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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Microscale spatiotemporal patterns of water, soil organic carbon, and enzymes in plant litter detritusphere

Understanding biophysical and biochemical processes in detritusphere is critical to quantifying and modeling plant residue decomposition dynamics and subsequent soil organic carbon (C) accrual. The objectives of the study were to explore (i) micro-environmental conditions within the detritusphere formed around decomposing corn and soybean leaves, and (ii) the relationships between moisture distribution, enzyme activity, and C dynamics during decomposition. We assessed spatial and temporal dynamics of moisture distribution using X-ray and neutron computed tomography, and activities of β-glucosidase and chitinase, two enzymes involved in soil C and N processing, using zymography. We used 13 C labeled residue to track residue contribution to atmospheric CO 2 and soil organic C. Moisture redistribution pattern varied depending on the residue type. While the water was immediately absorbed by the corn leaves and maintained afterward, switchgrass leaves absorbed water more slowly and created water-deficient zones within ~1mm from the residue. This initial moisture depletion led to lower chitinase activity and residue-derived CO 2 emissions in switchgrass. In contrast to chitinase, β-glucosidase activity was influenced by a combination of vegetation history and residue type, and it was higher when the origin of the residue matched the vegetation history of the soil. Pore size had an opposite impact on the studied enzymes, supporting the notion that contrasting soil pore architecture can stimulate activities of different enzymes through a selection of dominant enzyme producers. We concluded that the decomposition dynamics of plant residues is not only a simple function of residue chemistry, but rather a combined effect of the vegetation history, in part through its effect on microbial community composition, the plant residue chemical and likely physical characteristics, and the soil pore structure in the detritusphere. Together, they create temporally dynamic micro-environmental conditions influencing decomposition. Specifically, our study demonstrated that the initial micro-environment formulated in detritusphere can play an important role in enzyme activities and consequent C dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Control of valley polarization in gapped graphene by linearly polarized ultrashort optical pulse

We present a versatile model of gapped graphene to manipulate valley polarization by using ultrafast linearly polarized pulses of zero areas. First, a circularly polarized pulse of a single oscillation produces a valley-selective population of the conduction band by means of topological resonance. Then we apply a linearly polarized femtosecond-long pulse that changes the valley polarization. The magnitude of such a change depends on the amplitude and the direction of polarization of the pulse. In conclusion, our protocol provides a favorable platform for applications in valleytronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

CH 3 Radical Generation in Microplasmas for Up-Conversion of Methane

The conversion of methane, CH 4 , into higher value chemicals using low temperature plasmas is challenged by both improving efficiency and selectivity. One path towards selectivity is capturing plasma produced methyl radicals, CH 3 , in a solvent for aqueous processing. Due to the rapid reactions of methyl radicals in the gas phase, the transport distance from production of the CH 3 to its solvation should be short, which then motivates the use of microplasmas. The generation of CH 3 in Ar/CH 4 /H 2 O plasmas produced in nanosecond pulsed dielectric barrier discharge microplasmas is discussed using results from a computational investigation. The microplasma is sustained in the channel of a microfluidic chip in which the solvent flows along one wall or in droplets. CH 3 is primarily produced by electron-impact of and dissociative excitation transfer to CH 4 , as well as CH 2 reacting with CH 4 . CH 3 is rapidly consumed to form C 2 H 6 which, in spite of being subject to these same dissociative processes, accumulates over time, as do other stable products including C 3 H 8 and CH 3 OH. The gas mixture and electrical properties were varied to assess their effects on CH 3 production. CH 3 production is largest with 5% CH 4 in the Ar/CH 4 /H 2 O mixture due to an optimal balance of electron-impact dissociation, which increases with CH 4 percentage, and dissociative excitation transfer and CH 2 reacting with CH 4 , which decrease with CH 4 percentage. Design parameters of the microchannels were also investigated. Increasing the permittivity of the dielectrics in contact with the plasma increased the ionization wave intensity which increased CH 3 production. Increased energy deposition per pulse generally increased CH 3 production as does lengthening pulse length up to a certain point. The arrangement of the solvent flow in the microchannel can also affect the CH 3 density and fluence to the solvent. The fluence of CH 3 to the liquid solvent is increased if the liquid is immersed in the plasma as a droplet or is a layer on the wall where the ionization wave terminates. The solvation dynamics of CH 3 with varying numbers of droplets was also examined. Here, the maximum density of solvated methyl radicals CH 3aq occurs with a large number of droplets in the plasma. However, the solvated CH 3aq density can rapidly decrease due to desolvation, emphasizing the need to quickly react the solvated species in the solvent.

03 NATURAL GAS↗
DOE OSTI2024

Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities

Abstract The gut microbiome plays a major role in human health; however, little is known about the structural arrangement of microbes and factors governing their distribution. In this work, we present an in silico agent-based model (ABM) to conceptually simulate the dynamics of gut mucosal bacterial communities. We explored how various types of metabolic interactions, including competition, neutralism, commensalism, and mutualism, affect community structure, through nutrient consumption and metabolite exchange. Results showed that, across scenarios with different initial species abundances, cross-feeding promotes species coexistence. Morphologically, competition and neutralism resulted in segregation, while mutualism and commensalism fostered high intermixing. In addition, cooperative relations resulted in community properties with little sensitivity to the selective uptake of metabolites produced by the host. Moreover, metabolic interactions strongly influenced colonization success following the invasion of newcomer species. These results provide important insights into the utility of ABM in deciphering complex microbiome patterns.

Biotechnology & Applied Microbiology↗
DOE OSTI2022

Elemental chalcogen reactions of a tetravalent uranium imidophosphorane complex: cleavage of dioxygen

Herein we report the first example of a mononuclear uranium complex, [U 4+ (NP(pip) 3 ) 4 ] (1-U), that selectively reduces dioxygen to produce a terminal oxo complex, [U 6+ O(NP(pip) 3 ) 4 ] (2-U; [NP(pip) 3 ] 1- is tris(piperidinyl)imidophosphorane). Reactions between 1-U and the heavier elemental chalcogens, S 8 or Se 0 , result in six-coordinate U(VI) complexes, [U 6+ (κ 2 -E 3 )(NP(pip) 3 ) 4 ] (E = S (3-U) or Se (4-U)).

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Randomized Projection for Rank-Revealing Matrix Factorizations and Low-Rank Approximations

Rank-revealing matrix decompositions provide an essential tool in spectral analysis of matrices, including the Singular Value Decomposition (SVD) and related low-rank approximation techniques. QR with Column Pivoting (QRCP) is usually suitable for these purposes, but it can be much slower than the unpivoted QR algorithm. For large matrices, the difference in performance is due to increased communication between the processor and slow memory, which QRCP needs in order to choose pivots during decomposition. Our main algorithm, Randomized QR with Column Pivoting (RQRCP), uses randomized projection to make pivot decisions from a much smaller sample matrix, which we can construct to reside in a faster level of memory than the original matrix. This technique may be understood as trading vastly reduced communication for a controlled increase in uncertainty during the decision process. Furthermore, for rank-revealing purposes, the selection mechanism in RQRCP produces results that are the same quality as the standard algorithm, but with performance near that of unpivoted QR (often an order of magnitude faster for large matrices). Additionally, we also propose two formulas that facilitate further performance improvements. The first efficiently updates sample matrices to avoid computing new randomized projections. The second avoids large trailing updates during the decomposition in truncated low-rank approximations. Our truncated version of RQRCP also provides a key initial step in our truncated SVD approximation, TUXV. These advances open up a new performance domain for large matrix factorizations that will support efficient problem-solving techniques for challenging applications in science, engineering, and data analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Herbaceous Feedstock 2018 State of Technology Report

The U.S. Department of Energy (DOE) promotes the production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement with this mission, Idaho National Laboratory (INL) completes an annual SOT report for biomass feedstock logistics. This report summarizes supply system impacts of Bioenergy Technologies Office (BETO)-funded research and development efforts at INL and elsewhere (such as the High-Tonnage Feedstock Logistics projects (Webb et al. 2013a, Webb et al. 2013b, Webb et al. 2013c, Webb and Sokhansanj 2014, Sokhansanj et al. 2014) that lead to improvements in feedstock supply systems. These include improvements to and observed performance of innovative harvest and collection methods, storage technologies, transportation and handling approaches, and advanced preprocessing technologies. Biomass quality and variability, and the interface between feedstock quality and conversion performance are key drivers in addition to delivered feedstock cost. In this report, we estimate the benefits of R&D improvements to individual supply system unit operations, and present the status of feedstock logistics technology development for converting biomass into biofuels. These analyses are supported by experimental data where possible, and help to align the SOT relative to the cost goals defined in the Multi-Year Program Plan. The 2018 Herbaceous SOT aligned feedstock logistic design with current biorefinery’s design capacity utilized by biochemical conversion platform. Currently biochemical conversion platform utilizes a 725,000 dry ton/year biorefiney design for the techno economic analysis. Hence, feedstock delivered cost in the 2018 Herbaceous SOT is calculated based on biorefinery’s 725,000 dry ton design capacity instead of 800, 000 dry ton capacity utilized in the 2017 Herbaceous SOT. Biomass availabilities in this SOT were updated to year 2018 data from the 2016 Billion-Ton Report (BT16) (DOE 2016a), with the exception of switchgrass, for which the 2018 Herbaceous SOT utilized the 2019 switchgrass availability data from BT16. The BT16 report (DOE 2016a) does not project switchgrass availability in 2018; the soonest switchgrass is available in the BT16 report is 2019. Therefore, availability of switchgrass for this analysis was that projected for 2019. The 2018 Herbaceous SOT incorporates same technologies utilized in the 2017 Herbaceous SOT. However, a sensitivity analysis is performed to understand the impact of variation of process parameters on those technologies on feedstock logistic cost. New R&D data that shows the variations of process parameters affecting process performance is incorporated in the 2018 SOT to measure the variations in delivered feedstock cost. The 2018 Herbaceous SOT has also provided projected delivered feedstock of 2022 design case based on near term technical target under BETO funded R&D project. Finally, updated biorefinery size of 725,000 dry ton/year was incorporated within least-cost formulation model to select optimal siting and depot scales during optimization of the least cost blend. This modification to the optimization algorithm allows the trade-off between the cost of increased supply radius and the savings from selecting biomass from higher producing counties to be assessed. Such optimization has also showed the economic benefit of decentralized depots in comparison to centralized preprocessing co-located with the biorefinery by decoupling the biorefinery and feedstock locations. The 2018 Herbaceous SOT report documents the current modeled cost of a herbaceous feedstock supply system (from harvest to the pretreatment reactor throat, including grower payment) for hydrocarbon fuel production via biochemical conversion, based on equipment and processes now available or potentially available in the near term. The modeled cost also considers both the required quality and the availability of the biomass resources. The 2018 Herbaceous SOT predicts a modeled delivered feedstock cost of $83.67/dry ton (2016$); this is a $0.23/dry ton (2016$) decrease from the 2017 Herbaceous SOT. The modification of biorefinery’s designed capacity and increased projected biomass availability in the same supply shed contributed to this modeled cost reduction. The least-cost formulation model to optimally site and scale local distributed preprocessing depots also contributed to the cost reduction by considering county-level grower payment and distance from the biorefinery as variables in the optimization algorithm. Sensitivity analysis on various process parameters that affect delivered feedstock cost in the 2018 Herbaceous SOT shows that the delivered cost could varies from $80.45-$88.83/dry ton. The top factors that causes such variations are: effective baling rate, bale density, hammer mill throughput, interest rate and storage dry matter loss.

09 BIOMASS FUELS↗
DOE OSTI2026

Effect of Mo precursors in Microwave-assisted Methane Dehydroaromatization over Mo/HZSM5 catalysts

Natural gas flaring occurs in remote shale regions due to limited pipeline takeaway capacity. The conversion of the associated natural gas into aromatics in modular microwave reactors is a viable alternative to monetize the wasted gas. Microwaves offer rapid, selective heating in compact reactor systems that can enable on-demand chemical production at the well-site. Mo-HZSM-5 catalysts are widely used for aromatic production, but the location and nature of the active sites are still under debate. This study focuses on the use of 6 different Mo precursors to elucidate insights into the Mo properties that are desirable for BTX production. The catalysts were characterized by different methods (XPS, TPR, Raman, etc) to determine differences in Mo catalytic properties that may affect performance and understand these differences through performance testing under microwave at 700C for methane dehydroaromatization. Metal precursors that enable a better distribution of Mo into the pores and over the surface lead to improved benzene yield, whereas those that limited Mo to primarily the surface suffer rapid deactivation and low benzene yields. Additionally, strong Lewis acidity that arises from the sodium containing precursor drastically shifts the product selectivity towards dehydrogenation, which produces more ethylene and carbon. This catalyst had the highest deactivation constant of all catalysts tested.

gas flaring reduction↗
DOE OSTI2024

The Near-Gapless Penicillium fuscoglaucum Genome Enables the Discovery of Lifestyle Features as an Emerging Post-Harvest Phytopathogen

Penicillium spp. occupy many diverse biological niches that include plant pathogens, opportunistic human pathogens, saprophytes, indoor air contaminants, and those selected specifically for industrial applications to produce secondary metabolites and lifesaving antibiotics. Recent phylogenetic studies have established Penicillium fuscoglaucum as a synonym for Penicillium commune, which is an indoor air contaminant and toxin producer and can infect apple fruit during storage. During routine culturing on selective media in the lab, we obtained an isolate of P. fuscoglaucum Pf_T2 and sequenced its genome. The Pf_T2 genome is far superior to available genomic resources for the species. Our assembly exhibits a length of 35.1 Mb, a BUSCO score of 97.9% complete, and consists of five scaffolds/contigs representing the four expected chromosomes. It was determined that the Pf_T2 genome was colinear with a type specimen P. fuscoglaucum and contained a lineage-specific, intact cyclopiazonic acid (CPA) gene cluster. For comparison, a highly virulent postharvest apple pathogen, P. expansum strain TDL 12.1, was included and showed a similar growth pattern in culture to our Pf_T2 isolate but was far more aggressive in apple fruit than P. fuscoglaucum. The genome of Pf_T2 serves as a major improvement over existing resources, has superior annotation, and can inform forthcoming omics-based work and functional genetic studies to probe secondary metabolite production and disparities in aggressiveness during apple fruit decay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Thresholding Analysis and Feature Extraction from 3D Ground Penetrating Radar Data for Noninvasive Assessment of Peanut Yield

This study explores the efficacy of utilizing a novel ground penetrating radar (GPR) acquisition platform and data analysis methods to quantify peanut yield for breeding selection, agronomic research, and producer management and harvest applications. Sixty plots comprising different peanut market types were scanned with a multichannel, air-launched GPR antenna. Image thresholding analysis was performed on 3D GPR data from four of the channels to extract features that were correlated to peanut yield with the objective of developing a noninvasive high-throughput peanut phenotyping and yield-monitoring methodology. Plot-level GPR data were summarized using mean, standard deviation, sum, and the number of nonzero values (counts) below or above different percentile threshold values. Best results were obtained for data below the percentile threshold for mean, standard deviation and sum. Data both below and above the percentile threshold generated good correlations for count. Correlating individual GPR features to yield generated correlations of up to 39% explained variability, while combining GPR features in multiple linear regression models generated up to 51% explained variability. The correlations increased when regression models were developed separately for each peanut type. This research demonstrates that a systematic search of thresholding range, analysis window size, and data summary statistics is necessary for successful application of this type of analysis. The results also establish that thresholding analysis of GPR data is an appropriate methodology for noninvasive assessment of peanut yield, which could be further developed for high-throughput phenotyping and yield-monitoring, adding a new sensor and new capabilities to the growing set of digital agriculture technologies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Energy Efficient, Incrementally Scalable, Continuous Basalt Fiber Manufacturing Process (Final Technical Report)

This project focused on new materials, bushing materials, that had the ability to produce continuous basalt or glass fiber. The original scope of the project was designed to identify bushing materials and produce fiber, but that scope did change during the program. The team put significant work into bushing material development in the place of producing fiber. The final bushing materials had to be able to produce fiber and the final sets of the project saw single strands of fiber be produced. The final materials selected was a unique MMC bushing composition. Using advanced chemistry, the interface chemistry was tailored between metallic and ceramic powders. Powders and fibers were consolidated using cold isostatic pressing and electrified ceramic hot pressing to form a near net shape composite bushing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Mineral Recovery Enhanced Desalination (MRED) process: An innovative technology for desalinating hard brackish water

Desalination of water containing high concentrations of calcium, dissolved carbon dioxide, sulfate, silica and other sparingly soluble salts is difficult because of the scaling potential. An innovative pre-treatment scheme was investigated at bench scale that selectively removes these constituents and produces a soft water to enable desalination with high feed water recovery. The process first removes dissolved carbon dioxide by air stripping at low pH. Magnesium is removed by precipitation at high pH. Calcium is removed by ion exchange (IX), and sulfate is removed by nanofiltration (NF). Cation regenerant from IX, containing calcium, and concentrate from NF, containing sulfate, is combined to precipitate gypsum. Concentrate from the desalination process consisting of a concentrated NaCl solution is used to regenerate the IX resins. The selective precipitation, IX, and NF processes were tested in laboratory experiments and produced magnesium hydroxide and gypsum at greater than 90% and 95% purity respectively. A process model was developed to calculate process performance, mass and liquid flow rates. Finally, the MRED process offers the following benefits: 1) greater recovery of brackish feedwater by a desalination process, 2) recovery of marketable commodities and 3) reduction in the volume and mass of waste products from the treatment process.

42 ENGINEERING↗
DOE OSTI2023

C−N Coupling through Hydroaminoalkylation on a Single‐Atom Rh Heterogeneous Catalyst

Abstract C−N coupling is significant for the synthesis of fine chemicals toward various applications. Hydroaminoalkylation of olefins is a tandem reaction of C−N coupling involving first the formation of an aldehyde through hydroformylation of an olefin and then the production of amine through reductive amination of the aldehyde. Here we report a stable, supported catalyst of singly dispersed Rh 1 atoms anchored on TiO 2 (P25) nanoparticles designated as Rh 1 /P25. Its high activity for C−N coupling was demonstrated by six hydroaminoalkylations of olefins and amines with selectivity of higher than 90% for producing tertiary amines. The singly dispersed Rh 1 O 4 on P25 exhibit activity and selectivity for hydroaminoalkylation comparable or even higher than some reported molecular catalysts. In contrast to molecular catalysts, the Rh‐based single‐atom Rh heterogeneous catalysis (Rh 1 /P25) can be readily separated from reactants and products, reused for multiple runs of hydroaminoalkylation, and recycled with a low cost.

Li, Yuting↗
DOE OSTI2020

FieLDS

Field Landscape Decision Support (FieLDS) is a decision support tool that assists agricultural producers and farm managers in selecting parts of the field that can be converted to bioenergy plants, like perennial grasses, from the conventional use, like corn or soybean growth. That conversion of parts of the field is done based on the specific landscape properties and the agricultural producer’s priorities. The decision support tool generates a map of the field layout and spatially marks where to place each plant based on the spatial input from the user. Also, the user selects which priorities (sustainability indicators) are most relevant to them in their decision-making. By allowing the user to set the weights among the priorities, the tool empowers the user to generate field designs specific to their needs instead of imposing the developer’s set of priorities, and increases the transparency of the decision process.

Vazhnik, Veronika↗
DOE OSTI2023

C–N Coupling through Hydroaminoalkylation on a Single–Atom Rh Heterogeneous Catalyst

C–N coupling is significant for the synthesis of fine chemicals toward various applications. Hydroaminoalkylation of olefins is a tandem reaction of C–N coupling involving first the formation of an aldehyde through hydroformylation of an olefin and then the production of amine through reductive amination of the aldehyde. Here we report a stable, supported catalyst of singly dispersed Rh 1 atoms anchored on TiO 2 (P25) nanoparticles designated as Rh 1 /P25. Its high activity for C–N coupling was demonstrated by six hydroaminoalkylations of olefins and amines with selectivity of higher than 90% for producing tertiary amines. Furthermore, the singly dispersed Rh 1 O 4 on P25 exhibit activity and selectivity for hydroaminoalkylation comparable or even higher than some reported molecular catalysts. In contrast to molecular catalysts, the Rh-based single-atom Rh heterogeneous catalysis (Rh 1 /P25) can be readily separated from reactants and products, reused for multiple runs of hydroaminoalkylation, and recycled with a low cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗