SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Transient absorption (TA)microscopy is an emerging new microscopy technique that combines access to the nanoscale, with time-domain dynamic spectroscopy that can uniquely inform both composition and function in complex, heterogeneous systems
The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.
Several material properties have been studied as a function of composition as part of the USHPRR effort to use U-10Mo for LEU monolithic fuel foils, with special attention to areas where simulation outcomes can be improved. The liquidus and solidus phase boundaries are important for engineering design of processing parameters and for predicting the degree of microsegregation within initial castings. The numerous phase diagram constructions available in the literature differ significantly in their solid/liquid boundary definitions, therefore, an experimental strategy was employed in order to resolve some of the discord. That strategy focuses not on proving any singular point, but instead to provide data with highly characterized uncertainty. The data presented here is the most consistent with the U-rich liquidus and solidus boundaries provided by H. Okamoto (2012), Berche et al. (2011), and Mardon et al. (1959). The recently suggested change in the peritectic reaction temperature (to 1302 K) suggested by Berchè and adopted by Okamoto is also supported, but with lower confidence. The enthalpy of fusion is a basic characteristic of the solidification reaction property for which is required for both research-oriented predictions of behavior and development of applied design strategies for casting engineering. It has been determined that an admixture model for the heat of fusion between U BCC and Mo BCC is a reasonable assumption within the composition region of interest, though limitations of the measurement accuracy impacts the ability to support any trends more detailed than this baseline behavior. A limited number of thermal diffusivity measurements were also performed into the gamma region to provide additional information for solidification modeling and simulations as well as a check on the component properties of thermal conductivity, density, and heat capacity.
The Aquificales are thermophilic microorganisms that inhabit hydrothermal systems worldwide and are considered one of the earliest lineages of the domain Bacteria. We analyzed metagenome sequence obtained from six thermal “filamentous streamer” communities (~40 Mbp per site), which targeted three different groups of Aquificales found in Yellowstone National Park (YNP). Unassembled metagenome sequence and PCR-amplified 16S rRNA gene libraries revealed that acidic, sulfidic sites were dominated by Hydrogenobaculum (Aquificaceae) populations, whereas the circum-neutral pH (6.5–7.8) sites containing dissolved sulfide were dominated by Sulfurihydrogenibium spp. (Hydrogenothermaceae). Thermocrinis (Aquificaceae) populations were found primarily in the circum-neutral sites with undetectable sulfide, and to a lesser extent in one sulfidic system at pH 8. Phylogenetic analysis of assembled sequence containing 16S rRNA genes as well as conserved protein-encoding genes revealed that the composition and function of these communities varied across geochemical conditions. Each Aquificales lineage contained genes for CO2 fixation by the reverse-TCA cycle, but only the Sulfurihydrogenibium populations perform citrate cleavage using ATP citrate lyase (Acl). The Aquificaceae populations use an alternative pathway catalyzed by two separate enzymes, citryl-CoA synthetase (Ccs), and citryl-CoA lyase (Ccl). All three Aquificales lineages contained evidence of aerobic respiration, albeit due to completely different types of heme Cu oxidases (subunit I) involved in oxygen reduction. The distribution of Aquificales populations and differences among functional genes involved in energy generation and electron transport is consistent with the hypothesis that geochemical parameters (e.g., pH, sulfide, H2, O2) have resulted in niche specialization among members of the Aquificales.
Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptative and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabiting this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g. glycolate) and fermentation (e.g. acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gases (e.g. H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: 1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; 2) Synechococcus spp. produce CH4 via metabolism of phosphonates, and photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; 3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and 4) fluctuations in many metabolite pools (e.g. wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches.
Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica . The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.
Determining the mechanisms, traits, and pathways that regulate microbial transformation of natural organic matter (NOM) is critical to informing our understanding of the microbial impacts on the global carbon cycle. The capillary fringe of subsurface soils is a highly dynamic environment that remains poorly understood. Characterization of organo-mineral chemistry combined with a nuanced understanding of microbial community composition and function is necessary to understand microbial impacts on NOM speciation in the capillary fringe. We present a critical review of the popular analytical and omics techniques used for characterizing complex carbon transformation by microbial communities and focus on how complementary information obtained from the different techniques enable us to connect chemical signatures with microbial genes and pathways. This holistic approach offers a way forward for the comprehensive characterization of the formation, transformation, and mineralization of terrestrial NOM as influenced by microbial communities.
The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline called volcalc that uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate how volcalc might be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. With volcalc , we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. The volcalc package is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems.
The presence of methylmercury in aquatic environments and marine food sources is of global concern. The chemical reaction for the addition of a methyl group to inorganic mercury occurs in diverse bacterial taxonomic groups including the Gram-negative, sulfate-reducing Desulfovibrionaceae family that inhabit extreme aquatic environments. The availability of whole-genome sequence datasets for members of the Desulfovibrionaceae presents opportunities to understand the microbial mechanisms that contribute to methylmercury production in extreme aquatic environments. We have applied bioinformatics resources and developed visual analytics resources to categorize a collection of 719 putative universal stress protein (USP) sequences predicted from 93 genomes of Desulfovibrionaceae. We have focused our bioinformatics investigations on protein sequence analytics by developing interactive visualizations to categorize Desulfovibrionaceae universal stress proteins by protein domain composition and functionally important amino acids. We identified 651 Desulfovibrionaceae universal stress protein sequences, of which 488 sequences had only one USP domain and 163 had two USP domains. The 488 single USP domain sequences were further categorized into 340 sequences with ATP-binding motif and 148 sequences without ATP-binding motif. The 163 double USP domain sequences were categorized into (1) both USP domains with ATP-binding motif (3 sequences); (2) both USP domains without ATP-binding motif (138 sequences); and (3) one USP domain with ATP-binding motif (21 sequences). We developed visual analytics resources to facilitate the investigation of these categories of datasets in the presence or absence of the mercury-methylating gene pair (hgcAB). Future research could utilize these functional categories to investigate the participation of universal stress proteins in the bacterial cellular uptake of inorganic mercury and methylmercury production, especially in anaerobic aquatic environments.
The increasing incidence of implant-associated infections has prompted the development of effective strategies to prevent biofilm formation on these devices. In this work, pristine graphene nanoplatelet/polydimethylsiloxane (GNP/PDMS) surfaces containing different GNP loadings (1, 2, 3, 4, and 5 wt%) were produced and evaluated on their ability to mitigate biofilm development. After GNP loading optimization, the most promising surface was tested against single- and dual-species biofilms of Staphylococcus aureus and Pseudomonas aeruginosa. The antibiofilm activity of GNP/PDMS surfaces was determined by the quantification of total, viable, culturable, and viable but nonculturable (VBNC) cells, as well as by confocal laser scanning microscopy (CLSM). Results showed that 5 wt% GNP loading reduced the number of total (57%), viable (69%), culturable (55%), and VBNC cells (85%) of S. aureus biofilms compared to PDMS. A decrease of 25% in total cells and about 52% in viable, culturable, and VBNC cells was observed for P. aeruginosa biofilms. Dual-species biofilms demonstrated higher resistance to the antimicrobial activity of GNP surfaces, with lower biofilm cell reductions (of up to 29% when compared to single-species biofilms). Still, the effectiveness of these surfaces in suppressing single- and dual-species biofilm formation was confirmed by CLSM analysis, where a decrease in biofilm biovolume (83% for S. aureus biofilms and 42% for P. aeruginosa and dual-species biofilms) and thickness (on average 72%) was obtained. Overall, these results showed that pristine GNPs dispersed into the PDMS matrix were able to inhibit biofilm growth, being a starting point for the fabrication of novel surface coatings based on functionalized GNP/PDMS composites.
We consider infrastructures consisting of a network of systems, each composed of discrete components. The network provides the vital connectivity between the systems and hence plays a critical, asymmetric role in the infrastructure operations. The individual components of the systems can be attacked by cyber and physical means and can be appropriately reinforced to withstand these attacks. We formulate the problem of ensuring the infrastructure performance as a game between an attacker and a provider, who choose the numbers of the components of the systems and network to attack and reinforce, respectively. The costs and benefits of attacks and reinforcements are characterized using the sum-form, product-form and composite utility functions, each composed of a survival probability term and a component cost term. We present a two-level characterization of the correlations within the infrastructure: (i) the aggregate failure correlation function specifies the infrastructure failure probability given the failure of an individual system or network, and (ii) the survival probabilities of the systems and network satisfy first-order differential conditions that capture the component-level correlations using multiplier functions. We derive Nash equilibrium conditions that provide expressions for individual system survival probabilities and also the expected infrastructure capacity specified by the total number of operational components. We apply these results to derive and analyze defense strategies for distributed cloud computing infrastructures using cyber-physical models.
Bacterial-fungal interactions (BFIs) play an integral role in shaping microbial community composition, biogeochemical functions, spatial dynamics, and microbial dispersal. Mycelial networks created by filamentous fungi or other filamentous microorganisms (e.g., Oomycetes) act as 'fungal highways' that can be utilized by bacteria for transport throughout heterogeneous environments, greatly facilitating their mobility and granting them access to regions that may be challenging or impossible to reach on their own (e.g., due to air pockets within the soil). Several devices and experimental protocols have been created to study these fungal highways, including fungal highway columns. The fungal highway column designed by our group can be used for a variety of in situ or in vitro applications, as well as with diverse environmental and host-associated sample types. Herein, we describe the methods for performing experiments with these columns, including designing, printing, sterilizing, and preparing the devices. The options for analyzing data obtained from the use of these devices are also discussed here, and troubleshooting advice regarding potential pitfalls associated with experiments using fungal highway columns is offered. These devices can be used to gain a more comprehensive understanding of the diversity, mechanisms, and dynamics of fungal highway BFIs to provide valuable insights into the structural and functional dynamics within complex environments (e.g., soils) and across diverse habitats in which bacteria and fungi co-exist.
1.Perennial bioenergy systems, such as switchgrass and restored prairies, are alternatives to commonly used annual monocultures such as maize. Perennial systems require lower chemical input, provide greater ecosystem services such as carbon storage, greenhouse gas mitigation, and support greater biodiversity of beneficial insects. However, biomass harvest will be necessary in managing these perennial systems for bioenergy production, and it is unclear how repeated harvesting might affect ecosystem services. 2.In this study, we examined how repeated production-scale harvesting of diverse perennial grasslands influences vegetation structure, natural enemy communities (arthropod predators and parasitoids), and natural biocontrol services in two states (Wisconsin and Michigan, USA) over multiple years. 3.We found that repeated biomass harvest reduced litter biomass and increased bare ground cover. Some natural enemy groups, such as ground-dwelling arthropods, decreased in abundance with harvest whereas others, such as foliar-dwelling arthropods increased in abundance. The disparity in responses is likely due to how different taxonomic groups utilize vegetation and differences in dispersal abilities. 4.At the community level, biomass harvest altered community composition, increased total arthropod abundance, and decreased evenness but did not influence species richness, diversity, or biocontrol services. Harvest effects varied with time, diminishing in strength both within the season (for total abundance and evenness), across seasons (for evenness), or were consistent throughout the duration of the study (for community composition). Greater functional redundancy and compensatory responses of the different taxonomic groups may have buffered against the potentially negative effects of harvest on biocontrol services. 5.Synthesis and applications. Our results show that in the short-term, repeated harvesting of perennial grasslands (when insect activity is low) consistently altered vegetation structure but had mixed effects on natural enemy communities and no discernable effects on biocontrol services. However, the long-term effects of repeated harvesting on vegetation structure, natural enemies, and other arthropod-derived ecosystem services such as pollination and decomposition remain largely unknown.
NMDA receptors, which regulate synaptic strength and are implicated in learning and memory, consist of several subtypes with distinct subunit compositions and functional properties. To enable spatiotemporally defined, rapid and reproducible manipulation of function of specific subtypes, we engineered a set of photoswitchable GluN subunits ('LiGluNs'). Photo-agonism of GluN2A or GluN2B elicits an excitatory drive to hippocampal neurons that can be shaped in time to mimic synaptic activation. Photo-agonism of GluN2A at single dendritic spines evokes spine-specific calcium elevation and expansion, the morphological correlate of LTP. Photo-antagonism of GluN2A alone, or in combination with photo-antagonism of GluN1a, reversibly blocks excitatory synaptic currents, prevents the induction of long-term potentiation and prevents spine expansion. In addition, photo-antagonism in vivo disrupts synaptic pruning of developing retino-tectal projections in larval zebrafish. By providing precise and rapidly reversible optical control of NMDA receptor subtypes, LiGluNs should help unravel the contribution of specific NMDA receptors to synaptic transmission, integration and plasticity.
Optical second-harmonic generation in zinc sulfide-cadmium sulfide and cadmium sulfide- cadmium selenide alloys measured as function of composition
Thermal conductance of chars from nylon - phenolic composites as function of graphitization, density, and pore spectra
The heats of solution in liquid tin of pure praseodymium, pure neodymium and nine praseodymium-neodymium binary alloys have been measured using liquid metal solution calorimetry. A plot of the measured heat effect for the alloys as a function of composition is linear, with the terminal points being the measured values for the pure components. This linear dependency indicates that the heat of mixing in the binary praseodymium-neodymium system is zero within experimental error, and therefore the binary alloys obey one of the criteria for an ideal solution.
Construction of Cayley-Dickson type and involution type bimodules for composition algebras