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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparing Adjoint Waveform Tomography Models of California Using Different Starting Models

Abstract Adjoint waveform tomography (AWT) sits at the cutting edge of seismic tomography on local, regional, and global scales. However, the choice in starting model may have a significant impact on the final inversion results. In this paper, we present 3 AWT models of California that are based on different starting models. We chose three models that were inverted at different scales: SPiRaL, a global travel‐time tomography model (Simmons et al., 2021, 10.1093/gji/ggab277 ), CSEM_NA, a regional adjoint tomography model of North America and the North Atlantic (Krischer et al., 2018, 10.1029/2017JB015289 ), and WUS256, a regional adjoint tomography model of the western US (Rodgers et al., 2022, https://doi.org/10.1029/2022JB024549 ). We then inverted three AWT models using the same source and receiver set. We ran each model over three period bands: 30–100 s, 25–100 s, and 20–80 s. Once the iterations were finalized, we used five methods of testing model similarity in both the model and data space. We conclude that the choice of starting model has a minimal impact on long wavelength models if an appropriate multi‐scale inversion approach is used.

58 GEOSCIENCES↗
DOE OSTI2026

Comparing Synoptic Pattern Evolution for Flash‐Flood‐Producing and Non‐Flash‐Flood‐Producing Mesoscale Convective Systems in the United States

Understanding how the short-term evolution of synoptic weather patterns influence Mesoscale Convective Systems (MCSs) is essential, as these systems are responsible for over half of central U.S. flash floods, leading to substantial socioeconomic and water resource management impacts. This study analyzes long-term MCS data, flash flood reports, and atmospheric reanalyses from 2007 to 2017 using a machine learning clustering algorithm to examine how the synoptic weather patterns evolve prior to MCS initiation. While the clusters reflect seasonal and regional differences in MCS occurrence, they do not consistently distinguish between MCSs that do and do not produce flash floods. Systems in the southern Great Plains are more flood-prone when a synoptic-scale forcing, located near the system, drives strong water vapor transport from the nearby moisture source. More generally under different synoptic weather patterns, a broader precipitating area is the most dominant factor governing MCS flash flood potential.

atmospheric dynamics↗
DOE OSTI2022

Coarse-grained molecular dynamics integrated with convolutional neural network for comparing shapes of temperature sensitive bottlebrushes

Quantification of shape changes in nature-inspired soft material architectures of stimuli-sensitive polymers is critical for controlling their properties but is challenging due to their softness and flexibility. Here, we have computationally designed uniquely shaped bottlebrushes of a thermosensitive polymer, poly(N-isopropylacrylamide) (PNIPAM), by controlling the length of side chains along the backbone. Coarse-grained molecular dynamics simulations of solvated bottlebrushes were performed below and above the lower critical solution temperature of PNIPAM. Conventional analyses (free volume, asphericity, etc.) show that lengths of side chains and their immediate environments dictate the compactness and bending in these architectures. We further developed 100 unique convolutional neural network models that captured molecular-level features and generated a statistically significant quantification of the similarity between different shapes. Thus, our study provides insights into the shapes of complex architectures as well as a general method to analyze them. The shapes presented here may inspire the synthesis of new bottlebrushes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Comparative and pangenomic analysis of the genus Streptomyces

Abstract Streptomycetes are highly metabolically gifted bacteria with the abilities to produce bioproducts that have profound economic and societal importance. These bioproducts are produced by metabolic pathways including those for the biosynthesis of secondary metabolites and catabolism of plant biomass constituents. Advancements in genome sequencing technologies have revealed a wealth of untapped metabolic potential from Streptomyces genomes. Here, we report the largest Streptomyces pangenome generated by using 205 complete genomes. Metabolic potentials of the pangenome and individual genomes were analyzed, revealing degrees of conservation of individual metabolic pathways and strains potentially suitable for metabolic engineering. Of them, Streptomyces bingchenggensis was identified as a potent degrader of plant biomass. Polyketide, non-ribosomal peptide, and gamma-butyrolactone biosynthetic enzymes are primarily strain specific while ectoine and some terpene biosynthetic pathways are highly conserved. A large number of transcription factors associated with secondary metabolism are strain-specific while those controlling basic biological processes are highly conserved. Although the majority of genes involved in morphological development are highly conserved, there are strain-specific varieties which may contribute to fine tuning the timing of cellular differentiation. Overall, these results provide insights into the metabolic potential, regulation and physiology of streptomycetes, which will facilitate further exploitation of these important bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Salinity tolerance mechanisms of an Arctic Pelagophyte using comparative transcriptomic and gene expression analysis

Abstract Little is known at the transcriptional level about microbial eukaryotic adaptations to short-term salinity change. Arctic microalgae are exposed to low salinity due to sea-ice melt and higher salinity with brine channel formation during freeze-up. Here, we investigate the transcriptional response of an ice-associated microalgae over salinities from 45 to 8. Our results show a bracketed response of differential gene expression when the cultures were exposed to progressively decreasing salinity. Key genes associated with salinity changes were involved in specific metabolic pathways, transcription factors and regulators, protein kinases, carbohydrate active enzymes, and inorganic ion transporters. The pelagophyte seemed to use a strategy involving overexpression of Na + -H + antiporters and Na + -Pi symporters as salinity decreases, but the K + channel complex at higher salinities. Specific adaptation to cold saline arctic conditions was seen with differential expression of several antifreeze proteins, an ice-binding protein and an acyl-esterase involved in cold adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Comparative genomics of Mollicutes-related endobacteria supports a late invasion into Mucoromycota fungi

Abstract Diverse members of early-diverging Mucoromycota, including mycorrhizal taxa and soil-associated Mortierellaceae, are known to harbor Mollicutes-related endobacteria (MRE). It has been hypothesized that MRE were acquired by a common ancestor and transmitted vertically. Alternatively, MRE endosymbionts could have invaded after the divergence of Mucoromycota lineages and subsequently spread to new hosts horizontally. To better understand the evolutionary history of MRE symbionts, we generated and analyzed four complete MRE genomes from two Mortierellaceae genera: Linnemannia (MRE-L) and Benniella (MRE-B). These genomes include the smallest known of fungal endosymbionts and showed signals of a tight relationship with hosts including a reduced functional capacity and genes transferred from fungal hosts to MRE. Phylogenetic reconstruction including nine MRE from mycorrhizal fungi revealed that MRE-B genomes are more closely related to MRE from Glomeromycotina than MRE-L from the same host family. We posit that reductions in genome size, GC content, pseudogene content, and repeat content in MRE-L may reflect a longer-term relationship with their fungal hosts. These data indicate Linnemannia and Benniella MRE were likely acquired independently after their fungal hosts diverged from a common ancestor. This work expands upon foundational knowledge on minimal genomes and provides insights into the evolution of bacterial endosymbionts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

TbasCO: trait-based comparative ‘omics identifies ecosystem-level and niche-differentiating adaptations of an engineered microbiome

A grand challenge in microbial ecology is disentangling the traits of individual populations within complex communities. Various cultivation-independent approaches have been used to infer traits based on the presence of marker genes. However, marker genes are not linked to traits with complete fidelity, nor do they capture important attributes, such as the timing of gene expression or coordination among traits. To address this, we present an approach for assessing the trait landscape of microbial communities by statistically defining a trait attribute as a shared transcriptional pattern across multiple organisms. Leveraging the KEGG pathway database as a trait library and the Enhanced Biological Phosphorus Removal (EBPR) model microbial ecosystem, we demonstrate that a majority (65%) of traits present in 10 or more genomes have niche-differentiating expression attributes. For example, while many genomes containing high-affinity phosphorus transporter pstABCS display a canonical attribute (e.g. up-regulation under phosphorus starvation), we identified another attribute shared by many genomes where transcription was highest under high phosphorus conditions. Taken together, we provide a novel framework for unravelling the functional dynamics of uncultivated microorganisms by assigning trait-attributes through genome-resolved time-series metatranscriptomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comparing quantum annealing and spiking neuromorphic computing for sampling binary sparse coding QUBO problems

We consider the problem of computing a sparse binary representation of an image. Given an image and an overcomplete, non-orthonormal basis, we aim to find a sparse binary vector indicating the minimal set of basis vectors that when added together best reconstruct the given input. We formulate this problem with an L 2 loss on the reconstruction error, and an L 0 loss on the binary vector enforcing sparsity. First, we solve the sparse representation QUBOs by solving them both on a D-Wave quantum annealer with Pegasus chip connectivity, as well as on the Intel Loihi 2 spiking neuromorphic processor using a stochastic Non-equilibrium Boltzmann Machine (NEBM). Second, using Quantum Evolution Monte Carlo with Reverse Annealing and iterated warm starting on Loihi 2 to evolve the solution quality from the respective machines. We demonstrate that both quantum annealing and neuromorphic computing are suitable for solving binary sparse coding QUBOs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Generalized vs. fractional: a comparative analysis of Maxwell models applied to entangled polymer solutions

Fractional viscoelastic models provide an excellent description of rheological data for polymer systems with power-law behaviour. However, the physical interpretation of their model parameters, which carry fractional units of time, often remains elusive. We show that for poly(ethylene oxide) (PEO) solutions, the fractional Maxwell model (FMM) requires much fewer model parameters than the classical generalized Maxwell model for a good description of the data and that it can be applied consistently to solutions with varying degrees of viscoelasticity. Despite their fractional units, the parameters exhibit scaling laws similar to classical parameters as a function of polymer concentration.

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

Hydropower Scheduling Toolchains: Comparing Experiences in Brazil, Norway, and USA and Implications for Synergistic Research

While hydropower scheduling is a well-defined problem, there are institutional differences that need to be identified to promote constructive and synergistic research. We study how established toolchains of computer models are organized to assist operational hydropower scheduling in Brazil, Norway, and the United States’ Colorado River System (CRS). These three systems have vast hydropower resources, with numerous, geographically widespread, and complex reservoir systems. Although the underlying objective of hydropower scheduling is essentially the same, the systems are operated in different market contexts and with different alternative uses of water, where the stakeholders’ objectives clearly differ. This in turn leads to different approaches when it comes to the scope, organization, and use of models for operational hydropower scheduling and the information flow between the models. Here, we describe these hydropower scheduling toolchains, identify the similarities and differences, and shed light on the original ideas that motivated their creation. We then discuss the need to improve and extend the current toolchains and the opportunities to synergistic research that embrace those contextual differences.

13 HYDRO ENERGY↗