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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Self-Assembly of Atomically Aligned Nanoparticle Superlattices from Pt–Fe 3 O 4 Heterodimer Nanoparticles

Multicomponent nanoparticle superlattices (SLs) promise the integration of nanoparticles (NPs) with remarkable electronic, magnetic, and optical properties into a single structure. Here, we demonstrate that heterodimers consisting of two conjoined NPs can self-assemble into novel multicomponent SLs with a high degree of alignment between the atomic lattices of individual NPs, which has been theorized to lead to a wide variety of remarkable properties. Specifically, by using simulations and experiments, we show that heterodimers composed of larger Fe 3 O 4 domains decorated with a Pt domain at one vertex can self-assemble into an SL with long-range atomic alignment between the Fe 3 O 4 domains of different NPs across the SL. The SLs show an unanticipated decreased coercivity relative to nonassembled NPs. In situ scattering of the self-assembly reveals a two-stage mechanism of self-assembly: translational ordering between NPs develops before atomic alignment. Here our experiments and simulation indicate that atomic alignment requires selective epitaxial growth of the smaller domain during heterodimer synthesis and specific size ratios of the heterodimer domains as opposed to specific chemical composition. This composition independence makes the self-assembly principles elucidated here applicable to the future preparation of multicomponent materials with fine structural control.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

A Novel Modeling Framework for Computationally Efficient and Accurate Real-Time Ensemble Flood Forecasting With Uncertainty Quantification

A novel modeling framework that simultaneously improves accuracy, predictability, and computational efficiency is presented. It embraces the benefits of three modeling techniques integrated together for the first time: surrogate modeling, parameter inference, and data assimilation. The use of polynomial chaos expansion (PCE) surrogates significantly decreases computational time. Parameter inference allows for model faster convergence, reduced uncertainty, and superior accuracy of simulated results. Ensemble Kalman filters assimilate errors that occur during forecasting. To examine the applicability and effectiveness of the integrated framework, we developed 18 approaches according to how surrogate models are constructed, what type of parameter distributions are used as model inputs, and whether model parameters are updated during the data assimilation procedure. We conclude that (1) PCE must be built over various forcing and flow conditions, and in contrast to previous studies, it does not need to be rebuilt at each time step; (2) model parameter specification that relies on constrained, posterior information of parameters (so-called Selected specification) can significantly improve forecasting performance and reduce uncertainty bounds compared to Random specification using prior information of parameters; and (3) no substantial differences in results exist between single and dual ensemble Kalman filters, but the latter better simulates flood peaks. The use of PCE effectively compensates for the computational load added by the parameter inference and data assimilation (up to ~80 times faster). Therefore, the presented approach contributes to a shift in modeling paradigm arguing that complex, high-fidelity hydrologic and hydraulic models should be increasingly adopted for real-time and ensemble flood forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Role of Stratigraphy and Loading History in Generating Complex Compaction Bands in Idealized Field-Scale Settings

The Buckskin Gulch locality in Utah is a landmark example of compaction localization. The outcrop of this locality involves distinct stratigraphic heterogeneity and was exposed to complex loading history. It features multiple sets of deformation bands with different kinematics and orientation. Similar formations were seen in the Valley of Fire, Nevada, and the Orange quarry, France, among other localities. The formation of such complex structures, their propagation mechanisms, and frequency is affected by numerous local and ambient factors whose impacts are not yet fully understood. The simulation of the above-mentioned localities is not feasible because of the limited amount of available information. This work, instead, investigates from a geomechanics standpoint how the interplay among material nonlinearity, outcrop stratigraphy, and loading history interconnects with specific spatiotemporal patterns of compaction band propagation. Our study shows that the system stratigraphy can be responsible for the emergence of coexisting compaction bands with different inclination and kinematics. Specifically, we show that stiffness contrasts induce nonlocal stress changes which may favor the initiation of secondary structures with different compaction localization characteristics. Furthermore, systems of inclined compaction bands induced by burial increase display secondary, noncontemporaneous sets of vertical compaction bands under the effects of postburial shortening. Our results indicate that stages of intermediate burial decrease prior to tectonic shortening can promote the formation of such complex systems. Despite the simplifications involved in our analyses, these findings show how geomechanics computations complement field observations and could provide a mechanics-based validation of site-specific reconstruction hypothesis.

58 GEOSCIENCES↗
DOE OSTI2022

Atmospheric Structure Prediction for Infrasound Propagation Modeling Using Deep Learning

Abstract Infrasound is generated by a variety of natural and anthropogenic sources. Infrasonic waves travel through the dynamic atmosphere, which can change on the order of minutes to hours. Infrasound propagation largely depends on the wind and temperature structure of the atmosphere. Numerical weather prediction models are available to provide atmospheric specifications, but uncertainties in these models exist and they are computationally expensive to run. Machine learning has proven useful in predicting tropospheric weather using Long Short‐Term Memory (LSTM) networks. An LSTM network is utilized to make atmospheric specification predictions up to ∼30 km for three different training and testing scenarios: (a) the model is trained and tested using only radiosonde data from the Albuquerque, NM, USA station, (b) the model is trained on radiosonde stations across the contiguous US, excluding the Albuquerque, NM, USA station, which was reserved for testing, and (c) the model is trained and tested on radiosonde stations across the contiguous US. Long Short‐Term Memory predictions are compared to a state‐of‐the‐art reanalysis model and show cases where the LSTM outperforms, performs equally as well, or underperforms in comparison to the state‐of‐the‐art. Regional and temporal trends in model performance across the US are also discussed. Results suggest that the LSTM model is a viable tool for predicting atmospheric specifications for infrasound propagation modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Floods and Heavy Precipitation at the Global Scale: 100‐Year Analysis and 180‐Year Reconstruction

Floods and heavy precipitation have disruptive impacts worldwide, but their historical variability remains only partially understood at the global scale. This article aims at reducing this knowledge gap by jointly analyzing seasonal maxima of streamflow and precipitation at more than 3,000 stations over a 100‐year period. The analysis is based on Hidden Climate Indices (HCIs). Like standard climate indices (e.g., Nino 3.4, NAO), HCIs are used as covariates explaining the temporal variability of data, but unlike them, HCIs are estimated from the data. In this work, a distinction is made between common HCIs, that affect both heavy precipitation and floods, and specific HCIs, that exclusively affect one or the other. Overall, HCIs do not show noticeable autocorrelation, but some are affected by noticeable trends. In particular, strong and wide‐ranging trends are identified in precipitation‐specific HCIs, while trends affecting flood‐specific HCIs are weaker and have more localized effects. A probabilistic model is then derived to link HCIs and large‐scale atmospheric variables (pressure, wind, temperature) and to reconstruct HCIs since 1836 using the 20CRv3 reanalysis. In turn this allows estimating the probability of occurrence of floods and heavy precipitation at the global scale. This 180‐year reconstruction highlights flood hot‐spots and hot‐moments in the distant past, well before the establishment of perennial monitoring networks. Finally, the approach presented in this study is generic and paves the way for an improved characterization of historical variability by making a better use of long but highly irregular station data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Experimentally-validated correlation analysis reveals new anaerobic methane oxidation partnerships with consortium-level heterogeneity in diazotrophy

Abstract Archaeal anaerobic methanotrophs (“ANME”) and sulfate-reducing Deltaproteobacteria (“SRB”) form symbiotic multicellular consortia capable of anaerobic methane oxidation (AOM), and in so doing modulate methane flux from marine sediments. The specificity with which ANME associate with particular SRB partners in situ, however, is poorly understood. To characterize partnership specificity in ANME-SRB consortia, we applied the correlation inference technique SparCC to 310 16S rRNA amplicon libraries prepared from Costa Rica seep sediment samples, uncovering a strong positive correlation between ANME-2b and members of a clade of Deltaproteobacteria we termed SEEP-SRB1g. We confirmed this association by examining 16S rRNA diversity in individual ANME-SRB consortia sorted using flow cytometry and by imaging ANME-SRB consortia with fluorescence in situ hybridization (FISH) microscopy using newly-designed probes targeting the SEEP-SRB1g clade. Analysis of genome bins belonging to SEEP-SRB1g revealed the presence of a complete nifHDK operon required for diazotrophy, unusual in published genomes of ANME-associated SRB. Active expression of nifH in SEEP-SRB1g within ANME-2b—SEEP-SRB1g consortia was then demonstrated by microscopy using hybridization chain reaction (HCR-) FISH targeting nifH transcripts and diazotrophic activity was documented by FISH-nanoSIMS experiments. NanoSIMS analysis of ANME-2b—SEEP-SRB1g consortia incubated with a headspace containing CH4 and 15N2 revealed differences in cellular 15N-enrichment between the two partners that varied between individual consortia, with SEEP-SRB1g cells enriched in 15N relative to ANME-2b in one consortium and the opposite pattern observed in others, indicating both ANME-2b and SEEP-SRB1g are capable of nitrogen fixation, but with consortium-specific variation in whether the archaea or bacterial partner is the dominant diazotroph.

58 GEOSCIENCES↗
DOE OSTI2021

Changing expression patterns of TonB-dependent transporters suggest shifts in polysaccharide consumption over the course of a spring phytoplankton bloom

Algal blooms produce large quantities of organic matter that is subsequently remineralised by bacterial heterotrophs. Polysaccharide is a primary component of algal biomass. It has been hypothesised that individual bacterial heterotrophic niches during algal blooms are in part determined by the available polysaccharide substrates present. Measurement of the expression of TonB-dependent transporters, often specific for polysaccharide uptake, might serve as a proxy for assessing bacterial polysaccharide consumption over time. To investigate this, we present here high-resolution metaproteomic and metagenomic datasets from bacterioplankton of the 2016 spring phytoplankton bloom at Helgoland island in the southern North Sea, and expression profiles of TonB-dependent transporters during the bloom, which demonstrate the importance of both the Gammaproteobacteria and the Bacteroidetes as degraders of algal polysaccharide. TonB-dependent transporters were the most highly expressed protein class, split approximately evenly between the Gammaproteobacteria and Bacteroidetes , and totalling on average 16.7% of all detected proteins during the bloom. About 93% of these were predicted to take up organic matter, and for about 12% of the TonB-dependent transporters, we predicted a specific target polysaccharide class. Most significantly, we observed a change in substrate specificities of the expressed transporters over time, which was not reflected in the corresponding metagenomic data. From this, we conclude that algal cell wall-related compounds containing fucose, mannose, and xylose were mostly utilised in later bloom stages, whereas glucose-based algal and bacterial storage molecules including laminarin, glycogen, and starch were used throughout. Quantification of transporters could therefore be key for understanding marine carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Multivalency transforms SARS-CoV-2 antibodies into ultrapotent neutralizers

SARS-CoV-2, the virus responsible for COVID-19, has caused a global pandemic. Antibodies can be powerful biotherapeutics to fight viral infections. Here, we use the human apoferritin protomer as a modular subunit to drive oligomerization of antibody fragments and transform antibodies targeting SARS-CoV-2 into exceptionally potent neutralizers. Using this platform, half-maximal inhibitory concentration (IC 50 ) values as low as 9 × 10 - 14 M are achieved as a result of up to 10,000-fold potency enhancements compared to corresponding IgGs. Combination of three different antibody specificities and the fragment crystallizable (Fc) domain on a single multivalent molecule conferred the ability to overcome viral sequence variability together with outstanding potency and IgG-like bioavailability. The MULTi-specific, multi-Affinity antiBODY (Multabody or MB) platform thus uniquely leverages binding avidity together with multi-specificity to deliver ultrapotent and broad neutralizers against SARS-CoV-2. The modularity of the platform also makes it relevant for rapid evaluation against other infectious diseases of global health importance. Neutralizing antibodies are a promising therapeutic for SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Source sector and fuel contributions to ambient PM 2.5 and attributable mortality across multiple spatial scales

Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A symbiotic physical niche in Drosophila melanogaster regulates stable association of a multi-species gut microbiota

The gut is continuously invaded by diverse bacteria from the diet and the environment, yet microbiome composition is relatively stable over time for host species ranging from mammals to insects, suggesting host-specific factors may selectively maintain key species of bacteria. To investigate host specificity, we used gnotobiotic Drosophila, microbial pulse-chase protocols, and microscopy to investigate the stability of different strains of bacteria in the fly gut. We show that a host-constructed physical niche in the foregut selectively binds bacteria with strain-level specificity, stabilizing their colonization. Primary colonizers saturate the niche and exclude secondary colonizers of the same strain, but initial colonization by Lactobacillus species physically remodels the niche through production of a glycan-rich secretion to favor secondary colonization by unrelated commensals in the Acetobacter genus. Our results provide a mechanistic framework for understanding the establishment and stability of a multi-species intestinal microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Double DAP-seq uncovered synergistic DNA binding of interacting bZIP transcription factors

Many eukaryotic transcription factors (TF) form homodimer or heterodimer complexes to regulate gene expression. Dimerization of BASIC LEUCINE ZIPPER (bZIP) TFs are critical for their functions, but the molecular mechanism underlying the DNA binding and functional specificity of homo- versus heterodimers remains elusive. To address this gap, we present the double DNA Affinity Purification-sequencing (dDAP-seq) technique that maps heterodimer binding sites on endogenous genomic DNA. Using dDAP-seq we profile twenty pairs of C/S1 bZIP heterodimers and S1 homodimers in Arabidopsis and show that heterodimerization significantly expands the DNA binding preferences of these TFs. Analysis of dDAP-seq binding sites reveals the function of bZIP9 in abscisic acid response and the role of bZIP53 heterodimer-specific binding in seed maturation. The C/S1 heterodimers show distinct preferences for the ACGT elements recognized by plant bZIPs and motifs resembling the yeast GCN4 cis -elements. This study demonstrates the potential of dDAP-seq in deciphering the DNA binding specificities of interacting TFs that are key for combinatorial gene regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Machine-learning-assisted material discovery of oxygen-rich highly porous carbon active materials for aqueous supercapacitors

Abstract Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures. However, the development of carbon active materials with improved physicochemical and electrochemical properties is generally carried out via time-consuming and cost-ineffective experimental processes. In this regard, machine-learning technology provides a data-driven approach to examine previously reported research works to find the critical features for developing ideal carbon materials for supercapacitors. Here, we report the design of a machine-learning-derived activation strategy that uses sodium amide and cross-linked polymer precursors to synthesize highly porous carbons (i.e., with specific surface areas > 4000 m 2 /g). Tuning the pore size and oxygen content of the carbonaceous materials, we report a highly porous carbon-base electrode with 0.7 mg/cm 2 of electrode mass loading that exhibits a high specific capacitance of 610 F/g in 1 M H 2 SO 4 . This result approaches the specific capacitance of a porous carbon electrode predicted by the machine learning approach. We also investigate the charge storage mechanism and electrolyte transport properties via step potential electrochemical spectroscopy and quasielastic neutron scattering measurements.

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

Conserved enhancers control notochord expression of vertebrate Brachyury

The cell type-specific expression of key transcription factors is central to development and disease. Brachyury/T/TBXT is a major transcription factor for gastrulation, tailbud patterning, and notochord formation; however, how its expression is controlled in the mammalian notochord has remained elusive. Here, we identify the complement of notochord-specific enhancers in the mammalian Brachyury/T/TBXT gene. Using transgenic assays in zebrafish, axolotl, and mouse, we discover three conserved Brachyury-controlling notochord enhancers, T3, C, and I, in human, mouse, and marsupial genomes. Acting as Brachyury-responsive, auto-regulatory shadow enhancers, in cis deletion of all three enhancers in mouse abolishes Brachyury/T/Tbxt expression selectively in the notochord, causing specific trunk and neural tube defects without gastrulation or tailbud defects. The three Brachyury-driving notochord enhancers are conserved beyond mammals in the brachyury/tbxtb loci of fishes, dating their origin to the last common ancestor of jawed vertebrates. Our data define the vertebrate enhancers for Brachyury/T/TBXTB notochord expression through an auto-regulatory mechanism that conveys robustness and adaptability as ancient basis for axis development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evolution of connectivity architecture in the Drosophila mushroom body

Brain evolution has primarily been studied at the macroscopic level by comparing the relative size of homologous brain centers between species. How neuronal circuits change at the cellular level over evolutionary time remains largely unanswered. Here, using a phylogenetically informed framework, we compare the olfactory circuits of three closely related Drosophila species that differ in their chemical ecology: the generalists Drosophila melanogaster and Drosophila simulans and Drosophila sechellia that specializes on ripe noni fruit. We examine a central part of the olfactory circuit that, to our knowledge, has not been investigated in these species—the connections between projection neurons and the Kenyon cells of the mushroom body—and identify species-specific connectivity patterns. We found that neurons encoding food odors connect more frequently with Kenyon cells, giving rise to species-specific biases in connectivity. These species-specific connectivity differences reflect two distinct neuronal phenotypes: in the number of projection neurons or in the number of presynaptic boutons formed by individual projection neurons. Finally, behavioral analyses suggest that such increased connectivity enhances learning performance in an associative task. Our study shows how fine-grained aspects of connectivity architecture in an associative brain center can change during evolution to reflect the chemical ecology of a species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Local structural distortions drive magnetic molecular field in compositionally complex spinel oxide

Understanding how local distortions determine the functional properties of high entropy materials, containing five or more elements at the same crystallographic site, is an open challenge. We address this for a compositionally complex spinel oxide (Mn 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )Cr 2 O 4 (A 5 Cr 2 O 4 ). By comparatively examining extended X-ray absorption fine structure on A 5 Cr 2 O 4 and its parent counterparts, ACr 2 O 4 , along with density functional theory calculations for multiple configurations, we find that the element-specific distortions go beyond the first neighbor. Specifically, the strong Jahn-Teller distortion present in CuCr 2 O 4 is found to be completely suppressed in A 5 Cr 2 O 4 even locally. Instead, there is a broad distribution of Cu-O and Cu-Cr bond distances, while other A-O distances acquire certain specific values. This study demonstrates the additional flexibility of a cationic sublattice in maintaining a uniform long-range structure, in contrast to previous reports showing only the accommodative anionic sublattice. The mean-field magnetic interactions of A 5 Cr 2 O 4 exhibit a striking resemblance to those of NiCr 2 O 4 , despite the presence of multiple magnetic ions and variable bond lengths. This originates from the comparability of bond lengths around Cr in both materials. Our study paves the way for a deeper understanding of the impact of local structural distortions on the physical properties of compositionally complex quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Single-cell chromatin accessibility and cis -regulatory element analyses in plants using the scPlantReg platform

Understanding gene regulation is fundamental to plant improvement, but the lack of plant-specific single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) frameworks and cross-species databases has limited insights into cell-type-specific cellular regulation. Here we present ‘scPlantReg’, an integrated framework and database for plant scATAC-seq data. scPlantReg supports end-to-end analyses from raw data processing to biological interpretation and features ‘scATACtor’, a supervised machine-learning approach that outperforms existing tools for cell-type annotation. We applied scPlantReg to pearl millet to characterize cell-type-specific chromatin accessibility and identify validated activating and repressing accessible chromatin regions (ACRs), revealing WRKY transcription factors as potential regulators of xylem development. Furthermore, we reanalysed scATAC-seq datasets from 8 plant species, spanning 11 tissues and multiple developmental stages, enabling cross-species comparisons. Furthermore, these analyses uncovered conserved regulatory programmes, including AP2/EREBP-associated ACRs linked to cell wall development and cell-type-conserved TFs across grasses. Collectively, scPlantReg provides a general framework and resource for comparative regulatory analysis in plants.

Epigenomics↗
DOE OSTI2024

Silicon ion radiation as a viable surrogate for emulating neutron radiation damage in silicates

Abstract Nuclear power plants are aging around the world, and a precise assessment of irradiation damage in their components is needed. One key component, concrete, and specifically the silicates in its aggregates, can undergo significant expansion upon neutron radiation, which can lead to cracking and, ultimately, structural failure. However, assessing and predicting the extent of damage via neutron radiation is challenging due to reasons such as residual radioactivity and, most importantly, the high time involved. Here, we evaluate whether ion radiation can be a viable surrogate. Specifically, by employing Si 2+ ion radiations and a comprehensive multi-modal imaging protocol, we report mineral-specific responses for key silicates such as quartz, albite, anorthite, and microcline. We find that 10 MeV Si 2+ ions result in mineral expansions that are remarkably comparable to neutron radiation equivalent expansions (R 2 = 0.86, RMSE = 1.29%), opening up pathways towards rapid assessment of silicates subject to irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A high-energy and long-cycling lithium–sulfur pouch cell via a macroporous catalytic cathode with double-end binding sites

Lithium-sulfur batteries are attractive alternatives to lithium-ion batteries because of their high theoretical specific energy and natural abundance of sulfur. However, the practical specific energy and cycle life of Li-S pouch cells are significantly limited by the use of thin sulfur electrodes/flooded electrolytes and polysulfides shuttle/Li metal degradation, respectively. In this work we propose a cathode design concept to achieve good Li-S pouch cell performances. The cathode is composed of uniformly embedded ZnS nanoparticles and Co-N-C single-atom catalyst to form double-end biding sites inside a highly oriented macroporous host, which can effectively immobilize and catalytically convert polysulfides intermediates during cycling, thus eliminating the shuttle effect and lithium metal corrosion. The ordered macropores enhance ionic transport under high sulfur loading by forming sufficient catalyst/conductive support/electrolyte triple-phase boundaries. This prevents the formation of inactive sulfur (dead sulfur). Our cathode structure shows improved performances in a pouch cell configuration under high sulfur loading and lean electrolyte operation. An Ah-level pouch cell with only 100% lithium excess can deliver a cell specific energy of > 300 Wh kg –1 with a Coulombic efficiency >95% for 80 cycles.

25 ENERGY STORAGE↗