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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Working With Your Utility Series: Interconnection Basics

This training provided information on interconnection basics for federal agencies developing distributed energy projects. Considerations covered included: Understanding interconnection processes and timelines, interconnection siting considerations, technology-specific interconnection issues, and interconnect agreements. This webinar is the first in a multi-part series on working with electric utilities to develop distributed energy projects on federal sites.

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

2.3.4.100 - Lignin Utilization

Lignin depolymerization to aromatic monomers is a primary route for myriad lignin valorization strategies. To date, there are many strategies able to cleave aryl-ether linkages in lignin, but the lignin polymer, in both its native and processed forms, contains a substantial fraction of refractory carbon-carbon linkages between aromatic units, which typically limits aromatic monomer yields to -30-40 wt% or lower, depending on the feedstock. To that end, the Lignin Utilization (LigU) project addresses the critical challenge of lignin depolymerization catalysis with emphasis on C-C bond cleavage. Being able to achieve cost-effective C-C bond catalysis in lignin depolymerization would enable a substantial increase in accessible aromatic monomer yields from lignin. Among the catalysis strategies that have been investigated in the LigU project, we have made substantial progress in the use of autoxidation catalysis, inspired by the industrial conversion of p-xylene to terephthalic acid, for C-C bond cleavage in lignin. Using multiple substrates, we have demonstrated that autoxidation catalysis can produce mixtures of bio-available aromatic monomers for conversion to exemplary bioproducts, such as cis,cis-muconic acid, in collaboration with the Biological Lignin Valorization project. Prior to FY23, the LigU project also included lignin analytical chemistry method development, lignin analytics for BETO-funded projects, and model compound syntheses, which will also be presented.

BIOMASS FUELS↗
DOE OSTI2026

State-Tribal Collaboration: Utility Programs

This is one of 6 fact sheets for the State/Tribal Collaboration project for Office of Policy. This fact sheets discusses low-income utility programs that can benefit Tribes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

High-Entropy Metal-Organic Frameworks (HEMOFs): A New Frontier in Materials Design for CO 2 Utilization

High-entropy materials (HEMs) emerged as promising candidates for a diverse array of chemical transformations, including CO 2 utilization. However, traditional HEMs catalysts are nonporous, limiting their activity to surface sites. Designing HEMs with intrinsic porosity can open the door toward enhanced reactivity while maintaining the many benefits of high configurational entropy. Here, in this study, a synergistic experimental, analytical, and theoretical approach to design the first high-entropy metal-organic frameworks (HEMOFs) derived from polynuclear metal clusters is implemented, a novel class of porous HEMs that is highly active for CO 2 fixation under mild conditions and short reaction times, outperforming existing heterogeneous catalysts. HEMOFs with up to 15 distinct metals are synthesized (the highest number of metals ever incorporated into a single MOF) and, for the first time, homogenous metal mixing within individual clusters is directly observed via high-resolution scanning transmission electron microscopy. Importantly, density functional theory studies provide unprecedented insight into the electronic structures of HEMOFs, demonstrating that the density of states in heterometallic clusters is highly sensitive to metal composition. This work dramatically advances HEMOF materials design, paving the way for further exploration of HEMs and offers new avenues for the development of multifunctional materials with tailored properties for a wide range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phase‐Change‐Memory Process at the Limit: A Proposal for Utilizing Monolayer Sb 2 Te 3

Abstract One central task of developing nonvolatile phase change memory (PCM) is to improve its scalability for high‐density data integration. In this work, by first‐principles molecular dynamics, to date the thinnest PCM material possible (0.8 nm), namely, a monolayer Sb 2 Te 3 , is proposed. Importantly, its SET (crystallization) process is a fast one‐step transition from amorphous to hexagonal phase without the usual intermediate cubic phase. An increased spatial localization of electrons due to geometrical confinement is found to be beneficial for keeping the data nonvolatile in the amorphous phase at the 2D limit. The substrate and superstrate can be utilized to control the phase change behavior: e.g., with passivated SiO 2 (001) surfaces or hexagonal Boron Nitride, the monolayer Sb 2 Te 3 can reach SET recrystallization in 0.54 ns or even as fast as 0.12 ns, but with unpassivated SiO 2 (001), this would not be possible. Besides, working with small volume PCM materials is also a natural way to lower power consumption. Therefore, the proposed PCM working process at the 2D limit will be an important potential strategy of scaling the current PCM materials for ultrahigh‐density data storage.

2D limit↗
DOE OSTI2025

Floatable Protective Layers: a Strategy to Minimize Solid Electrolyte Interphase Growth and Maximize the Lithium Utilization

Abstract Maximizing lithium (Li) utilization is crucial for enhancing the long‐term stability of Li‐based batteries. In anode‐free Li batteries (AFLBs), although the initial formation of solid electrolyte interphase (SEI) is beneficial on limiting further reaction between Li and electrolyte, large volume change of Li metal anode (LMA) during cycling often leads to continuous breakdown and re‐formation of SEI and formation of inactive Li, hindering its efficiency. In this study, a novel strategy is presented to protect Li metal by applying a floatable protection layer (FPL) on a copper substrate, enabling large Li particles to be primarily deposited below FPL, but SEI to be primarily formed above FPL. This approach effectively minimizes the direct contact between electrolyte and freshly deposited Li, therefore mitigating the continuous side reactions and early failure of AFLBs. As a result, Li consumption is minimized, and the overall stability of the battery is significantly enhanced. Further development of this approach can also be used to improve the performance of other Li‐based batteries for large‐scale applications.

Lim, Hyung‐Seok [Energy and Environment Directorat↗
DOE OSTI2023

Stability of Cu(In x Ga 1− x )Se 2 Solar Cells Utilizing RbF Postdeposition Treatment under a Sulfur Atmosphere

Alkali halide postdeposition treatments (PDTs) have become a key tool to maximize efficiency in Cu(In x Ga 1− x )Se 2 (CIGS) photovoltaics. RbF PDTs have emerged as an alternative to the more common Na‐ and K‐based techniques. This study utilizes temperature‐dependent current–voltage ( JVT ) measurements to study a unique RbF PDT performed in a S atmosphere. The samples are measured before and after 6 months in a desiccator to study device stability. Both samples contain Na and K which diffuse from the soda–lime glass substrate. A reference sample and a RbF + S PDT sample both show the development of a rear contact barrier after aging. The contact barrier is higher for the RbF + S PDT sample, leading to decreased current in forward bias. Series resistance is also higher in the RbF + S PDT device which leads to lower fill factor. However, after aging the reference sample has a larger decrease in open‐circuit voltage ( V OC ). Ideality factor measurements suggest Shockley–Read–Hall recombination dominates both samples. V OC versus temperature and a temperature‐dependent activation energy model are used to calculate diode activation energies for each sample condition. Both techniques produce similar values that indicate recombination primarily occurs within the bulk absorber.

14 SOLAR ENERGY↗
DOE OSTI2026

All You Can Eat Yeast: Substituting Hexose Transporters With AtSWEET7 Alleviates Glucose Repression, Enabling Simultaneous Utilization of Sugars in Renewable Feedstocks

Yeast sugar transporters have highly evolved for preferential glucose transport, a significant roadblock for utilizing non-glucose sugars in renewable feedstocks such as lignocellulosic biomass. To enable simultaneous transport of multiple sugars, native hexose transporters were replaced by SWEET7p from Arabidopsis thaliana in engineered Saccharomyces cerevisiae capable of fermenting xylose. Engineered S. cerevisiae exhibited reduced glucose preference, simultaneously co-fermenting glucose, mannose, fructose, and xylose both in synthetic and industrial media. Continuous culture experiments demonstrated the co-consuming phenotype and alleviation of glucose repression by engineered S. cerevisiae. In addition to hexose and pentose, the NKSW7-1 strain consumed xylitol as a carbon source. Through transcriptomic and metabolomic analysis of the NKSW7-1 strain, we show that the replacement of HXT1-7 with AtSWEET7 led to systemwide reprogramming of the central carbon metabolism. This broad transport capacity of AtSWEET7p holds promise for achieving co-consumption of all sugars in underutilized renewable feedstocks by microbial cell factory.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarks

Abstract Machine learning (ML) continues to grow in importance across nearly all domains in modeling to learn from data. Often a tradeoff exists between a model's ability to minimize bias and variance. In this article, we utilize ensemble learning to combine linear, nonlinear, and tree‐/rule‐based ML methods to cope with the bias‐variance tradeoff and result in more accurate models. We use the datasets collected for two parallel cancer deep learning CANDLE benchmarks, NT3 and P1B2, to build performance and power models based on hardware performance counters using single‐object and multiple‐objects ensemble learning to identify the most important counters for improvement on the Cray XC40 Theta at Argonne National Laboratory. Based on the insights from these models, we improve the performance and energy of P1B2 and NT3 by optimizing the deep learning environments TensorFlow, Keras, Horovod, and Python under the huge page size of 8 MB. Experimental results show that ensemble learning not only produces more accurate models but also provides more robust performance counter ranking. We achieve up to 61.15% performance improvement and up to 62.58% energy saving for P1B2 and up to 55.81% performance improvement and up to 52.60% energy saving for NT3 on up to 24,576 cores.

Wu, Xingfu↗
DOE OSTI2022

Utility of anthesis–silking interval information to predict grain yield under water and nitrogen limited conditions

Delayed silking relative to pollen shed, measured as the anthesis–silking interval (ASI, the period between pollen shed and silking), is a good indicator of response to abiotic stresses in maize ( Zea mays L.). This research was conducted to investigate how ASI is affected by nitrogen (N) and water availability and to assess the utility of ASI to indirectly predict grain yield (GY) under contrasting water and N treatments. Two experiments were conducted in Hancock, WI, in 2018 and 2019. One experiment (Diverse hybrids) included 302 hybrids resulting from the cross of diverse inbred lines by a single tester evaluated at four different treatment levels resulting from combining nonlimited and low N with nonlimited and low water treatments. The second experiment (NSS FAC) included a set of 408 hybrids derived from the cross of biparental doubled-haploid lines from 13 factorial populations and evaluated under nonlimited and low N treatments. Anthesis and silk time in growing degree days, and GY (Mg ha -1 ) were measured. Genomic prediction was assessed using a genomic best linear unbiased prediction model, and predictive ability was calculated as the correlation between genomic predictions and adjusted means in the different treatments. Predictive ability ranged from .15 to .49 for NSS FAC and from .06 to .51 for Diverse hybrids across traits and treatments. The ASI was a good indicator of stress and showed higher heritability than GY in the limited treatments for both experiments; however, it did not improve yield predictability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Molten‐Salt‐Mediated Chemical Looping Oxidative Dehydrogenation of Ethane with In‐Situ Carbon Capture and Utilization

Abstract The molten‐salt‐mediated oxidative dehydrogenation (MM‐ODH) of ethane (C 2 H 6 ) via a chemical looping scheme represents an effective carbon capture and utilization (CCU) method for the valorization of ethane‐rich shale gas and concurrent mitigation of carbon dioxide (CO 2 ) emissions. Here, stepwise experimentation with Li 2 CO 3 ‐Na 2 CO 3 ‐K 2 CO 3 (LNK) ternary salts (i) assessed how each component of the LNK mixture impacted ethane MM‐ODH performance and (ii) explored physicochemical and thermodynamic mechanisms behind melt‐induced changes to ethylene (C 2 H 4 ) and carbon monoxide (CO) yields. Of fifteen screened LNK compositions, nine exhibited ethylene yields greater than 50 % at 800 °C while maintaining C 2 H 4 selectivities of 85 % or higher. LNK salts rich in Li 2 CO 3 content yielded more ethylene and CO on average than their counterparts, and net CO 2 capture per cycle reached a maximum of ~75 %. Extended MM‐ODH cycling also demonstrated long‐term stability of a high‐performing LNK medium. Density functional theory (DFT) calculations andab initiomolecular dynamics (AIMD) simulations suggested that the molten salt does not directly activate C 2 H 6 . Meanwhile, an empirical model informed by experimental data and reaction thermodynamics adequately predicted overall MM‐ODH performance from LNK composition and provided insights into the system′s primary drivers.

Chemistry↗
DOE OSTI2021

The fate of carbon utilized by the subterranean termite Reticulitermes flavipes

Abstract Subterranean termites are ecosystem engineers that modulate the flow of carbon from dead wood to the atmosphere and soil, yet their contributions to the latter pool are largely unaccounted for in carbon cycling models. The fate of C from wood utilized by Reticulitermes flavipes (Kollar) was determined using a reductionist design in a closed system with δ 13 C labeled wood as a stable isotope tracer. The percentage of wood‐based carbon in termite respiratory gases, tissues, and organic deposits (frass and construction materials) was measured for five colonies to budget wood‐C mass distributed into metabolic and behavioral pathways during a 160‐h incubation period. We found that termites emitted 42% of the C from wood as gas (largely as carbon dioxide), returned 40% to the environment as organic deposits (frass and construction materials), and retained 18% in their tissues (whole alimentary tracts and de‐gutted bodies). Our findings affirm that termites are a source of greenhouse gases but are also ecosystem engineers that return approximately half the C from dead wood as organic deposits into their surrounding environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Carbon capture, utilization, and storage hub development on the Gulf Coast

Abstract The Gulf Coast of the United States hosts diverse power generation, refining, and petrochemical processing facilities, resulting in the nation's largest volumetric concentration of industrial CO 2 emissions, rivaled only by the Ohio River Valley. These emissions sources are concentrated in specific industrial clusters that allow combining emissions streams to achieve economies of scale. The region is currently undergoing globally significant industrial expansion and investment as a result of abundant and inexpensive regional unconventional natural gas availability, and is a growing exporter of liquefied natural gas (LNG). Opportunities to integrate CO 2 emission management within the diverse energy chains in the region are volumetrically significant and include both concentrated and dilute sources. Significant examples of capture, transport, and storage exist. Offshore storage is particularly attractive, as it provides simplified land leasing models (single governmental land owner), proven reservoir quality, and presents fewer risks to both protected groundwater and populated areas. Projects can now take advantage of recently expanded opportunities under section 45Q of the Internal Revenue Service tax code. The region continues to evolve as an active carbon‐handling hub, and is uniquely suited to justify additional investment in carbon capture, utilization, and storage (CCUS) technologies via a large‐scale integrated project development. Continued development of integrated projects will allow the region to continue to grow economically within its strong fossil‐fuel handling competence focus while advancing low‐carbon energy technologies that maintain globally competitiveness. © 2021 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

45Q↗
DOE OSTI2025

Predictive links between microbial communities and biological oxygen utilization in the Arctic Ocean

Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.

Chamberlain, Emelia J. [Univ. of San Diego, San Di↗
DOE OSTI2022

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗