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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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A methodology for corrosion testing ODS steels in liquid tin under reactor conditions in HFIR
Liquid metal–based divertor concepts have promising attributes for application in fusion reactors. Liquid tin is being considered as one of those liquid metals due to its excellent thermophysical properties. However, tin is extremely corrosive to steels at elevated temperatures, and the coupled effects of corrosion with neutron irradiation for application in fusion reactors have not been quantified. Researchers at Oak Ridge National Laboratory (ORNL) have designed and irradiated a series of capsules in the High Flux Isotope Reactor (HFIR) to help address gaps in the literature with respect to coupled corrosion and neutron irradiation effects. The capsules are filled with solid tin designed to melt due to the gamma heating in HFIR and allow interaction with the specimens. The capsules contain a SiC thermometer for post-irradiation temperature verification. Five capsules were irradiated in HFIR for 10.5 days, accumulating 0.93 dpa in the FeCrAl specimens. Post-irradiation temperature verification was performed on the SiC thermometers, and temperatures were observed to be higher than what was expected from thermal models. An explanation for the model underprediction is given herein. In conclusion, the capsules described within this article are the first to irradiate liquid metal within the HFIR flux trap and demonstrated the safety basis for continued liquid coolant studies in HFIR.
Wave energy converter arrays: A methodology to assess performance considering the disturbed wave field
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Electrodialysis: An effective methodology to purify the leachate of spent Li-ion batteries
The electrification of transportation and the transition of society towards low or net-zero carbon emissions has led to a skyrocketing global demand for Li-ion batteries. After a service life of three to ten years, Li-ion batteries have less than 80 % of their initial capacities and draw near to the end of their lives for practical utilization. Due to potential supply chain shortages and the value embodied in Li-ion batteries, it is imperative to recycle them, to recover the materials, and to improve the circularity and the sustinability of the industry. How to cost-effectively purify spent batteries while reducing time, energy, and waste emissions is a challenge faced by Li-ion battery recyclers. The first electrochemical membrane reactor reported in our group hasa high selectivity towards lower Cu 2+ , Al 3+ and Fe 3+ ions (<5 ppm) and retains >95% of the Ni 2+ , Co 2+ and Mn 2+ ions in the leachate. An advanced electrochemical membrane reactor was developed in this study. Further, not only does the new reactor have the same selectivity as the original reactor, but other advantages including a faster leachate processing rate (up to 10X faster). The advanced reactor can also directly generate acid at the anode side; eliminating the reactor restoration step. The prominent advantages that this electrodialysis technology has over chemical-precipitation methods include: (1) ion recovery efficiencies do not diminish after removing the impurities, Ni 2+ , Co 2+ and Mn 2+ , even at a higher initial Ni 2+ ion concentrations; in comparison, chemical precipitation has Ni 2+ , Co 2+ and Mn 2+ ion recovery efficiencies reduced significantly when the initial Ni 2+ , Co 2+ and Mn 2+ ion concentrations increase. (2) electrodialysis does not change the concentrations of Ni 2+ , Co 2+ and Mn 2+ ions significantly, but chemical precipitation could reduce Ni 2+ and Co 2+ ions to less than half of their initial values. Through electro-dialyzing the leachate, the H 2 evolution reaction mechanism was found to switch from the Volmer-acid Heyrovsky mechanism to the Volmer-alkaline Heyrovsky mechanism at a pH of around 3.7.
Methodology of Atomic Force Microscopy Visualization of Electrode–Electrolyte Interfaces
Electrochemical atomic force microscopy (EC-AFM) provides unprecedented insights into the microstructure of electrode–electrolyte interfaces during electrochemical reactions. However, performing EC-AFM measurements has many challenges, for example, drift, contamination, and probe degradation. We present solutions to these experimental issues through electrochemical cell design and carefully chosen experimental parameters. The possibility that the probes can react with the interface during scanning, generating false-positive electrochemical dynamics, is discussed as an example of the challenge of high-fidelity EC-AFM measurement. Here, we demonstrate this effect in highly ordered pyrolytic graphite and show that we could use electrochemical control of the AFM probe to enable high-fidelity in situ AFM visualization of solid–liquid interfaces during electrochemical reactions.
Systematic Benchmarking of Climate Models: Methodologies, Applications, and New Directions
As climate models become increasingly complex, there is a growing need to comprehensively and systematically assess model performance with respect to observations. Given the increasing number and diversity of climate model simulations in use, the community has moved beyond simple model intercomparison and toward developing methods capable of benchmarking a large number of simulations against a suite of climate metrics. Here, we present a detailed review of evaluation and benchmarking methods and approaches developed in the last decade, focusing primarily on scientific implications for Coupled Model Intercomparison Project (CMIP) simulations and CMIP6 results that contributed to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Based on this review, we explain the resulting contemporary philosophy of model benchmarking, and provide clear distinctions and definitions of the terms model verification, process validation, evaluation, and benchmarking. While significant progress has been made in model development based on systematic evaluation and benchmarking efforts, some climate system biases still remain. The development of open‐source community software packages has played a fundamental role in identifying areas of significant model improvement and bias reduction. We review the key features of several software packages that have been commonly used over the past decade to evaluate and benchmark global and regional climate models. Additionally, we discuss best practices for the selection of evaluation and benchmarking metrics and for interpreting the obtained results, the importance of selecting suitable sources of reference data and accurate uncertainty quantification.
Response of hypoxia to future climate change is sensitive to methodological assumptions
Climate-induced changes in hypoxia are among the most serious threats facing estuaries, which are among the most productive ecosystems on Earth. Future projections of estuarine hypoxia typically involve long-term multi-decadal continuous simulations or more computationally efficient time slice and delta methods that are restricted to short historical and future periods. We make a first comparison of these three methods by applying a linked terrestrial–estuarine model to the Chesapeake Bay, a large coastal-plain estuary in the eastern United States. Results show that the time slice approach accurately captures the behavior of the continuous approach, indicating a minimal impact of model memory. However, increases in mean annual hypoxic volume by the mid-twenty-first century simulated by the delta approach (+ 19%) are approximately twice as large as the time slice and continuous experiments (+ 9% and + 11%, respectively), indicating an important impact of changes in climate variability. Our findings suggest that system memory and projected changes in climate variability, as well as simulation length and natural variability of system hypoxia, should be considered when deciding to apply the more computationally efficient delta and time slice methods.
Analysis methodology of coherent oscillations in time- and angle-resolved photoemission spectroscopy
Oscillatory signals from coherently excited phonons are regularly observed in ultrafast pump–probe experiments on condensed matter samples. Electron–phonon coupling implies that coherent phonons also modulate the electronic band structure. These oscillations can be probed with energy and momentum resolution using time- and angle-resolved photoemission spectroscopy (trARPES), which reveals the orbital dependence of the electron–phonon coupling for a specific phonon mode. However, a comprehensive analysis remains challenging when multiple coherent phonon modes couple to multiple electronic bands. Complex spectral line shapes due to strong correlations in quantum materials add to this challenge. In this work, we examine how the frequency domain representation of trARPES data facilitates a quantitative analysis of coherent oscillations of the electronic bands. Here, we investigate the frequency domain representation of the photoemission intensity and the first moment of the energy distribution curves. Both quantities provide complementary information and are able to distinguish oscillations of binding energy, linewidth, and intensity. We analyze a representative trARPES dataset of the transition metal dichalcogenide WTe 2 and construct composite spectra, which intuitively illustrate how much each electronic band is affected by a specific phonon mode. We also show how a linearly chirped probe pulse can generate extrinsic artifacts that are distinct from the intrinsic coherent phonon signal.
Development and validation of a humidified CAPS-PMSSA with an improved methodology to calculate the truncation correction factor
Absorbing aerosols play an important role in the Earth’s radiation budget, and current uncertainties associated with their radiative impacts remain substantial. An element of this uncertainty derives from insufficient understanding of the extent to which water, as a coating on absorbing particles, enhances the absorption. Here, we describe and characterize the performance of a cavity-attenuated phase shift single scatter albedo spectrometer (CAPS-PMSSA) system that has been modified to enable concurrent aerosol extinction and scattering measurements, from which aerosol absorption is derived, at relative humidities up to ~90%. The modified instrument is referred to as the humidified CAPS (HCAPS). Additionally, we develop and validate an update to a method to calculate the truncation correction factor, used to correct the scattering measurements, that can account for the effects of particle growth and compositional changes resulting from water uptake. The method can be applied to experiments that use either size-selected or polydisperse aerosol samples of either known or unknown composition. Overall, we show that measurements made with the HCAPS, when processed using the updated truncation correction method, enable accurate measurement of the influence of water uptake on light absorption.
Development and validation of a humidified CAPS-PM SSA with an improved methodology to calculate the truncation correction factor
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The Atacama Cosmology Telescope: R eionization kSZ trispectrum methodology and limits
Patchy reionization generates kinematic Sunyaev–Zel’dovich (kSZ) anisotropies in the cosmic microwave background (CMB). Large-scale velocity perturbations along the line of sight modulate the small-scale kSZ power spectrum, leading to a trispectrum (or four-point function) in the CMB that depends on the physics of reionization. We investigate the challenges in detecting this trispectrum and use tools developed for CMB lensing, such as realization-dependent bias subtraction and cross-correlation based estimators, to counter uncertainties in the instrumental noise and assumed CMB power spectrum. We also find that both lensing and extragalactic foregrounds can impart larger trispectrum contributions than the reionization kSZ signal. We present a range of mitigation methods for both of these sources of contamination, validated on microwave-sky simulations. We use ACT DR6 and Planck data to calculate an upper limit on the reionization kSZ trispectrum from a measurement dominated by foregrounds. The upper limit is about 50 times the signal predicted from recent simulations.
The XMM Cluster Survey: automating the estimation of hydrostatic mass for large samples of galaxy clusters – I. Methodology, validation, and application to the SDSSRM-XCS sample
ABSTRACT We describe features of the X-ray: Generate and Analyse (xga) open-source software package that have been developed to facilitate automated hydrostatic mass ($M_{\rm hydro}$) measurements from XMM X-ray observations of clusters of galaxies. This includes describing how xga measures global, and radial, X-ray properties of galaxy clusters. We then demonstrate the reliability of xga by comparing simple X-ray properties, namely the X-ray temperature and gas mass, with published values presented by the XMM Cluster Survey (XCS), the Ultimate XMM eXtragaLactic survey project (XXL), and the Local Cluster Substructure Survey (LoCuSS). xga measured values for temperature are, on average, within 1 per cent of the values reported in the literature for each sample. xga gas masses for XXL clusters are shown to be ${\sim }$10 per cent lower than previous measurements (though the difference is only significant at the $\sim 1.8\sigma$ level), LoCuSS $R_{2500}$ and $R_{500}$ gas mass re-measurements are 3 per cent and 7 per cent lower, respectively (representing 1.5$\sigma$ and 3.5$\sigma$ differences). Like-for-like comparisons of hydrostatic mass are made to LoCuSS results, which show that our measurements are $10{\pm }3~{{\rm per\ cent}}$ ($19{\pm }7~{{\rm per\ cent}}$) higher for $R_{2500}$ ($R_{500}$). The comparison between $R_{500}$ masses shows significant scatter. Finally, we present new $M_{\rm hydro}$ measurements for 104 clusters from the Sloan Digital Sky Survey (SDSS) DR8 redMaPPer XCS sample (SDSSRM-XCS). Our SDSSRM-XCS hydrostatic mass measurements are in good agreement with multiple literature estimates, and represent one of the largest samples of consistently measured hydrostatic masses. We have demonstrated that xga is a powerful tool for X-ray analysis of clusters; it will render complex-to-measure X-ray properties accessible to non-specialists.
Combining Machine Learning and Comparative Effectiveness Methodology to Study Primary Care Pharmacotherapy Pathways for Veterans With Depression
Our objective is to demonstrate an innovative method combining machine learning with comparative effectiveness research techniques and to investigate a hitherto unstudied question about the effectiveness of common prescribing patterns. For Operation Enduring Freedom/Operation Iraqi Freedom veterans with major depressive disorder, we generate pharmacotherapy pathways (of antidepressants) using process mining and machine learning. We select the medication episodes that were started at subtherapeutic doses by the first assigned primary care physician and observe the paths that those medication episodes follow. Using 2-stage least squares, we test the effectiveness of starting at a low dose and staying low for longer versus ramping up fast while balancing observable and unobservable characteristics of patients and providers through instrumental variables. We leverage predetermined provider practice patterns as instruments. We collected outpatient pharmacy data for selective serotonin reuptake inhibitors and selective norepinephrine reuptake inhibitors, patient and provider characteristics (as control variables), and the instruments for our cohort. All data were extracted for the period between 2006 and 2020. There is a statistically significant positive effect (0.68, 95% CI 0.11–1.25) of “ramping up fast” on engagement in care. When we examine the effect of “ramping up slow”, we see an insignificant negative impact on engagement in care (−0.82, 95% CI −1.89 to 0.25). As expected, the probability of drop-out also seems to have a negative effect on engagement in care (−0.39, 95% CI −0.94 to 0.17). We further validate these results by testing with medication possession ratios calculated periodically as an alternative engagement in care metric. Our findings contradict the “Start low, go slow” adage, indicating that ramping up the dose of an antidepressant faster has a significantly positive effect on engagement in care for our population.
Optimization Methodology of Polar Direct-Drive Illumination for the National Ignition Facility
Improved laser illumination uniformity drives shocks and implosions to create more extreme high energy density environments. Predominantly, the geometry of experiments that can be performed is dictated by the layout of beams at laser facilities, limiting inter-facility and multiscale investigations. This Letter presents the first automated, algorithmic approach for generating illumination configurations for high energy density experiments. The method is demonstrated in comparison to a polar direct drive solid target experiment at the National Ignition Facility. The new illumination configuration is simulated to create greater than ×3 higher peak pressure and almost ×2 higher density by maintaining better shock uniformity. Furthermore, the optimization process is performed with reduced computational expense and isotropic plasma profiles, while accounting for the impact of cross-beam energy transfer.
Elasticity and acoustic velocities of δ − AlOOH at extreme conditions: A methodology assessment
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