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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Low-Cost, High-Performance Carbon Fiber for Compressed Natural Gas Storage Tanks (Final Technical Report – Down Select Report)

The aim of this project is to reduce the cost of Type IV, carbon fiber (CF) composite overwrap compressed gas storage tanks by reducing the cost of CF and CF composites. The project team worked to reduce the cost of CF by exploring and testing opportunities for a low-cost alternative precursor material for CF production to supplant market-dominant and costly polyacrylonitrile (PAN). Concurrently, the team aimed to reduce the cost of the tanks at the composite level by improving the interfacial adhesion between the fibers and the matrix resin through the incorporation of low-cost nanoparticles recycled from waste materials, which would reduce the volume of costly CF required to achieve the same tank performance. At the end of the first year, the project team selected mesophase pitch as the primary precursor candidate from a field of materials based on the superior mechanical performance and cost-saving potential. During the second year, the team produced CFs derived from mesophase pitch achieving an average tensile strength of 365.6 ksi and average tensile modulus of 40.74 Msi. Facility availability for spinning and converting these fibers at greater scale has hindered scale-up demonstration, but the team has identified opportunities to conduct this work in the near term. Cost modeling shows that these mesophase pitch-derived CFs can be up to 40% less expensive than PAN-derived CFs due to the lower cost of the feedstock material, higher throughput, greater conversion yield, and lower cost spinning method and compared to PAN. Additionally, the team has demonstrated at lab-scale that nanoparticle coating CFs can significantly increase the interfacial shear strength and load transfer efficiency of CFs in a matrix. Single filament pull-out testing showed a 27% average increase in max interfacial shear strength due to this coating. A continuous method of applying these coatings to a tow of CF has been developed for scale-up. 26 m tows of coated CFs were produced using this system and formed into composite ring samples for ASTM ring burst testing. Issues with the testing protocol have limited assessment of these results. A prototype Type IV tank was designed to meet ANSI HGV2 standards, and the design criteria set out by DOE, using the CF properties developed by the team paired with a proprietary resin matrix, a polyamide liner, and aluminum end bosses. The tank weighs 153.1 kg and with a total capacity of 5.8 kg H2 (5.6 kg usable), which yields a gravimetric capacity of 1.17 kWh/kg. Cost modeling predicts that the tank will have a projected cost of $15.73/kWh. Tank performance modeling does not include considerations for fiber-matrix load transfer efficiency improvements offered by nanoparticle coating method.

08 HYDROGEN↗
DOE OSTI2023

Reliability of double probe measurements in nanodusty plasmas

Abstract Nonthermal plasmas are attractive sources for nanoparticles synthesis, however, their plasma properties are notoriously difficult to assess due to the chemically reactive environment and high nanoparticle concentrations. Here, we are using a floating double probe to measure the plasma properties of a nanoparticle-forming argon:silane plasma. We demonstrate good stability of current–voltage characteristics over several minutes of operation. However, unexpectedly larger electron temperatures are measured with increasing the silane mole fraction. To test the validity of these results, we developed a zero-dimensional global model to investigate the effect of the presence of nanoparticles on the plasma properties. Using this model, we show that increasing particle concentration leads to an increasing electronegativity of the plasma, causing an increase of the reduced electric field. However, this causes only a moderate increase in mean electron energy, in contrast to the much larger increase measured by the double probe. We argue that these large electron temperatures are based on the fact that a double probe measures an ‘apparent’ electron temperature, which is defined by the negative inverse slope of the logarithm of the electron energy probability function (EEPF) at an energy corresponding to the probe’s floating potential. As the silane mole fraction is increased, the plasma becomes more electronegative and the probe’s floating potential moves closer to the plasma potential. Combined with the strong non-Maxwellian EEPF, this leads to the large apparent electron temperatures obtained by the probe. Thus, the apparent electron temperatures measured with the double probe do not follow the trends in mean electron energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Experimental Measurement of Out-of-Time-Ordered Correlators at Finite Temperature

Out-of-time-ordered correlators (OTOCs) are a key observable in a wide range of interconnected fields including many-body physics, quantum information science, and quantum gravity. Measuring OTOCs using near-term quantum simulators will extend our ability to explore fundamental aspects of these fields and the subtle connections between them. Here, we demonstrate an experimental method to measure OTOCs at finite temperatures and use the method to study their temperature dependence. These measurements are performed on a digital quantum computer running a simulation of the transverse field Ising model. Our flexible method, based on the creation of a thermofield double state, can be extended to other models and enables us to probe the OTOC’s temperature-dependent decay rate. Measuring this decay rate opens up the possibility of testing the fundamental temperature-dependent bounds on quantum information scrambling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

In-field bioreactors demonstrate dynamic shifts in microbial communities in response to geochemical perturbations

Subsurface microbial communities mediate the transformation and fate of redox sensitive materials including organic matter, metals and radionuclides. Few studies have explored how changing geochemical conditions influence the composition of groundwater microbial communities over time. We temporally monitored alterations in abiotic forces on microbial community structure using 1L in-field bioreactors receiving background and contaminated groundwater at the Oak Ridge Reservation, TN. Planktonic and biofilm microbial communities were initialized with background water for 4 days to establish communities in triplicate control reactors and triplicate test reactors and then fed filtered water for 14 days. On day 18, three reactors were switched to receive filtered groundwater from a contaminated well, enriched in total dissolved solids relative to the background site, particularly chloride, nitrate, uranium, and sulfate. Biological and geochemical data were collected throughout the experiment, including planktonic and biofilm DNA for 16S rRNA amplicon sequencing, cell counts, total protein, anions, cations, trace metals, organic acids, bicarbonate, pH, Eh, DO, and conductivity. We observed significant shifts in both planktonic and biofilm microbial communities receiving contaminated water. This included a loss of rare taxa, especially amongst members of the Bacteroidetes, Acidobacteria, Chloroflexi, and Betaproteobacteria, but enrichment in the Fe- and nitrate- reducing Ferribacterium and parasitic Bdellovibrio. These shifted communities were more similar to the contaminated well community, suggesting that geochemical forces substantially influence microbial community diversity and structure. These influences can only be captured through such comprehensive temporal studies, which also enable more robust and accurate predictive models to be developed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Testing of PIP-II pre-production 650 MHz couplers in warm test stand and in cryomodule

650 MHz fundamental power couplers were developed for PIP-II project to deliver RF power for low-beta and high-beta elliptical cavities. Few prototypes were built and tested and after some modification we built 8 pre-production couplers (with few spares for vacuum side) for HB650 cryomodule. All couplers were successfully tested in pulse mode (up to 100kW) and in CW mode (up to 50kW) in test stand at full reflection at 8 phases. In baseline configuration with DC bias we do not see any multipactoring activity after short processing. We also tested power processing without bias for uncoated and TiN coated ceramic window. Results of these studies presented in this paper. One of the coupler was assembled on LB650 cavity and tested at cryogenic environment in STC cryostat at ~20kW power with full reflection at different reflection phase. We also demonstrated good result from power processing without bias for warm and cold cavity. Six couplers were assembled on HB650 cavities in pre-production cryomodule. Test results from cryomodule qualification is discussing in this paper.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Next Generation Solid Oxide Fuel Cell Module Development

The overall objective of this project was to develop a transformative Solid Oxide Fuel Cell (SOFC) building block configuration comprised of multi-stack arrays that can be utilized in large-scale power plants. This transformative design signified the benefits of lower performance degradation coupled with improved reliability, low cost, smaller packaging for easier transport and installation, and improved maintenance and field serviceability characteristics. The project goal was to design and fabricate a scalable hot module for housing an array of SOFC stacks and to demonstrate the characteristics of the module gas distribution, insulation and instrumentation, and DC power take-off. The approach was to validate the design of a stack prototype scalable to megawatt (MW) class systems using FuelCell Energy’s Compact SOFC Architecture (CSA) stacks. The scope of work was intended to design, build, and test a compact and low-cost multi-stack sub-module with flexibility to house CSA stacks and scalable to 350 kW which could ultimately be deployed in construction of MW-class systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Integration and Demonstration of Monitoring, Modeling, and Prediction of DV-1 Amendment Performance at the Bench Scale: DV-1 Amendment Demonstration

During fiscal years 2024 and 2025, the U.S. Department of Energy’s Hanford Field Office commissioned Pacific Northwest National Laboratory to conduct applied research aimed at reducing the cost, time, and uncertainty associated with in situ treatment of vadose zone contaminants at the Hanford Site. This report outlines the integration of three key research efforts into a meso-scale demonstration designed to advance field-scale solutions that aim to (1) optimize the delivery of chemical amendments to contaminated soils, (2) reduce uncertainty in amendment delivery performance assessment using advanced monitoring techniques, and (3) provide real-time insights into when and where amendment-induced precipitation reactions occur in the subsurface. To achieve these objectives, the tank-scale (~ 1 cubic meter) Geophysical Imaging of Flow and Transport (GIFT) system was developed. GIFT enables experimental testing of amendment delivery while incorporating automated multi-modal monitoring approaches, including pressure measurements, direct fluid sampling, and remote time-lapse geophysical imaging. The data generated from these monitoring techniques will serve as inputs for a generative artificial-intelligence-driven digital twin – a numerical simulation model designed to honor observed data while quantifying uncertainty in simulation accuracy. Using this simulator, researchers will refine an amendment injection strategy to maximize delivery efficiency within a low-permeability soil zone. Monitoring data will be interpreted through simulated outputs to enhance understanding of the injection process. The efficacy of this integrated approach will be evaluated through direct sampling at the conclusion of the experiment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A Compound Poisson Generator Approach to Point-source Inference in Astrophysics

Abstract The identification and description of point sources is one of the oldest problems in astronomy, yet even today the correct statistical treatment for point sources remains one of the field’s hardest problems. For dim or crowded sources, likelihood-based inference methods are required to estimate the uncertainty on the characteristics of the source population. In this work, a new parametric likelihood is constructed for this problem using compound Poisson generator (CPG) functionals that incorporate instrumental effects from first principles. We demonstrate that the CPG approach exhibits a number of advantages over non-Poissonian template fitting (NPTF)—an existing method—in a series of test scenarios in the context of X-ray astronomy. These demonstrations show that the effect of the point-spread function, effective area, and choice of point-source spatial distribution cannot, generally, be factorized as they are in NPTF, while the new CPG construction is validated in these scenarios. Separately, an examination of the diffuse-flux emission limit is used to show that most simple choices of priors on the standard parameterization of the population model can result in unexpected biases: when a model comprising both a point-source population and diffuse component is applied to this limit, nearly all observed flux will be assigned to either the population or to the diffuse component. A new parameterization is presented for these priors that properly estimates the uncertainties in this limit. In this choice of priors, CPG correctly identifies that the fraction of flux assigned to the population model cannot be constrained by the data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Quantifying Species Populations in Multivalent Borohydride Electrolytes

Multivalent batteries represent an important beyond Li-ion energy storage concept. The prospect of calcium batteries, in particular, has emerged recently due to novel electrolyte demonstrations, especially that of a ground-breaking combination of the borohydride salt Ca(BH 4 ) 2 dissolved in tetrahydrofuran. Recent analysis of magnesium and calcium versions of this electrolyte led to the identification of divergent speciation pathways for Mg 2+ and Ca 2+ despite identical anions and solvents, owing to differences in cation size and attendant flexibility of coordination. To test these proposed speciation equilibria and develop a more quantitative understanding thereof, we have applied pulsed-field-gradient nuclear magnetic resonance and dielectric relaxation spectroscopy to study these electrolytes. Additionally, concentration-dependent variation in anion diffusivities and solution dipole relaxations, interpreted with the aid of molecular dynamics simulations, confirms these divergent Mg 2+ and Ca 2+ speciation pathways. These results provide a more quantitative description of the electroactive species populations. We find that these species are present in relatively small quantities, even in the highly active Ca(BH 4 ) 2 /tetrahydrofuran electrolyte. This finding helps interpret previous characterizations of metal deposition efficiency and morphology control and thus provides important fundamental insight into the dynamic properties of multivalent electrolytes for next-generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Benchmarking Optimizers for Qumode State Preparation with Variational Quantum Algorithms

Quantum state preparation involves preparing a target state from an initial system, a process integral to applications such as quantum machine learning and solving systems of linear equations. Recently, there has been a growing interest in qumodes due to advancements in the field and their potential applications. However there is a notable gap in the literature specifically addressing this area. This paper aims to bridge this gap by providing performance benchmarks of various optimizers used in state preparation with Variational Quantum Algorithms. We conducted extensive testing across multiple scenarios, including different target states, both ideal and sampling simulations, and varying numbers of basis gate layers. Our evaluations offer insights into the complexity of learning each type of target state and demonstrate that some optimizers perform better than others in this context. Notably, the Powell optimizer was found to be exceptionally robust against sampling errors, making it a preferred choice in scenarios prone to such inaccuracies. Additionally, the Simultaneous Perturbation Stochastic Approximation optimizer was distinguished for its efficiency and ability to handle increased parameter dimensionality effectively.

Kan, Shuwen [Fordham University]↗
DOE OSTI2023

Commissioning of a two-target DC cylindrical magnetron sputter coater for depositing Nb 3 Sn film on Nb superconducting radiofrequency cavities

A DC cylindrical magnetron sputter coater was commissioned and used to coat Nb 2.6 GHz superconducting radiofrequency (SRF) cavity with Nb 3 Sn. The sputter coater has two identical cylindrical magnetrons that can move, with a controlled speed, along the axis of the SRF cavity to coat the inside surface of the cavity. The design of the sputter coater is discussed, along with its performance. Initially, a sample holder that allows coating on flat substrates at positions similar to the equator and beam tubes of a 2.6 GHz SRF cavity was used to test conditions for fabricating Nb 3 Sn layers. Multilayers of Nb and Sn were sequentially sputtered on flat Nb and sapphire substrates mounted on the equivalent positions of the cavity's beam tubes and the equator using the two identical cylindrical magnetrons. Then, the Nb/Sn multilayers were annealed at 950 °C for 3 h. Here, the ~1.2 μm thick Nb 3 Sn film did not show any other Nb–Sn compounds and had a superconducting transition temperature of 17.61–17.76 K. The 2.6 GHz SRF cavity was coated using similar conditions as flat samples. Cryogenic RF testing of the Nb 3 Sn-coated cavity demonstrated a quality factor of 3.2 × 10 8 at an accelerating gradient of 5 MV/m at 4.4 K.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Exploring Primordial Black Holes from the Multiverse with Optical Telescopes

Primordial black holes (PBHs) are a viable candidate for dark matter if the PBH masses are in the currently unconstrained “sublunar” mass range. We revisit the possibility that PBHs were produced by nucleation of false vacuum bubbles during inflation. We show that this scenario can produce a population of PBHs that simultaneously accounts for all dark matter, explains the candidate event in the Subaru Hyper Suprime-Cam (HSC) data, and contains both heavy black holes as observed by LIGO and very heavy seeds of supermassive black holes. Here, we demonstrate with numerical studies that future observations of HSC, as well as other optical surveys, such as LSST, will be able to provide a definitive test for this generic PBH formation mechanism if it is the dominant source of dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗
DOE OSTI2022

Assessing rodents as carriers of pathogenic Leptospira species in the U.S. Virgin Islands and their risk to animal and public health

Leptospirosis is a global zoonotic disease caused by pathogenic bacteria of the genus Leptospira. We sought to determine if rodents in U.S. Virgin Islands (USVI) are carriers of Leptospira. In total, 140 rodents were sampled, including 112 Mus musculus and 28 Rattus rattus. A positive carrier status was identified for 64/140 (45.7%); 49 (35.0%) were positive by dark-field microscopy, 60 (42.9%) by culture, 63 (45.0%) by fluorescent antibody testing, and 61 (43.6%) by real-time polymerase chain reaction (rtPCR). Molecular typing indicated that 48 isolates were L. borgpetersenii and 3 were L. kirschneri; the remaining nine comprised mixed species. In the single culture-negative sample that was rtPCR positive, genotyping directly from the kidney identified L. interrogans. Serotyping of L. borgpetersenii isolates identified serogroup Ballum and L. kirschneri isolates as serogroup Icterohaemorrhagiae. These results demonstrate that rodents are significant Leptospira carriers and adds to understanding the ecoepidemiology of leptospirosis in USVI.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Optimal reference genes for RNA tissue analysis in small animal models of hemorrhagic fever viruses

Abstract Reverse-transcription quantitative polymerase chain reaction assays are frequently used to evaluate gene expression in animal model studies. Data analyses depend on normalization using a suitable reference gene (RG) to minimize effects of variation due to sample collection, sample processing, or experimental set-up. Here, we investigated the suitability of nine potential RGs in laboratory animals commonly used to study viral hemorrhagic fever infection. Using tissues (liver, spleen, gonad [ovary or testis], kidney, heart, lung, eye, brain, and blood) collected from naïve animals and those infected with Crimean–Congo hemorrhagic fever (mice), Nipah (hamsters), or Lassa (guinea pigs) viruses, optimal species-specific RGs were identified based on five web-based algorithms to assess RG stability. Notably, the Ppia RG demonstrated stability across all rodent tissues tested. Optimal RG pairs that include Ppia were determined for each rodent species ( Ppia and Gusb for mice; Ppia and Hrpt for hamsters; and Ppia and Gapdh for guinea pigs). These RG pair assays were multiplexed with viral targets to improve assay turnaround time and economize sample usage. Finally, a pan-rodent Ppia assay capable of detecting Ppia across multiple rodent species was developed and successfully used in ecological investigations of field-caught rodents, further supporting its pan-species utility.

Davies, Katherine A.↗