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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Emergency department overcrowding and its associated factors at HARME medical emergency center in Eastern Ethiopia

Introduction: Emergency department (ED) overcrowding has become a significant concern as it can lead to compromised patient care in emergency settings. Various tools have been used to evaluate overcrowding in ED. However, there is a lack of data regarding this issue in resource-limited countries, including Ethiopia. This study aimed to validate NEDOCS, assess level of ED overcrowding and identify associated factors at HARME Medical Emergency Center, located in Hiwot Fana Comprehensive Specialized Hospital, Harar, Ethiopia. Methods: A cross-sectional study was conducted at the HARME Medical Emergency Center, Hiwot Fana Comprehensive Specialized Hospital, involving a total of 899 patients during 120 sampling intervals. The area under the receiver operating characteristic curves (AUC) was calculated to evaluate the agreement between objective and subjective assessments of ED overcrowding. A multivariable logistic regression analysis was employed to identify factors associated with ED overcrowding and statistically significant association was declared using 95% confidence level and a p-value < 0.05. Results: The interrater agreement showed a strong correlation with a Cohen's kappa (κ) of 0.80. The National Emergency Department Overcrowding Study Score demonstrated a strong association with subjective assessments from residents and case team nurses, with an AUC of 0.81 and 0.79, respectively. According to residents' perceptions, ED were considered overcrowded 65.8% of the time. Factors significantly associated with ED overcrowding included waiting time for triage (AOR: 2.24; 95% CI: 1.54–3.27), working time (AOR: 2.23; 95% CI: 1.52–3.26), length of stay (AOR: 2.40; 95% CI: 1.27–4.54), saturation level (AOR: 2.35; 95% CI: 1.31–4.20), chronic illness (AOR: 2.19; 95% CI: 1.37–3.53), and abnormal pulse rate (AOR: 1.52; 95% CI: 1.06–2.16). Conclusion: The study revealed that ED were overcrowded approximately two-thirds of the time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Trajectory of Growth of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants in Houston, Texas, January through May 2021, Based on 12,476 Genome Sequences

Certain genetic variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of substantial concern because they may be more transmissible or detrimentally alter the pandemic course and disease features in individual patients. SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist health care system diagnosed from January 1 through May 31, 2021 are reported here. Prevalence of the B.1.1.7 (Alpha) variant increased rapidly and caused 63% to 90% of new cases in the latter half of May. Eleven B.1.1.7 genomes had an E484K replacement in spike protein, a change also identified in other SARS-CoV-2 lineages. Compared with non–B.1.1.7-infected patients, individuals with B.1.1.7 had a significantly lower cycle threshold (a proxy for higher virus load) and significantly higher hospitalization rate. Other variants [eg, B.1.429 and B.1.427 (Epsilon), P.1 (Gamma), P.2 (Zeta), and R.1] also increased rapidly, although the magnitude was less than that in B.1.1.7. Twenty-two patients infected with B.1.617.1 (Kappa) or B.1.617.2 (Delta) variants had a high rate of hospitalization. Breakthrough cases (n = 207) in fully vaccinated patients were caused by a heterogeneous array of virus genotypes, including many not currently designated variants of interest or concern. Finally, in the aggregate, this study delineates the trajectory of SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, TX, and heralds the arrival of B.1.617 variants in the metroplex.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Electron transfer calculations between edge sharing octahedra in hematite, goethite, and annite

A key reaction underlying the charge transport in iron containing oxides, clays, micas is the Fe$^{2+}$-Fe$^{3+}$ exchange reaction between edge-sharing iron octahedra. These reactions facilitate conduction in these minerals by the thermally-activated hopping of small polarons across the lattice. Depending on the mineral and local charge state the small polaron can either encase an electron or hole. The probability for conduction of small polarons depends strongly on the height and adiabicity of the reaction barrier, with larger and more diabatic barriers yielding slow conduction associated with either weak coupling or a large prerequisite rearrangement of the lattice during charge transport. To model these reactions, a first principle electron transfer (ET) method was developed to model the small polaron hopping between the edge-sharing octahedra sites in hematite ($e^{-}$ polaron), goethite ($e^{-}$ polaron), and annite ($h^{+}$ polaron) bulk structures. The ET method is based on electronic structure methods (i.e., plane-wave Density Functional Theory) capable of performing calculations with periodic cells and large size systems efficiently while at the same time being accurate enough to be used in the estimation of the electron-transfer coupling matrix element, $V_{AB}$, and the electron transfer transmission factor, $\kappa_{el}$. Additionally, the calculations confirmed the existence of small polarons in all three minerals, and the reactions were predicted to be strongly adiabatic. It was found that transfer of a hole in the octahedral layer of annite had an adiabatic barrier of $0.311$ eV, and the transfer of an extra electron in hematite and goethite had adiabatic barriers of $0.242$ eV and $0.232$ eV respectively. The electronic coupling parameters,$V_{AB}$, were found to be $0.188$ eV, $0.196$ eV, and $0.102$ eV respectively for hematite, goethite, and annite. While similar bonding topologies pertain, the underlying basis for the differences is the subtle differences in local structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

NF-κB Blockade by NEMO Binding Domain Peptide Ameliorates Inflammation and Neurobehavioral Sequelae After Cranial Radiation Therapy in Juvenile Mice

Cranial radiation therapy (CRT) is a common treatment for pediatric brain tumor patients. However, side effects include significant neurobehavioral dysfunction in survivors. This dysfunction may in part be caused by inflammation, including increased production of tumor necrosis factor alpha (TNFα) and its receptor TNFR1, which can activate the nuclear factor kappa light-chain enhancer of activated B cells (NF-κB). The TNFα blockade abrogates this inflammatory response, although it presents immunologic risks. Thus, modulation of pathway subsets may be preferable. Here, we test whether inhibition of NF-κB activation using an NF-κB essential modulator binding domain (NBD) peptide mitigates CRT-induced neuroinflammation and improves behavioral outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Composite biopolymer electrolytes for high-performance reversible zinc-air batteries

Zinc-air batteries (ZABs) are regarded as one of the most promising candidates for next-generation energy storage systems due to their inherent safety, high energy density, and low cost. In this study, we optimized the composition of gel polymer electrolytes (GPEs), which play a crucial role in enhancing ZAB reversibility due to their water retention capabilities. The GPEs are synthesized using a combination of polyacrylic acid (PAA), polyacrylamide (PAM), and biopolymer kappa-carrageenan (KC), with and without additional additives. Among these, the composite GPE containing KC, PAA, and PAM demonstrated superior ionic conductivity (6.68 mS/cm at 30 °C) and enhanced water retention compared to the PAA–PAM-based GPE. Furthermore, this composite electrolyte operates within a wider electrochemical window of −1.0 V–2.2 V. A bifunctional catalyst, nickel–iron layered double hydroxide (NiFe-LDH), is electrochemically synthesized on a modified activated carbon cloth (CC). The catalyst loading is optimized based on oxygen evolution reaction (OER) performance, showing an overpotential of 555 mV. The oxygen reduction reaction (ORR) occurred at a half-wave potential of 0.620 V, which is lower than that of Pt/C (0.852 V), indicating better catalytic activity. The KC based cell exhibit better cycling stability than PAA–PAM-based GPE. The electrochemical performance of ZAB cells is evaluated under various atmospheres: ambient air and humid conditions and temperatures. Notably, in a humid environment, the cells achieved extended cycling stability, operating for over 500 h—significantly longer than under open-air conditions. Overall, this study highlights the importance of tailored GPE design and efficient bifunctional catalysts to enhance the performance and longevity of zinc-air batteries for long-duration energy storage applications.

Catalyst↗
DOE OSTI2021

Predicting measures of soil health using the microbiome and supervised machine learning

Soil health encompasses a range of biological, chemical, and physical soil properties that sustain the commercial and ecological value of agroecosystems. Monitoring soil health requires a comprehensive set of diagnostics that can be cost-prohibitive for routine analyses. The soil microbiome provides a rich source of information about soil properties, which can be assayed in a high-throughput, cost-effective way. We evaluated the accuracy of random forest (RF) and support vector machine (SVM) regression and classification models in predicting 12 measures of soil health, tillage status, and soil texture from 16S rRNA gene amplicon data with an operationally relevant sample set. We validated the efficacy of the best performing models against independent datasets and also tested best practices for processing microbiome data for use in machine learning. Soil health metrics could be predicted from microbiome data with the best models achieving a Kappa value of ~0.65, for categorical assessments, and a R2 value of ~0.8, for numerical scores. Biological health ratings were better predicted than chemical or physical ratings. Validation with independent datasets revealed that models had general predictive value for soil properties, including yield. The ecological profiles of several taxa important for model accuracy matched the observed relationships with soil health, including Pyrinomonadaceae, Nitrososphaeraceae, and Candidatus Udeaobacter. Models trained at the highest taxonomic resolution proved most accurate, with losses in accuracy resulting from rarefying, sparsity filtering, and aggregating at higher taxonomic ranks. Furthermore, our study provides the groundwork for developing scalable technology to use microbiome-based diagnostics for the assessment of soil health.

16S rRNA gene↗
DOE OSTI2021

AGTR1 blocker attenuates activation of Tenon's capsule fibroblasts after glaucoma filtration surgery via the NF-κB signaling pathway

Activation of Tenon's capsule fibroblasts limits the success rate of glaucoma filtration surgery (GFS), the most efficacious therapy for patients with glaucoma. Angiotensin type 1 receptor (AGTR1) is involved in tissues remodeling and fibrogenesis. However, whether AGTR1 is involved in the progress of fibrogenesis after GFS is not fully elucidated. The aim of this study was to investigate the role of an AGTR1 in scar formation after GFS and the potential anti-fibrosis effect of AGTR1 blocker. AGTR1 expression level was increased in subconjunctival tissues in a rat model of GFS and transforming growth factor-beta 2 (TGF-β2)-induced human Tenon's capsule fibroblasts (HTFs). AGTR1 blocker treatment suppressed TGF-β2-induced HTF migration and α-smooth muscle actin (α-SMA) and fibronectin (FN) expression. AGTR1 blocker treatment also attenuated collagen deposition and α-SMA and FN expression in subconjunctival tissues of the rat model after GFS. Moreover, AGTR1 blocker decreased TGF-β2-induced P65 phosphorylation, P65 nuclear translocation, and nuclear factor kappa B (NF-κB) luciferase activity. Additionally, BAY 11–7082 (an NF-κB inhibitor) significantly suppressed HTF fibrosis. In conclusion, our results indicate that AGTR1 is involved in scar formation after GFS. The AGTR1 blocker attenuates subconjunctival fibrosis after GFS by inhibiting the NF-κB signaling pathway. These findings indicate that targeting AGTR1 is a potential approach to attenuate fibrosis after GFS.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

FOXM1-activated SIRT4 inhibits NF-κB signaling and NLRP3 inflammasome to alleviate kidney injury and podocyte pyroptosis in diabetic nephropathy

Highlights: • FOXM1 is downregulated in kidney tissues of patients with DN. • Overexpression of FOXM1 alleviates kidney injury in DN modeled mice. • Overexpression of FOXM1 reduces pyroptosis of HG-treated podocytes. • FOXM1 activates SIRT4 to inhibit the NFκB pathway and the NLRP3 inflammasome. • Downregulation of SIRT4 blocks the protective roles of FOXM1 in podocytes and mice. Forkhead box M1 (FOXM1) has been reported to play a protective role against acute kidney injury by driving tubular regeneration. This study aims to probe the function of FOXM1 in diabetic nephropathy (DN) and the molecules involved. FOXM1 was poorly expressed in DN-diseased kidney tissues. A murine model of DN was established, and podocytes cells (MPC5) were treated with high-glucose (HG) for in vitro studies. FOXM1 overexpression improved kidney function and reduced pathological changes in mice, and it increased the expression of the podocyte marker Nephrin in kidney tissues. In vitro, FOXM1 increased viability and reduced pyroptosis of the HG-treated MPC5 cells, and it elevated the expression of the podocyte marker Nephrin whereas reduced the expression of pyroptosis-related NLRP3 inflammasome and cleaved caspase 1. FOXM1 bound to the promoter of sirtuin 4 (SIRT4) to induce transcriptional activation. Downregulation of SIRT4 blocked the protective roles of FOXM1 both in vivo and in vitro. Phosphorylation of nuclear factor-kappa B (NF-κB) in HG-treated cells was suppressed by FOXM1 but restored after SIRT4 inhibition. In conclusion, this study suggested that FOXM1 transcriptionally activates SIRT4 and inhibits NF-κB signaling and the NLRP3 inflammasome to alleviate kidney injury and podocyte pyroptosis in DN.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Development of compact tokamak fusion reactor use cases to inform future transport studies

The OMFIT STEP (Meneghini et al. , Nucl. Fusion , vol. 10, 2020, p. 1088) workflow has been used to develop inductive and steady-state H-mode core plasma scenario use cases for a $B_0 = 8 \, {\rm T}$ , $R_0 = 4 \, {\rm m}$ machine to help guide and inform future higher-fidelity studies of core transport and confinement in compact tokamak reactors. Both use cases are designed to produce 200 MW or more of net electric power in an up-down symmetric plasma with minor radius $a = 1.4 \, {\rm m}$ , elongation $\kappa = 2.0$ , triangularity $\delta = 0.5$ and effective charge $Z_{{\rm eff}} \simeq 2$ . Additional considerations based on the need for compatibility of the core with reactor-relevant power exhaust solutions and external actuators were used to guide and constrain the use case development. An extensive characterization of core transport in both scenarios is presented, the most important feature of which is the extreme sensitivity of the results to the quantitative stiffness level of the transport model used as well as the predicted critical gradients. This sensitivity is shown to arise from different levels of transport stiffness exhibited by the models, combined with the gyroBohm-normalized fluxes of the predictions being an order of magnitude larger than other H-mode plasmas. Additionally, it is shown that although heating in both plasmas is predominantly to the electrons and collisionality is low, the plasmas remain sufficiently well coupled for the ions to carry a significant fraction of the thermal transport. As neoclassical transport is negligible in these conditions, this situation inherently requires long-wavelength ion gyroradius-scale turbulence to be the dominant transport mechanism in both plasmas. These results are combined with other basic considerations to propose a simple heuristic model of transport in reactor-relevant plasmas, along with simple metrics to quantify coupling and core transport properties across burning and non-burning plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Improved Boundary Conditions for Coupled Geospace Models: An Application in Modeling Spacecraft Surface Charging Environment

Abstract Spacecraft surface charging in the inner magnetosphere often occurs in the pre‐midnight to the dawn sector when electron fluxes of tens of keV increase. Inner magnetosphere ring current models can be used to simulate/predict the spacecraft surface charging environment, with their outer boundary conditions specified either based on observations or provided by other models, such as MHD models. In the latter approach, using MHD quantities, the flux spectrum at the outer boundary is commonly assumed to follow a Kappa or Maxwellian distribution function. Such a method however often departs greatly from the realistic spectrum at E < tens of keV, a crucial energy range in the surface charging anomaly. In order to achieve a better representation of the surface charging environment, we propose to combine the MHD‐parameterized flux spectrum with an empirical electron flux model of E < 40 keV to set the electron flux boundary condition. Results indicate that as opposed to the case where the MHD‐parameterized flux distribution is solely used at the model boundary, simulations with the new boundary condition yields a more intense surface charging environment. The integrated electron flux between 10 < E < 50 keV, a measure of the severity of the surface charging environment, is significantly enhanced by 1‐2 orders of magnitude, leading to a much better agreement with Van Allen Probes measurements. This study hence demonstrates a reasonable solution to the setting of outer boundary conditions for inner magnetosphere models and is recommended for coupled geospace circulation models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Comprehensive Characterization of Water Group Ion Composition and Distributions in Saturn's Magnetosphere With Cassini Plasma Spectrometer Data

Saturn's magnetosphere is continuously supplied with neutrals from the Enceladus plume and the icy rings, which undergo ionization and charge-exchange to form a complex water-group plasma environment. While the Cassini Plasma Spectrometer (CAPS) instrument has provided extensive compositional information, detailed separation of individual water-group ion species in time-of-flight (TOF) data has not previously been achieved. In this study, we perform forward modeling of CAPS-IMS energy-per-charge (E/Q) and TOF spectra obtained between 2004 and 2012 to resolve O + , OH + , H 2 O + , and H 3 O + and to characterize their plasma properties, including number density, temperature, and thermodynamic κ. Our results demonstrate that O + is the dominant thermal ion species throughout Saturn's magnetosphere, comprising up to ∼70% of the total ion population beyond ∼5 Saturn radii (R S ). In contrast, molecular ions such as OH + , H 2 O + , and H 3 O + dominate closer to Enceladus but rapidly dissociate into atomic ions between ∼5 and 10 R S . This radial region is also characterized by the steepest increase in plasma flow speed, which rises from ∼40% to ∼80% of rigid corotation. Simultaneously, ion velocity distributions approach Maxwell–Boltzmann equilibrium, as indicated by high kappa values. These findings provide new constraints on the ion–neutral chemistry that regulates the balance between molecular and atomic ions in Saturn's magnetosphere. They also emphasize the critical role of the 5–10 R S region as a transition zone for both plasma composition and dynamics. Our results refine previous CAPS-based studies and underscore the need to incorporate seasonal variability and ionospheric coupling into future global models of Saturn's plasma environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Robust production of monovalent bispecific IgG antibodies through novel electrostatic steering mutations at the C H 1-C λ interface

Bispecific antibodies represent an increasingly large fraction of biologics in therapeutic development due to their expanded scope in functional capabilities. Asymmetric monovalent bispecific IgGs (bsIgGs) have the additional advantage of maintaining a native antibody-like structure, which can provide favorable pharmacology and pharmacokinetic profiles. The production of correctly assembled asymmetric monovalent bsIgGs, however, is a complex engineering endeavor due to the propensity for non-cognate heavy and light chains to mis-pair. Previously, we introduced the DuetMab platform as a general solution for the production of bsIgGs, which utilizes an engineered interchain disulfide bond in one of the C H 1-C L domains to promote orthogonal chain pairing between heavy and light chains. While highly effective in promoting cognate heavy and light chain pairing, residual chain mispairing could be detected for specific combinations of Fv pairs. Here, we present enhancements to the DuetMab design that improve chain pairing and production through the introduction of novel electrostatic steering mutations at the C H 1-C L interface with lambda light chains (C H 1-C λ ). These mutations work together with previously established charge-pair mutations at the C H 1-C L interface with kappa light chains (C H 1-C κ ) and Fab disulfide engineering to promote cognate heavy and light chain pairing and enable the reliable production of bsIgGs. Importantly, these enhanced DuetMabs do not require engineering of the variable domains and are robust when applied to a panel of bsIgGs with diverse Fv sequences. We present a comprehensive biochemical, biophysical, and functional characterization of the resulting DuetMabs to demonstrate compatibility with industrial production benchmarks. Overall, this enhanced DuetMab platform substantially streamlines process development of these disruptive biotherapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein–protein interaction network

Abstract Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover new synergistic drug combinations due to the combinatorial explosion. Deep learning technology holds immense promise for better prediction of in vitro synergistic drug combinations for certain cell lines. In methods applying such technology, omics data are widely adopted to construct cell line features. However, biological network data are rarely considered yet, which is worthy of in-depth study. In this study, we propose a novel deep learning method, termed PRODeepSyn, for predicting anticancer synergistic drug combinations. By leveraging the Graph Convolutional Network, PRODeepSyn integrates the protein–protein interaction (PPI) network with omics data to construct low-dimensional dense embeddings for cell lines. PRODeepSyn then builds a deep neural network with the Batch Normalization mechanism to predict synergy scores using the cell line embeddings and drug features. PRODeepSyn achieves the lowest root mean square error of 15.08 and the highest Pearson correlation coefficient of 0.75, outperforming two deep learning methods and four machine learning methods. On the classification task, PRODeepSyn achieves an area under the receiver operator characteristics curve of 0.90, an area under the precision–recall curve of 0.63 and a Cohen’s Kappa of 0.53. In the ablation study, we find that using the multi-omics data and the integrated PPI network’s information both can improve the prediction results. Additionally, the case study demonstrates the consistency between PRODeepSyn and previous studies.

Wang, Xiaowen↗
DOE OSTI2024

Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living

Abstract Age assessment of the living is a fundamental procedure in the process of human identification, in order to guarantee fair treatment of individuals, which has ethical, civil, legal, and medical repercussions. The careful selection of the appropriate methods requires evaluation of several parameters: accuracy, precision of the method, as well as its reproducibility. The approach proposed by Mincer et al. adapted from Demirjian et al. exploring third molar mineralisation, is one of the most frequently considered for age estimation of the living. Thus, this work aims to assess potential bias in the data collection when applying the classification stages for dental mineralisation adapted by Mincer et al. A total of 102 orthopantomographs, of clinical origin, belonging to individuals aged between 12 and 25 years ($ \bar{\textit x} $ = 20.12 years, SD = 3.49 years; 65 females, 37 males, all of Portuguese nationality) were included and a retrospective analysis performed by five observers with different levels of experience (high, average, and basic). The performance and agreement between five observers were evaluated using Weighted Cohen’s Kappa and the Intraclass Correlation Coefficient. To access the influence of impaction on third molar classification, variables were tested using ordinal logistic regression Generalised Linear Model. It was observed that there were variations in the number of teeth identified among the observers, but the agreement levels ranged from moderate to substantial (0.4–0.8). Upon closer examination of the results, it was observed that although there were discernible differences between highly experienced observers and those with less experience, the gap was not as significant as initially hypothesised, and a greater disparity between the classifications of the upper (0.24–0.49) and lower third molars (>0.55) was observed. When bone superimposition is present, the classification process is not significantly influenced; however, variation in teeth angulation affects the assessment. The results suggest that with an efficient preparation, the level of experience as a factor can be overcome. Mincer and colleague's classification system can be replicated with ease and consistency, even though the classification of upper and lower third molars presents distinct challenges.

de Oliveira Santos, Inês (ORCID:0000000267324347)↗
DOE OSTI2020

Testing general relativity on cosmological scales at redshift z ∼ 1.5 with quasar and CMB lensing

ABSTRACT We test general relativity (GR) at the effective redshift $\bar{z} \sim 1.5$ by estimating the statistic EG, a probe of gravity, on cosmological scales $19 - 190\, h^{-1}{\rm Mpc}$. This is the highest redshift and largest scale estimation of EG so far. We use the quasar sample with redshifts 0.8 < z < 2.2 from Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 as the large-scale structure (LSS) tracer, for which the angular power spectrum $C_\ell ^{qq}$ and the redshift-space distortion parameter β are estimated. By cross-correlating with the Planck 2018 cosmic microwave background (CMB) lensing map, we detect the angular cross-power spectrum $C_\ell ^{\kappa q}$ signal at $12\, \sigma$ significance. Both jackknife resampling and simulations are used to estimate the covariance matrix (CM) of EG at five bins covering different scales, with the later preferred for its better constraints on the covariances. We find EG estimates agree with the GR prediction at $1\, \sigma$ level over all these scales. With the CM estimated with 300 simulations, we report a best-fitting scale-averaged estimate of $E_G(\bar{z})=0.30\pm 0.05$, which is in line with the GR prediction $E_G^{\rm GR}(\bar{z})=0.33$ with Planck 2018 CMB + BAO matter density fraction Ωm = 0.31. The statistical errors of EG with future LSS surveys at similar redshifts will be reduced by an order of magnitude, which makes it possible to constrain modified gravity models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Cross-correlation of Planck CMB lensing with DESI-like LRGs

ABSTRACT Cross-correlations between the lensing of the cosmic microwave background (CMB) and other tracers of large-scale structure provide a unique way to reconstruct the growth of dark matter, break degeneracies between cosmology and galaxy physics, and test theories of modified gravity. We detect a cross-correlation between Dark Energy Spectroscopic Instrument (DESI)-like luminous red galaxies (LRGs) selected from DECam Legacy Survey imaging and CMB lensing maps reconstructed with the Planck satellite at a significance of S/N = 27.2 over scales ℓmin = 30, ℓmax = 1000. To correct for magnification bias, we determine the slope of the LRG cumulative magnitude function at the faint limit as s = 0.999 ± 0.015, and find corresponding corrections of the order of a few per cent for $C^{\kappa g}_{\ell }, C^{gg}_{\ell }$ across the scales of interest. We fit the large-scale galaxy bias at the effective redshift of the cross-correlation zeff ≈ 0.68 using two different bias evolution agnostic models: a HaloFit times linear bias model where the bias evolution is folded into the clustering-based estimation of the redshift kernel, and a Lagrangian perturbation theory model of the clustering evaluated at zeff. We also determine the error on the bias from uncertainty in the redshift distribution; within this error, the two methods show excellent agreement with each other and with DESI survey expectations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Spectroscopic diagnostics of high-temperature plasma in stellar coronae using Fe XXIV-XXIV K-shell lines with XRISM

The RS CVn type binary star GT Muscae was observed during its quiescence using the Resolve X-ray microcalorimeter spectrometer onboard XRISM. The main and satellite lines of the Fe XXIV-XXIV K-shell transitions were resolved for the first time from stellar sources. We conducted line ratio analysis to investigate any deviations from collisional ionization equilibrium and Maxwell electron energy distribution with a single temperature. By using five combinations of direct excitation lines and dielectronic recombination satellite lines in three line complexes (Fe He$\alpha$, Ly$\alpha$, and He$\beta$), we found that the plasma is well characterized by two-temperature thermal plasmas with temperatures of 1.7 and 4.3 keV, which is consistent with thermal broadening of Fe xxv, and the broad-band fitting results in the 1.7–10 keV band. Other forms of deviation from a single-temperature plasma, such as different ionization and electron temperatures or the $\kappa$ distribution for the electron energy distributions, are not favored, which is reasonable for stellar coronae at quiescence. This study demonstrates the utility of the Fe K-shell line ratio diagnostics to probe plasma conditions using X-ray microcalorimeters.

X-rays: stars↗
DOE OSTI2021

Probing the effect of magnetic field on charge order in the quasi-two-dimensional Mott insulator κ - (ET) 2 Hg(SCN) 2 Cl

Molecular-based quasi-two-dimensional charge-ordered Mott insulators can possess both spin S = 1/2 and an electric dipole degree of freedom residing on each (BEDT - TTF) 2 lattice site. There exists a theoretical proposal for a magnetoelectric effect in such a material, which can manifest itself as a sensitivity of charge distribution on (BEDT - TTF) 2 dimers to the magnetic field. Here in this work, we used Raman scattering spectroscopy in the magnetic field up to 31 T applied perpendicular to the two-dimensional triangular lattice planes to probe a magnetoelectric effect in $\kappa$ - (ET) 2 H g (SCN) 2 Cl. This is a model compound, which shows charge order and antiferromagnetic correlations at temperatures below 30 K. We discuss possible reasons for the absence of an observable magnetoelectric effect in the probed temperature and magnetic field ranges.

36 MATERIALS SCIENCE↗