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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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Time-variant spectral analysis of plants can classify stress-based perturbations (e.g., dry soil or increased salination) and quantify mechanistic attributes associated with plant photosynthesis, respiration, hormone function, and plant morphology. This project will investigate the utility of hyperspectral cameras for detecting and monitoring these perturbations.
The fundamental process of electron transfer (ET) within and between molecules dictates all biological energy conversion strategies, including respiration and photosynthesis. This project resulted in a comprehensive physics-based understanding of the mechanisms and limits of redox networks that mediate and regulate electron transport through microbial metabolic pathways, with special emphasis on environmental microbes that can acquire energy by catalyzing anodic or cathodic reactions on solid-state electrodes (extracellular electron transfer, or EET). By performing electron transfer to/from electrodes, such microbes may be used as biocatalysts for converting the energy stored in diverse chemical fuels to electricity, or vice versa (microbial electrosynthesis), in renewable energy technologies.
Microbial biomanufacturing is important to accelerate lunar construction because it can leverage lunar material and waste streams as feedstocks to create a circular production system. In-space bio-mining and biomanufacturing using moon and asteroidal source material will enable the creation of infrastructure, produce industrial fuels and lubricants, and enable recovery of actinides and rare-earth elements (REEs) present in trace concentrations. Moreover, biomanufacturing in closed-loop systems (recycling and reuse of resources toward the establishment of a circular economy) will enable long-term lunar activities by recycling waste (CO 2 , gray water) and producing oxygen and biomaterials. Our response focuses on the use of lunar regolith and waste streams as feedstocks for protein and microbial-enabled biomining and bioprocessing to extract actinides and REEs, and to create biocomposites for lunar infrastructure. We envision an enclosed process that initiates with (1a) extracting actinides and REEs from lunar regolith using immobilized proteins, followed by (1b) creating biocomposites from the post-extracted lunar regolith for infrastructure, and (1c) cultivating diatoms and other microalgae on waste streams to harvest silica shells for incorporating into biocomposites and to generate O 2 for human respiration and/or producing refinable feedstocks. LLNL has significant expertise in all three processes and provides facilities, personnel, and expertise at the intersection of metal (lanthanide, actinide, transition) separations, purifications, biohydrometallurgy, radiobiochemistry, synthetic and systems biology, and materials science and engineering. Importantly, all three processes are relatively well-studied for Earth-based workflows and can be derisked for demonstration on the lunar surface by 2029.
A 5Qt Hagan container with a 20-year history of nuclear material storage was challenged with three successive drop tests at a height of 3.7 meters. The total mass of the test package was 12.1 kg. The 1st and 2nd drop tests (center of gravity over the container bottom corner but 180 degrees apart on the container bottom face) passed the pre- and post- impact helium leak criterion at less than 1.00E-6 atm-cc/sec (ambient cubic centimeters per second). The 3rd and final test (center of gravity over top corner) failed with a post-impact gross leak of 1.1E-1 atmcc/sec. The RRFMC (Respirable Release Fraction Measurement Chamber) is a drop tower test system that is critical for the sustainability of the SAVY-4000™ series and Hagan-type (NFT Inc. Golden CO) nuclear material storage containers. These are the primary in-use nuclear material storage container types at the Los Alamos National Laboratory TA-55 facility. Results are presented to expand the technical knowledge basis for container lifetime, regarding actual exposure to corrosive gas species on the container inner surfaces. The primary source of general corrosion throughout the container is gaseous hydrogen chloride (HCl). This gas is generated by the degradation of the polyvinylchloride (PVC) bag-out bag. Additionally, in most cases, the nuclear material itself also releases HCl gas (due to residual chemical components associated with the material formation). The RRFMC drop tower gives the end-user the ability record and analyze high-speed video and photography and if needed aerosol mass release measurements. In this report the principal issue is the physical deformation of the 5Qt Hagan container. There were no mass release experiments of test aerosol mass in the present study.
Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.
Licensing a new nuclear reactor involves evaluating credible accident scenarios by developing models that simulate accident progression to predict possible outcomes and their impact on safety. The formation of radionuclide-bearing aerosols in the respirable size range can significantly affect dose consequence and threaten human health and is therefore a focus of nuclear reactor safety assessments. Recent reviews of the literature identified a lack of existing experimental data describing the mechanisms of formation and properties (size, concentration, and composition) of radionuclide-bearing aerosols that may be produced from molten salt reactor (MSR) facilities during postulated accident scenarios. Experiments on aerosol formation from molten salt systems are a high priority need that will support MSR licensing by indicating the radiological consequences of aerosol formation and providing the data required for model development and validation. The evolving conditions that occur during a MSR accident, such as a spill of molten fuel salt, may affect aerosol formation mechanisms and aerosol properties over time. There is a need to conduct experiments that simulate credible MSR accidents in a laboratory to generate aerosols with realistic characteristics and behaviors and a need to measure these aerosols in real time under accident-relevant conditions. This report describes the development of a method that can be used to quantify the size and concentration of salt aerosol particles that form from molten salt systems in real time. This method will be employed in future integral effects tests that are conducted at an engineering scale to simulate realistic MSR accidents and in future separate effects tests that will provide mechanistic insight into aerosol formation and properties to support process model development.
CONCLUSIONS Scalability: could reduce produce cost of nanomaterials for widespread application • Nanomaterials can be produced on macro-scale supports, i.e. metal filters, textile, via solution chemistries • Applications: • Antimicrobial and antiviral applications • Capturing contaminants from aqueous environments • Biocompatibility and Toxicity: safety & long-term effects • Airborne Release Fraction and Respirable Fraction must be considered when moieties released in the atmosphere • Evidence for Bioavailability of Au Nanoparticles from Soil and Biodistribution within Earthworms
The GREEN ‘omics of Nutrient Feedbacks in Soil project advanced the DOE Biological and Environmental Research (BER) mission by developing and applying isotope-enabled ’omics tools to understand how soil microbes regulate carbon and nutrient cycling. Guided by the Growth Rate, growth Efficiency, and stoichiometry of Essential Nutrients (GREEN ’omics) framework, the project aimed to build a predictive, systems-level understanding of microbial traits that control ecosystem biogeochemistry. In a collaboration among Northern Arizona University (lead), West Virginia University, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory, we combined quantitative stable isotope probing (qSIP), Chip-SIP, NanoSIMS, and genome-resolved metagenomics across long-term experiments in Arctic, boreal, temperate, and tropical ecosystems. The project produced three key outcomes: 1) We showed that community-weighted temperature sensitivities of bacterial growth (Q10) can predict ecosystem-scale soil respiration responses across diverse soils. 2) We provided the first in situ evidence for density-dependent population dynamics in soil bacteria and demonstrated that nutrient additions intensify competition, concentrating carbon use into fewer taxa. 3) We improved and extended isotope-enabled ’omics methods by quantifying qSIP measurement error to guide experimental design and coupling SIP with genome-resolved metagenomics to reveal cross-kingdom interactions among bacteria, fungi, and viruses. Together, these results show that a small number of microbial traits and taxa exert disproportionate control over soil carbon and nutrient cycling, providing critical data and methods to improve representation of microbial processes in Earth system models.
The formation of radionuclide-bearing aerosols in the respirable size range has the potential to significantly influence offsite dose consequences and is, therefore, an important consideration in nuclear facility safety assessments. Molten salt reactor (MSR) developers will likely need to demonstrate an understanding of the conditions under which radionuclide-bearing aerosols may be generated from their reactor under normal operating and accident conditions, as well as the characteristics and transport behavior of these aerosols, to demonstrate to the U.S. Nuclear Regulatory Commission (NRC) that the facility can be operated safely. Recent reviews of the literature identified a lack of experimental data describing the mechanisms of formation and properties (size, concentration, and composition) of salt aerosol particles that are produced from molten salts. Experiments that identify the conditions that lead to radionuclide-bearing salt aerosol releases and quantify the characteristics of salt aerosols formed by different mechanisms are high-priority needs to support MSR licensing. This report describes tests that were conducted within the Argonne Salt Aerosol Test Stand (a sealed vessel and measurement system) to generate salt aerosols from static and sparged molten salts and measure their size and concentration in real-time. The results provide insight into salt aerosol formation by the vapor condensation and bubble bursting mechanisms and inform the potential radiological consequences of aerosol formation from molten fuel salt. Videos of the salt surface were taken during salt sparge tests to observe surface bubble behavior. The data in this report can be used to develop mechanistic source term and accident progression models for MSRs. The real-time salt aerosol characterization technique used in this study will be employed in future integral effects tests that are conducted at an engineering scale to simulate realistic MSR accidents and in future separate effects tests to address additional variables that may impact salt aerosol characteristics (e.g., presence of fission products in salt and humidity in atmosphere).
MONet provides novel soil molecular data to the research community for understanding biogeochemical processes and complementing other soil datasets. This study assesses MONet's ability to replicate known soil patterns via a comparative analysis of soil respiration (Rs), pH, and clay content against benchmark datasets. Results show moderate agreement for pH and clay content, highlighting MONet's strengths in capturing soil biogeochemical variation in underrepresented regions like urban areas. Rs data are marked by the appropriate trends relative to other datasets, but direct comparison is impractical due to methodological differences in underlying data. Strategic sampling is recommended to improve MONet's coverage and eventual utility in bridging molecular observations with global datasets.
Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.
Biomass-based Carbon Removal and Storage (BiCRS) is a suite of technological pathways that provide a relatively affordable and high-potential way to remove carbon dioxide from the atmosphere and simultaneously re-purpose residual biomass. BiCRS technologies are individually optimized to different biomass feedstocks, temperatures and oxygen, with the primary goal of capturing a high percentage of biomass-derived carbon dioxide and storing it in permanent below-ground storage (i.e. geologic storage), and a secondary goal of producing renewable energy. The current standard for BiCRS life cycle assessments does not account for greenhouse gas (carbon dioxide, methane and nitrous oxide) fluxes from surface soil amendment of BiCRS byproducts (e.g. char, ash) and their alternate fates. This is partly due to a paucity of empirical data due to the novelty of BiCRS conversion technologies, the range in feedstocks, and the heterogeneity of soils to which they might be amended. To fill this gap in in the life-cycle assessment and provide a realistic range of parameters for a soil amendment component of the BiCRS life cycle assessment, we conducted an incubation experiment to measure soil carbon changes, microbial respiration, methane fluxes, and nitrous oxide fluxes from two different soils amended with char- and ash- byproducts from biomass after gasification to hydrogen, fast pyrolysis to bio-oil, and torrefaction. Our results suggest that nitrous oxide and methane emission or consumption from BiCRS char amendments to soil are context dependent. Nitrous oxide emissions from amendments are higher in soils with higher pH, whereas some char amendments to low pH soil can reduce N 2 O emissions relative to control. In contrast, methane is emitted from BiCRS char amended to low pH soil, but consumed or neutral relative to control when amended to high pH soil. We present carbon and nitrogen mass balance throughout the experiment to help understand short-term durability of BiCRS chars and their counterfactuals, and preliminary suggestions for revisions to the broader BiCRS Measurement, Reporting, and Verification framework.
This study assesses the air quality impacts of an advanced biorefinery that produces renewable diesel blendstock (RDB) from lignocellulosic biomass via aerobic respiration (Davis et al. 2022) by estimating fine particulate matter (PM2.5) impacts from biorefinery emissions. It continues a prior analysis that used a geospatial assessment to identify source regions for biomass feedstocks and studied the impact of feedstock production emissions on air quality (Thind et al. 2022). Thind et al. (2022) identified RDB biorefineries that can use corn stover feedstocks of 2,000; 5,200; and 9,100 dry metric tons per day (DMT/day), based in Iowa, and suggested 7 unique counties can serve as hosts for a biorefinery that draws biomass feedstock from neighboring counties. Given 13 unique county-biorefinery size combinations and two waste lignin end uses at the biorefinery (lignin as a fuel for electricity generation and lignin for pellet production), the air-quality-related sustainability aspects of each of these 26 scenarios are assessed by estimating the annual average impacts of biorefinery emissions on the dispersion and formation of secondary PM2.5 in the atmosphere using a novel reduced-complexity air quality model called the Intervention Model for Air Pollution (InMAP). The 26 biorefinery design combinations help capture how a biorefinery's emissions of air pollutants and their resulting impact on local and regional air quality are influenced by the magnitude of production scale, lignin utilization strategy, and location of a proposed biorefinery. Methods developed in Thind et al. (2022) are applied to estimate the constraints on primary PM2.5 and secondary PM2.5 precursor emissions based on compliance with U.S. Environmental Protection Agency's (EPA's) annual primary National Ambient Air Quality Standard (NAAQS) of PM2.5 (i.e.12.0 micrograms per cubic meter (microgram/m3)) at downwind receptors of a biorefinery. Incremental PM2.5 concentrations caused by the emission of biorefining corn stover into RDB are assessed and compared to those of corn stover production. To illuminate which upstream supply chain stage of renewable diesel production contributes most to air quality impacts, marginal PM2.5 concentrations are compared between both stages at multiple downwind air quality monitor locations. In addition, through a hotspot analysis, we identify the primary contributing factors of emissions within the feedstock production and biorefinery stage operations. In doing so, we provide insights for improving the air pollutant emission-related sustainability of advanced lignocellulosic biofuel production.
Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.
Biomass with Carbon Removal and Sequestration (BiCRS) is a suite of technological pathways that provide a relatively affordable and high-potential way to remove carbon dioxide from the atmosphere and simultaneously re-purpose residual biomass. BiCRS technologies are individually optimized to different biomass feedstocks, temperatures and oxygen, with the goal of capturing a high percentage of biomass-derived carbon dioxide and storing it in permanent below-ground storage (i.e. geologic storage). The current standard for BiCRS life cycle assessments does not account for carbon dioxide, methane and nitrous oxide (CO 2 , CH 4 , and N 2 O) fluxes from surface soil amendment of BiCRS byproducts (e.g. char, ash) and their alternate fates. This is partly due to a paucity of empirical data due to the novelty of BiCRS conversion technologies, the range in feedstocks, and the heterogeneity of soils to which they might be amended. To fill this gap in in the life-cycle assessment (LCA) and provide a realistic range of parameters for a soil amendment component of the BiCRS LCA, we conducted an incubation experiment to measure soil carbon changes, microbial respiration, methane fluxes, and nitrous oxide fluxes from two different soils amended with char- and ash- byproducts from biomass after gasification to hydrogen, fast pyrolysis to bio-oil, and torrefaction.
In this preliminary study, we constructed gene regulatory networks (GRNs) from transcriptional expression data of axenic and interspecies microbial cultures with the goal of predicting how cocultivation affected greenhouse gas respiration by these species. The specific strains of Methylotuvimicrobium alkaliphilum 20Z, a methylotroph, and Cyanobacterium stanieri HL-69, a phototroph, were chosen for their viability in industrial bioprocessing. We ranked directed interactions between gene pairs based on the ability of the input gene to predict the expression of a target gene relative to their transcriptomes. While we were able to identify topological differences between conditions, our initial findings require validation through experimental analysis and further modeling. We aimed to develop a systematic thresholding approach to optimize the accuracy of our networks. We filtered out trial networks separately from top gene interactions of the scored rankings. Parameters of unfiltered and filtered networks were used to test and develop thresholding approaches. Knee point detection of edge weight distributions was explored as an approach for separating significant interactions from insignificant interactions in unfiltered networks. While knee detection failed to produce analogous networks for broad cross-condition comparisons, the results informed us about the proportions of significant edges present in unfiltered networks. We also calculated the average mean degree for nodes in a selection of trial networks to find a thresholding value characteristic to all groups. While we did not reach a definitive conclusion, we gained insight into the coregulatory structures of our groups and made critical evaluations of systematic methods for filtering networks. We recommend an iterative process for the inference of GRNs, where the most significant results from preliminary explorations are used to improve the efficiency with which regulatory motifs are chosen for experimental characterization. Experimental results can then inform the framework of adjusted models to improve broad interpretations of GRNs.
This dataset contains soil microbial biomass data compiled from published laboratory studies and field manipulations of organic inputs to soils. Each study included at least three levels of a given type of organic input applied to a given type of soil. Studies were selected from the literature that had experimentally manipulated organic input rates to soils using unburned, non-synthetic material (e.g. plant litters, manures, and composts). Fifty-five (55) studies, conducted from 1997 to October 2019, were chosen and compiled into a dataset with 358 observations from 96 combinations of a given organic material applied to a given soil in agricultural systems, laboratory incubations, forests, or grasslands. • Studies were selected when biomass measurements used the chloroform fumigation-extraction procedure followed by carbon analysis, or, in two instances, studies estimated microbial biomass using phospholipid fatty acid analysis. • Studies that used fewer than three input rates or characterized microbial biomass via substrate induced respiration were excluded. • The temporal and spatial aspects of the laboratory and field studies were not essential to the analyses (Craig et al., 2021) and were not included with the measurement data. These data were used to assess the relationship between organic input amounts and microbial biomass. Complete reference citations are provided if additional information is needed. The compiled data are provided in two .csv files: (1) soil treatments and microbial biomass data and (2) literature citations. The “Study” field is the cross reference between files. Also provided is the R code for reproducing the results in the related publication.
This dataset contains quarterly soil core measurements from the Missouri Ozarks AmeriFlux (MOFLUX) site located at the University of Missouri’s Thomas H. Baskett Wildlife Research and Education Area near Ashland, Missouri. These data will be used to parameterize an ensemble of MOFLUX-optimized soil carbon-nitrogen models, used to simulate carbon (C) and nitrogen (N) cycling responses to future hydroclimatic scenarios and the trajectory of soil C stocks with concomitant forest decline. Beginning in 2017, eight soil cores were collected approximately quarterly near plot 1 of the southeast transect, near the automated soil respiration flux chambers, from 0–15 cm depth. Data are currently available through 2023 (2017-06-14 to 2023-11-13); additional observations will be appended to this dataset as they become available. Cores were analyzed for gravimetric moisture content, pH, total carbon and nitrogen, texture, microbial biomass carbon and nitrogen, and extractable dissolved organic carbon and nitrogen. This dataset contains one data file in comma separate (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.