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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Detection of Apparent Early Rabies Infection by LN34 Pan-Lyssavirus Real-Time RT-PCR Assay in Pennsylvania

The Pennsylvania Department of Health Bureau of Laboratories (PABOL) tested 6855 animal samples for rabies using both the direct fluorescent antibody test (DFA) and LN34 pan-lyssavirus reverse transcriptase quantitative PCR (RT-qPCR) during 2017–2019. Only two samples (0.03%) were initially DFA negative but positive by LN34 RT-qPCR. Both cases were confirmed positive upon re-testing at PABOL and confirmatory testing at the Centers for Disease Control and Prevention by LN34 RT-qPCR and DFA. Rabies virus sequences from one sample were distinct from all positive samples processed at PABOL within two weeks, ruling out cross-contamination. Levels of rabies virus antigen and RNA were low in all brain structures tested, but were higher in brain stem and rostral spinal cord than in cerebellum, hippocampus or cortex. Taken together, the low level of rabies virus combined with higher abundance in more caudal brain structures suggest early infection. These cases highlight the increased sensitivity and ease of interpretation of LN34 RT-qPCR for low positive cases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Intermediate-phase engineering via dimethylammonium cation additive for stable perovskite solar cells

Achieving the long-term stability of perovskite solar cells is arguably the most important challenge required to enable widespread commercialization. Understanding the perovskite crystallization process and its direct impact on device stability is critical to achieving this goal. The commonly employed dimethyl-formamide/dimethyl-sulfoxide solvent preparation method results in a poor crystal quality and microstructure of the polycrystalline perovskite films. In this work, we introduce a high-temperature dimethyl-sulfoxide-free processing method that utilizes dimethylammonium chloride as an additive to control the perovskite intermediate precursor phases. By controlling the crystallization sequence, we tune the grain size, texturing, orientation (corner-up versus face-up) and crystallinity of the formamidinium (FA)/caesium (FA) y Cs 1-y Pb(I x Br 1-x )3 perovskite system. A population of encapsulated devices showed improved operational stability, with a median T80 lifetime (the time over which the device power conversion efficiency decreases to 80% of its initial value) for the steady-state power conversion efficiency of 1,190 hours, and a champion device showed a T80 of 1,410 hours, under simulated sunlight at 65 degrees C in air, under open-circuit conditions. In conclusion, this work highlights the importance of material quality in achieving the long-term operational stability of perovskite optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2025

RingX: Scalable Parallel Attention for Long-Context Learning on HPC

The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to power frontier models such as large-scale reasoning language models and high-resolution image/video generators. However, its quadratic computational and memory complexities present substantial challenges. Current state-of-the-art parallel attention methods, such as ring attention, are widely adopted for long-context training but utilize a point-to-point communication strategy that fails to fully exploit the capabilities of modern HPC network architectures. In this work, we propose ringX, a scalable family of parallel attention methods optimized explicitly for HPC systems. By enhancing workload partitioning, refining communication patterns, and improving load balancing, ringX achieves up to 3.4 × speedup compared to conventional ring attention on the Frontier supercomputer. Optimized for both bi-directional and causal attention mechanisms, ringX demonstrates its effectiveness through training benchmarks of a Vision Transformer (ViT) on a climate dataset and a Generative Pre-Trained Transformer (GPT) model, Llama3 8B. Our method attains an end-to-end training speedup of approximately 1.5 × in both scenarios. To our knowledge, the achieved 38% model FLOPs utilization (MFU) for training Llama3 8B with a 1M-token sequence length on 4,096 GPUs represents one of the highest training efficiencies reported for long-context learning on HPC systems. Our code implementation is available at https://github.com/jqyin/ringX-attention.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗
DOE OSTI2025

Direct observation of oxygen vacancy ordering evolution in cerium oxide at varying concentrations via high-resolution transmission electron microscopy

Under illumination by a 300 keV electron beam, oxygen vacancy ordering structures are induced within cerium oxide grains. Here, our high-resolution transmission electron microscopy (HRTEM) study, supported by image simulation, reveals the evolution of these structures as vacancy concentration increases. The observed fluorite-type superlattice structures are identified as CeO 1.825 , CeO 1.75 , Ce 2 O 3 , displaying a gradient in oxygen vacancy concentration moving away from the grain surface. Correspondingly, the structural sequence transitions from Ce 2 O 3 to CeO 1.75 and then to CeO 1.825 . Without the constraints of surrounding grains, fluorite-type Ce 2 O 3 nanocrystals show a preference for transformation into an A-type trigonal structure. Notably, at temperatures up to 200°C, only the perfect fluorite structure is observed. Structural models were validated through both [110] and [001] projections. Our findings further confirm lattice expansion associated with local oxygen vacancy enrichment, which can be compensated by the formation of stacking faults, where a {111} oxygen plane is lost at defect sites.

Cerium oxide↗
DOE OSTI2022

An expanded role for the transcription factor WRINKLED1 in the biosynthesis of triacylglycerols during seed development

The transcription factor WRINKLED1 ( WRI1 ) is known as a master regulator of fatty acid synthesis in developing oilseeds of Arabidopsis thaliana and other species. WRI1 is known to directly stimulate the expression of many fatty acid biosynthetic enzymes and a few targets in the lower part of the glycolytic pathway. However, it remains unclear to what extent and how the conversion of sugars into fatty acid biosynthetic precursors is controlled by WRI 1. To shortlist possible gene targets for future in-planta experimental validation, here we present a strategy that combines phylogenetic foot printing of cis-regulatory elements with additional layers of evidence. Upstream regions of protein-encoding genes in A. thaliana were searched for the previously described DNA-binding consensus for WRI1, the ASML1/WRI1 (AW)-box. For about 900 genes, AW-box sites were found to be conserved across orthologous upstream regions in 11 related species of the crucifer family. For 145 select potential target genes identified this way, affinity of upstream AW-box sequences to WRI1 was assayed by Microscale Thermophoresis. This allowed definition of a refined WRI1 DNA-binding consensus. We find that known WRI1 gene targets are predictable with good confidence when upstream AW-sites are phylogenetically conserved, specifically binding WRI1 in the in vitro assay, positioned in proximity to the transcriptional start site, and if the gene is co-expressed with WRI1 during seed development. When targets predicted in this way are mapped to central metabolism, a conserved regulatory blueprint emerges that infers concerted control of contiguous pathway sections in glycolysis and fatty acid biosynthesis by WRI1. Several of the newly predicted targets are in the upper glycolysis pathway and the pentose phosphate pathway. Of these, plastidic isoforms of fructokinase ( FRK 3) and of phosphoglucose isomerase ( PGI 1) are particularly corroborated by previously reported seed phenotypes of respective null mutations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

DeepShake: Shaking Intensity Prediction Using Deep Spatiotemporal RNNs for Earthquake Early Warning

Abstract We propose a deep spatiotemporal recurrent neural network, DeepShake, to project future shaking intensity directly from current ground-motion observations. DeepShake is a network-based forecasting model, able to predict future shaking intensity at all stations within a network given previously measured ground shaking. The model is not given any a priori knowledge of station locations; instead, it learns wave propagation amplitudes and delays solely from training data. We developed DeepShake with the 35,679 earthquakes from the 2019 Ridgecrest sequence. Tasked with alerting for modified Mercalli intensity (MMI) IV+ shaking on 3568 validation earthquakes at least 5 s in advance, DeepShake achieves an equal error rate of 11.4%. For the Mw 7.1 earthquake that hit Ridgecrest on 5 July 2019, DeepShake was able to provide targeted alerts to all stations inside the network 5 s prior to the arrival of MMI IV+ waveforms. DeepShake demonstrates that deep spatiotemporal neural networks can effectively provide one-step earthquake early warning with reasonable accuracy and latency.

Geochemistry & Geophysics↗
DOE OSTI2021

The Ephb2 Receptor Uses Homotypic, Head-to-Tail Interactions within Its Ectodomain as an Autoinhibitory Control Mechanism

The Eph receptor tyrosine kinases and their ephrin ligands direct axon pathfinding and neuronal cell migration, as well as mediate many other cell–cell communication events. Their dysfunctional signaling has been shown to lead to various diseases, including cancer. The Ephs and ephrins both localize to the plasma membrane and, upon cell–cell contact, form extensive signaling assemblies at the contact sites. The Ephs and the ephrins are divided into A and B subclasses based on their sequence conservation and affinities for each other. The molecular details of Eph–ephrin recognition have been previously revealed and it has been documented that ephrin binding induces higher-order Eph assemblies, which are essential for full biological activity, via multiple, distinct Eph–Eph interfaces. One Eph–Eph interface type is characterized by a homotypic, head-to-tail interaction between the ligand-binding and the fibronectin domains of two adjacent Eph molecules. While the previous Eph ectodomain structural studies were focused on A class receptors, we now report the crystal structure of the full ectodomain of EphB2, revealing distinct and unique head-to-tail receptor–receptor interactions. The EphB2 structure and structure-based mutagenesis document that EphB2 uses the head-to-tail interactions as a novel autoinhibitory control mechanism for regulating downstream signaling and that these interactions can be modulated by posttranslational modifications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

GRIP: Constraint-based Explanation of Missing Answers for Graph Queries

Abstract: A useful feature in graph query engines is to clarify “Why certain entities (nodes, attribute values or edges) are missing” in query answers. This task is even more challenging when the relevant data is already missing in the underlying data source. Missing data, on the other hand, can be inferred by enforcing data constraints for graphs. We demonstrate GRIP, a system that exploits data constraints to clarify missing answers for graph queries. (1) Constraint-based ex- planation. Given a desired yet missing entity in the query answer, GRIP ensures to generate finite and minimal sequences of data con- strains (an “explanation”) that should be consecutively enforced to ?? to ensure its occurrence for the same query. (2) Answering “why” and“how” questions. Users can query GRIP with both“Why”(“Why” the element is missing) and “How” questions (“How” to refine the graph to include the missing answer). GRIP engine supports run- time generation of explanations by incrementally maintaining a set of bi-directional search trees. (3) Interactive exploration. GRIP provides a user-friendly GUI to support interactive ad visual exploration of explanations, including both automated generation and step-by-step inspection of graph manipulations.

graphs↗
DOE OSTI2021

Optical Biosensor Platforms Display Varying Sensitivity for the Direct Detection of Influenza RNA

Detection methods that do not require nucleic acid amplification are advantageous for viral diagnostics due to their rapid results. These platforms could provide information for both accurate diagnoses and pandemic surveillance. Influenza virus is prone to pandemic-inducing genetic mutations, so there is a need to apply these detection platforms to influenza diagnostics. Here, we analyzed the Fast Evaluation of Viral Emerging Risks (FEVER) pipeline on ultrasensitive detection platforms, including a waveguide-based optical biosensor and a flow cytometry bead-based assay. The pipeline was also evaluated in silico for sequence coverage in comparison to the U.S. Centers for Disease Control and Prevention’s (CDC) influenza A and B diagnostic assays. The influenza FEVER probe design had a higher tolerance for mismatched bases than the CDC’s probes, and the FEVER probes altogether had a higher detection rate for influenza isolate sequences from GenBank. When formatted for use as molecular beacons, the FEVER probes detected influenza RNA as low as 50 nM on the waveguide-based optical biosensor and 1 nM on the flow cytometer. In addition to molecular beacons, which have an inherently high background signal we also developed an exonuclease selection method that could detect 500 pM of RNA. The combination of high-coverage probes developed using the FEVER pipeline coupled with ultrasensitive optical biosensors is a promising approach for future influenza diagnostic and biosurveillance applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The Relationship Between Dose Rate and Decay Heat for Spent Nuclear Fuel Casks

Decay heat and dose rate are two important limits used for determining the allowable contents of spent fuel (SNF) in dry storage systems and transportation packages. While the decay heat limit is used to maintain fuel cladding integrity and ensure retrievability, dose rates are used to demonstrate compliance with regulatory requirements on radiation protection. Because both dose rate and decay heat result from decay of radioisotopes in SNF, this study is an attempt to examine the relationship between dose rate and decay heat for a given cask design. Dose rates were evaluated for 198 cask configurations, that include various SNF system designs (e.g., storage, transfer, transport), SNF characteristics (e.g., fuel types, burnup, cooling time), and loading maps (e.g., uniform loading, zone loading), while a constant decay heat was maintained. The decay heat was calculated using US Nuclear Regulatory Commission (NRC) Regulatory Guide (RG) 3.54, Revision 2, and verified using ORIGEN sequence within SCALE code system. The ORIGEN outputs were used as source terms in the dose analysis using 198 different configurations. A computer script was developed to calculate the cooling time necessary to achieve a given decay heat for a given enrichment, assembly average burnup, assembly mass, and in-core history using a rootfinder algorithm. Initially the computer script was developed to provide cooling time and burnup calculations directly to the analysis of dose rates and decay heats, so a comparison between Used Nuclear Fuel-Storage Transportation and Disposal Analysis Resource Data System (UNF-ST&DARDS) results and RG3.54 data was made; results are included in the appendix to this document. However, an iterative approach was used to compute cooling time, and its accuracy did not depend on the results of the RG3.54r2 algorithm, although the algorithm was still used. The results of the evaluation presented herein clearly demonstrate that a given decay heat does not correspond to a unique dose rate for a variety of cask and package designs. There is no clear pattern to develop a correlation between decay heat and the source terms. Depending on burnup, enrichment, cask type, and loading pattern, dose rates varied for the exact same decay heat—in some cases by 400% for a given cask. For cases in which decay heat was held constant through selection of the appropriate cooling time, dose rates would decrease with increasing burnup, and in other cases, dose rates would increase. The large variation in dose rates for a constant decay heat indicates that casks loaded based on decay heat—that is allowing any burnup, cooling time, and enrichment combinations that yield the qualified decay heat limit(s) —cannot ensure that an Independent Spent Fuel Storage Installation or a spent fuel transportation package will meet the regulatory limits set forth by the respective regulations, i.e., 10 CFR 72 or 10 CFR 71.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Chimera Spectrum Diagnostics for Peptides Using Two-Dimensional Partial Covariance Mass Spectrometry

The rate of successful identification of peptide sequences by tandem mass spectrometry (MS/MS) is adversely affected by the common occurrence of co-isolation and co-fragmentation of two or more isobaric or isomeric parent ions. This results in so-called `chimera spectra’, which feature peaks of the fragment ions from more than a single precursor ion. The totality of the fragment ion peaks in chimera spectra cannot be assigned to a single peptide sequence, which contradicts a fundamental assumption of the standard automated MS/MS spectra analysis tools, such as protein database search engines. This calls for a diagnostic method able to identify chimera spectra to single out the cases where this assumption is not valid. Here, we demonstrate that, within the recently developed two-dimensional partial covariance mass spectrometry (2D-PC-MS), it is possible to reliably identify chimera spectra directly from the two-dimensional fragment ion spectrum, irrespective of whether the co-isolated peptide ions are isobaric up to a finite mass accuracy or isomeric. We introduce ‘3-57 chimera tag’ technique for chimera spectrum diagnostics based on 2D-PC-MS and perform numerical simulations to examine its efficiency. We experimentally demonstrate the detection of a mixture of two isomeric parent ions, even under conditions when one isomeric peptide is at one five-hundredth of the molar concentration of the second isomer.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Intense Reactivity in Sulfur–Hydrogen Mixtures at High Pressure under X-ray Irradiation

Superconductivity near room temperature in the sulfur–hydrogen system arises from a sequence of reactions at high pressures, with X-ray diffraction experiments playing a central role in understanding these chemical–structural transformations and the corresponding S:H stoichiometry. Here we document X-ray irradiation acting as both a probe and as a driver of chemical reaction in this dense hydride system. We observe a reaction between molecular hydrogen (H 2 ) and elemental sulfur (S 8 ) under high pressure, induced directly by X-ray illumination, at photon energies of 12 keV using a free electron laser. The rapid synthesis of hydrogen sulfide (H 2 S) at 0.3 GPa was confirmed by optical observations, spectroscopic measurements, and microstructural changes detected by X-ray diffraction. These results document X-ray induced chemical synthesis of superconductor-forming dense hydrides, revealing an alternative production strategy and confirming the disruptive nature of X-ray exposure in studies on high-pressure hydrogen chalcogenides, from water to high-temperature superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

MUSEQuBES: calibrating the redshifts of Ly α emitters using stacked circumgalactic medium absorption profiles

ABSTRACT Ly α emission lines are typically found to be redshifted with respect to the systemic redshifts of galaxies, likely due to resonant scattering of Ly α photons. Here, we measure the average velocity offset for a sample of 96 z ≈ 3.3 Ly α emitters (LAEs) with a median Ly α flux (luminosity) of ${\approx}10^{-17}~\rm erg~cm^{-2}~s^{-1}$ (${\approx}10^{42}~\rm erg~s^{-1}$) and a median star formation rate (SFR) of ≈1.3 $\rm M_{\odot }~yr^{-1}$ (not corrected for possible dust extinction), detected by the Multi-Unit Spectroscopic Explorer as part of our MUSEQuBES circumgalactic medium (CGM) survey. By postulating that the stacked CGM absorption profiles of these LAEs, probed by eight background quasars, must be centred on the systemic redshift, we measure an average velocity offset, Voffset = 171\pm 8 km s−1, between the Ly α emission peak and the systemic redshift. The observed Voffset is lower by factors of ≈1.4 and ≈2.6 compared to the velocity offsets measured for narrow-band-selected LAEs and Lyman break galaxies, respectively, which probe galaxies with higher masses and SFRs. Consistent with earlier studies based on direct measurements for individual objects, we find that the Voffset is correlated with the full width at half-maximum of the red peak of the Ly α line, and anticorrelated with the rest-frame equivalent width. Moreover, we find that Voffset is correlated with SFR with a sub-linear scaling relation, $V_{\rm offset}\propto \rm SFR^{0.16\pm 0.03}$. Adopting the mass scaling for main-sequence galaxies, such a relation suggests that Voffset scales with the circular velocity of the dark matter haloes hosting the LAEs.

Muzahid, Sowgat↗
DOE OSTI2022

Precision genome editing in plants using gene targeting and prime editing: existing and emerging strategies

Precise modification of plant genomes, such as seamless insertion, deletion, or replacement of DNA sequences at a predefined site, is a challenging task. Gene targeting (GT) and prime editing are currently the best approaches for this purpose. However, these techniques are inefficient in plants, which limits their applications for crop breeding programs. Recently, substantial developments have been made to improve the efficiency of these techniques in plants. Several strategies, such as RNA donor templating, chemically modified donor DNA template, and tandem-repeat homology-directed repair, are aimed at improving GT. Additionally, improved prime editing gRNA design, use of engineered reverse transcriptase enzymes, and splitting prime editing components have improved the efficacy of prime editing in plants. These emerging strategies and existing technologies are reviewed along with various perspectives on their future improvement and the development of robust precision genome editing technologies for plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

One-pot generation of lignin microspheres and digestible substrate with a polyol-DES pretreatment in high solid loading

Previous lignin microspheres (LMS) preparation needs multiple steps with very low yield and high cost. Herein, we developed a high-solid deep eutectic solvent (DES) pretreatment for an effective lignin fractionation and enzymatic saccharification of moso bamboo under mild temperature (110 °C) with high-solid loading. Lignin was significantly removed from the plant cell wall, and cellulose properties (e.g., crystallinity and degree of polymerization) were also altered during the pretreatment. As a result, the enzymatic digestibility of the pretreated bamboo was dramatically increased. Uniform micro-spherical lignin was directly produced from the pretreatment system, and its particle size could be regulated by controlling the solid loadings and pretreatment temperatures. The lignin microspheres formation mechanism was investigated by analyzing the lignin's size distribution, molecular weight distribution, chemical structure, and hydrophobicity. The DES showed excellent recyclability, and the recycled DES could still remove 42.78% lignin even after 7th circulation associated with 100% glucan saccharification. Further, the mass balance based on 1000 g biomass showed that 196.28 g LMS was directly recovered, which exhibited a high RhB adsorption. Besides, 404.91 g glucose and 36.67 g xylose were obtained after the enzymatic saccharification process. Specifically, GAPI analysis exhibited a near total green and yellow portions of the pictogram, indicating our DES process was green enough to make this biorefinery sustainable. Overall, the proposed DES generated synergistic productions of digestible solid and LMS which could contribute to establish a green and sustainable biorefinery sequence with diverse outputs in one pot.

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

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2023

UniKP: a unified framework for the prediction of enzyme kinetic parameters

Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes for various biotechnological and industrial applications, but the limited performance of current prediction tools on diverse tasks hinders their practical applications. Here, we introduce UniKP, a unified framework based on pretrained language models for the prediction of enzyme kinetic parameters, including enzyme turnover number (k cat ), Michaelis constant (K m ), and catalytic efficiency (k cat / K m ), from protein sequences and substrate structures. A two-layer framework derived from UniKP (EF-UniKP) has also been proposed to allow robust k cat prediction in considering environmental factors, including pH and temperature. In addition, four representative re-weighting methods are systematically explored to successfully reduce the prediction error in high-value prediction tasks. We have demonstrated the application of UniKP and EF-UniKP in several enzyme discovery and directed evolution tasks, leading to the identification of new enzymes and enzyme mutants with higher activity. UniKP is a valuable tool for deciphering the mechanisms of enzyme kinetics and enables novel insights into enzyme engineering and their industrial applications.

59 BASIC BIOLOGICAL SCIENCES↗