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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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To compare, in a national population-based study, severe genitourinary (GU) and gastrointestinal (GI) toxicity in patients with prostate cancer who were treated with radical intensity modulated radiation therapy (IMRT) or 3-dimensional conformal radiation therapy (3D-CRT).
This study constructed cell‐free glycolytic enzyme systems and compared them to their in vivo functions in Escherichia coli . Under in vitro conditions, flux regulation followed enzyme concentrations and kinetics. In E. coli, only one of the isozymes of phosphofructokinase (PfkA) and fructose‐bisphosphate aldolase (FbaA) facilitate Embden‐Meyerhof‐Parnas (EMP) flux, but under in vitro assays, these isozymes were interchangeable. Additionally, in vitro introduction of the Entner–Doudoroff (ED) pathway improved glycolysis rates, while in vivo overexpression of the ED pathway could not capture significant flux unless its phosphotransferase system (PTS) was knocked out. Lastly, in vivo dynamic 13 C‐experiments revealed that the labeling order of EMP pathway intermediates was not strictly cascade, indicating intracellular metabolites were not well mixed. These enigmatic observations cannot be fully explained by thermodynamics or substrate level regulations. This article supports the long‐time conjecture that EMP enzymes are channeled, and the PTS may be an anchor point to initiate enzyme assemblies. © 2018 American Institute of Chemical Engineers AIChE J , 65: 483–490, 2019
Highlights: • Leaching processes of waste from alkaline batteries are reviewed and compared. • The recovery of Zn and Mn by electrolysis in acid medium is highly dependent on pH. • Reaction of Zn with the O{sub 2} is released at the anode in the electrodeposition of Zn. • Zn is recovered as ZnO in a single step by acidifying the basic leachate with HCl. - Abstract: A parallel study of acidic and alkaline leaching for the recovery of Mn and Zn from spent alkaline batteries is outlined. Using H{sub 2}SO{sub 4} as solvent and selecting appropriate conditions of temperature and concentration, all residues were dissolved except carbon. The separation and recovery of the two components were performed by electrodeposition with satisfactory results at pH values above 4 (current efficiency above 70% for Zn and Mn) but rather lower efficiencies as the pH decreased. Most of the Zn was selectively dissolved by alkaline leaching using a 6.5 M NaOH solution, and its recovery was examined by means of both electrochemical and chemical processes. The expected formation of pure Zn by electrowinning failed due to the formation of ZnO, the content of which was highly dependent on the electrodeposition time. For short periods, Zn was the main component. For longer periods the electrodeposit consisted of agglomerated microparticles of ZnO with a minor fraction of Zn metal (barely 3% as measured by X-ray diffraction). A chemical reaction of the element with oxygen released at the anode surface might be responsible for its conversion to ZnO. A simple chemical route is described for the first time for the direct conversion of Zn(OH){sub 4}{sup 2−} solution to nanostructured ZnO by lowering the pH to values around 12 using 2 M HCl solution.
The present work deals with the study of tribo-pair interaction in lubricated sliding contacts. By considering the environmental issues, the sunflower oil was extracted from the sunflower seeds and used as a base lubricant. The two types of the nanoadditives, i.e., CuO and CeO{sub 2}, varying concentrations from 0.10 to 0.50% w/v were used to formulate the nanolubricants. The compatibility/synergism of the nanoadditives was examined from antifriction and antiwear behavior study with four-ball tester. Also, sunflower oil was modified by the chemical method to improve its fatty acid structure. A comparative tribological and compatibility study was also done in modified oil at similar concentration levels with both types of nanoparticles. The tribological test result exhibits 0.10% w/v concentration of the nanoadditive as optimum due to lowest wear scar and coefficient of friction. Higher concentration of the nanoparticles impaired the base oil performance. Different analytical tools were used to characterize the oil modification and worn surfaces. Moreover, the role of subsurface of the contacting material with the tribological performance has been reported.
We present a systematic study of thermal oxidation resistance of transition metal borides and carbides up to 1300 °C in a dry air environment. A High-Entropy Metal Boride (HEMB), of composition (Hf 0.2 , Mo 0.2 , Nb 0.2 , Ta 0.2 , Zr 0.2 )B 2 , and a similar High-Entropy Metal Carbide (HEMC) (Hf, Mo, Nb, Ta, Zr)C 5 were synthesized from precursor mixtures, under 30 MPa of pressure at a temperature of 1800 °C using a Spark Plasma Sintering Device. The synthesized phases were confirmed via X-ray Diffraction analysis, which showed a pure hexagonal AlB 2 -type structure for HEMB and a face-centered cubic (FCC) structure for HEMC, with lattice parameters, a = 3.10 Å and c = 3.37 Å for HEMB and a = 4.524 Å for HEMC. Oxidation resistance was evaluated using a simultaneous thermogravimetric analysis and differential scanning calorimetry (TGA/DSC) stage in which HEMB and HEMC were heated up to 1300 °C at a rate of 2 °C/min in a dry air environment. Scanning electron microscopy (SEM) was used to analyze the resulting oxidized material. Our study demonstrates that HEMB shows better thermal oxidation resistance as compared to a similar metal composition HEMC at high temperatures.
Here, this article presents a comparative analysis of total ionizing dose (TID) response in GlobalFoundries’ (GF) 12 low-power (LP) and 12LP+12-nm bulk fin field effect transistor (FinFET) technologies using 10-keV X-rays. Our findings show that 12LP+ n-type transistors demonstrate higher sensitivity to TID degradation of the off-state leakage drain current compared to 12LP. Data indicate that for both 12LP and 12LP+, transistors with higher threshold voltages (VTs) exhibit lower off-state drain-source leakage postirradiation compared to transistors with lower VTs. Data consistently show that transistors with fewer fins per transistor show superior TID tolerance, in both 12LP and 12LP+ technologies. Lower VT transistors in both technologies display similar preirradiation leakage currents. On the other hand, higher VT transistors in 12LP+ show lower preirradiation leakage currents than those in 12LP, highlighting that the front-end-of-line of 12LP+ technology has been modified compared to 12LP. p-type devices in 12LP+ presented negligible degradation. Larger TID sensitivity in 12LP+ might be attributed to the implementation of dual-metal gate work functions, reduced halo doping, deeper source/drain (S/D) doping profiles, and/or 12LP+ having narrower fins compared to 12LP.
According to Bureau of Transportation Statistics, the U.S. transportation system handled 14,329 million ton-miles of freight per day in 2020. Understanding the generation of these freight shipments is crucial for transportation researchers, planners, and policymakers to design and plan for a more efficient and connected freight transportation system. Traditionally, the freight generation modeling has been based on Ordinary Least Square (OLS) regression, although more advanced Machine Learning (ML) algorithms have been evaluated and proven to have excellent performance in various transportation applications in recent years. Furthermore, one modeling approach applied for one industry might not always be applicable for another as their freight generation logics can be quite different. The objective of this study is to apply and evaluate alternative ML algorithms in the estimation of freight generation for each of 45 industry types. Seven alternative ML algorithms, along with the base OLS regression, were evaluated and compared. In addition, the study considered different combinations of variables in both the original and logarithmic form as well as hyperparameters of those ML algorithms in the model selection for each industry type. The results showed statistically significant improvements in the root mean square error reduction by the alternative ML algorithms over the OLS for over 80% of cases. The study suggests utilizing the alternative ML algorithms can reduce the root mean square error by about 30%, depending on industry types.
Background: Suicide is a leading cause of death in the US Comparative State-level spatial analysis between Veterans Health Administration (VHA veterans) and the whole US population can reveal differences in conditions for targeted interventions and intricate geographical patterns. Methods: The study population contains 2018 and 2019 suicide deaths of VHA veterans and the whole US population. They were used to calculate state-level rates. States were classified by whether their VHA veteran and whole US population rates were above or below respective mean rates. Local Moran’s I was leveraged to examine spatial autocorrelation. Results: State-level suicide mortality rates and disparities among states were generally higher for VHA veterans (2018: 37.3 ± 7.2; 2019: 46.8 ± 8.3) than for the whole US population (2018: 16.6 ± 4.3; 2019: 16.4 ± 4.4). For both populations, there were statistically significant clusters with high suicide rates. Over one-fourth of states demonstrated inverse relationships, with rates above mean for one group but below for other. VHA veterans are at higher risk with over one-third of states had greater than average veteran suicide risk ratio. Conclusions: VHA veterans are at higher risk than the whole population across all states. Mortality disparities among states and clusters of states with high and low rates suggest targeted interventions and cooperative health strategies may help address these differences.
As concerns around water scarcity and energy security increase, so too has interest in the connections between these resources, through a concept called the water–energy nexus. Efforts to improve the integration of water and energy management and to understand their cross-sector relevance are growing. In particular, this paper develops a better empirical understanding on the extent to which governance settings hinder and/or enable policy coherence between the water and energy sectors through a comparative analysis of two case studies, namely, Los Angeles County, California, the United States, and the city of Beijing, China. This paper examines the extent to which the institutional context enables policy coordination within (vertically) and between (horizontally) the water and energy sectors in Beijing and Los Angeles. To do so, we propose a framework for analyzing policy integration for the water energy nexus based on environmental policy integration (EPI). The results highlight the multiple and flexible approaches of EPI in nexus governance, not least with regards to horizontal and vertical policy integration, but also in terms of explicit (i.e., intended) and implicit (i.e., unintended) coordination. The level of nexus-focused policy integration is highly dependent on the motivation at the local context and the criteria to evaluate policy success in each sector.
Atomic layer deposition (ALD) of zinc oxide (ZnO) has been widely researched using diethyl zinc (DEZ)-based methods. The significant importance of thin films of ZnO as transparent conductive oxides (TCO) in optoelectronic devices and photovoltaics warrants examining alternative Zn precursors for ZnO ALD as potential replacements for the pyrophoric DEZ. In this study, we investigated three alternative Zn precursors: Zn(EEKI)2, Zn(DMP)2, ZnEt(HMDS), in the process development for high-quality ZnO thin films and compared them to DEZ. The ALD processes were studied using in situ spectroscopic ellipsometry. The properties of the ALD ZnO films were characterized using ex situ X-ray photoelectron spectroscopy (XPS), Rutherford backscattering spectrometry and nuclear reaction analysis (RBS/NRA), X-ray diffraction (XRD), atomic force microscopy (AFM), transmission electron microscopy (TEM), and ultraviolet-visible (UV/Vis) spectrophotometry. These measurements confirmed the formation of pure, stoichiometric, and polycrystalline ZnO films using all four Zn precursors. Although the selected precursors are chemically diverse Zn compounds, they all yielded saturating ALD processes and high-quality ZnO thin films at 200 °C. This study highlights the potential benefits of alternative zinc precursors in designing ALD processes for ZnO thin films.
Microstructure, tensile and wear properties of as-cast A4 (Mg-4Al), AE41 (Mg-4Al-0.5Ce-0.5La), AS41 (Mg-4Al-1Si) and AJ41 (Mg-4Al-1Sr) alloys were investigated, and the results were compared with each other in this study. Microstructures were investigated by XRD, optical and scanning electron microscopes. Tensile tests were conducted at both room and elevated temperatures. Tribological properties were examined by pin-on-disk wear tests under different applied loads. Microstructure characterizations revealed that the volume fraction of second phases considerably increased by alloying additions of 1 wt.% Ce/La, Si and Sr. The microstructure of A4 alloy consisted of α-Mg grains and divorced β-Mg{sub 17}Al{sub 12} phases. After individual alloying additions of 1 wt.% Ce/La, Si and Sr, the secondary phases were primarily replaced by needle-shaped and massive blocky-shaped Al{sub 11}(Ce,La){sub 3} phases in AE41 alloy, Chinese-script-type Mg{sub 2}Si phases in AS41 alloy and divorced globular-like and massive blocky-shaped Al{sub 4}Sr and (Mg,Al){sub 17}Sr{sub 2} phases in AJ41 alloy. The tensile tests showed that at both room and elevated temperatures alloying additions of 1 wt.% Ce/La, Si and Sr resulted in an increase in the strength but a decrease in the ductility. Among the studied alloys, AS41 alloy exhibited the best strength. Wear test results showed that AE41 and AJ41 alloys similarly exhibited the best wear resistance owing to the presence of hard and dense intermetallics. Abrasion was the main wear mechanism under low applied loads while delamination, adhesion and oxidation mechanisms were majorly observed under high applied loads.
In this article, we present a gauge R & R study that is different from the standard setup in several ways. A balanced incomplete block design (BIBD) was used to collect the data because the measurement is destructive. Besides addressing reproducibility, differences in repeatability (i.e., tester variances) were also of interest. Here we use Bayesian methods to analyze the study data to address whether the three tester means and variances are similar. We also consider what happens if the BIBD structure of the data and possibly different tester variances are ignored in analyzing the study data.
We investigated and compared optoelectronic properties, crystallographic structures, and nanoscale surface morphologies of ex-situ phosphorus-doped polycrystalline silicon (poly-Si)/SiO x passivating contacts, formed by different deposition methods (sputtering, plasma-enhanced chemical vapour deposition (PECVD), and low-pressure chemical vapour deposition (LPCVD)). Across all these deposition technologies, a similar trend is observed: higher diffusion temperatures yield films that are more crystalline but have rougher surface morphologies due to bigger surface crystal grains. Also, the recrystallization process of the as-deposited Si films starts from the SiO x interface, rather than from the film surface and bulk. However, there are some distinct differences among these technologies. Firstly, the LPCVD method yields the roughest surface and smallest degree of crystallinity on finished poly-Si films. In contrast, the PECVD method has the smoothest surface for both as-deposited Si and annealed poly-Si films. Secondly, as-deposited sputtered and PECVD Si films contain only an amorphous phase whereas as-deposited LPCVD films has already had some crystalline phase. Thirdly, the LPCVD phosphorus in-diffusion into the substrate depends strongly on the initial film thickness, whereas for the other two methods it is weakly dependent on thickness.
We present a performance analysis appropriate for comparing algorithms using different numerical discretizations. By taking into account the total time-to-solution, numerical accuracy with respect to an error norm, and the computation rate, a cost-benefit analysis can be performed to determine which algorithm and discretization are particularly suited for an application. This work extends the performance spectrum model in for interpretation of hardware and algorithmic tradeoffs in numerical PDE simulation. As a proof-of-concept, popular finite element software packages are used to illustrate this analysis for Poisson’s equation.
Based on first principle calculations, we carried out comparative research of Cs,O coadsorption on Ga{sub 0.75}Al{sub 0.25}N (0001) surface and Ga{sub 0.75}Al{sub 0.25}N (001) (2 × 2) reconstruction surface. On the (0001) surface, the average coordinate difference between Cs and O atoms along [0001] direction is obviously smaller than that along [001] direction on (001) (2 × 2) reconstruction surface. This is due to the existence of dimers and trenches on the (001) (2 × 2) reconstruction surface. Cs atoms are favored to locate on the dimers while O atoms are favored to locate in the trenches. As a result, Cs–O dipoles on (001) (2 × 2) reconstruction surface make an important contribution on lowering work function. For both (0001) and (001) (2 × 2) reconstruction surface, work function values fluctuate up and down at the stage of Cs,O alternative adsorption, and the valley values are smaller and smaller. The site of Mg dopant has an influence on work function of the surfaces, which results in the “fish scale field” effect.
This paper explores the detection and localization of cyber-attacks on power systems, focusing on comparing conventional machine learning (ML) and deep learning methods, and graph neural network (GNN)-based techniques. We assess the detection accuracy of these approaches and their potential to pinpoint the locations of specific buses under attack. Given the demonstrated success of GNNs in other time series anomaly detection applications, we aim to evaluate their performance within the context of power systems cyber-attack. Utilizing the IEEE 68-bus system, we simulated four types of attacks to test the selected approaches. Our results indicate that GNN-based methods outperform conventional machine learning and deep learning models in detection. Additionally, GNNs show promise in accurately localizing attacks for simple scenarios, although they still face challenges in more complex cases.
Domain-overarching system models are crucial to investigate sector coupling concepts. Specifically, the coupling of building and electrical energy systems becomes crucial to integrate renewable energy sources such as photovoltaic power systems (PV). For such interdisciplinary simulation models, Modelica is a suitable language. However, most open-source Modelica libraries are either domain-specific or lack simple-to-parameterize PV models. We close this gap by developing a PV model for the IBPSA Modelica library. The model comprises two I-V-characteristic models and three mounting-dependent approaches to calculate the cell temperature. The I-V-characteristic models follow a single- and two-diodes approach. This study uses measurement data from a rooftop PV system in Berlin, Germany, for validation. The focus lies on comparing the implemented single- and two-diodes approach. Results prove that both models accurately calculate the modules’ DC power output and cell temperature. The two-diodes approach slightly outperforms the single-diode one at the expense of a higher parameterization effort.
Motivation: Crucial aspect of mechanical design is joining methodology of parts. Ability to analyze joint and fasteners in system for structural integrity is fundamental. Different modeling representations of fasteners include spring, beam, and solid elements. Various methods compared for linear system to decide method appropriate for design study. New method for modeling fastener joint is explored from full system perspective. Analysis results match well with published experimental data for new method.