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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Nuclear fuel irradiation testbed for nuclear security applications

The nuclear security community has long been interested in the identification and quantification of nuclear material signatures to understand a material’s provenance, use, and ultimate application. New forensics signatures and methods intended for non-traditional or advanced nuclear fuel applications require fuel irradiation experiments to demonstrate viability and validity. Integral fuel irradiations have historically required significant costs and long timelines to design, irradiate, and characterize. This paper describes how a recently developed nuclear fuel irradiation testbed can be used to provide a low cost, rapid turnaround, modular test environment for irradiation and evaluation of nuclear fuel specimens for nuclear security applications. The irradiation testbed houses six small ‘MiniFuel’ samples within hermetically sealed capsules inside targets that can be removed in between each ∼25-day operating cycle of the High Flux Isotope Reactor (HFIR). As many as nine targets can be irradiated using a single irradiation position (reflector region) in HFIR, allowing for varying irradiation temperatures and burnups. A suite of hot cell capabilities have been established to perform post-irradiation examination for measuring performance (e.g., fuel swelling, fission gas release) and facilitating experiment disassembly for subsequent property measurements, microstructural analysis, or chemical assay. This new testbed allows fuel irradiations to be conducted on an accelerated timeframe to enable rapid proof of concept testing and to provide reference material for nuclear fuel security applications. Recent applications using this testbed include the testing of isotopic taggants in UO 2 fuel (intentional forensics), testing of U-10Mo fuel for down-conversion of highly enriched uranium–fueled reactors, and the production of irradiated UO 2 fuel material for signature analysis of its isotopic composition (plutonium, fission gases, etc.).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Squeeze Film Damper Experimental and Numerical Correlation: Test Setup Description and Parameter Identification of Dry System

The process of characterizing a damper involves both experimental techniques and model simulation. Experiments characterize dynamic behavior of a system through empirical modal analysis using impact and shaker testing. The layout of the test setup is crucial for a low-mass, nonlinear system. Physical arrangement, orientation of the system, and instrumentation affect the results that are discussed in this paper. These results can be used to validate a numerical simulation of the same system. With a validated model, important physical input parameters and modeling techniques can be determined and implemented in future designs. In other words, this modeling can be used with confidence to design alternative dampers that may be difficult, costly, and time-consuming to characterize experimentally.

Cook, Jason↗
DOE OSTI2025

Generating multi-scale Li-ion battery cathode particles with radial grain architectures using stereological generative adversarial networks

Abstract Understanding structure-property relationships of Li-ion battery cathodes is crucial for optimizing rate-performance and cycle-life resilience. However, correlating the morphology of cathode particles, such as in LiNi0.8Mn0.1Co0.1O2 (NMC811), and their inner grain architecture with electrode performance is challenging, particularly, due to the significant length-scale difference between grain and particle sizes. Experimentally, it is not feasible to image such a high number of particles with full granular detail. A second challenge is that sufficiently high-resolution 3D imaging techniques remain expensive and are sparsely available at research institutions. Here, we present a stereological generative adversarial network-based model fitting approach to tackle this, that generates representative 3D information from 2D data, enabling characterization of materials in 3D using cost-effective 2D data. Once calibrated, this multi-scale model can rapidly generate virtual cathode particles that are statistically similar to experimental data, and thus is suitable for virtual characterization and materials testing through numerical simulations. A large dataset of simulated particles with inner grain architecture has been made publicly available.

25 ENERGY STORAGE↗
DOE OSTI2020

Review of on-line and near real-time spectroscopic monitoring of processes relevant to nuclear material management

Spectroscopic chemometric based on-line monitoring of used nuclear fuel (UNF) reprocessing solutions and characterization of legacy nuclear waste (LNW) stored at Hanford is discussed in this manuscript. Using on-line and near real-time monitoring with spectroscopy, as opposed to traditional off-line monitoring, can significantly reduce the cost, risk and improve the efficiency of characterizing UNF reprocessing streams and LNW since the data can be collected non-destructively and analyzed nearly instantly. It can accurately quantify and qualify nuclear material in near-real time which can help to know the immediate UNF reprocessing stream and LNW conditions and detect the diversion of materials. The ability to be applied in a real reprocessing plant and in an actual Hanford waste tank/transfer pipe has been demonstrated by applying this technique to accurately quantify analytes in real UNF streams and LNW samples. Furthermore, the future development of spectroscopy based on-line monitoring is also discussed in this manuscript.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enabling Grid-Aware Market Participation of Aggregate Flexible Resources

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. With the new FERC 2222 order, DER aggregations are allowed to participate in energy market. To enable market participation, these virtual power plants need to provide their generation cost curves. This paper proposes efficient optimization formulations and solution approaches for the characterization of hourly as well as multi-time-step generation cost curves for a distribution system with high penetration of DERs. Network and DER constraints are taken into account when deriving these cost curves, and they enable active distribution systems to bid into the electricity market. The problems of deriving linear and quadratic cost curves are formulated as robust optimization problems and tractable reformulation/solution algorithm are developed to facilitate efficient calculations. The proposed formulations and solution algorithm are validated on a realistic test feeder with high penetration of flexible resources.

aggregated distributed energy resources↗
DOE OSTI2023

Anthradithiophene (ADT)-Based Polymerized Non-Fullerene Acceptors for All-Polymer Solar Cells

Realizing efficient all-polymer solar cell (APSC) acceptors typically involves increased building block synthetic complexity, hence potentially unscalable syntheses and/or prohibitive costs. Here we report the synthesis, characterization, and implementation in APSCs of three new polymer acceptors P1–P3 using a scalable donor fragment, bis(2-octyldodecyl)anthra[1,2-b : 5,6-b’]dithiophene-4,10-dicarboxylate (ADT) co-polymerized with the high-efficiency acceptor units, NDI, Y6, and IDIC. Further, all three copolymers have comparable photophysics to known polymers; however, APSCs fabricated by blending P1, P2 and P3 with donor polymers PM5 and PM6 exhibit modest power conversion efficiencies (PCEs), with the champion P2-based APSC achieving PCE=5.64 %. Detailed morphological and microstructural analysis by AFM and GIWAXS reveal a non-optimal APSC active layer morphology, which suppresses charge transport. Despite the modest efficiencies, these APSCs demonstrate the feasibility of using ADT as a scalable and inexpensive electron rich/donor building block for APSCs.

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

In Search of a Cost-Effective Approach for Estimating Dam Passage Survival

Abstract Passage of downstream-migrating fishes through hydropower dams poses a management issue in rivers throughout the world. As such, regulations have been enacted at many locales to understand and limit fish losses by requiring dam passage survival estimation. However, limiting estimates of survival to the dam and immediate tailrace presents a challenge to researchers. In this study, two alternative release–recapture methods were used to estimate dam passage survival of juvenile salmonids through Lower Granite Dam on the Snake River, Washington, in 2018. One approach, the virtual/paired-release (ViPRe) model, was extensively used in the Columbia–Snake River basin at federally operated hydroelectric dams during 2010–2014. This existing approach uses three releases of tagged smolts to isolate dam passage survival, defined as survival from the upstream dam face to the tailrace mixing zone 1–2 km downstream of the dam. An alternative approach, the virtual release/dead-fish correction (ViRDCt) model, uses one live-release group paired with a release of dead tagged fish at the dam to estimate the same survival parameter. The alternative estimation approaches were tested on two spring out-migrating stocks, yearling Chinook Salmon Oncorhynchus tshawytscha and steelhead Oncorhynchus mykiss, and on a summer out-migrating stock of subyearling Chinook Salmon. The alternative estimates for these stocks were all within 1 SE. However, the ViRDCt model produced survival estimates with SEs that were 59% smaller than those of the existing ViPRe model and did so using 42% fewer tagged fish and one less downstream acoustic detection array. Because of the reduced sample size, nearly US$540,000 less in tag costs and 4,000 fewer labor-hours were required to implement the ViRDCt model compared to the ViPRe model. As such, the ViRDCt model represents a cost-effective and precise approach to characterizing dam passage survival.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Thermal conductivity evaluation of ion irradiated Si 3 N 4 and ZrN ceramics using spatial domain thermoreflectance

Nitride ceramics have been investigated for different applications in the nuclear industry, such as space nuclear power, fusion reactor diagnostics and plasma heating, inert matrix fuels, and accident tolerant fuels. Although thermal conductivity remains one of the most important properties to track following irradiation, traditional techniques such as laser flash and xenon flash are limited to bulk sample characterization, which requires lengthy and cost-consuming neutron irradiation. This work used spatial domain thermoreflectance (SDTR) for the micrometer-scale measurement of thermal conductivity in 15 MeV Ni ion-irradiated silicon nitride and zirconium nitride from 1 to 50 dpa and 300 to 700 °C. Here, the SDTR-measured unirradiated thermal conductivity was found to be consistent with the published data on bulk samples. Electrically conductive ZrN exhibits modest reduction after irradiation which is minimal at the highest irradiation temperatures. In electrically insulating Si 3 N 4 , the reduction is more significant and unlike ZrN, the reduction remains significant even at a higher irradiation temperature. The thermal resistance evolution following irradiation was compared with lattice swelling, which was determined using grazing incidence x-ray diffraction, and radiation-induced defects were observed using transmission electron microscopy. A saturation value was observed between 15 and 50 dpa for thermal conductivity degradation in both nitride ceramics and a direct correlation with high-temperature defect recombination was observed, as well as the potential presence of additional carrier scattering mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗
DOE OSTI2020

Using geodetic data in geothermal areas

Geodetic observations, often in conjunction with other data, provide a cost-effective means for identifying and characterizing geothermal resources. Here, a review of the various methods reveals how the technology for measuring deformation has advanced considerably in the past few decades. Currently, interferometric synthetic aperture radar is the method of choice for monitoring deformation at a geothermal field. A discussion of geodetic monitoring at The Geysers geothermal field, California, illustrates some of the progress made and the challenges that remain.

58 GEOSCIENCES↗
DOE OSTI2023

Development of a Metocean Reference Site near the Massachusetts and Rhode Island Wind Energy Areas

This project developed the first long-term U.S.-based offshore MetOcean Reference Site (MORS-1) by capitalizing on a unique combination of one of the few existing publicly available offshore wind energy metocean observational campaigns in the United States and the only existing research-grade offshore fixed tower. Data collected at MORS-1 has facilitated improved wind resource assessments, improved short-term power production estimates, and reduced costs for sensor validation and calibration efforts, which translate into reduced overall wind energy project risk and cost for developers. Now operational, MORS-1 serves the needs of both industry and researchers using a nonprofit, joint industry-academic partnership model. Led by the Woods Hole Oceanographic Institution, the MORS-1 development effort focused on creating both a recognized organizational structure that will ensure support of the MORS-1 by the wider wind energy industry and research community, and a highly validated data collection and sensor validation facility that will serve as the premier location for cost- and uncertainty-reducing resource characterization and research efforts.

17 WIND ENERGY↗
DOE OSTI2021

Development of an inexpensive matrix-assisted laser desorption—time of flight mass spectrometry method for the identification of endophytes and rhizobacteria cultured from the microbiome associated with maize

Many endophytes and rhizobacteria associated with plants support the growth and health of their hosts. The vast majority of these potentially beneficial bacteria have yet to be characterized, in part because of the cost of identifying bacterial isolates. Matrix-assisted laser desorption-time of flight (MALDI-TOF) has enabled culturomic studies of host-associated microbiomes but analysis of mass spectra generated from plant-associated bacteria requires optimization. In this study, we aligned mass spectra generated from endophytes and rhizobacteria isolated from heritage and sweet varieties of Zea mays. Multiple iterations of alignment attempts identified a set of parameters that sorted 114 isolates into 60 coherent MALDI-TOF taxonomic units (MTUs). These MTUs corresponded to strains with practically identical (>99%) 16S rRNA gene sequences. Mass spectra were used to train a machine learning algorithm that classified 100% of the isolates into 60 MTUs. These MTUs provided >70% coverage of aerobic, heterotrophic bacteria readily cultured with nutrient rich media from the maize microbiome and allowed prediction of the total diversity recoverable with that particular cultivation method. Acidovorax sp., Pseudomonas sp. and Cellulosimicrobium sp. dominated the library generated from the rhizoplane. Relative to the sweet variety, the heritage variety contained a high number of MTUs. The ability to detect these differences in libraries, suggests a rapid and inexpensive method of describing the diversity of bacteria cultured from the endosphere and rhizosphere of maize.

dereplication↗
DOE OSTI2026

Towards Commercialization of Low-Cost, Crack-Tolerant, Screen-Printable Metallization by Full-Size Module Testing and Field Characterization

This project is motivated by the need to develop a materials engineering solution to reduce solar module degradation caused by cell cracks. The cell-crack-induced power loss is a long-term degradation mechanism and one of the main causes of solar panel field failures. Cell cracks can occur during module fabrication, transportation, installation, and long-term operation due to thermomechanical stressors. Our team’s internal estimation – based on the national weather pattern, frequency of severe weather, and 39- GW asset survey by Heliolytics – reveals that the cell-crack-induced module degradation translates to lost revenues >$17B over an average 5-year period for solar farm owners and to reduced reliability (<25 years panel lifetime) for solar energy consumers. In response to this challenge, the prime recipient offers a metal matrix composite (MMC) silver paste that is tailor-engineered for screen-printing gridlines and busbars, which serve as the electrical contacts on solar cells. We formulate our MMC paste by adding low-cost (∼0.02¢/WDC for research grade), surface-engineered carbon nanotubes to commercially available silver paste. The MMC paste offers a drop-in, cost-effective solution to cell cracks for solar cell and module manufacturers. The main goal of this project was to conduct field-relevant, module-level analysis and qualification of MMC metallization.

14 SOLAR ENERGY↗
DOE OSTI2026

Electric Utility Distribution Costs: Scoping Study on Trends, Drivers, and Possible Response Strategies [Slides]

This scoping study synthesizes information that will help stakeholders understand the scope, scale, and drivers of recent increases in investor-owned utility (IOU) expenditures on local distribution power grids, while providing regulators and other decision-makers with potential strategies to keep electricity bills down. The study includes five distinct components. Drawing first on data from FERC Form 1, it summarizes key trends in past and recent IOU distribution costs. Next, through a review of a sample of distribution-system plans, it characterizes material drivers of planned distribution expenditures. Ultimately, regulators must approve cost recovery for IOU expenditures, including those for the distribution system. The study therefore also: examines trends in utility requests and regulatory approvals related to changes in retail rates and return on equity; identifies areas where utility shareholder and customer incentives may be misaligned; and develops a menu of options that state regulators might consider to optimize distribution system expenditures. Some of the key findings include: - IOU distribution spending at a national level has grown by 6%/yr since 2014 in real dollar terms, 4x faster than in the prior 20 years and consisting mostly of capital (not operating) expenditure. - On a per-kWh basis, increases in IOU distribution costs since 2014 represent over 30% of the overall national-average increase in retail electricity rates. - Regional spending growth has ranged from 2-8%/yr, with larger estimated rate impacts in CAISO, then NYISO & ISO-NE, and then the Southeast, MISO & PJM (see figure). - Some utilities are planning for significantly increased distribution system spending. Planned spending on managing the existing system (asset replacement, safety & reliability, and resilience are all important drivers) exceeds that for capacity expansion. - IOU rate increase requests ($18 billion in 2025) and public utility commission (PUC) approval levels (average of 64% of requested amounts from 2021-2025) have recently hit multi-decadal highs. - PUCs in New England and the Southeast have recently approved a greater fraction of rate requests (>75%, on average) than in ther regions, while PUCs in California and the Southeast have generally authorized higher equity returns than in other regions. - Regulators have many tools to tackle potential misalignments between utility and customer interests and, more specifically, to optimize and reduce distribution costs. Shorter-term options include those related to return on equity, capital structure, depreciation, trackers, construction work in progress, and securitization. Longer-term options include performance-based regulation and a wide variety of planning-related requirements. All options embed important tradeoffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

On the energy landscape of symmetric quantum signal processing

Symmetric quantum signal processing provides a parameterized representation of a real polynomial, which can be translated into an efficient quantum circuit for performing a wide range of computational tasks on quantum computers. For a given polynomial f , the parameters (called phase factors) can be obtained by solving an optimization problem. However, the cost function is non-convex, and has a very complex energy landscape with numerous global and local minima. It is therefore surprising that the solution can be robustly obtained in practice, starting from a fixed initial guess &#x03A6; 0 that contains no information of the input polynomial. To investigate this phenomenon, we first explicitly characterize all the global minima of the cost function. We then prove that one particular global minimum (called the maximal solution) belongs to a neighborhood of &#x03A6; 0 , on which the cost function is strongly convex under the condition &#x2016; f &#x2016; &#x221E; = O ( d &#x2212; 1 ) with d = d e g ( f ) . Our result provides a partial explanation of the aforementioned success of optimization algorithms.

Wang, Jiasu↗
DOE OSTI2023

A Workflow for Accelerating Multimodal Data Collection for Electrodeposited Films

Abstract Future machine learning strategies for materials process optimization will likely replace human capital-intensive artisan research with autonomous and/or accelerated approaches. Such automation enables accelerated multimodal characterization that simultaneously minimizes human errors, lowers costs, enhances statistical sampling, and allows scientists to allocate their time to critical thinking instead of repetitive manual tasks. Previous acceleration efforts to synthesize and evaluate materials have often employed elaborate robotic self-driving laboratories or used specialized strategies that are difficult to generalize. Herein we describe an implemented workflow for accelerating the multimodal characterization of a combinatorial set of 915 electroplated Ni and Ni–Fe thin films resulting in a data cube with over 160,000 individual data files. Our acceleration strategies do not require manufacturing-scale resources and are thus amenable to typical materials research facilities in academic, government, or commercial laboratories. The workflow demonstrated the acceleration of six characterization modalities: optical microscopy, laser profilometry, X-ray diffraction, X-ray fluorescence, nanoindentation, and tribological (friction and wear) testing, each with speedup factors ranging from 13–46x. In addition, automated data upload to a repository using FAIR data principles was accelerated by 64x.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Status of Multiple Channel Fuel Performance Capabilities Within the SAS4A/SASSYS-1 Safety Analysis Software

SAS4A/SASSYS-1 (SAS) is a fast-running simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. It is a critical element of safety analysis capabilities for the U.S. Department of Energy and is utilized within industry to perform the transient safety analyses required to support the licensing of Liquid Metal-cooled Fast Reactors (LMFRs). Although SAS is exceptionally fast for most transient scenarios, fuel performance calculations, along with the associated pre-transient characterization of the fuel pin, may be required for transient scenarios where fuel pin failure is hypothesized. Both the pre-transient characterization and the transient fuel performance calculation are necessary to properly quantify margins to potential fuel failure and assess the time spent potentially exceeding such margins during events. While safety analysis calculations with fuel performance models provide a more detailed characterization of the reactor during a transient, the pre-transient characterization can be time-consuming and computationally expensive. Often, large numbers of fuel pins have been exposed to similar pre-transient irradiation conditions. Similarly, the same pre-transient fuel characterization may be applicable to numerous transient conditions. This provides an opportunity to optimize the SAS computational framework such that pre-transient fuel characterization can be shared across multiple channels (fuel pins) and across multiple simulations, thus dramatically reducing overall computational costs. This report summarizes progress toward enhancing the SAS computational framework to support shared, multiple channel fuel performance characterizations intended to significantly reduce computational costs. Preliminary testing has shown that the computational time saved by using the pre-transient sharing capability is approximately equal to the time it takes to perform the pre-transient characterization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗