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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Solving protein structure from sparse serial microcrystal diffraction data at a storage ring synchrotron source

This dataset consists of 79,992 diffraction patterns stored in cbf format. A step-by-step tutorial on the reconstruction of the Bragg intensities using the EMC algorithm (Loh & Elser 2009) is described [here](https://github.com/tl578/EMC-for-SMX/wiki). We thank the authors of Martin-Garcia et al. (2017) for their gracious access to the data. Reduced data files: For those who would like to try an EMC reconstruction immediately, the data reduction step can be skipped by downloading the reduced data files provided by us. See [here](https://github.com/tl578/EMC-for-SMX/wiki/Data-reduction#skipping-data-reduction) for more details.

23-ID-D↗
DOE OSTI2022

Streaked Sub-ps-resolution X-ray Line Shapes and Implications for Solid-density Plasma Dynamics

A high-resolution x-ray spectrometer was coupled with an ultrafast x-ray streak camera to produce time-resolved line shape spectra measured from hot, solid-density plasmas. A Bragg crystal was placed near a laser-produced plasma to maximize throughput; alignment tolerances were established by raytracing. The streak camera produced single-shot time-resolved spectra, heavily sloped due to photon time-of-flight differences, with sufficient reproducibility to accumulate photon statistics. The images are time-calibrated by the slope of streaked spectra and dewarped to generate spectra emitted at different times defined at the source. The streaked spectra demonstrate the evolution of spectral shoulders and other features on ps timescales, showing the feasibility of plasma parameter measurements on the rapid timescales necessary to study high-energy-density plasmas.

High-energy-density plasmas↗
DOE OSTI2020

Global Climate

The 2019 global lower tropospheric temperature (LTT), which encompasses the atmosphere from the surface to ~10 km, ranked second warmest in seven datasets and first or third in the remaining two (Fig. 2.7). These records extend back to 1958 using radiosonde (balloon-borne instrumentation) data and one reanalysis dataset (JRA55), which demonstrate reasonable agreement with the 40+ year satellite record (since late 1978) and two other reanalysis datasets (since 1979 and 1980, ERA5 and MERRA2, respectively). Aweak El Niño contributed to increased global temperatures as 2019 values were +0.44° to +0.68°C higher than the 1981–2010 average (depending on the dataset), being just slightly cooler (~0.07°C on average) than the record warm year of 2016. At least fourof the five globally complete datasets (ERA5, MERRA2, JRA55, RSS, UAH) recorded each of the four months—June, September, November, and December—as experiencing their warmest monthly global LTT.

58 GEOSCIENCES↗
DOE OSTI2025

Dependence of Convective Cloud Microphysical Properties on Environmental Conditions during the TRACER and ESCAPE Field Campaigns: A Synergistic Approach of Observations, Machine Learning and Parcel Models

The sensitivity of convective clouds to aerosols and their interactions with environment, combined with limited observational constraints in parameterizations, introduces significant uncertainties in atmospheric models. Here, this study investigates the dependence of convective cloud microphysical properties on environmental conditions using a synergistic approach that combines unique observations from the TRACER and ESCAPE field campaigns, machine learning techniques, and parcel model simulations with a super-droplet microphysics scheme. A random forest algorithm identifies in-situ vertical velocity (w), temperature (T), and surface fine-mode aerosol mass concentration as the three most important environmental conditions influencing cloud properties including liquid water content (LWC), number concentration for particles with D max < 50 μm (N c ,<50), 50 μm ≤ D max ≤ 3000 μm (N c,50–3000 ), and droplet effective diameter (D e ). Results show that LWC, N c,<50 , and N c,50–3000 significantly increase with w in updrafts. Across w bins, as T decreases, LWC, D e , and N c,50–3000 increase, while N c,<50 decreases, which are closely linked to the distance above cloud bases. Warmer cloud bases yield higher LWC, greater N c,50–3000 , and smaller N c,<50 , while polluted environments produce greater N c,<50 . Parcel model simulations successfully replicate these observed dependencies. The simulation results indicate that warmer cloud bases enhance condensation generating larger droplets, and differences in droplet sizes are then amplified through collision-coalescence, resulting in a greater N c,50–3000 . Polluted conditions result in a greater N c,<50 primarily due to enhanced cloud condensation nuclei activation despite increased collision-coalescence rates compared to pristine conditions. This study provides observed quantitative patterns characterizing cloud microphysical properties as a function of key environmental parameters, offering valuable constraints for improving physics parameterizations and numerical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Efficient exascale discretizations: High-order finite element methods

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a research partnership involving more than 30 computational scientists from two US national labs and five universities, including members of the Nek5000, MFEM, MAGMA and PETSc projects. We discuss the CEED co-design activities based on targeted benchmarks, miniapps and discretization libraries and our work on performance optimizations for large-scale GPU architectures. We also provide a broad overview of research and development activities in areas such as unstructured adaptive mesh refinement algorithms, matrix-free linear solvers, high-order data visualization, and list examples of collaborations with several ECP and external applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Finding the missing honey bee genes: lessons learned from a genome upgrade

Background: The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. Results: Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. Conclusions: Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform

The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Institute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Dynamic life-cycle carbon analysis for fast pyrolysis biofuel produced from pine residues: implications of carbon temporal effects

Abstract Background Woody biomass has been considered as a promising feedstock for biofuel production via thermochemical conversion technologies such as fast pyrolysis. Extensive Life Cycle Assessment studies have been completed to evaluate the carbon intensity of woody biomass-derived biofuels via fast pyrolysis. However, most studies assumed that woody biomass such as forest residues is a carbon–neutral feedstock like annual crops, despite a distinctive timeframe it takes to grow woody biomass. Besides, few studies have investigated the impacts of forest dynamics and the temporal effects of carbon on the overall carbon intensity of woody-derived biofuels. This study addressed such gaps by developing a life-cycle carbon analysis framework integrating dynamic modeling for forest and biorefinery systems with a time-based discounted Global Warming Potential (GWP) method developed in this work. The framework analyzed dynamic carbon and energy flows of a supply chain for biofuel production from pine residues via fast pyrolysis. Results The mean carbon intensity of biofuel given by Monte Carlo simulation across three pine growth cases ranges from 40.8–41.2 g CO 2 e MJ −1 (static method) to 51.0–65.2 g CO 2 e MJ −1 (using the time-based discounted GWP method) when combusting biochar for energy recovery. If biochar is utilized as soil amendment, the carbon intensity reduces to 19.0–19.7 g CO 2 e MJ −1 (static method) and 29.6–43.4 g CO 2 e MJ −1 in the time-based method. Forest growth and yields (controlled by forest management strategies) show more significant impacts on biofuel carbon intensity when the temporal effect of carbon is taken into consideration. Variation in forest operations and management (e.g., energy consumption of thinning and harvesting), on the other hand, has little impact on the biofuel carbon intensity. Conclusions The carbon temporal effect, particularly the time lag of carbon sequestration during pine growth, has direct impacts on the carbon intensity of biofuels produced from pine residues from a stand-level pine growth and management point of view. The carbon implications are also significantly impacted by the assumptions of biochar end-of-life cases and forest management strategies.

09 BIOMASS FUELS↗
DOE OSTI2024

Cultivation of novel Atribacterota from oil well provides new insight into their diversity, ecology, and evolution in anoxic, carbon-rich environments

Background: The Atribacterota are widely distributed in the subsurface biosphere. Recently, the first Atribacterota isolate was described and the number of Atribacterota genome sequences retrieved from environmental samples has increased significantly; however, their diversity, physiology, ecology, and evolution remain poorly understood. Results: We report the isolation of the second member of Atribacterota, Thermatribacter velox gen. nov., sp. nov., within a new family Thermatribacteraceae fam. nov., and the short-term laboratory cultivation of a member of the JS1 lineage, Phoenicimicrobium oleiphilum HX-OS.bin.34 TS , both from a terrestrial oil reservoir. Physiological and metatranscriptomics analyses showed that Thermatribacter velox B11 T and Phoenicimicrobium oleiphilum HX-OS.bin.34 TS ferment sugars and n-alkanes, respectively, producing H 2 , CO 2 , and acetate as common products. Comparative genomics showed that all members of the Atribacterota lack a complete Wood-Ljungdahl Pathway (WLP), but that the Reductive Glycine Pathway (RGP) is widespread, indicating that the RGP, rather than WLP, is a central hub in Atribacterota metabolism. Ancestral character state reconstructions and phylogenetic analyses showed that key genes encoding the RGP (fdhA, fhs, folD, glyA, gcvT, gcvPAB, pdhD) and other central functions were gained independently in the two classes, Atribacteria (OP9) and Phoenicimicrobiia (JS1), after which they were inherited vertically; these genes included fumarate-adding enzymes (faeA; Phoenicimicrobiia only), the CODH/ACS complex (acsABCDE), and diverse hydrogenases (NiFe group 3b, 4b and FeFe group A3, C). Finally, we present genome-resolved community metabolic models showing the central roles of Atribacteria (OP9) and Phoenicimicrobiia (JS1) in acetate- and hydrocarbon-rich environments. Conclusion: Our findings expand the knowledge of the diversity, physiology, ecology, and evolution of the phylum Atribacterota. This study is a starting point for promoting more incisive studies of their syntrophic biology and may guide the rational design of strategies to cultivate them in the laboratory.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

High-quality draft genome sequence of the Thermus amyloliquefaciens type strain YIM 77409T with an incomplete denitrification pathway

Abstract Thermus amyloliquefaciens type strain YIM 77409 T is a thermophilic, Gram-negative, non-motile and rod-shaped bacterium isolated from Niujie Hot Spring in Eryuan County, Yunnan Province, southwest China. In the present study we describe the features of strain YIM 77409 T together with its genome sequence and annotation. The genome is 2,160,855 bp long and consists of 6 scaffolds with 67.4 % average GC content. A total of 2,313 genes were predicted, comprising 2,257 protein-coding and 56 RNA genes. The genome is predicted to encode a complete glycolysis, pentose phosphate pathway, and tricarboxylic acid cycle. Additionally, a large number of transporters and enzymes for heterotrophy highlight the broad heterotrophic lifestyle of this organism. A denitrification gene cluster included genes predicted to encode enzymes for the sequential reduction of nitrate to nitrous oxide, consistent with the incomplete denitrification phenotype of this strain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Complete genome sequence of Jiangella gansuensis strain YIM 002T (DSM 44835T), the type species of the genus Jiangella and source of new antibiotic compounds

Jiangella gansuensis strain YIM 002 T is the type strain of the type species of the genus Jiangella, which is at the present time composed of five species, and was isolated from desert soil sample in Gansu Province (China). The five strains of this genus are clustered in a monophyletic group when closer actinobacterial genera are used to infer a 16S rRNA gene sequence phylogeny. The study of this genome is part of the Genomic Encyclopedia of Bacteria and Archaea project, and here we describe the complete genome sequence and annotation of this taxon. The genome of J. gansuensis strain YIM 002T contains a single scaffold of size 5,585,780 bp, which involves 149 pseudogenes, 4905 protein-coding genes and 50 RNA genes, including 2520 hypothetical proteins and 4 rRNA genes. From the investigation of genome sizes of Jiangella species, J. gansuensis shows a smaller size, which indicates this strain might have discarded too much genetic information to adapt to desert environment. Seven new compounds from this bacterium have recently been described; however, its potential should be higher, as secondary metabolite gene cluster analysis predicted 60 gene clusters, including the potential to produce the pristinamycin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Impact of Long-Course Neoadjuvant Radiation on Postoperative Low Anterior Resection Syndrome and Quality of Life in Rectal Cancer: Post Hoc Analysis of a Randomized Controlled Trial

Background: Neoadjuvant radiation is recommended for locally advanced rectal cancer, with proven benefit in local control but not in disease-free survival. However, the impact of long-course radiation on postoperative bowel function and quality of life (QOL) remains controversial. This study aimed to investigate the impact of long-course neoadjuvant radiation on bowel function and QOL, and to identify risk factors for severe bowel dysfunction. Methods: Patients who underwent long-course neoadjuvant chemoradiotherapy (nCRT) or chemotherapy (nCT) followed by radical low anterior resection for locally advanced rectal cancer were recruited from the FOWARC randomized controlled trial. Low anterior resection syndrome (LARS) score and European Organisation for Research and Treatment of Cancer (EORTC) C30/CR29 questionnaires were used to assess bowel function and QOL, respectively. Results: Overall, 220 patients responded after a median follow-up of 40.2 months, of whom 119 (54.1%) reported major LARS, 74 (33.6%) reported minor LARS, and 27 (12.3%) reported no LARS. Compared with the nCT group, the nCRT group reported more major LARS (64.4% vs. 38.6%, p < 0.001) and worse QOL. Long-course neoadjuvant radiation (OR 2.20, 95% CI 1.24–3.91; p = 0.007), height of anastomosis (OR 0.74, 95% CI 0.63–0.88; p < 0.001), and diverting ileostomy (OR 2.59, 95% CI 1.27–5.30; p = 0.009) were independent risk factors for major LARS. Conclusions: Long-course neoadjuvant radiation, along with low anastomosis, are likely independent risk factors for postoperative bowel function and QOL. Our findings might have implications for alleviating LARS and improving QOL by informing selection of neoadjuvant treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Computational modeling of continuum scale constitutive equations to improve biomass feedstock material handling and conveying systems

Existing design practices for common feedstock handling equipment such as hoppers and screw feeders have not been successful in many situations. The lack of an appropriate toolset to characterize and model biomass flow behavior is deemed the root cause of plugging, stalls, and flow-related issues in biomass handling systems design and operations. New standardized characterization protocols in conjunction with appropriate constitutive models will lead to successful biomass handling system design and operations. This study investigates constitutive models for bulk solid flow based on the first principles to overcome issues in biomass handling. The focus is on two major issues in biomass handling, i.e., initiating and sustaining of flow in the hopper that is widely used in biomass conveying operation. Accordingly, this article focuses on analytical models of biomass hopper flow. Mohr-Coulomb, Drucker-Prager, and modified Cam-clay models are investigated as constitutive bulk solid flow models. Parameters of those models are determined using a set of triaxial tests. Triaxial tests are conducted using the cubical triaxial tester (CTT) in the Food and Biomaterials Lab of the Pennsylvania State University. Milled 1mm corn stover and 2mm wood chip biomass materials having different flow characteristics are examined, and their respective flow behavior out of a hopper are simulated using the Finite Element method implementing identified constitutive models and determined fundamental mechanical properties. It is found that, with the same hopper geometry, ground corn stover 1mm tends to exhibit funnel flow whereas ground Douglas fir 2 mm tends to exhibit mass flow. These simulation results are validated with hopper flow experiments. This study demonstrates how biomass flow problems can be predicted and mitigated by numerically modeled fundamental constitutive equations.

09 BIOMASS FUELS↗