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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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88 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Viruses of Nitrogen-Fixing Mesorhizobium Bacteria in Globally Distributed Chickpea Root Nodules

Legume nodules are specialized environments on plant roots that are induced and dominated by nitrogen-fixing bacteria. Bacteriophages (phages) in these nodules could potentially provide top-down controls on the population size and, therefore, the function of nitrogen-fixing symbionts. Here we sought to characterize the diversity and biogeographical patterns of phages that infect nitrogen-fixing Mesorhizobium symbionts isolated from root nodules, leveraging 266 genomes of Mesorhizobium isolated from nodules and 648 nodule metagenomes collected from three species of chickpea plants ( Cicer spp.) under different agricultural management practices, spanning eight countries on five continents. We identified 106 phage populations (viral operational taxonomic units [vOTUs]) in Mesorhizobium draft genomes, 37% of which were confirmed as likely prophages. These vOTUs were detected in 64% of the Mesorhizobium-dominated nodule metagenomes and 58% of the Mesorhizobium isolates. Per metagenome, 1 to 16 putative Mesorhizobium vOTUs were detected, with more than half of the nodules containing only one such vOTU. The majority of vOTUs were detected exclusively in Ethiopia, followed by India and Morocco, with the lowest richness of putative Mesorhizobium phages in countries that applied industrial Mesorhizobium inoculants to crops. Two vOTUs were identified in five or more countries and in nodules dominated by different strains of Mesorhizobium, suggesting infection of diverse Mesorhizobium hosts and long-term interactions. Beta-diversity of these Mesorhizobium phage assemblages was significantly correlated with the dominant Mesorhizobium strain, but not with measured environmental parameters. Our findings indicate that nitrogen-fixing nodules in chickpea plants can contain distinct viral assemblages, with potential impacts on the nodule microbiome that bear further exploration.

Microbiology↗
DOE OSTI2020

Anomalous neutron yields confirmed for Ba-Mo and newly observed for Ce-Zr from spontaneous fission of Cf 252

We reinvestigated the neutron multiplicity yields of Ba-Mo, Ce-Zr, Te-Pd, and Nd-Sr from the spontaneous fission of 252 Cf by (i) using both γ -γ -γ -γ and γ -γ -γ coincidence data, (ii) using up to date level scheme structures, and (iii) crosschecking analogous energy transitions in multiple isotopes, we have achieved higher precision than previous analyses. Particular attention was given to the Ba-Mo pairs where our results clearly confirm that the Ba-Mo yield data have a second hot fission mode where 8–10, and now 11 neutron evaporation channels are observed. These are the first observations of the 11 neutron channel. These 8–11 neutron channels are observed for the first time in the Ce-Zr pairs, but are not observed in other fission pairs. The measured intensities of the second mode in Ba-Mo and Ce-Zr pairs are ~1.5(4)% and ~1.0(3)%, respectively. These high neutron number evaporation modes can be an indication of hyperdeformation and/or octupole deformation in 143-145 Ba and in 146,148 Ce at scission to give rise to such high neutron multiplicities.

252-Cf↗
DOE OSTI2020

Structure of Nd 155 and Gd 163 from Cf 252 spontaneous fission

Background: A puzzle has arisen recently caused by the apparent shift in maximum deformation from the expected 66 Dy isotopic chain to the Nd 60 isotopic chain in the 82 155 Nd and 163 Gd, useful for constraining parameters in models that seek to answer the six proton shift in maximum deformation. Method: Data from the spontaneous fission of 252 Cf were taken by the Gammasphere detector array at Lawrence Berkeley National Laboratory to observe the excited states of 155 Nd and 163 Gd. Results: The structure of 163 Gd has been expanded with the addition of two new levels and three new γ rays, which are found to be consistent with previously published calculations and the structure of 165 Dy. In 155 Nd, nine new levels and 12 new γ rays are observed. The spins and parities of the previously known levels in 155 Nd have been reassigned from a ν3/2 - [521] ground state configuration to a ν5/2 + [642] isomeric configuration by comparison of these newly observed levels with levels in 153 Nd and 155 Sm. Conclusion: Further experimentation is required to determine the energy of the newly reassigned ν5/2+[642] level in 155 Nd with respect to the suspected ν3/2-[521] ground state. Additionally, more experiments should be conducted to further determine the structure of neutron rich nuclei, rarely produced in the spontaneous fission of 252 Cf, such as 163 Gd.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Pseudospin-doublet bands and Gallagher Moszkowski doublet bands in 100 Y

New transitions in neutron-rich 100 Y have been identified in a 9 Be + 238 U experiment with mass and Z gates to provide full fragment identification. These transitions and high spin levels of 100 Y have been investigated by analyzing the high statistics γ–γ–γ and γ–γ–γ–γ coincidence data from the spontaneous fission of 252 Cf at the Gammasphere detector array. Two new bands, 14 new levels, and 23 new transitions have been identified. The K π = 4 + new band decaying to a 1s isomeric state is assigned to be the high-K Gallagher-Moszkowski (GM) partner of the known K π = 1 + band, with the π5/2[522]Ⓧν3/2[411] configuration. This 4 + band is also proposed to be the pseudospin partner of the new K π = 5 + band with a 5 + π5/2[422] Ⓧ ν5/2[413] configuration, to form a π5/2[422] Ⓧ ν[3125/2,3/2] neutron pseudospin doublet. Here, constrained triaxial covariant density-functional theory and quantal particle rotor model calculations have been applied to interpret the band structure and available electromagnetic transition probabilities and are found to be in good agreement with experimental values.

100Y↗
DOE OSTI2020

Coexistence of Reflection Asymmetric and Symmetric Shapes in $^{144}\mathrm{Ba}$

Level structures in the neutron-rich $^{144}\mathrm{Ba}$ nucleus have been reinvestigated by measuring prompt gamma rays in the spontaneous fission of $^{252}\mathrm{Cf}$. The previous $s = +1$ octupole band structure with reflection asymmetric shape has been expanded, and a side quadrupole band structure based on a $3^+$ state with reflection symmetric shape is identified. Thus, the results show the coexistence of reflection asymmetric and symmetric shapes in $^{144}\mathrm{Ba}$. This is a first identification of such a shape coexistence structure in a nuclear structure. Finally, the other structural characteristics are discussed.

144Ba↗
DOE OSTI2025

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

DNase Treatment Improves Viral Enrichment in Agricultural Soil Viromes

Viromics is becoming an increasingly popular method for characterizing soil viral communities. DNase treatment of the viral size fraction prior to DNA extraction is meant to reduce contaminating free DNA and is a common step within viromics protocols to ensure that sequences are of viral origin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

First observation of collective rotational bands in neutron-rich 142 La and the study of octupole/triaxial deformations in 142,143 La

Collective rotational bands were observed for the first time in neutron-rich odd–odd 142 La by means of γ-γ-γ and γ-γ-γ-γ coincidence measurements of prompt fission γ rays from 252 Cf using multi-detector array Gammasphere. Similarity between the yrast band of 142 La and those of neighboring 144 La, 144 Ce was found and interpreted as quasiparticle excitations. Here, PES calculations suggested triaxial deformation for the ground state of 142La. Considerable triaxial and near zero octupole deformations were deduced for the yrast band of 142 La by the TRS model calculations. The band-crossing observed in the yrast band of 142 La was interpreted to be caused by alignment of the (h 11/2 ) 2 proton pair, and the crossing frequency was best reproduced by the TRS calculations taking into account triaxial deformations. In contrast to the interpretations for the band crossing of 142 La, alignments of the (i 13/2 ) 2 neutron pair were found to be responsible for the band-crossing of the yrast band in the neighboring even-N 143 La, and triaxial degree of freedom was found to play a more significant role than octupole deformations in the nucleus, although its β 3 values deduced are large.

142La↗
DOE OSTI2024

GraphEM

An unsupervised segmentation method for structural analysis of Scanning Transmission Electron Microscopy (STEM) images

Pope, Jenna↗
DOE OSTI2021

Minnesota peat viromes reveal terrestrial and aquatic niche partitioning for local and global viral populations

Abstract Background Peatlands are expected to experience sustained yet fluctuating higher temperatures due to climate change, leading to increased microbial activity and greenhouse gas emissions. Despite mounting evidence for viral contributions to these processes in peatlands underlain with permafrost, little is known about viruses in other peatlands. More generally, soil viral biogeography and its potential drivers are poorly understood at both local and global scales. Here, 87 metagenomes and five viral size-fraction metagenomes (viromes) from a boreal peatland in northern Minnesota (the SPRUCE whole-ecosystem warming experiment and surrounding bog) were analyzed for dsDNA viral community ecological patterns, and the recovered viral populations (vOTUs) were compared with our curated PIGEON database of 266,125 vOTUs from diverse ecosystems. Results Within the SPRUCE experiment, viral community composition was significantly correlated with peat depth, water content, and carbon chemistry, including CH 4 and CO 2 concentrations, but not with temperature during the first 2 years of warming treatments. Peat vOTUs with aquatic-like signatures (shared predicted protein content with marine and/or freshwater vOTUs) were significantly enriched in more waterlogged surface peat depths. Predicted host ranges for SPRUCE vOTUs were relatively narrow, generally within a single bacterial genus. Of the 4326 SPRUCE vOTUs, 164 were previously detected in other soils, mostly peatlands. None of the previously identified 202,371 marine and freshwater vOTUs in our PIGEON database were detected in SPRUCE peat, but 0.4% of 80,714 viral clusters (VCs, grouped by predicted protein content) were shared between soil and aquatic environments. On a per-sample basis, vOTU recovery was 32 times higher from viromes compared with total metagenomes. Conclusions Results suggest strong viral “species” boundaries between terrestrial and aquatic ecosystems and to some extent between peat and other soils, with differences less pronounced at higher taxonomic levels. The significant enrichment of aquatic-like vOTUs in more waterlogged peat suggests that viruses may also exhibit niche partitioning on more local scales. These patterns are presumably driven in part by host ecology, consistent with the predicted narrow host ranges. Although more samples and increased sequencing depth improved vOTU recovery from total metagenomes, the substantially higher per-sample vOTU recovery after viral particle enrichment highlights the utility of soil viromics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Use of Graph Theory and Neural Networks for Microstructural Classification

Recent advances in materials data analytics have provided new avenues for determining process-structure-property (PSP) linkages in a variety of materials. Machine learning techniques including few-shot learning have increased the efficiency of classifying microscopy images for the purposes of material characterization. Modifications in segmentation also show potential in improving the accuracy of our current pyCHIP classifier. Replacing previous encoders trained on ImageNet with those trained on microscopy images like MicroNet has initially shown better performance at classifying images of irradiated samples. Additionally, different normalization approaches were tested to show no discernable effect on classification. The Louvain method for community detection is analyzed on a set of irradiated samples with different parameters to determine which proved beneficial under what circumstances. We suggest that microscopy experiments be automated in the future using a combination of these techniques to enable high-throughput analyses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of Multimodal Few-Shot Analytics for Electron Micrographs

Recent advances in materials data analytics have provided new avenues for determining process-structure-property (PSP) linkages in a variety of materials. Machine learning techniques including few-shot learning have increased the efficiency of classifying microscopy images for the purposes of material characterization. Attempts at creating a multimodal approach can provide further improvements to current models and help extract more salient features from data. In this vein, raw spectrum data was taken to provide an additional modality to our current pyCHIP classifier. Modifications in segmentation also show potential in improving the accuracy of the pyCHIP classifier. Classifier output was analyzed using network graphs and unsupervised clustering algorithms such as spectral clustering to detect better segmentation methods than the current “chipping” approach. We suggest that the chip selection process can be automated in the future using a combination of these techniques to enable high-throughput analyses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of Equiatomic CrMnFeCoNiCu System and Subsequent Derivation of a Non-Equiatomic MnFeCoNiCu Alloy

Investigation into non-equiatomic high-entropy alloys has grown in recent years due to questions about the role of entropy stabilization in forming single-phase solid solutions. Non-equiatomic alloys have been shown to retain the outstanding mechanical properties exhibited by their equiatomic counterparts and even improve electrical, thermal, and magnetic properties, albeit with relaxed composition bounds. However, much remains to understand the processing–structure–property relationships in all classes of so-called high-entropy alloys (HEAs). Here, we are motivated by the natural phenomena of crystal growth and equilibrium conditions to introduce a method of HEA development where controlled processing conditions determine the most probable and stable composition. This is demonstrated by cooling an equiatomic CrMnFeCoNiCu alloy from the melt steadily over 3 days (cooling rate ~4 °C/h). The result is an alloy containing large Cr-rich precipitates and an almost Cr-free matrix exhibiting compositions within the MnFeCoNiCu system (with trace amounts of Cr). From this juncture, it is argued that the most stable composition is within the CrMnFeCoNiCu system rather than the CrMnFeCoNi system. With further optimization and evaluation, a unique non-equiatomic alloy, Mn 17 Fe 21 Co 24 Ni 24 Cu 14 , is derived. The alloy solidifies and recrystallizes into a single-phase face-centered cubic (FCC) polycrystal. In addition to possible applications where Invar is currently utilized, this alloy can be used in fundamental studies that contrast its behavior with its equiatomic counterpart and shed light on the development of HEAs.

36 MATERIALS SCIENCE↗