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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

β-Delayed One and Two Neutron Emission Probabilities Southeast of 132 Sn and the Odd-Even Systematics in r-Process Nuclide Abundances

Here, the β-delayed one- and two-neutron emission probabilities (P 1n and P 2n ) of 20 neutron-rich nuclei with N≥82 have been measured at the RIBF facility of the RIKEN Nishina Center. P 1n of 130,131 Ag, 133,134 Cd, 135,136 In, and 138,139 Sn were determined for the first time, and stringent upper limits were placed on P2n for nearly all cases. β-delayed two-neutron emission (β2n) was unambiguously identified in 133 Cd and 135,136 In, and their P 2n were measured. Weak β2n was also detected from 137,138 Sn. Our results highlight the effect of the N=82 and Z=50 shell closures on β-delayed neutron emission probability and provide stringent benchmarks for newly developed macroscopic-microscopic and self-consistent global models with the inclusion of a statistical treatment of neutron and γ emission. The impact of our measurements on r-process nucleosynthesis was studied in a neutron star merger scenario. Our P 1n and P 2n have a direct impact on the odd-even staggering of the final abundance, improving the agreement between calculated and observed Solar System abundances. The odd isotope fraction of Ba in r-process-enhanced (r-II) stars is also better reproduced using our new data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, sub­tomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement↗
DOE OSTI2022

Systematic electronic structure in the cuprate parent state from quantum many-body simulations

The quantitative description of correlated electron materials remains a modern computational challenge. We demonstrate a numerical strategy to simulate correlated materials at the fully ab initio level beyond the solution of effective low-energy models and apply it to gain a detailed microscopic understanding across a family of cuprate superconducting materials in their parent undoped states. We uncover microscopic trends in the electron correlations and reveal the link between the material composition and magnetic energy scales through a many-body picture of excitation processes involving the buffer layers. Our work illustrates a path toward a quantitative and reliable understanding of more complex states of correlated materials at the ab initio many-body level.

Science & Technology - Other Topics↗
DOE OSTI2023

Systematic Analysis of Metabolic Bottlenecks in the Methylerythritol 4-Phosphate (MEP) Pathway of Zymomonas mobilis

Engineered microorganisms have the potential to convert renewable substrates into biofuels and valuable bioproducts, which offers an environmentally sustainable alternative to fossil-fuel-derived products. Isoprenoids are a diverse class of biologically derived compounds that have commercial applications as various commodity chemicals, including biofuels and biofuel precursor molecules.

isoprene↗
DOE OSTI2023

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes.

16S rRNA↗
DOE OSTI2025

Revealing systematic changes in the transcriptome during the transition from exponential growth to stationary phase

ABSTRACT The composition of bacterial transcriptomes is determined by the transcriptional regulatory network (TRN). The TRN regulates the transition from one physiological state to another. Here, we use independent component analysis to monitor the composition of the transcriptome during the transition from the exponential growth phase to the stationary phase. With Escherichia coli K-12 MG1655 as a model strain, we trigger the transition using carbon, nitrogen, and sulfur starvation. We find that (i) the transition to the stationary phase accompanies common transcriptome changes, including increased stringent responses and reduced production of cellular building blocks and energy regardless of the limiting element; (ii) condition-specific changes are strongly associated with transcriptional regulators ( e.g. , Crp, NtrC, CysB, Cbl) responsible for metabolizing the limiting element; and (iii) the shortage of each limiting element differentially affects the production of amino acids and extracellular polymers. This study demonstrates how the combination of genome-scale datasets and new data analytics reveals the fundamental characteristics of a key transition in the life cycle of bacteria. IMPORTANCE Nutrient limitations are critical environmental perturbations in bacterial physiology. Despite its importance, a detailed understanding of how bacterial transcriptomes are adjusted has been limited. By utilizing independent component analysis (ICA) to decompose transcriptome data, this study reveals key regulatory events that enable bacteria to adapt to nutrient limitations. The findings not only highlight common responses, such as the stringent response, but also condition-specific regulatory shifts associated with carbon, nitrogen, and sulfur starvation. The insights gained from this work advance our knowledge of bacterial physiology, gene regulation, and metabolic adaptation.

Lim, Hyun Gyu (ORCID:0000000204692388)↗
DOE OSTI2020

Systematic Study of the Cathode Compositional Dependency of Cross-Talk Behavior in Li-Ion Battery

While LiNi x Mn y Co 1-x-y O 2 (NMC) is one of the most widely used cathode materials for lithium-ion batteries (LIBs), the composition of NMC is evolving to Ni-rich NMC to achieve higher lithium capacity that fulfills the constant demand for LIBs with ever-higher energy densities. The change in the composition of NMC affects electrochemical features and electrode cross-talk, which explains the performance change during cycling. Here in this study, we introduce various NMC materials (LiNi 0.5 Mn 0.3 Co 0.2 O 2 , LiNi 0.6 Mn 0.2 Co 0.2 O 2 and LiNi 0.8 Mn 0.1 Co 0.1 O 2 ) to reveal how the NMC composition affects electrode cross-talk. The study reveals that NMC composition strongly affects transition metal dissolution; dissolution of manganese linearly decreases as its stoichiometric ratio in NMC decreases, while dissolution of nickel is only prominent in LiNi 0.8 Mn 0.1 Co 0.1 O 2 . Aged electrolyte samples are characterized with high-performance liquid chromatography, and two electrolyte decomposition species, C 8 H 16 O 5 and C 9 H 18 O 5 , are identified across all samples.

25 ENERGY STORAGE↗
DOE OSTI2020

The Efficacy and Safety of Mesalamine and Probiotics in Mild‐to‐Moderate Ulcerative Colitis: A Systematic Review and Meta‐Analysis

Objective . To evaluate the efficacy and safety of mesalamine in conjunction with probiotics for ulcerative colitis. Methods . Random controlled trials (RCTs) were searched in PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang, and VIP (VIP Database for Chinese Technical Periodicals) from inception to October 2019. Methodological quality was assessed by the Cochrane Collaboration tool. The quality of evidence was rated by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Data analysis was carried out in Review Manager 5.3. Results . A total of fifteen studies met the criteria for inclusion. Thirteen studies reported the clinical efficacy, three studies provided data on the clinical symptom scores, two trials reported disease activity index, four studies evaluated endoscopic score, and twelve studies reported adverse events. For ulcerative colitis (UC), mesalamine and probiotics had better clinical efficacy than mesalamine alone (≤8 weeks: RR = 1.12, 95% CI: 1.07–1.18, P < 0.0001; >8 weeks: RR = 1.25, 95% CI: 1.11–1.41, P = 0.0003). On the clinical symptom scores, disease activity index, and endoscopic score, UC patients receiving mesalamine and probiotics had significant difference than patients receiving mesalazine alone (MD = −2.02, 95% CI: −3.28 to −0.76, P = 0.002; MD = −1.20, 95% CI: −1.76 to −0.65, P < 0.001; and MD = −0.42, 95% CI: −0.61 to −0.23, P < 0.0001, respectively). There was no statistically significant difference in adverse events between the two groups (RR = 0.88, 95% CI: 0.54 to 1.43, P = 0.60). Conclusion . Our meta‐analysis results supported that mesalamine and probiotics were effective and safe in treating ulcerative colitis.

Tian, Chunying↗