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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Downselection and Basic Properties of Additively Manufactured ODS Alloys

In the AMMT program the work package for development of new materials aimed to explore the advanced manufacturing techniques that are feasible for the manufacturing of advanced materials components. A merit-based feasibility study was attempted to identify an accelerated development path for dispersion strengthened (ODS) alloys by creatively combining additive manufacturing (AM) technologies with the recent advances in ODS materials and traditional manufacturing technologies. For the fiscal year, the primary tasks were focused to develop additive manufacturing (AM) and post-build processing route for oxide dispersion strengthened (ODS) ferritic (Fe-Cr alloy or 14YWT) and austenitic (Fe-Cr-Ni alloys or 316L and 316H) alloys and to perform basic microstructural and mechanical characterizations to provide feedbacks to the alloy and processing design. Further, the multi-laboratory effort created collaboratively a decision criteria matrix to evaluate and downselect the new materials processed by advanced manufacturing methods. This report is to describe the ODS alloy processing routes combining AM processes and post-build thermomechanical treatments, mechanical and microstructural characteristics of the newly developed materials, and the application results of the decision criteria matrix for the AM ODS alloys including a downselected material and feasible processing route. Key mechanical test results including tensile strength, tensile ductility, and fracture toughness data and are reported and explained. Higher strength was measured from the ferritic ODS alloys, while higher ductility and fracture toughness were measured from the austenitic ODS alloys. Many of the decision criteria were scored the same for the AM ferritic and austenitic ODS alloys, however, the generally known fact that the austenitic alloys have higher corrosion resistance and significantly better ductility. Although these scores are not significantly different to make them highly discernable, the austenitic ODS alloys were downselected to be the primary materials group in the future research on ODS materials in AMMT program.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Feasibility Studies and Downselection of New Materials and Manufacturing Technologies for Nuclear Applications

This report is intended to present the results of multi-laboratory collaborative studies on the feasibility and downselection of the structural materials that are newly considered for application to future nuclear energy technologies. The Advanced Materials and Manufacturing Techniques (AMMT) program has been implemented to develop cross-cutting technologies in support of a broad range of nuclear reactor technologies and to maintain U.S. leadership in materials and manufacturing technologies for nuclear energy applications. In line with these program objectives, this collaborative studies aim to explore new materials utilizing advanced manufacturing technologies. The FY23 research scope consists of the feasibility studies on new materials and relevant advanced manufacturing technologies, collection of materials properties data and knowledge through experiments and literature survey, and development and application of decision criteria matrix for downselecting candidate materials and manufacturing technologies. The three-laboratory efforts for FY23 have focused on the three new material groups including oxide dispersion strengthened (ODS) materials, refractory composites and alloys, and high entropy alloys (HEAs) investigated, respectively, by Oak Ridge National Laboratory (ORNL) (work package: CT-23OR130406), Los Alamos National Laboratory (LANL) (CT-23LA130403) and Pacific Northwest National Laboratory (PNNL) (CT-23PN130408). The execution of this multi-lab research aimed to provide the AMMT program a merit-based feasibility study identifying an accelerated development path for these materials. A collaborative approach for achieving this goal was to develop a common materials evaluation criteria matrix and apply to all new candidate materials for the evaluation and prioritization of new materials using advanced manufacturing processes. The decision criteria matrix created is a matrix of criteria which a prospective material is scored against. The evaluation criteria are divided into four categories: Application Space, Environmental Compatibility, Physical & Mechanical Properties, and Manufacturability. Materials are given a score from 1−5 for each criterion, with the highest score (5) essentially mean that a material has the most near-term potential for application. Application of the decision criteria matrix will provide guidance to the future research on new materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

THESEUS: A techno-economic design, integration and downselection framework for energy storage

Optimal selection of energy storage technologies is critical to ensure reliable integration of intermittent and often uncertain renewable energy in electricity grids. The consideration of a diverse set of energy storage technologies is required for a more sustainable deployment of energy storage. We present THESEUS (TecHno-Economic framework for Systematic Energy storage Utilization and downSelection), which is a comprehensive framework for the optimal selection, design and operation of energy storage systems. THESEUS includes rigorous models of major energy storage technologies at different maturity levels, such as thermal storage using phase-change materials or molten salt, cryogenic storage, mechanical storage in the form of compressed air and pumped hydro storage, chemical storage using hydrogen, and electrochemical storage in the form of lithium-ion, sodium sulfur and vanadium flow batteries. An illustrative case study on state-wide prospective energy storage shows that storage integration with fossil power plants could reduce the cost of meeting the grid energy demand by 20%, with mechanical storage as the best suited technology. Although high-temperature thermal storage has low storage efficiency, it is optimal for integration with renewable energy plants. In addition, Li-ion batteries are optimal for high ramping but low storage duration requirements. Furthermore, such insights can enable the deployment of both existing and emerging energy storage technologies to facilitate a smooth transition to a clean energy future.

25 ENERGY STORAGE↗
DOE OSTI2023

Similarity Downselection: Finding the n Most Dissimilar Molecular Conformers for Reference-Free Metabolomics

Computational methods for creating in silico libraries of molecular descriptors (e.g., collision cross sections) are becoming increasingly prevalent due to the limited number of authentic reference materials available for traditional library building. These so-called “reference-free metabolomics” methods require sampling sets of molecular conformers in order to produce high accuracy property predictions. Due to the computational cost of the subsequent calculations for each conformer, there is a need to sample the most relevant subset and avoid repeating calculations on conformers that are nearly identical. The goal of this study is to introduce a heuristic method of finding the most dissimilar conformers from a larger population in order to help speed up reference-free calculation methods and maintain a high property prediction accuracy. Finding the set of the n items most dissimilar from each other out of a larger population becomes increasingly difficult and computationally expensive as either n or the population size grows large. Because there exists a pairwise relationship between each item and all other items in the population, finding the set of the n most dissimilar items is different than simply sorting an array of numbers. For instance, if you have a set of the most dissimilar n = 4 items, one or more of the items from n = 4 might not be in the set n = 5. An exact solution would have to search all possible combinations of size n in the population exhaustively. We present an open-source software called similarity downselection (SDS), written in Python and freely available on GitHub. SDS implements a heuristic algorithm for quickly finding the approximate set(s) of the n most dissimilar items. We benchmark SDS against a Monte Carlo method, which attempts to find the exact solution through repeated random sampling. We show that for SDS to find the set of n most dissimilar conformers, our method is not only orders of magnitude faster, but it is also more accurate than running Monte Carlo for 1,000,000 iterations, each searching for set sizes n = 3–7 out of a population of 50,000. We also benchmark SDS against the exact solution for example small populations, showing that SDS produces a solution close to the exact solution in these instances. Using theoretical approaches, we also demonstrate the constraints of the greedy algorithm and its efficacy as a ratio to the exact solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Downselection of Cladding Materials for Zirconium Hydride Moderator

This report complete Milestone M3.1.1 — “Cladding downselection: Team will report to ARPA-E on at least two down-selected cladding options—one metallic and one ceramic.” In this milestone, we systematically assess FeCrAl alloys and SiC-based cladding options for a zirconium hydride (ZrHx) moderator in terms of their neutronics, radiation stability, hydrogen permeability, chemical compatibility, and fabricability. The analysis shows that FeCrAl alloys are excellent candidate cladding materials for a ZrHx moderator given their proven radiation stability, acceptable compatibility with ZrHx, and industrially established fabricability. The relative high hydrogen permeability is manageable by introducing a thin layer of an Al 2 O 3 hydrogen permeation barrier on the external surface. The SiC-cladded ZrHx moderator is promising because of its outstanding neutronics performance, excellent radiation stability, and extremely low intrinsic hydrogen permeability. However, potential interactions of SiC and Zr and the challenge in achieving a hermetic SiC-based cladding require further investigation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Graph-Directed Approach for Downselecting Toxins for Experimental Structure Determination

Conotoxins are short, cysteine-rich peptides of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. Currently, of the approximately 6000 known conotoxin sequences, only about 3% have associated structural characterization, which leads to a bottleneck in rapid high-throughput screening (HTS) for identification of potential leads or threats. In this work, we combine a graph-based approach with homology modeling to expand the library of conotoxin structures and to identify those conotoxin sequences that are of the greatest value for experimental structural characterization. The latter would allow for the rapid expansion of the known structural space for generating high quality template-based models. Our approach generalizes to other evolutionarily-related, short, cysteine-rich venoms of interest. Overall, we present and validate an approach for venom structure modeling and experimental guidance and employ it to produce a 290%-larger library of approximate conotoxin structures for HTS. We also provide a set of ranked conotoxin sequences for experimental structure determination to further expand this library.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Development of High Temperature (>700°C) molten Salt Pump Technology for Gen3 Solar Power Tower Systems

Generation 3 Concentrating Solar Power (CSP) Systems require thermal energy storage that can efficiently receive solar heat and deliver it to a working fluid at temperatures greater than 700°C. For liquid systems, the thermal transfer fluid must be phase stable over large temperature ranges. High temperature molten salts meet this criteria, but are difficult liquids to handle. The high heat and salt content can be very corrosive to several different materials that are wetted by the liquid salt. For power tower collectors, the molten salt must be pumped under high pressure to the top of the collector tower. These pumps have impellers and shafts as part of their rotating elements, and under load, require bearings to control shaft movement while rotating. These high temperature pumps require submerged bearings, and thus bearing materials that can withstand the temperature and molten salt contact over long periods of time. This is essential for keeping pump maintenance costs low, and downtime to a minimum. Long running bearing materials is an enabling technology for integrated liquid systems in Generation 3 CSP Systems. Keeping costs low and systems reliable are critical for the broad adoption of Gen 3 CSP Systems. Hayward Tyler, Inc (HTI) proposed development of journal bearing materials for use in vertical pumps designed for pumping high temperature molten salt on both the hot and cold sides of the solar power tower. To complete this objective, HTI utilized the testing capabilities of Oak Ridge National Laboratory (ORNL) and High Temperature System Design (HTSD). Materials would first be selected for static corrosion testing, then downselected for tribological testing. Successful tribologically tested materials would then be downselected for use in additional test regimes. Ten samples were selected for static corrosion testing. Three passed the static testing regime. Two of these materials were downselected for ball material in tribological testing against three metallic alloys: Sintered Y2O3 Partially Stabilized Zirconia YTZP and Silicon Nitride, Grade 147-31N. HTI also proposed collecting data from a thorough bearing test regime using a test rig designed and built as part of this project, and also a conceptual design for a high temperature molten salt vertical pump. HTI withdrew from the project prior to completion of this work and this report reflects only the work completed prior to withdrawal. The completed work produced two papers, one manuscript submitted for publication, and one paper published in the journal Solar Energy Materials and Solar Cells. The papers are: “Tribological behavior of ceramic-alloy bearing contacts in molten salt lubrication for concentrating solar power” and “Material Selection and Corrosion Studies Of Candidate Bearing Materials For Use In Molten Chloride Salt."

14 SOLAR ENERGY↗
DOE OSTI2022

Droplet Evaporation-Based Approach for Microliter Fuel Property Measurements

Small-volume, high-throughput screening techniques are sought to enable downselection from a large candidate pool of bio-blendstocks to a select few, having physical properties consistent with requirements of downsized, turbo-boosted internal combustion engines. Herein, this work presents a droplet evaporation-based approach to predict heat of vaporization, vapor pressure, diffusion coefficient, and Lennard–Jones parameters for an unknown fuel. Two different schemes, considering the isothermal evaporation of a moving droplet in ambient air, are proposed, which combine droplet velocity and temperature measurements, with some known properties to predict unknown properties. The schemes utilize an inverse solution of a transient model of droplet evaporation solved in an iterative fashion. A baseline scheme, which only requires droplet size change measurements, is evaluated using test data for three liquid fuels, comprising of alkanes and alcohols, as obtained in a temperature-controlled chamber. Results yield temperature-dependent heat of vaporization and vapor pressure predictions within 10 % and 22 %, respectively, of reference values. The advanced scheme, which additionally requires droplet temperature measurement, is numerically evaluated in the current work and will be experimentally validated in future efforts. The advanced scheme is found to significantly improve prediction quality, with deviations less than 2 % and 1 % for heat of vaporization and vapor pressure, while also predicting diffusion coefficient and Lennard–Jones parameters within 5 % and 8 %, respectively. The combined set of approaches, which primarily track droplet evaporation, can be incorporated into a small-volume, high-throughput fuel screening process.

09 BIOMASS FUELS↗
DOE OSTI2022

A Low-Enriched Uranium (LEU) option for the conversion of FRM II

The Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II) is Germany’s most powerful research reactor and uses Highly Enriched Uranium (HEU) fuel enriched at 93 %. The Technical University of Munich (TUM) operates the reactor and has been mandated to convert the FRM II to a lower-enrichment fuel. In preparation for the lower-enrichment fuel downselection, planned for 2023, TUM is evaluating multiple conversion scenarios. In this paper, it is demonstrated that a conversion of FRM II to Low-Enriched Uranium (LEU) is scientifically possible when using the novel monolithic U-10Mo fuel system, which is currently in the qualification process. As a research reactor, safety criteria, neutron flux distribution and cycle length are key metrics. To begin, neutronic and thermal-hydraulic models were created based on current technical drawings and relevant material properties. Specifically tailored computational methods and coupling schemes have also been developed to properly evaluate all relevant characteristics for the conversion of the FRM II reactor. Using these models and methods, a systematic parameter study was performed to explore the defined design space. The results of that study indicate that many LEU designs using monolithic U-10Mo appear to be viable to convert FRM II to LEU. One example of an LEU solution for the FRM II reactor that fulfills the stated safety, compatibility and scientific performance requirements is discussed in more detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A machine learning approach for increased throughput of density functional theory substitutional alloy studies

In this study, a machine learning-based technique is developed to reduce the computational cost required to explore large design spaces of substitutional alloys. The first advancement is based on a neural network (NN) approach to predict the initial position of minority and majority ions prior to DFT relaxation. The second advancement is to allow the NN to predict the total energy for every possibility minority ion position and select the most stable configuration in the absence of relaxing each trial minority configuration. A bismuth oxide materials system, (Bi x La y Yb z ) 2 MoO 6 , was used as the model system to demonstrate the developed methods and quantify the resulting computational speedup. Compared to a brute force method that requires the calculation of every permutation of minority configuration and subsequent DFT relaxation, a 1.3× speedup was realized if the NN predicted the initial configuration of ions prior to relaxation. Implementation of the second advancement allowed the NN to predict the total energy for all possible trial configurations and downselect the most stable configurations prior to relaxation, resulting in a speedup of approximately 37×. Validation was done by comparing position and energy between the NN and DFT predictions. A maximum position vector mean squared error (MSE) of 1.6 × 10 -2 and a maximum energy MSE of 2.3 × 10 -7 was predicted for the worst case configuration. This method demonstrates a significant computational speedup, which has the potential for even greater computational savings for larger compositional design spaces.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The U.S. Fusion Materials Community Roadmap: Near-term research priorities for the development of plasma-facing and structural materials for fusion power plants

In response to the needs of a rapidly growing private fusion industry, the U.S. Fusion Materials Coordinating Committee (FMCC) and the broader U.S. fusion materials research community undertook an extensive effort to create a comprehensive roadmap for fusion materials development. The result of this effort was the U.S. Fusion Materials Community Roadmap (US-FMCR), which describes the steps needed to advance the technical maturity of leading candidates for plasma-facing materials and structural materials for fusion power plants from laboratory-scale experiments to a point of sufficient technological readiness for industrial adoption and implementation. However, researchers face significant resource constraints as well as very aggressive pilot plant development timelines. Thus, the research strategies detailed in the US-FMCR require further assessment to downselect the specific tasks that must be prioritized within the next two to three years, in order to make the most efficient use of funding, human resources, and experimental facilities. This paper presents an overview of the US-FMCR and its development process. We also present the subset of research objectives that the FMCC identified as the most urgent research priorities for the U.S. fusion materials research community. The state-of-the-art of materials research is also highlighted for each class of materials considered in the US-FMCR. The recommendations presented here integrate an extensive evaluation of the current status of fusion materials research with a broad cross-section of opinion from the wider U.S. fusion community.

Ferry, Sara [Massachusetts Institute of Technology↗
DOE OSTI2020

Transformational Challenge Reactor preconceptual core design studies

In the nuclear industry, a manufacturing-informed design approach has the potential to yield the most benefit from advanced manufacturing. By leveraging advanced materials, data science, and rapid testing and deployment, manufacturing-informed design can drive down costs and development times, ultimately improving future commercial viability. This approach is being demonstrated in the US Department of Energy Office of Nuclear Energy (DOE-NE) Transformational Challenge Reactor (TCR) program. Preconceptual design activities for TCR have been focused on analyzing and maturing four reactor core design concepts: two fast-spectrum and two thermal-spectrum systems. Furthermore, the designs were iteratively modified and analyzed, and subcomponents were manufactured in parallel over weeks instead of months or years. To meet key program initiatives (e.g., timeline and material use), several constraints—including fissile material availability, component availability, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small cores less than one cubic meter in volume with near-term viability. Additionally, the TCR program has made significant progress on development of advanced moderator materials such as yttrium hydride, advancing the feasibility of gas-cooled thermal spectrum systems using less than 250 kg of high-assay low enriched uranium (HALEU) and occupying less than 1 m3. Each of the two resulting thermal designs uses a different fuel form: traditional UO2 ceramic fuel and tristructural isotropic (advanced TRISO) fuel particles embedded inside a SiC matrix. Core neutronics and thermal performance for these systems were assessed and summarized. Evaluation of the performance metrics for these two moderated designs has yielded the downselected TCR design: a TRISO-fueled and yttrium hydride moderated gas-cooled reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Sooting tendencies of terpenes and hydrogenated terpenes as sustainable transportation biofuels

Terpenes are a diverse group of molecules that are synthesized by plants and microorganisms through combining units of isoprene (2-methyl-1,3-butadiene). They typically contain rings and methyl branches, which gives them high energy densities and low freezing points and makes them appealing candidates for sustainable transportation biofuels. Between the original biosynthesis and upgrading options such as hydrogenation, they have a large degree of freedom of structures, e.g., different carbon skeletons, positions of double bonds, and functional groups. Therefore, structure-property data is needed to downselect potential fuel candidates. Here, we measured the sooting tendencies of 17 C10 monoterpenes and 7 of their hydrogenated analogues. The hydrogenated compounds were custom synthesized, so the quantities were too small for conventional smoke point measurements. Thus, the sooting tendencies were quantified with yield sooting index (YSI), which is based on the soot yield in a fuel-doped non-premixed methane flame. Derived smoke points (DSPs) were estimated from a correlation between YSI and smoke point for other hydrocarbons. The YSI of terpenes and their derivatives varies widely from 85.6 to 248.5. The YSI follows the trend: terpenes > dihydroterpenes > tetrahydroterpenes. The DSPs of all the tetrahydroterpenes and some dihydroterpenes are higher than that of a Jet-A fuel sample, suggesting that they offer soot reduction benefits. Further, the YSIs depend strongly on molecular structure; for example, α-pinene and β-pinene have identical carbon skeletons and differ only in the position of one carbon-carbon double bond, but the YSI of α-pinene is 34% higher than that of β-pinene. Detailed decomposition analysis via density functional theory (DFT) suggests that compared with β-pinene, α-pinene requires fewer steps to form the first aromatic ring and the process is more thermodynamically favorable. The YSI difference between the pinenes is mainly affected by the identity of the products from the dominant decomposition pathways.

09 BIOMASS FUELS↗
DOE OSTI2022

Accelerating Solvent Selection for Type II Porous Liquids

Type II porous liquids, comprising intrinsically porous molecules dissolved in a liquid solvent, potentially combine the adsorption properties of porous adsorbents with the handling advantages of liquids. Previously, discovery of appropriate solvents to make porous liquids had been limited to direct experimental tests. We demonstrate an efficient screening approach for this task that uses COSMO-RS calculations, predictions of solvent pK a values from a machine-learning model, and several other features and apply this approach to select solvents from a library of more than 11,000 compounds. Additionally, this method is shown to give qualitative agreement with experimental observations for two molecular cages, CC13 and TG-TFB-CHEDA, identifying solvents with higher solubility for these molecules than had previously been known. Ultimately, the algorithm streamlines the downselection of suitable solvents for porous organic cages to enable more rapid discovery of Type II porous liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗