (non-milk); grains and grain products; vegetables and vegetable products; fats, oils and their products; meats and meat products were associated with BC risk. Since these food groups are corresponded with previously proposed BC-related dietary factors, data mining seems to be a promising technique in the field of nutritional epidemiology and deserves further examination.

Nutrition & Dietetics↗
DOE OSTI2024

A bioactive supramolecular and covalent polymer scaffold for cartilage repair in a sheep model

Regeneration of hyaline cartilage in human-sized joints remains a clinical challenge, and it is a critical unmet need that would contribute to longer healthspans. Injectable scaffolds for cartilage repair that integrate both bioactivity and sufficiently robust physical properties to withstand joint stresses offer a promising strategy. We report here on a hybrid biomaterial that combines a bioactive peptide amphiphile supramolecular polymer that specifically binds the chondrogenic cytokine transforming growth factor β-1 (TGFβ-1) and crosslinked hyaluronic acid microgels that drive formation of filament bundles, a hierarchical motif common in natural musculoskeletal tissues. The scaffold is an injectable slurry that generates a porous rubbery material when exposed to calcium ions once placed in cartilage defects. The hybrid material was found to support in vitro chondrogenic differentiation of encapsulated stem cells in response to sustained delivery of TGFβ-1. Using a sheep model, we implanted the scaffold in shallow osteochondral defects and found it can remain localized in mechanically active joints. Evaluation of resected joints showed significantly improved repair of hyaline cartilage in osteochondral defects injected with the scaffold relative to defects injected with the growth factor alone, including implantation in the load-bearing femoral condyle. These results demonstrate the potential of the hybrid biomimetic scaffold as a niche to favor cartilage repair in mechanically active joints using a clinically relevant large-animal model.

Science & Technology - Other Topics↗
DOE OSTI2017

Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning

Abstract. Mounting evidence from field and laboratory observations coupled with atmospheric model analyses shows that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality model version 5.2 (CMAQv5.2) accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the secondary organic aerosol (SOA) from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: (1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, (2) multigenerational aging of organic vapor products from known SOA precursors (e.g., toluene, alkanes), (3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and (4) reversible organic compounds–water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 and 12 km), gas-phase chemical mechanisms, and seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May–June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g., the correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g., bias at Pasadena from −5.62 to −2.42 µg m−3). Daily averaged predictions of observations at routine-monitoring networks from simulations over the continental US (CONUS) in 2011 show modest improvement during winter, with mean biases reducing from 1.14 to 0.73 µg m−3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too-high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

LARP7 suppresses P-TEFb activity to inhibit breast cancer progression and metastasis

Transcriptional elongation by RNA polymerase (Pol) II is essential for gene expression during cell growth and differentiation. The positive transcription elongation factor b (P-TEFb) stimulates transcriptional elongation by phosphorylating Pol II and antagonizing negative elongation factors. A reservoir of P-TEFb is sequestered in the inactive 7SK snRNP where 7SK snRNA and the La-related protein LARP7 are required for the integrity of this complex. Here, we show that P-TEFb activity is important for the epithelial–mesenchymal transition (EMT) and breast cancer progression. Decreased levels of LARP7 and 7SK snRNA redistribute P-TEFb to the transcriptionally active super elongation complex, resulting in P-TEFb activation and increased transcription of EMT transcription factors, including Slug, FOXC2, ZEB2, and Twist1, to promote breast cancer EMT, invasion, and metastasis. Our data provide the first demonstration that the transcription elongation machinery plays a key role in promoting breast cancer progression by directly controlling the expression of upstream EMT regulators.

59 BASIC BIOLOGICAL SCIENCES↗