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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Repeated exposure to eucalyptus wood smoke alters pulmonary gene and metabolic profiles in male Long-Evans rats

Abstract Exposure to wildfire smoke is associated with both acute and chronic cardiopulmonary illnesses, which are of special concern for wildland firefighters who experience repeated exposure to wood smoke. It is necessary to better understand the underlying pathophysiology by which wood smoke exposure increases pulmonary disease burdens in this population. We hypothesize that wood smoke exposure produces pulmonary dysfunction, lung inflammation, and gene expression profiles associated with future pulmonary complications. Male Long-Evans rats were intermittently exposed to smoldering eucalyptus wood smoke at 2 concentrations, low (11.0 ± 1.89 mg/m3) and high (23.7 ± 0.077 mg/m3), over a 2-week period. Whole-body plethysmography was measured intermittently throughout. Lung tissue and lavage fluid were collected 24 h after the final exposure for transcriptomics and metabolomics. Increasing smoke exposure upregulated neutrophils and select cytokines in the bronchoalveolar lavage fluid. In total, 3446 genes were differentially expressed in the lungs of rats in the high smoke exposure and only 1 gene in the low smoke exposure (Cd151). Genes altered in the high smoke group reflected changes to the Eukaryotic Initiation Factor 2 stress and oxidative stress responses, which mirrored metabolomics analyses. xMWAS-integrated analysis revealed that smoke exposure significantly altered pathways associated with oxidative stress, lung morphogenesis, and tumor proliferation pathways. These results indicate that intermittent, 2-week exposure to eucalyptus wood smoke leads to transcriptomic and metabolic changes in the lung that may predict future lung disease development. Collectively, these findings provide insight into cellular signaling pathways that may contribute to the chronic pulmonary conditions observed in wildland firefighters.

Toxicology↗
DOE OSTI2024

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗
DOE OSTI2020

The cytochrome bc 1 complex as an antipathogenic target

The cytochrome bc 1 complex is a key component of the mitochondrial respiratory chains of many eukaryotic microorganisms that are pathogenic for plants or humans, such as fungi responsible for crop diseases and Plasmodium falciparum, which causes human malaria. Cytochrome bc 1 is an enzyme that contains two (ubi)quinone/quinol-binding sites, which can be exploited for the development of fungicidal and chemotherapeutic agents. In this article, we review recent progress in determination of the structure and mechanism of action of cytochrome bc 1 , and the associated development of antimicrobial agents (and associated resistance mechanisms) targeting its activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Employing the Dynamics of the Electrochemical Interface in Aqueous Zinc-Ion Battery Cathodes

Intrinsically stable materials are desirable for constructing energy storage devices, which aim to demonstrate durability under the harsh electrochemical conditions that are detrimental to their lifespan. However, in this study it is demonstrated that the intrinsic instability of an electrochemical interface can be converted from an obstacle into an advantage. In aqueous zinc-ion batteries, manganese oxide (MnO 2 ) exhibits considerable dissolution even in electrolyte containing Mn 2+ salt. Balancing with redeposition alleviates the harmful impact of dissolution on performance and alters the trajectory of the active phase. Inclusion of Mn 2+ salt in the electrolyte induces MnO 2 deposition on all conductive surfaces, requiring that distracting side reactions be eliminated to isolate the dynamics of the active phase. Under conditions favoring dissolution, capacity decreases dramatically and a highly crystalline tetragonal ZnMn 2 O 4 phase forms, while redeposition helps maintain capacity and promotes a disordered cubic Zn-rich phase. Ultimately, this work aims to illuminate a path forward to unlock the potential of batteries made with materials that are fundamentally unstable in their operating environment.

25 ENERGY STORAGE↗
DOE OSTI2020

Constructing an Adaptive Heterojunction as a Highly Active Catalyst for the Oxygen Evolution Reaction

Electrochemical water splitting is of prime importance to green energy technology. Particularly, the reaction at the anode side, namely the oxygen evolution reaction (OER), requires a high overpotential associated with O—O bond formation, which dominates the energy-efficiency of the whole process. Activating the anionic redox chemistry of oxygen in metal oxides, which involves the formation of superoxo/peroxo-like (O 2 ) n – , commonly occurs in most highly active catalysts during the OER process. Here, a highly active catalyst is designed: electrochemically delithiated LiNiO 2 , which facilitates the formation of superoxo/peroxo-like (O 2 ) n – species, i.e., NiOO*, for enhancing OER activity. The OER-induced surface reconstruction builds an adaptive heterojunction, where NiOOH grows on delithiated LiNiO 2 (delithiated-LiNiO 2 /NiOOH). At this junction, the lithium vacancies within the delithiated LiNiO 2 optimize the electronic structure of the surface NiOOH to form stable NiOO* species, which enables better OER activity. This finding provides new insight for designing highly active catalysts with stable superoxo-like/peroxo-like (O 2 ) n – for water oxidation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reconstruction of Thiospinel to Active Sites and Spin Channels for Water Oxidation

Water electrolysis is a promising technique for carbon neutral hydrogen production. A great challenge remains at developing robust and low-cost anode catalysts. Many pre-catalysts are found to undergo surface reconstruction to give high intrinsic activity in the oxygen evolution reaction (OER). The reconstructed oxyhydroxides on the surface are active species and most of them outperform directly synthesized oxyhydroxides. The reason for the high intrinsic activity remains to be explored. Here, a study is reported to showcase the unique reconstruction behaviors of a pre-catalyst, thiospinel CoFe 2 S 4 , and its reconstruction chemistry for a high OER activity. The reconstruction of CoFe 2 S 4 gives a mixture with both Fe–S component and active oxyhydroxide (Co(Fe)O x H y ) because Co is more inclined to reconstruct as oxyhydroxide, while the Fe is more stable in Fe–S component in a major form of Fe 3 S 4 . The interface spin channel is demonstrated in the reconstructed CoFe 2 S 4 , which optimizes the energetics of OER steps on Co(Fe)O x H y species and facilitates the spin sensitive electron transfer to reduce the kinetic barrier of O–O coupling. The advantage is also demonstrated in a membrane electrode assembly (MEA) electrolyzer. Finally, this work introduces the feasibility of engineering the reconstruction chemistry of the precatalyst for high performance and durable MEA electrolyzers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

On the Topotactic Phase Transition Achieving Superconducting Infinite‐Layer Nickelates

Abstract Topotactic reduction is critical to a wealth of phase transitions of current interest, including synthesis of the superconducting nickelate Nd 0.8 Sr 0.2 NiO 2 , reduced from the initial Nd 0.8 Sr 0.2 NiO 3 /SrTiO 3 heterostructure. Due to the highly sensitive and often damaging nature of the topotactic reduction, however, only a handful of research groups have been able to reproduce the superconductivity results. A series of in situ synchrotron‐based investigations reveal that this is due to the necessary formation of an initial, ultrathin layer at the Nd 0.8 Sr 0.2 NiO 3 surface that helps to mediate the introduction of hydrogen into the film such that apical oxygens are first removed from the Nd 0.8 Sr 0.2 NiO 3 / SrTiO 3 (001) interface and delivered into the reducing environment. This allows the square‐planar / perovskite interface to stabilize and propagate from the bottom to the top of the film without the formation of interphase defects. Importantly, neither geometric rotations in the square planar structure nor significant incorporation of hydrogen within the films is detected, obviating its need for superconductivity. These findings unveil the structural basis underlying the transformation pathway and provide important guidance on achieving the superconducting phase in reduced nickelate systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Aerosol-Jet Printed Sensors for Environmental, Safety, and Health Monitoring: A Review

An emergent direct-write approach, aerosol-jet printing (AJP), is gaining attention for the deployment of rapid and affordable microadditively manufactured energy-efficient sensors and printed electronics. AJP enables a broad range of ink viscosities (0.001–1 Pa s) for printing diverse materials ranging from ceramics and metals to polymers and biological matter. Reproducible, high-spatial-resolution features (≈10 µm), and wide standoff distances (1–11 mm) between the nozzle and the substrate facilitate conformal printing of complex geometrical designs on nonplanar—e.g., stepped or curved—surfaces. Here this paper aims to provide a comprehensive overview of state-of-the-art AJP-based sensors (e.g., strain and temperature gauges, biosensors, photosensors, humidity and surface acoustic wave sensors, dielectric elastomer actuators, and motion, smoke, and hazardous gas detectors) and to discuss prospective applications. The drive toward cost-effective devices that are smaller, lighter, and better-performing remains a frontier challenge in the field of printed electronics. Consequently, as AJP becomes increasingly utilized in the high-volume manufacturing of miniaturized active and passive sensors, it opens a pathway for facile large-scale fabrication of devices for a wide range of consumer and industrial applications, including transportation, agriculture, infrastructure, aerospace, national defense, and healthcare.

3-dimensional↗
DOE OSTI2025

End–to–End Metasurface Design for Temperature Imaging via Broadband Planck‐Radiation Regression

A theoretical framework is presented for temperature imaging from long-wavelength infrared (LWIR) thermal radiation (e.g., 8–12 µm) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. A new nonlinear reconstruction algorithm, “Planck regression”, is introduced to reconstruct the temperature map from a gray scale sensor image, even in the presence of severe chromatic aberration, by exploiting black body and optical physics particular to thermal imaging. This algorithm is combined with an end-to-end approach that optimizes manufacturable, single-layer metasurfaces to yield the most accurate reconstruction. The designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. Here, it is also shown that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Giant Magnetostriction in Ferrimagnetic SmFe 5 As 3

Magnetostrictive materials are of interest not only from a fundamental perspective but also for their potential applications, spanning spintronics to energy harvesting. A new magnetostrictive material—SmFe 5 As 3 —reveals a complex interplay between magnetostriction, magnetic properties, and the crystal structure behavior. The ground state of SmFe 5 As 3 is ferrimagnetic, as evidenced by magnetic susceptibility data, band-structure calculations, and XANES measurements. At T m1 = 28 ± 4 K, part of the Fe sublattice reorients, transitioning into a ferromagnetic state. This is followed by an entrance into the paramagnetic state at T m2 = 76 ± 4 K. The effects observed in the magnetic measurements are accompanied by structural phase transitions. All three phases—below T m1 , between T m1 and T m2 , and above T m2 —are described by the same structural motif of the UCr 5 P 3 type (monoclinic space group P2 1 /m), differing only in the degree of deformation of the Fe–As framework. The new material exhibits giant magnetostriction of 2500 x 10 -6 . Dilatometry measurements on a SmFe 5 As 3 single crystal indicate strongly diverse behavior, exhibiting not only negative, but also zero, as well as positive thermo-elastic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here, in this study, we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size

Abstract Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain ( https://centilebrain.org/#/brainAGE2 ), an open‐science, web‐based platform for individualized neuroimaging metrics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Substrate, temperature, and geographical patterns among nearly 2000 natural yeast isolates

Yeasts have broad importance as industrially and clinically relevant microbes and as powerful models for fundamental research, but we are only beginning to understand the roles yeasts play in natural ecosystems. Yeast ecology is often more difficult to study compared to other, more abundant microbes, but growing collections of natural yeast isolates are beginning to shed light on fundamental ecological questions. In this work, we used environmental sampling and isolation to assemble a dataset of 1962 isolates collected from throughout the contiguous United States of America (USA) and Alaska, which were then used to uncover geographic patterns, along with substrate and temperature associations among yeast taxa. We found some taxa, including the common yeasts Torulaspora delbrueckii and Saccharomyces paradoxus, to be repeatedly isolated from multiple sampled regions of the USA, and we classify these as broadly distributed cosmopolitan yeasts. A number of yeast taxon-substrate associations were identified, some of which were novel and some of which support previously reported associations. Further, we found a strong effect of isolation temperature on the phyla of yeasts recovered, as well as for many species. We speculate that substrate and isolation temperature associations reflect the ecological diversity of and niche partitioning by yeast taxa.

59 BASIC BIOLOGICAL SCIENCES↗