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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The smectic Z A phase: Antiferroelectric smectic order as a prelude to the ferroelectric nematic

We have structurally characterized the liquid crystal (LC) phase that can appear as an intermediate state when a dielectric nematic, having polar disorder of its molecular dipoles, transitions to the almost perfectly polar-ordered ferroelectric nematic. This intermediate phase, which fills a 100-y-old void in the taxonomy of smectic LCs and which we term the “smectic Z A ,” is antiferroelectric, with the nematic director and polarization oriented parallel to smectic layer planes, and the polarization alternating in sign from layer to layer with a 180 Å period. A Landau free energy, originally derived from the Ising model of ferromagnetic ordering of spins in the presence of dipole–dipole interactions, and applied to model incommensurate antiferroelectricity in crystals, describes the key features of the nematic–SmZ A –ferroelectric nematic phase sequence.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The solar internetwork. I. Contribution to the network magnetic flux

The magnetic network (NE) observed on the solar surface harbors a sizable fraction of the total quiet Sun flux. However, its origin and maintenance are not well known. Here we investigate the contribution of internetwork (IN) magnetic fields to the NE flux. IN fields permeate the interior of supergranular cells and show large emergence rates. We use long-duration sequences of magnetograms acquired by Hinode and an automatic feature tracking algorithm to follow the evolution of NE and IN flux elements. We find that 14% of the quiet Sun (QS) flux is in the form of IN fields with little temporal variations. IN elements interact with NE patches and modify the flux budget of the NE either by adding flux (through merging processes) or by removing it (through cancellation events). Mergings appear to be dominant, so the net flux contribution of the IN is positive. The observed rate of flux transfer to the NE is 1.5 × 10{sup 24} Mx day{sup –1} over the entire solar surface. Thus, the IN supplies as much flux as is present in the NE in only 9-13 hr. Taking into account that not all the transferred flux is incorporated into the NE, we find that the IN would be able to replace the entire NE flux in approximately 18-24 hr. This renders the IN the most important contributor to the NE, challenging the view that ephemeral regions are the main source of flux in the QS. About 40% of the total IN flux eventually ends up in the NE.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Application of State Quantization-Based Methods in HEP Particle Transport Simulation

Simulation of particle-matter interactions in complex geometries is one of the main tasks in high energy physics (HEP) research. An essential aspect of it is an accurate and efficient particle transportation in a non-uniform magnetic field, which includes the handling of volume crossings within a predefined 3D geometry. Quantized State Systems (QSS) is a family of numerical methods that provides attractive features for particle transportation processes, such as dense output (sequences of polynomial segments changing only according to accuracy-driven discrete events) and lightweight detection and handling of volume crossings (based on simple root-finding of polynomial functions). In this work we present a proof-of-concept performance comparison between a QSS-based standalone numerical solver and an application based on the Geant4 simulation toolkit, with its default Runge-Kutta based adaptive step method. In a case study with a charged particle circulating in a vacuum (with interactions with matter turned off), in a uniform magnetic field, and crossing up to 200 volume boundaries twice per turn, simulation results showed speedups of up to 6 times in favor of QSS while it being 10 times slower in the case with zero volume boundaries.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Infrared spectroscopy of nearby radio active early-type galaxies - II: spectral atlas

ABSTRACT We present a near-infrared spectroscopic atlas of nearby, bright early-type galaxies with radio emission, containing 163 galaxies observed by the Palomar 200″ TripleSpec instrument, measuring the emission line fluxes for H, He, [Fe ii], and H2 and determined the nuclear excitation mechanisms. By stacking spectra, we deduced the H2 excitation temperature (1957 ± 182 K) and dominant excitation mechanism (thermal and shock heating combined) from the K-band emission line sequence. Stacking also produces an ‘average’ spectrum of absorption features and spectral indices from the literature; the CO12 absorption line index versus J − K colour shows a trend of stronger nuclear activity producing a weaker CO12 index and a redder (flatter) continuum. The correlations between the radio and the emission-line luminosities finds a trend with radio power; however, the large scatter in the upper limits shows that the two are not directly coupled and the duty cycles of SF and AGN activity are not synchronized.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Learning Heterogeneous Features Jointly: A Deep End-to-End Framework for Multi-Step Short-Term Wind Power Prediction

Leveraging multiple heterogeneous measurements to predict wind power has long been a challenging task in the electrical community. In this paper, a deep architecture incorporated with multitask learning and multimodal learning for wind power prediction, termed predictive stacked autoencoder (PSAE), is presented. PSAE is a unified framework integrating multiple stacked autoencoders (SAEs), one feature fusion layer, and one prediction terminal layer, which expands the architecture from two spatial dimensions, including the depth and width, compared to conventional prediction models. Initially, the SAEs at the bottom of PSAE extracted features from multiple kinds of measurements respectively. Following, the feature fusion layer encodes the high-order features extracted by different SAEs into a unified feature that is more informative and representative for wind power prediction. Finally, the prediction terminal layer functions as a regression machine which generates the predicted targets based on the fusion features. Trained in an end-to-end (E2E) manner, PSAE is capable of learning heterogeneous features jointly and achieving the prediction task of sequence-to-sequence (S2S). Experiments for multi-step short-term predictions are conducted on real-world data, and the results demonstrate the superiority of PSAE to prior methods.

17 WIND ENERGY↗
DOE OSTI2018

Functional Profiling and Crystal Structures of Isothiocyanate Hydrolases Found in Gut-Associated and Plant-Pathogenic Bacteria

Isothiocyanates (ITCs) are produced by cruciferous plants to protect them against herbivores and infection by microbes. These compounds are of particular interest due to their antimicrobial and anticarcinogenic properties. The breakdown of ITCs in nature is catalyzed by isothiocyanate hydrolases (ITCases), a novel family within the metallo-β-lactamase (MBL)-fold superfamily of proteins. saxA genes that code for ITCases are particularly widespread in insect- and plant-associated bacteria. Enzymatic characterization of seven phylogenetically related but distinct ITCases revealed similar activities on six selected ITCs, suggesting that phylogenetic diversity does not determine the substrate specificity of ITCases. X-ray crystallography studies of two ITCases sharing 42% amino acid sequence identity revealed a highly conserved tertiary structure. Notable features of ITCases include a hydrophobic active site with two Zn 2+ ions coordinating water/hydroxide and a flexible cap that is implicated in substrate recognition and covers the active site. Furthermore, this report reveals the function and structure of the previously uncharacterized family of isothiocyanate hydrolases within the otherwise relatively well-studied superfamily of metallo-β-lactamases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Full Karyotype Interphase Cell Analysis

Aneuploidy seems to play not only a decisive role in embryonal development but also in tumorigenesis where chromosomal and genomic instability reflect a universal feature of malignant tumors. The cost of whole genome sequencing has fallen significantly, but it is still prohibitive for many institutions and clinical settings. No applied, cost-effective, and efficient technique has been introduced yet aiming at research to assess the ploidy status of all 24 different human chromosomes in interphases simultaneously, especially in single cells. Here, we present the selection of human probe DNA and a technique using multistep fluorescence in situ hybridization (FISH) employing four sets of six labeled FISH probes able to delineate all 24 human chromosomes in interphase cells. This full karyotype analysis approach will provide additional diagnostic potential for single cell analysis. The use of spectral imaging (SIm) has enabled the use of up to eight different fluorochrome labels simultaneously. Thus, scoring can be easily assessed by visual inspection, because SIm permits computer-assigned and distinguishable pseudo-colors to each probe during image processing. This enables full karyotype analysis by FISH of single-cell interphase nuclei.

Baumgartner, Adi↗
DOE OSTI2016

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples

The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis). In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples) and computational (petabytes of sequence data) issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances) or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST) scheme). Finally, when analyzing empirical data (wholegenome sequence data from 18,997 Salmonella isolates) there are features (e.g., genomic, assembly, and contamination) that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Rokubacteria: Genomic Giants among the Uncultured Bacterial Phyla

Recent advances in single-cell genomic and metagenomic techniques have facilitated the discovery of numerous previously unknown, deep branches of the tree of life that lack cultured representatives. Many of these candidate phyla are composed of microorganisms with minimalistic, streamlined genomes lacking some core metabolic pathways, which may contribute to their resistance to growth in pure culture. Here we analyzed single-cell genomes and metagenome bins to show that the “Candidate phylum Rokubacteria,” formerly known as SPAM, represents an interesting exception, by having large genomes (6–8 Mbps), high GC content (66–71%), and the potential for a versatile, mixotrophic metabolism. We also observed an unusually high genomic heterogeneity among individual Rokubacteria cells in the studied samples. These features may have contributed to the limited recovery of sequences of this candidate phylum in prior cultivation and metagenomic studies. Our analyses suggest that Rokubacteria are distributed globally in diverse terrestrial ecosystems, including soils, the rhizosphere, volcanic mud, oil wells, aquifers, and the deep subsurface, with no reports from marine environments to date.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Targeted Biomining and Machine Learning Approaches in Critical Minerals Revealed by a Biogeochemical Survey of a Coal Mine Drainage Remediation System

Abandoned coal mine drainage (AMD) remediation systems in Pennsylvania can concentrate critical minerals and materials (CMM) at levels comparable to mining-grade ores. Remediation systems have varying engineering features and are open to the environment, resulting in diverse microbial colonization and seasonal climate influences that may impact CMM speciation. The location of CMMs, the types of bacterial communities tolerant of these pollutant conditions, and the influence of localized climate on CMM rich remediation systems are not well characterized. Through a one-year spatiotemporal survey of biogeochemistry at a remediation system, we have initiated the process to address these questions. Rare Earth Elements (REE) ranged 180-1,200 ppm and greater than 1,500 bacterial ASVs were classified via 16S sequencing. Analyses indicate biogeochemical differences are heavily influenced by engineering features. Additionally, REE precipitants correlate strongly with the elements Al, Cu, Zn, Be, and U. Unearthing these trends has refined our line of inquiry to explore biological mining opportunities more closely with these metals. Furthermore, we created a Machine Learning Model for predicting AMD REE content, with 89% accuracy, using the data from this study and several others. Further training data is required to create a more reputable model. Recently, global research efforts have prioritized modeling work or the use of the few historical surveys to design experiments. Through our data, we challenge this approach, emphasizing the importance of expanding fundamental survey efforts prior to advanced product design and experimentation.

critical minerals↗
DOE OSTI2023

The molecular basis of the neutralization breadth of the RBD-specific antibody CoV11

SARS-CoV-2, the virus behind the COVID-19 pandemic, has changed over time to the extent that the current virus is substantially different from what originally led to the pandemic in 2019–2020. Viral variants have modified the severity and transmissibility of the disease and continue do so. How much of this change is due to viral fitness versus a response to immune pressure is hard to define. One class of antibodies that continues to afford some level of protection from emerging variants are those that closely overlap the binding site for angiotensin-converting enzyme 2 (ACE2) on the receptor binding domain (RBD). Some members of this class that were identified early in the course of the pandemic arose from the VH 3-53 germline gene (IGHV3-53*01) and had short heavy chain complementarity-determining region 3s (CDR H3s). Here, we describe the molecular basis of the SARS-CoV-2 RBD recognition by the anti-RBD monoclonal antibody CoV11 isolated early in the COVID-19 pandemic and show how its unique mode of binding the RBD determines its neutralization breadth. CoV11 utilizes a heavy chain VH 3-53 and a light chain VK 3-20 germline sequence to bind to the RBD. Two of CoV11’s four heavy chain changes from the VH 3-53 germline sequence, $Thr^{28}_{FWRH1}$ to Ile and $Ser^{31}_{CDRH1}$ to Arg, and some unique features in its CDR H3 increase its affinity to the RBD, while the four light chain changes from the VK 3-20 germline sequence sit outside of the RBD binding site. Antibodies of this type can retain significant affinity and neutralization potency against variants of concern (VOCs) that have diverged significantly from original virus lineage such as the prevalent omicron variant. We also discuss the mechanism by which VH 3-53 encoded antibodies recognize spike antigen and show how minimal changes to their sequence, their choice of light chain, and their mode of binding influence their affinity and impact their neutralization breadth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering

Abstract CRISPR-Cas9 tools have transformed genetic manipulation capabilities in the laboratory. Empirical rules-of-thumb have been developed for only a narrow range of model organisms, and mechanistic underpinnings for sgRNA efficiency remain poorly understood. This work establishes a novel feature set and new public resource, produced with quantum chemical tensors, for interpreting and predicting sgRNA efficiency. Feature engineering for sgRNA efficiency is performed using an explainable-artificial intelligence model: iterative Random Forest (iRF). By encoding quantitative attributes of position-specific sequences for Escherichia coli sgRNAs, we identify important traits for sgRNA design in bacterial species. Additionally, we show that expanding positional encoding to quantum descriptors of base-pair, dimer, trimer, and tetramer sequences captures intricate interactions in local and neighboring nucleotides of the target DNA. These features highlight variation in CRISPR-Cas9 sgRNA dynamics between E. coli and H. sapiens genomes. These novel encodings of sgRNAs enhance our understanding of the elaborate quantum biological processes involved in CRISPR-Cas9 machinery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Distinct Strains of Toxoplasma gondii Feature Divergent Transcriptomes Regardless of Developmental Stage

Using high through-put RNA sequencing, we assayed the transcriptomes of three different strains of Toxoplasma gondii representing three common genotypes under both in vitro tachyzoite and in vitro bradyzoite-inducing alkaline stress culture conditions. Strikingly, the differences in transcriptional profiles between the strains, RH, PLK, and CTG, is much greater than differences between tachyzoites and alkaline stressed in vitro bradyzoites. With an FDR of 10%, we identify 241 genes differentially expressed between CTG tachyzoites and in vitro bradyzoites, including 5 putative AP2 transcription factors. We also observe close association between cell cycle regulated genes and differentiation. By Gene Set Enrichment Analysis (GSEA), there are a number of KEGG pathways associated with the in vitro bradyzoite transcriptomes of PLK and CTG, including pyrimidine metabolism and DNA replication. These functions are likely associated with cell-cycle arrest. When comparing mRNA levels between strains, we identify 1,526 genes that are differentially expressed regardless of culture-condition as well as 846 differentially expressed only in bradyzoites and 542 differentially expressed only in tachyzoites between at least two strains. Using GSEA, we identify ribosomal proteins as being expressed at significantly higher levels in the CTG strain than in either the RH or PLK strains. This association holds true regardless of life cycle stage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

High-quality permanent draft genome sequence of Bradyrhizobium sp. Tv2a.2, a microsymbiont of Tachigali versicolor discovered in Barro Colorado Island of Panama

Bradyrhizobiumsp. Tv2a.2 is an aerobic, motile, Gram-negative, non-spore-forming rod that was isolated from an effective nitrogen-fixing root nodule of Tachigali versicolor collected in Barro Colorado Island of Panama. Here we describe the features of Bradyrhizobiumsp. Tv2a.2, together with high-quality permanent draft genome sequence information and annotation. The 8,496,279 bp high-quality draft genome is arranged in 87 scaffolds of 87 contigs, contains 8,109 protein-coding genes and 72 RNA-only encoding genes. In conclusion, this rhizobial genome was sequenced as part of the DOE Joint Genome Institute 2010 Genomic Encyclopedia for Bacteria and Archaea-Root Nodule Bacteria (GEBA-RNB) project.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Deep convolutional neural networks for multi-scale time-series classification and application to tokamak disruption prediction using raw, high temporal resolution diagnostic data

In this paper we discuss recent advances in deep convolutional neural networks (CNN) for sequence learning, which allow identifying long-range, multi-scale phenomena in long sequences, such as those found in fusion plasmas. We point out several benefits of these deep CNN architectures, such as not requiring experts such as physicists to hand-craft input data features, the ability to capture longer range dependencies compared to the more common sequence neural networks (recurrent neural networks like long short-term memory (LSTM) networks), and the comparative computational efficiency. We apply this neural network architecture to the popular problem of disruption prediction in fusion energy tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. Initial results trained on a large ECEi dataset show promise, achieving an F 1 -score of ~91% on individual time-slices using only the ECEi data. This indicates the ECEi diagnostic by itself can be sensitive to a number of pre-disruption markers useful for predicting disruptions on timescales not only for mitigation but also avoidance. Future opportunities for utilizing these deep CNN architectures with fusion data are outlined, including impact of recent upgrades to the ECEi diagnostic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

MAGNETIC ACTIVITY ANALYSIS FOR A SAMPLE OF G-TYPE MAIN SEQUENCE KEPLER TARGETS

The variation of a stellar light curve owing to rotational modulation by magnetic features (starspots and faculae) on the star’s surface can be used to investigate the magnetic properties of the host star. In this paper, we use the periodicity and magnitude of the light-curve variation as two proxies to study the stellar magnetic properties for a large sample of G-type main sequence Kepler targets, for which the rotation periods were recently determined. By analyzing the correlation between the two magnetic proxies, it is found that: (1) the two proxies are positively correlated for most of the stars in our sample, and the percentages of negative, zero, and positive correlations are 4.27%, 6.81%, and 88.91%, respectively; (2) negative correlation stars cannot have a large magnitude of light-curve variation; and (3) with the increase of rotation period, the relative number of positive correlation stars decreases and the negative correlation one increases. These results indicate that stars with shorter rotation period tend to have positive correlation between the two proxies, and a good portion of the positive correlation stars have a larger magnitude of light-curve variation (and hence more intense magnetic activities) than negative correlation stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Genome sequence of the South American clover-nodulating Rhizobium leguminosarum bv. trifolii strain WSM597

Rhizobium leguminosarum bv. trifolii strain WSM597 is an aerobic, motile, Gram-negative, nonspore-forming rod isolated from a root nodule of the annual clover Trifolium pallidum L. growing at Glencoe Research Station near Tacuarembó, Uruguay. This strain is generally ineffective for nitrogen (N2 ) fixation with clovers of Mediterranean, North American and African origin, but is effective on the South American perennial clover T. polymorphum Poir. Here we describe the features of R. leguminosarum bv. trifolii strain WSM597, together with genome sequence information and annotation. The 7,634,384 bp high-quality-draft genome is arranged in 2 scaffolds of 53 contigs, contains 7,394 protein-coding genes and 87 RNA-only encoding genes, and is one of 20 rhizobial genomes sequenced as part of the DOE Joint Genome Institute 2010 Community Sequencing Program.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Genome sequence of the Wenxinia marina type strain (DSM 24838 T ), a representative of the Roseobacter group isolated from oilfield sediments

Wenxinia marina Ying et al. 2007 is the type species of the genus Wenxinia, a representative of the Roseobacter group within the alphaproteobacterial family Rhodobacteraceae, isolated from oilfield sediments of the South China Sea. This family was shown to harbor the most abundant bacteria especially from coastal and polar waters, but was also found in microbial mats, sediments and attached to different kind of surfaces. Here we describe the features of W. marina strain HY34 T together with the genome sequence and annotation of strain DSM 24838 T and novel aspects of its phenotype. The 4,181,754 bp containing genome sequence encodes 4,047 protein-coding genes and 59 RNA genes. The genome of W. marina DSM 24838 T was sequenced as part of the activities of the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes (KMG) project funded by the DoE and the Transregional Collaborative Research Centre 51 (TRR51) funded by the German Research Foundation (DFG).

59 BASIC BIOLOGICAL SCIENCES↗