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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Rhythm of the Night (and Day): Predictive Metabolic Modeling of Diurnal Growth in Chlamydomonas

We have developed the first transient metabolic model for diurnal growth of algae based on experimental data and capable of predicting phenotype from genotype. This model enables us to evaluate the impact of genetic and environmental changes on the growth, biomass composition and intracellular fluxes of the model green alga, Chlamydomonas reinhardtii . The availability of this model will enable faster and more efficient design of cells for production of fuels, chemicals, and pharmaceuticals.

09 BIOMASS FUELS↗
DOE OSTI2024

Comprehensive characterization of extracellular vesicles produced by environmental (Neff) and clinical (T4) strains of Acanthamoeba castellanii

We conducted a comprehensive comparative analysis of extracellular vesicles (EVs) from two Acanthamoeba castellanii strains, Neff (environmental) and T4 (clinical). Morphological analysis via transmission electron microscopy revealed slightly larger Neff EVs (average = 194.5 nm) compared to more polydisperse T4 EVs (average = 168.4 nm). Nanoparticle tracking analysis (NTA) and dynamic light scattering validated these differences. Proteomic analysis of the EVs identified 1,352 proteins, with 1,107 common, 161 exclusive in Neff, and 84 exclusively in T4 EVs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) mapping revealed distinct molecular functions and biological processes and notably, the T4 EVs enrichment in serine proteases, aligned with its pathogenicity. Lipidomic analysis revealed a prevalence of unsaturated lipid species in Neff EVs, particularly triacylglycerols, phosphatidylethanolamines (PEs), and phosphatidylserine, while T4 EVs were enriched in diacylglycerols and diacylglyceryl trimethylhomoserine, phosphatidylcholine and less unsaturated PEs, suggesting differences in lipid metabolism and membrane permeability. Metabolomic analysis indicated Neff EVs enrichment in glycerolipid metabolism, glycolysis, and nucleotide synthesis, while T4 EVs, methionine metabolism. Furthermore, RNA-seq of EVs revealed differential transcript between the strains, with Neff EVs enriched in transcripts related to gluconeogenesis and translation, suggesting gene regulation and metabolic shift, while in the T4 EVs transcripts were associated with signal transduction and protein kinase activity, indicating rapid responses to environmental changes. In this novel study, data integration highlighted the differences in enzyme profiles, metabolic processes, and potential origins of EVs in the two strains shedding light on the diversity and complexity of A. castellanii EVs and having implications for understanding host-pathogen interactions and developing targeted interventions for Acanthamoeba-related diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ultrafast Dynamics of Photosynthetic Light Harvesting: Strategies for Acclimation Across Organisms

Photosynthetic light harvesting exhibits near-unity quantum efficiency. The high efficiency is achieved through a series of energy and charge transfer steps within a network of pigment-containing proteins. Remarkably, high efficiency is conserved across many organisms despite differences in the protein structures and organization that allow each organism to respond to its own biological niche and the stressors within. In this review, we highlight recent progress toward understanding how organisms maintain optimal light-harvesting ability by acclimating to their environment. First, we review the building blocks of photosynthetic light harvesting, energy transfer, and time-resolved spectroscopic techniques. Then, we explore how three classes of photosynthetic organisms—purple bacteria, cyanobacteria, and green plants—optimize their light-harvesting apparatuses to their particular environment. Overall, research has shown that photosynthetic energy transfer is robust to changing environmental conditions, with each organism utilizing its own strategies to optimize photon capture in its particular biological niche.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

NEONiso R Package, versions greater than 0.5.2

Carbon fluxes in terrestrial ecosystems and their response to environmental change are a major source of uncertainty in the modern carbon cycle. The National Ecological Observatory Network (NEON) presents the opportunity to merge eddy covariance (EC)-derived fluxes with CO2 isotope ratio measurements to gain insights into carbon cycle processes. Collected continuously and consistently across >40 sites, NEON EC and isotope data facilitate novel integrative analyses. However, currently provisioned atmospheric isotope data are uncalibrated, greatly limiting ability to perform cross-site analyses. Here, we present two approaches to calibrating NEON CO2 isotope ratios, along with an R package to calibrate NEON data. We find that calibrating CO2 isotopologues independently yields a lower d13C bias (<0.05‰) and higher precision (<0.40‰) than directly correcting d13C with linear regression (bias: <0.11‰, precision: 0.42‰), but with slightly higher error and lower precision in calibrated CO2 mole fraction. The magnitude of the corrections to d13C and CO2 mole fractions vary substantially by site, underscoring the need for users to apply a consistent calibration framework to data in the NEON archive. Post-calibration data sets show that site mean annual d13C correlates negatively with precipitation, temperature, and aridity, but positively with elevation. Forested and agricultural ecosystems exhibit larger gradients in CO2 and d13C than other sites, particularly during the summer and at night. The overview and analysis tools developed here will facilitate cross-site analysis using NEON data, provide a model for other continental-scale observational networks, and enable new advances leveraging the isotope ratios of specific carbon fluxes.

Fiorella, Richard↗
DOE OSTI2025

A simple and highly efficient protocol for 13 C-labeling of plant cell wall for structural and quantitative analyses via solid-state nuclear magnetic resonance

Plant cell walls are made of a complex network of interacting polymers that play a critical role in plant development and responses to environmental changes. Thus, improving plant biomass and fitness requires the elucidation of the structural organization of plant cell walls in their native environment. The 13 C-based multi-dimensional solid-state nuclear magnetic resonance (ssNMR) has been instrumental in revealing the structural information of plant cell walls through 2D and 3D correlation spectral analyses. However, the requirement of enriching plants with 13 C limits the applicability of this method. To our knowledge, there is only a very limited set of methods currently available that achieve high levels of 13 C-labeling of plant materials using 13 CO 2 , and most of them require large amounts of 13 CO 2 in larger growth chambers. In this study, a simplified protocol for 13C-labeling of plant materials is introduced that allows ca 60% labeling of the cell walls, as quantified by comparison with commercially labeled samples. This level of 13 C-enrichment is sufficient for all conventional 2D and 3D correlation ssNMR experiments for detailed analysis of plant cell wall structure. The protocol is based on a convenient and easy setup to supply both 13 C-labeled glucose and 13 CO 2 using a vacuum-desiccator. The protocol does not require large amounts of 13 CO 2 . This study shows that our 13 C-labeling of plant materials can make the accessibility to ssNMR technique easy and affordable. The derived high-resolution 2D and 3D correlation spectra are used to extract structural information of plant cell walls. This helps to better understand the influence of polysaccharide-polysaccharide interaction on plant performance and allows for a more precise parametrization of plant cell wall models.

09 BIOMASS FUELS↗
DOE OSTI2024

Tipping points emerge from weak mutualism in metacommunities

The coexistence of obligate mutualists is often precariously close to tipping points where small environmental changes can drive catastrophic shifts in species composition. For example, microbial ecosystems can collapse by the decline of a strain that provides an essential resource on which other strains cross-feed. Here, we show that tipping points, ecosystem collapse, bistability and hysteresis arise even with very weak (non-obligate) mutualism provided the population is spatially structured. Based on numeric solutions of a metacommunity model and mean-field analyses, we demonstrate that weak mutualism lowers the minimal dispersal rate necessary to avoid stochastic extinction, while species need to overcome a mean threshold density to survive in this low dispersal rate regime. Our results allow us to make numerous predictions for mutualistic metacommunities regarding tipping points, hysteresis effects, and recovery from external perturbations, and let us draw general conclusions for ecosystems even with random, not necessarily mutualistic, interactions and systems with density-dependent dispersal rather than direct mutualistic interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

SPRUCE: Shrub Leaf and Stem Functional Traits from 10-year Shrub Layer Biomass Harvests (August 2025)

This data set contains Leaf Mass Area (LMA), Specific Leaf Area (SLA), Leaf Area Index (LAI), and Huber value (Hv) measurements from the 10-year Shrub-layer Biomass harvests in the Spruce and Peatland Responses Under Environmental Change (SPRUCE) experiment in August 2025. The total ground-level cross-sectional sapwood area of Chamaedaphne calyculata (CHCA), Rhododendron groenlandicum (RHGR), and Vaccinium angustifolium (VAAN) were calculated for each of the three shrub-layer community survey plots located in each experimental enclosure. Representative current-year leaves were removed, scanned, dried, and weighed to derive SLA. Grab-samples for VAAN were used to calculate SLA when no biomass was harvested in the shrub-layer community plots. These SLA values were used to infer total one-sided leave surface area from the total species lead dry mass for calculation of LAI and Hv.

Birkebak, Joshua [ORNL] (ORCID:0009000955611494)↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Ton Tonzi Ranch

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ton Tonzi Ranch. This is the FLUXNET version of the carbon flux data for the site US-Ton Tonzi Ranch produced by applying the standard ONEFlux (1F) software. Site Description - The Tonzi Ranch is located on the lower foothills of the Sierra Nevada Mountains. The site is classified as an oak savanna woodland (Davis et al, 2016) and is situated on privately owned land. This site is representative of the oak savanna ecosystem that rings the Great Central Valley of California and inhabits the lower reaches of the Sierra Nevada foothills. This ecosystem is a natural laboratory for studying how ecosystem scale carbon and water fluxes respond to environmental change. The temperatures range between 0 and 40 C, the autumn, winter and spring are wet and cool, while the summer growing season is hot, dry and rainless. The overstory is dominated by blue oak trees (40% of total vegetation) with intermittent grey pine trees (3 trees/ha). Understory species include a variety of grasses and herbs, including purple false brome, smooth cat's ear, and rose clover. These two distinctive layers operate in and out of phase from one another. Growing season of the understory is confined to the wet season only, typically from October to early May. In contrast, the deciduous blue oak trees are dormant and leafless during the rainy winter months. The trees tend to leaf out in March and reach maximum LAI in April. During the rainless summers, the grasses in the understory die and the leaves experience soil moisture deficit stress References Davis, F., et al. (2016). "Oak woodlands." Ecosystems of California: 509–529.

Ma, Siyan↗
DOE OSTI2024

Single-crystal X-ray diffraction on the structure of (Al,Fe)-bearing bridgmanite in the lower mantle

Abstract Here we have performed single-crystal X-ray diffraction (SCXRD) experiments on two high-quality crystal platelets of (Al,Fe)-bearing bridgmanite (Mg0.88Fe0.0653+Fe0.0352+Al0.03)(Al0.11Si0.90)O3 (Fe10-Al14-Bgm) up to 64.6(6) GPa at room temperature in a Boehler-Almax type diamond-anvil cell. Refinements on the collected SCXRD patterns reveal reliable structural information of single-crystal Fe10-Al14-Bgm, including unit-cell parameters, atomic coordinates, and anisotropic displacement parameters. Together with Mössbauer and electron microprobe analyses, our best single-crystal refinement model indicates that the sample contains ~6.5 mol% Fe3+, 3.5 mol% Fe2+, and 3 mol% Al3+ in the large pseudo-dodecahedral site (A site), and ~11 mol% Al3+ in the small octahedral site (B site). This may indicate that Al3+ in bridgmanite preferentially occupies the B site. Our results show that the compression of Fe10-Al14-Bgm with pressure causes monotonical decreases in the volumes of AO12 pseudo-dodecahedron and BO6 octahedron (VA and VB, respectively) as well as the associated A-O and B-O bond lengths. The interatomic angles of B-O1-B and B-O2-B decrease from 145.2–145.8° at 4.2(1) GPa to 143.3–143.5° at 64.6(6) GPa. Quantitative calculations of octahedral tilting angles (Ф) show that Ф increases smoothly with pressure. We found a linear relationship between the polyhedral volume ratio and the Ф in the bridgmanite with different compositions: VA/VB = –0.049Φ + 5.549. Our results indicate an increased distortion of the Fe10-Al14-Bgm structure with pressure, which might be related to the distortion of A-site Fe2+. The local environmental changes of A-site Fe2+ in bridgmanite could explain previous results on the hyperfine parameters, abnormal lattice thermal conductivity, mean force constant of iron bonds and other physical properties, which in turn provide insights into our understanding on the geophysics and geochemistry of the planet.

Geochemistry & Geophysics↗
DOE OSTI2020

DECOVALEX-2019 (Task C Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task C which was proposed and coordinated by the Japan Atomic Energy Agency (JAEA), presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. DECOVALEX-2019 Task C aims to develop modelling and prediction methods using numerical simulation based on the water-filling experiment to examine the post-driftclosure environment recovery processes. Three research teams, JAEA, Sandia National Laboratories in the United States (SNL), and the Technical University of Liberec in the Czech Republic (TUL) were challenged to simulate the observed environmental changes. The Task consisted of following three main steps. The simulation targets were the water pressure drawdown/recovery and the variation of water chemistry during the tunnel excavation and closure, as observed in the monitoring boreholes and the CTD.

58 GEOSCIENCES↗
DOE OSTI2022

National Renewable Energy Laboratory Wildland Fire Management Plan (August 2022-August 2025): February-August 2022

The National Renewable Energy Laboratory (NREL) is located in a moderate wildfire risk region. The region has a history of damaging wildland fire activity and is also susceptible to changing environmental conditions (drought, elevated temperatures) that may lead to an increase in wildfire frequency and consequence over time. An integrated, site-wide wildland fire management plan is required by the Department of Energy and is to be consistent with the Federal Wildland Fire Management Policy. The NREL Wildland Fire Management Plan (WFMP) provides an integrated approach to reducing risk to wildland fire at NREL. The goals of the WFMP are to protect human health and safety, protect NREL facilities and research, enhance community protection, diminish risk and consequences of wildland fires, and maintain the health of the ecosystem. The WFMP accomplishes these goals through the use of tools such as fire behavior modeling, fire growth modeling, a structure ignition risk assessment, and through the application of robust fire prevention, emergency management, and environmental programs. The NREL WFMP was developed in a collaborative manner with input from regional stakeholders including cities, counties, local fire departments, and other governmental agencies. The WFMP provides for recommendations to reduce overall wildland fire risk to life safety and property at NREL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Control and Calibration of GlueX Central Drift Chamber Using Gaussian Process Regression

The Gluonic Excitations (GlueX) experiment is designed to search for exotic hybrid mesons using photoproduction, and to study the hybrid meson spectrum predicted from Lattice Quantum Chromodynamics. For the first time, the GlueX Central Drift Chamber was controlled autonomously using machine learning (ML) to calibrate in real time while recording cosmic ray tracks. We demonstrate the ability of a Gaussian Process to predict the gain correction calibration factor used to determine a high voltage setting that will stabilize the CDC gain in response to changing environmental conditions; this is in contrast to the traditional, computationally expensive method of calibrating raw data after data collection is complete.

McSpadden, Helen↗
DOE OSTI2020

Biogeochemical Processes Across Aquatic Interfaces

The aquatic interfaces exposing terrestrial soils to oxic-anoxic regime shifts represent biogeochemical “hotspots” that are extremely sensitive to climate and environmental change. However, processes and interaction across theses aquatic interfaces are poorly understood and underrepresented in current Earth system models. In this project, we aim to develop predictive understanding of the feedbacks between microbial systems and geochemical environments that determine emergent ecosystem behaviors and resilience in response to disturbances. We use experimental, mechanistic modeling and meta-analysis tools to elucidate interactions among soil, water, geomorphology and microbiology that regulate the molecular transformations and fluxes of carbon, nutrients, and redox-sensitive compounds across aquatic interfaces.

58 GEOSCIENCES↗
DOE OSTI2024

ML based control systems for nuclear physics experiments

The Experimental Physics Software and Computing Infrastructure (EPSCI) group at Jefferson Lab is leading the use of machine learning (ML) to enhance control systems in nuclear physics experiments. Collaborating closely with domain experts and data scientists, we have developed an ML-based control system that uses a Gaussian process to dynamically adjust the high voltage of the GlueX Central Drift Chamber. This results in stable detector performance by adapting to environmental changes, thereby reducing the offline calibration effort. Furthermore, we are developing ML-driven systems for optimizing the polarization of photon beams and polarized cryotargets. These systems will maintain the optimal microwave frequency in cryogenic targets and make real-time adjustments to diamond radiators for polarized photon sources, tasks traditionally handled by human operators. By automating these functions, we aim to optimize the polarization, reduce downtime, and minimize human error. This talk will highlight the development of reliable ML-based control systems and the policies to ensure they are both effective and trustworthy.

Jeske, Torri↗
DOE OSTI2025

Feasibility of an Accelerometer-Based Structural Health Monitoring System for the LANL Blast Tube

A modeling- and simulation-based study was conducted on the feasibility of implementing an accelerometer-based SHM system on the Los Alamos National Laboratory blast tube. A blast tube experiment was modeled using the Abaqus explicit finite element solver. A custom user subroutine was written to apply test-like pressure loading to the inside surface of the blast tube. The subroutine applies analytically defined pressure loads derived from tracer output taken from a Compressible Flow Computational Fluid Dynamics Solver model of the blast tube. Five unique versions of the model were created: an undamaged reference model at 65°F was used as the baseline and compared to equivalent models at 10°F and 100°F. These three models were compared to models with small damage at the reference temperature. The two types of damage considered were a radial (circumferential) crack in the main tube body and a longitudinal crack in the supports. Acceleration outputs were extracted from accelerometer bodies included in the model and were post processed using a variety of standard SHM techniques. Different potential features signaling failure were extracted and compared using statistical methods in the time and frequency domains. A method was identified that clearly shows that differences in structural response resulting from the modeled damage can be differentiated from the structural response resulting from changing environmental conditions. However, the amount of damage applied to create observable differences in the accelerometer data was so large that simpler methods of damage detection would be more cost effective in locating damage.

42 ENGINEERING↗
DOE OSTI2024

Chloroform Fumigation Extraction for Microbial Biomass and Dissolved Organic Carbon from SPRUCE, Marcell Experimental Forest, Minnesota, 2021, 2022, and 2024

This data set provides the results for chloroform fumigation extraction (CFE) of peat samples collected from ambient and experimental plots in the Spruce and Peatland Responses Under Environmental Change (SPRUCE) Experiment site in June and August of 2021, June of 2022, and June, August, and October of 2024. The SPRUCE Experiment site is in the Marcell Experimental Forest in northern Minnesota, USA. The data set includes values for microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), dissolved organic carbon (DOC), dissolved nitrogen (DN), moisture content (MC, available for 2021 and 2022 only) and gravimetric water content (GWC) at 11 depth increments of two-meter peat cores taken from 12 sampling sites at SPRUCE (10 temperature treatment enclosures, 2 ambient temperature treatment enclosures). The sample analysis followed standard methods. The samples were analyzed using a Shimadzu Total Organic Carbon/Nitrogen (TOC/N) analyzer (TOC-V and TOC-L; 2021-2022) or an Elementar vario TOC Cube (2024), liquid catalytic oxidation combustion analyzers for total carbon and nitrogen analysis. This dataset contains two data files in comma separate (.csv) format. Additional metadata are provided: two data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

dissolved nitrogen↗
DOE OSTI2020

Lectin Receptor-Like Kinases: The Sensor and Mediator at the Plant Cell Surface

Lectin receptor-like kinases (LecRLKs), a plant-specific receptor-like kinase (RLK) sub-family, have been recently found to play crucial roles in plant development and responses to abiotic and biotic stresses. In this review, we first describe the classification and structures of Lectin RLKs. Then we focus on the analysis of functions of LecRLKs in various biological processes and discuss the status of LecRLKs from the ligands they recognize, substrate they target, signaling pathways they are involved in, to the overall regulation of growth-defense tradeoffs. LecRLKs and the signaling components they interact with constitute recognition and protection systems at the plant cell surface contributing to the detection of environmental changes monitoring plant fitness.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Biological insights from multi-omics analysis strategies: Complex pleotropic effects associated with autophagy

Research strategies that combine molecular data from multiple levels of genome expression (i.e., multi-omics data), often referred to as a systems biology strategy, has been advocated as a route to discovering gene functions. In this study we conducted an evaluation of this strategy by combining lipidomics, metabolite mass-spectral imaging and transcriptomics data from leaves and roots in response to mutations in two AuTophaGy-related ( ATG ) genes of Arabidopsis . Autophagy is an essential cellular process that degrades and recycles macromolecules and organelles, and this process is blocked in the atg7 and atg9 mutants that were the focus of this study. Specifically, we quantified abundances of ~100 lipids and imaged the cellular locations of ~15 lipid molecular species and the relative abundance of ~26,000 transcripts from leaf and root tissues of WT, atg7 and atg9 mutant plants, grown either in normal (nitrogen-replete) and autophagy-inducing conditions (nitrogen-deficient). The multi-omics data enabled detailed molecular depiction of the effect of each mutation, and a comprehensive physiological model to explain the consequence of these genetic and environmental changes in autophagy is greatly facilitated by the a priori knowledge of the exact biochemical function of the ATG7 and ATG9 proteins.

59 BASIC BIOLOGICAL SCIENCES↗