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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

On the product phases and the reaction kinetics of carbothermic reduction of UO 2 +C at relatively low temperatures

The synthesis of UC using carbothermic reduction of UO 2 and C mixtures has been well studied at high temperatures. However, the product phase behavior of carbothermic reduction at low temperatures (≤1773 K) is not well studied. Such a study is important as low temperatures permit single phase UC synthesis without forming secondary higher carbides, and it further supports the knowledge base of the process that needs to be used for transuranic elements such as plutonium that have high vapor pressures at elevated temperatures. Therefore, a low temperature carbothermic reduction of two different C/UO 2 molar ratios under inert and reducing environments have been studied here. Two different sample holding crucibles, alumina (Al 2 O 3 ) and graphite, were also used here to differentiate the hypostoichiometric (UC 1-a ) and oxygen dissolved (UC 1-x O x ) uranium monocarbide phases adding more details on the two systems. Also, the reaction kinetics involved in the formation of UC via the carbothermic reduction of UO 2 +C using product phases instead of evolved gases such as carbon monoxide is reported here. Under inert atmospheres but with significant oxygen partial pressures, the low temperature carbothermic reduction of UO 2 +C produced up to 90 wt.% UC 1-x O x type oxycarbides as was confirmed by Xray powder diffraction. Reducing Ar-4%H 2 environments at these temperatures were not successful in synthesizing UC as it reduces the amount of C required for the carbothermic reduction, leaving UC phase at a non-equilibrium state. Inert atmospheres with low or negligible oxygen partial pressures on the other hand produced near stoichiometric UC at high phase purity, especially at 1673 – 1773 K temperature range. An activation energy of 377±75 kJmol -1 was also calculated using product phase concentrations of the carbothermic reduction of UO 2 +C under these inert Ar (g) atmospheres.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications

Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Spatial variability of aerosol iron mineralogy and oxidation states over the Arctic Ocean

The mineralogy and oxidation state of aerosol iron (Fe) play important roles in controlling aerosol Fe solubility and consequent bioavailability in seawater. In this study, the spatial variability of Fe mineralogy and oxidation states in aerosols collected during the US GEOTRACES Western Arctic cruise (GN01) were determined using synchrotronbased X-ray absorption near edge structure (XANES) spectroscopy. Both Fe(II) minerals (biotite, ilmenite) and Fe (III) minerals (ferrihydrite, hematite, Fe(III) phosphate) were found in these samples. However, aerosol Fe mineralogy and solubility observed during this cruise varied spatially and can be grouped into three clusters based on the air masses that affected aerosols collected in different regions: (1) biotite-enriched particles (87 % biotite, 13 % hematite) with the air masses passing over Alaska, showing relatively low Fe solubility (4.0 +/- 1.7 %); (2) ferrihydrite-enriched particles (82 % ferrihydrite, 18 % ilmenite) collected in the remote Arctic air, showing relatively high Fe solubility (9.6 +/- 3.3 %); (3) the fresh dust derived from North America and Siberia, primarily dominated by hematite (41 % hematite, 25 % Fe(III) phosphate, 20 % biotite, 13 % ferrihydrite), showing relatively low Fe solubility (5.1 +/- 3.5). A significant positive correlation was found between Fe oxidation state and Fe fractional solubility, suggesting that long-range transport could modify iron (hydr) oxide such as ferrihydrite through atmospheric processing, influencing aerosol Fe solubility and consequently Fe bioavailability in the remote Arctic Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Molecular Characterization of Organophosphorus Compounds in Wildfire Smoke Using 21-T Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry

Here, we present a detailed molecular characterization of organophosphorus compounds in ambient organic aerosol influenced by wildfire smoke. Biomass burning organic aerosol (BBOA) is an important source of phosphorus (P) to surface waters, where even a small imbalance in the P flux can lead to substantial effects on water quality, such as eutrophication, algal blooms, and oxygen depletion. We aimed to exploit the ultrahigh resolving power, mass accuracy, and sensitivity of Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS) to explore the molecular composition of an ambient BBOA sample collected downwind of Pacific Northwest wildfires. The 21-T FT-ICR MS yielded 10533 distinct formulae, which included molecular species comprising C, H, O, and P with or without N, i.e., organophosphorus compounds that have long been quantified in wildfire smoke but have not yet been characterized at the molecular level. The lack of detailed molecular characterization of organophosphorus compounds in BBOA is primarily due to their inherently low concentrations in aerosols and poor ionization efficiency in complex mixtures. We demonstrate that the exceptional sensitivity of the 21-T FT-ICR MS allows qualitative analysis of a previously uncharacterized fraction of BBOA without its selective concentration from the organic matrix, exemplifying the need for ultrahigh-resolution tools for a more detailed and accurate molecular depiction of such complex mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A global soil plasmidome resource unveils functional and ecological roles of plasmids in soil microbiomes

Plasmids play significant roles in microbial adaptation to ecosystems, yet their dynamics remain poorly understood due to identification challenges. We present the Global Soil Plasmidome Resource (GSPR), a comprehensive dataset of 98,728 plasmid sequences amassed from 6860 terrestrial microbial communities and isolates. We explore this resource through various computational approaches, including phylogenetic diversity analysis, host prediction, and extensive functional annotation, to understand the contribution of plasmids to the genetic and functional diversity in soil, correlating these findings with sample type, as well as the soil habitat they were retrieved from. Our analysis reveals insights into plasmid-encoded functions such as effector modules, quorum sensing, and stress resistance, which may contribute to their persistence and microbial adaptation in soil. Furthermore, CRISPR analysis suggests a prevalent role of these elements related to intra-plasmid competition. By contrasting plasmids from cultivated and uncultivated organisms, we identify important functions that expand existing knowledge of plasmid roles in these habitats. This study represents a notable step forward in elucidating plasmid diversity and function within soil microbiomes and establishes a foundational framework for exploring their roles in natural environments.

Fiamenghi, Mateus B↗
DOE OSTI2023

BeyondPlanck: XII. Cosmological parameter constraints with end-to-end error propagation

We present cosmological parameter constraints estimated using the Bayesian BEYONDPLANCK analysis framework. This method supports seamless end-to-end error propagation from raw time-ordered data onto final cosmological parameters. As a first demonstration of the method, we analyzed time-ordered Planck LFI observations, combined with selected external data (WMAP 33–61 GHz, Planck HFI DR4 353 and 857 GHz, and Haslam 408 MHz) in the form of pixelized maps that are used to break critical astrophysical degeneracies. Overall, all the results are generally in good agreement with previously reported values from Planck 2018 and WMAP, with the largest relative difference for any parameter amounting about 1σ when considering only temperature multipoles between 30 ≤ ℓ ≤ 600. In cases where there are differences, we note that the BEYONDPLANCK results are generally slightly closer to the high-ℓ HFI-dominated Planck 2018 results than previous analyses, suggesting slightly less tension between low and high multipoles. Using low-ℓ polarization information from LFI and WMAP, we find a best-fit value of τ = 0.066 ± 0.013, which is higher than the low value of τ = 0.052 ± 0.008 derived from Planck 2018 and slightly lower than the value of 0.069 ± 0.011 derived from the joint analysis of official LFI and WMAP products. Most importantly, however, we find that the uncertainty derived in the BEYONDPLANCK processing is about 30 % greater than when analyzing the official products, after taking into account the different sky coverage. We argue that this uncertainty is due to a marginalization over a more complete model of instrumental and astrophysical parameters, which results in more reliable and more rigorously defined uncertainties. We find that about 2000 Monte Carlo samples are required to achieve a robust convergence for a low-resolution cosmic microwave background (CMB) covariance matrix with 225 independent modes, and producing these samples takes about eight weeks on a modest computing cluster with 256 cores.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Phosphorus chemistry in plant charcoal: interplay between biomass composition and thermal condition

Background Vegetation fire may change Phosphorus (P) cycling in terrestrial ecosystems through converting biomass into fire residues. Aim The aim of this study was to understand the chemistry and mobility of P in fire residues to help reveal P thermochemistry during biomass burning and post-fire P cycling. Methods A combination of sequential extraction, liquid 31P NMR and P K-edge XANES was used to obtain quantitative P speciation and explain P solubilisation behaviours of charcoal. Key results Despite varying diverse P species existing in raw biomass, only two P structural moieties – orthophosphate and pyrophosphate – were identified in charcoal. However, relative abundance of pyrophosphate differs greatly among charcoal samples from different biomass types, ranging between 0 and 40% of total extractable P. Although P K-edge XANES data indicates abundant soluble phosphate minerals, most P (70–90%) is likely occluded physically in the charcoal. The bicarbonate-extractable P (the Olsen-P) varies significantly and cannot be explained by surface P concentration or elemental stoichiometry alone. Conclusion and implications The results suggest the importance of starting biomass P speciation (i.e. molecular structure and complexation environment) and thermal conditions in controlling P speciation and availability in charcoal. The different P chemistry between charcoal and ash suggests the importance of fire types and severity in disturbing the P cycle.

Forestry↗
DOE OSTI2020

The Adaptive Potential of the Middle Domain of Yeast Hsp90

Abstract The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

Cote-Hammarlof, Pamela A.↗
DOE OSTI2024

RhizoMAP: a comprehensive, nondestructive, and sensitive platform for metabolic imaging of the rhizosphere

Elucidating the intricate structural organization and spatial gradients of biomolecular composition within the rhizosphere is critical to understanding important biogeochemical processes, which include the mechanisms of root-microbe interactions for maintaining sustainable plant ecosystem services. While various analytical methods have been developed to assess the spatial heterogeneity within the rhizosphere, a comprehensive view of the fine distribution of metabolites within the root-soil interface has remained a significant challenge. This is primarily due to the difficulty of maintaining the original spatial organization during sample preparation without compromising its molecular content.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study

Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study. This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset. This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets. Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19). To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Predictions for the Detectability of Milky Way Satellite Galaxies and Outer-Halo Star Clusters with the Vera C. Rubin Observatory

We predict the sensitivity of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) to faint, resolved Milky Way satellite galaxies and outer-halo star clusters. We characterize the expected sensitivity using simulated LSST data from the LSST Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) accessed and analyzed with the Rubin Science Platform as part of the Rubin Early Science Program. We simulate resolved stellar populations of Milky Way satellite galaxies and outer-halo star clusters over a wide range of sizes, luminosities, and heliocentric distances, which are broadly consistent with expectations for the Milky Way satellite system. We inject simulated stars into the DC2 catalog with realistic photometric uncertainties and star/galaxy separation derived from the DC2 data itself. We assess the probability that each simulated system would be detected by LSST using a conventional isochrone matched-filter technique. We find that assuming perfect star/galaxy separation enables the detection of resolved stellar systems with $M_V$ = 0 mag and $r_{1/2}$ = 10 pc with >50% efficiency out to a heliocentric distance of ~250 kpc. Similar detection efficiency is possible with a simple star/galaxy separation criterion based on measured quantities, although the false positive rate is higher due to leakage of background galaxies into the stellar sample. When assuming perfect star/galaxy classification and a model for the galaxy-halo connection fit to current data, we predict that 89 +/- 20 Milky Way satellite galaxies will be detectable with a simple matched-filter algorithm applied to the LSST wide-fast-deep data set. Different assumptions about the performance of star/galaxy classification efficiency can decrease this estimate by ~7%-25%, which emphasizes the importance of high-quality star/galaxy separation for studies of the Milky Way satellite population with LSST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Genetic Complexity of CC5 Staphylococcus aureus Isolates Associated with Sternal Bursitis in Chickens: Antimicrobial Resistance, Virulence, Plasmids, and Biofilm Formation

Sternal bursitis, a common inflammatory condition in poultry, poses significant challenges to both animal welfare and public health. This study aimed to investigate the prevalence, antimicrobial resistance, and genetic characteristics of Staphylococcus aureus isolates associated with sternal bursitis in chickens. Ninety-eight samples were collected from affected chickens, and 24 S. aureus isolates were identified. Antimicrobial susceptibility testing revealed resistance to multiple agents, with a notable prevalence of aminoglycoside resistance genes. Whole genome sequencing elucidated the genetic diversity and virulence profiles of the isolates, highlighting the predominance of clonal complex 5 (CC5) strains. Additionally, biofilm formation assays demonstrated moderate biofilm production capacity among the isolates. These findings underscore the importance of vigilant monitoring and targeted interventions to mitigate the impact of sternal bursitis in poultry production systems.

Silva, Vanessa (ORCID:0000000194068433)↗
DOE OSTI2021

Forward Modeling Populations of Flares from Tidal Disruptions of Stars by Supermassive Black Holes

Detections of the tidal disruption flares (TDFs) of stars by supermassive black holes (SMBHs) are rapidly accumulating as optical surveys improve. These detections may provide constraints on SMBH demographics, stellar dynamics, and stellar evolution in galaxies. To maximize this scientific impact, we require a better understanding of how astrophysical parameters interact with survey selection effects in setting the properties of detected flares. In this study, we develop a framework for modeling the distributions of optical TDF detections in surveys across attributes of the host galaxies and the flares themselves. This model folds in effects of the stellar disruption rate in each galaxy, the flare luminosity and temperature distributions, the effects of obscuration and reddening by dust in the host galaxy, and survey selection criteria. We directly apply this model to the sample of TDFs detected by the Zwicky Transient Facility, and find that the overall flare detection rate is in line with simple theoretical expectation. The model can also reproduce the distribution of total stellar mass and redshift of the host galaxies, but fails to match all details of the detected flares, such as their luminosity and temperature distributions. We also find that dust obscuration likely plays an important role in suppressing the TDF detection rate in star-forming galaxies. While we do not find that the unusual preference of TDFs to have hosts in post-starburst galaxies in the "green valley" can be entirely explained by selection effects, our model can help to quantify the true rate enhancement in those galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Discretization limits of lattice‐Boltzmann methods for studying immiscible two‐phase flow in porous media

Summary Digital images of porous media often include features approaching the image resolution length scale. The behavior of numerical methods at low resolution is therefore important even for well‐resolved systems. We study the behavior of the Shan‐Chen (SC) and Rothman‐Keller (RK) multicomponent lattice‐Boltzmann models in situations where the fluid‐fluid interfacial radius of curvature and/or the feature size of the medium approaches the discrete unit size of the computational grid. Various simple, small‐scale test geometries are considered, and a drainage test is also performed in a Bentheimer sandstone sample. We find that both RK and SC models show very high ultimate limits: in ideal conditions the models can simulate static fluid configuration with acceptable accuracy in tubes as small as three lattice units across for RK model (six lattice units for SC model) and with an interfacial radius of curvature of two lattice units for RK and SC models. However, the stability of the models is affected when operating in these extreme discrete limits: in certain circumstances the models exhibit behaviors ranging from loss of accuracy to numerical instability. We discuss the circumstances where these behaviors occur and the ramifications for larger‐scale fluid displacement simulations in porous media, along with strategies to mitigate the most severe effects. Overall we find that the RK model, with modern enhancements, exhibits fewer instabilities and is more suitable for systems of low fluid‐fluid miscibility. The shortcomings of the SC model seem to arise predominantly from the high, strongly pressure‐dependent miscibility of the two fluid components.

Li, Zhe↗
DOE OSTI2022

Designing Ceria/Alumina for Efficient Trapping of Platinum Single Atoms

Cerium oxide (ceria) has been shown to be very effective at trapping platinum atoms, due to formation of stable surface complexes at step edges, where coordinatively unsaturated cerium cations are present. But ceria loses its effectiveness when heated to high temperatures, due to loss of surface area and growth in particle size associated with sintering of the oxide. Being a rare-earth, and with limited supplies worldwide, it is important to develop methods to improve the effectiveness of ceria as a catalyst support. Here we explore the performance for trapping Pt atoms when the ceria is supported on a high surface area alumina carrier. This helps create a more sustainable catalyst formulation, especially if we can retain the high dispersion of Pt seen on ceria supports. For this work, we studied the atom trapping efficacy of ceria/alumina samples with increasing ceria content (8 wt% - 50%) and contrasted the behavior with pure ceria. Electron microscopy reveals that when dispersed on alumina, ceria is present in the form of crystalline nanoparticles as well as isolated cerium ions. These two forms of ceria differ markedly in their ability to trap Pt atoms. Atomically dispersed cerium is present in the form of Ce 3+ cations on alumina, however this form of ceria is not effective for trapping Pt atoms. Our results show that the atom trapped Pt resides primarily on crystalline ceria nanoparticles. CO oxidation was used as a probe reaction to evaluate the performance of these Pt AT /ceria-alumina catalysts. As a result, we conclude that over the range of ceria loadings we investigated, 50% ceria/alumina represents the optimal catalyst support for achieving high surface area and atom trapping efficiency while helping reduce the total ceria content in this catalyst system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Stochastic optimization of a uranium oxide reaction mechanism using plasma flow reactor measurements

Abstract In this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000–5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Analytical and EZmock covariance validation for the DESI 2024 results

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full-Shape two approaches are usually considered. First: analytical estimates of the covariance matrix use Gaussian approximations and (nonlinear) clustering measurements to estimate the matrix, which allows a relatively fast and computationally cheap way to generate matrices that adapt to an arbitrary clustering measurement. On the other hand, sample covariances are an empirical estimate of the matrix based on an ensemble of clustering measurements from fast and approximate simulations. While more computationally expensive due to the large amount of simulations and volume required, these allow us to take into account systematics that are impossible to model analytically. In this work we compare these two approaches in order to enable DESI's key analyses. We find that the configuration space analytical estimate performs satisfactorily in BAO analyses and its flexibility in terms of input clustering makes it the fiducial choice for DESI's 2024 BAO analysis. On the contrary, the analytical computation of the covariance matrix in Fourier space does not reproduce the expected measurements in terms of Full-Shape analyses, which motivates the use of a corrected mock covariance for DESI's 2024 Full Shape analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Emergence of asymmetric skew-scattering dominated anomalous Nernst effect in the spin gapless semiconductors Co 1+x Fe 1-x CrGa

Heusler alloy-based spin gapless semiconductors (SGSs) with very high Curie temperatures ( T C ) have recently gained enormous attention because of their unconventional electronic structures. They exhibit a nonzero band gap in one of the spin channels and a zero band gap in the other spin channel, making them an important class of materials for tunable spin transport. Here, we report the experimental observation of anomalous Nernst effect (ANE) in Co 1 + x Fe 1 - x CrGa ( x = 0 , 0.2, 0.4, and 0.5), which are the emerging quaternary Heusler alloy-based SGSs. While the electron-electron elastic scattering and the disorder-mediated weak localization effect play the major roles in electrical transport for all the samples at low temperatures, the magnon-drag effect was found to dominate the longitudinal thermoelectric transport. The ANE coefficient at room temperature increases from ≈ 0.018 μ V K - 1 for x = 0 to ≈ 0.063 μ V K - 1 for x = 0.5 , which is higher than that for Ni 81 Fe 19 and compressively strained SrRu O 3 films. Our analysis indicates that the observed ANE in these samples originates from asymmetric skew scattering of charge carriers.

36 MATERIALS SCIENCE↗