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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 181 records · Page 10

Conference Support: 50th Midwest/Southeast Regional Photosynthesis Conference 2024

The DOE grant referenced above supported the 50th Anniversary Meeting of the Midwest/Southeast Regional Photosynthesis Conference, held at Turkey Run State Park, Marshall, Indiana, from October 25-27, 2024. The meeting featured four keynote speakers – Drs. Govindjee, Wim Vermaas, David Vinyard, and Lauren Metskas – and 12 oral presentations by student and postdoctoral trainees, selected from submitted abstracts. The meeting had a total attendance of 85 participants, including 62 students and research scientists. DOE funds were used to waive the registration fees for all students and trainees (totaling $\$$2,500) and to support seven travel awards of $\$$350 each, for a total of $\$$2,450. Each travel award covered food and accommodation for the recipient at Turkey Run State Park during the conference.

14 SOLAR ENERGY↗

Advanced Functional Membranes for Noble Gas Management: Fabrication and Testing of Membranes on Porous Support

We selected several porous materials including PNW-24, CC3, SAPO-34, SAPO-56 and PNW-6, as the basis for fabricating membranes for Kr/Xe separation. Initially, we synthesized powder samples of the candidates and confirmed their crystallinity and morphology with X-ray diffraction and microscopy. In the case of PNW-24 and PNW-6, we further confirmed its Xe selectivity through Xe and Kr adsorption experiments, while we relied on literature reports for CC3, SAPO-34 and SAPO-56. We subsequently proceeded to fabricate membranes on porous alumina supports using techniques such as seeded-assisted secondary growth, in-situ growth and solution-processed method. PXRD on the membranes verified that the structures were well-grown on the surface of alumina support, while SEM provided visual confirmation of particle morphology. Importantly, defects were not visually observed in the fabricated membranes, which was further verified with pressure retention tests. We analyzed the separation performance of the synthesized membranes using a dilute gas mixture comprising of xenon, krypton and argon. We focused on PNW-6 to optimize the synthesis reaction time and study the effects of time on gas separation. While more research is necessary to reach a comprehensive conclusion, in alignment with our milestones, we have successfully achieved our goals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗

REopt Federal User Support Session Two

This presentation is for FEMP's second user support session for federal REopt users. These sessions cover topics such as: overviews of REopt capabilities, hands-on REopt trainings and demonstrations, discussion and feedback about the tool and user support, federal REopt case studies and success stories, and links to REopt resources. This particular session covers discussion about federal onsite energy projects and challenges, using REopt to evaluate air-source and geothermal heat pumps, a federal success story about using REopt for heat pump analysis, a summary of available resources, and open question and answer session.

14 SOLAR ENERGY↗

2025 Advances in NekRS: Supporting improved performance for nuclear applications

This report presents several 2025 advancements in NekRS, a high-fidelity spectral element CFD code developed at Argonne National Laboratory to support the NEAMS thermal-hydraulics program. The forthcoming v25 release consolidates several of these advances, adding new features for portability across heterogeneous GPU architectures, real-time in situ visualization, improved turbulence modeling, and conjugate heat transfer coupling. Over the past year, NekRS has demonstrated strong scalability and performance on DOE’s leading exascale platforms, including Aurora and Frontier, confirming its readiness for some of the largest and most complex simulations attempted to date. These achievements provide a powerful new platform for high-fidelity data generation, which in turn supports the development and validation of advanced closure models critical for reactor safety and design. Significant algorithmic innovations have also been introduced. A new global runtime h-refinement capability simplifies workflows by reducing mesh preparation burdens and enabling coarse-to-fine restarts. Building on this, a novel multigrid strategy was implemented to accelerate pressure and transport solves at scale, addressing long-standing bottlenecks in exascale CFD. Together, these developments improve both the efficiency and accessibility of high-fidelity simulations for reactor-relevant problems. Collectively, these enhancements represent a major step forward in simulation technology, positioning NekRS as a cornerstone of NEAMS efforts to enable accurate, efficient, and scalable high-fidelity analysis of advanced nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

OC6 project Phase IV: validation of numerical models for novel floating offshore wind support structures

Abstract. This paper provides a summary of the work done within Phase IV of the Offshore Code Comparison Collaboration, Continued with Correlation and unCertainty (OC6) project, under International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the loading on and motion of a novel floating offshore wind system. Numerical models of a 3.6 MW horizontal-axis wind turbine atop the TetraSpar floating support structure were compared using measurement data from a 1:43-Froude-scale test performed in the University of Maine's Alfond Wind–Wave (W2) Ocean Engineering Laboratory. Participants in the project ran a series of simulations, including system equilibrium, surge offsets, free-decay tests, wind-only conditions, wave-only conditions, and a combination of wind and wave conditions. Validation of the models was performed by comparing the aerodynamic loading, floating support structure motion, tower base loading, mooring line tensions, and keel line tensions. The results show a relatively good estimation of the aerodynamic loading and a reasonable estimation of the platform motion and tower base fore–aft bending moment. However, there is a significant dispersion in the dynamic loading for the upwind mooring line. Very good agreement was observed between most of the numerical models and the experiment for the keel line tensions.

17 WIND ENERGY↗

Status Report on Fast Flux Test Facility Mechanistic Fuel Failure Experiment Analysis with BISON for Post Irradiation Examination Support

The renewed interest in metallic U-Zr nuclear fuel alloy has led to a drive for deeper understanding of the mechanisms driving the phenomena observed under irradiation conditions. The Department of Energy Advanced Fuel Campaign has developed infrastructure to support metallic fuel development, including Post Irradiation Examination (PIE) of legacy Fast Flux Test Facility (FFTF) Mechanistic Fuel Failure (MFF) experiments. The PIE performed on legacy FFTF MFF experiments gives insight on metallic fuel performance and can address the lack of knowledge and scarcity of reliable data identified in several studies over recent years. Unfortunately, PIE efforts can cost significant time and resources which can impede the progress of metallic U-Zr fuel development. Metallic U-Zr fuel performance modeling can be used to inform PIE efforts on regions of interest for relevant investigations and can help understand phenomena observed in PIE. This report demonstrates the current progress of FFTF MFF fuel performance simulations using the BISON fuel performance code and discusses the support provided by simulation to PIE efforts. Progress in temperature, profilometry, fission gas release, plenum pressure, and zirconium redistribution simulation results have been demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Acoustic Measurements of Solvent Extraction Processes in Support of Safeguards

The proposed poster focuses on using acoustic monitoring to advance detection techniques for reprocessing equipment in support of nuclear safeguards. The usage of free air acoustic monitoring has been previously demonstrated at Idaho National Laboratory (INL) at facilities such as the Advanced Test Reactor and the National Security Test Range. However, this work focuses on a deployment environment dedicated to monitoring separation processes, using solvent extraction equipment such as centrifugal contactors. This environment offers an opportunity for signal discovery and in characterizing acoustic signatures of the equipment in operation. This data can support the development of safeguards by design and security by design measures for aqueous reprocessing facilities. Furthermore, this type of monitoring can aid in early detection and identification of removed materials indicating diversion, which is essential for initiating material recovery and actor identification. The results of this work include data from nine low-frequency acoustic sensors used to investigate potential acoustic characteristics of centrifugal contactors used in multi-stage processes. The results also discuss the correlation between the signatures and the operation of the contactor banks.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

Autonomous Grid Support Functionality in Variable-Speed Drive-Based End-Use Loads

High penetration of inverter-based resources into power systems causes lower inertia, and it becomes more challenging to maintain grid stability during contingency events. While conventional demand response and shedding at the load side suffer from slow response, impact by unavailability, and issues from communication, variable-speed drives (VSDs) are becoming strong candidates for fast frequency response (FFR) thanks to their fast response and reduced user impact from variable power adjustment capability. In this letter, we propose an autonomous frequency support control method for a residential refrigerator with a VSD, a promising target small end-use load for FFR. We analyze the effect of the proposed controller on grid stability, and we verify the performance through laboratory experiments with a commercially available refrigerator.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using AMReX's Embedded Boundaries to Support MFIX-Exa’s Geometry Capabilities

MFIX-Exa is an AMReX-based application used for the simulation of chemically reacting multiphase flows inside reactors. The reactor geometry is mostly a combination of primitive shapes such as cylinders, cubes and spheres of varying dimensions connected together with potentially a lot of dead space between them. Additionally, the reactors may have particle-laden jets introduced at different parts of their geometry to enhance reactant mixing. This talk presents how MFIX-Exa uses OpenSCAD’s csg format to allow users to define the embedded boundary (EB) geometry and how it supports specifying inflow through certain sections of the EB. The talk will describe how MFIX-Exa leverages the EB features of grid-pruning, restart files and redistribution. Finally, the talk goes over some capabilities which are currently not available in MFIX-Exa but planned for the future, such as moving parts of the reactor geometry.

embedded boundaries↗

GPS-supported smartphone app-based integrated travel diary and time-use data collection: challenges and lessons learned

Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.

GPS-supported smartphone apps↗

Adiabatic quantum support vector machines

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic quantum approach for training support vector machines. We show that the time complexity of our quantum approach is an order of magnitude better than the classical approach. Next, we compare the test accuracy of our quantum approach against a classical approach that uses the Scikit-learn library in Python across five benchmark datasets (Iris, Wisconsin Breast Cancer (WBC), Wine, Digits, and Lambeq). We show that our quantum approach obtains accuracies on par with the classical approach. Finally, we perform a scalability study in which we compute the total training times of the quantum approach and the classical approach with an increasing number of features and an increasing number of data points in the training dataset. In conclusion, our scalability results show that the quantum approach obtains a 3.5–4.5x speedup over the classical approach on datasets with many (millions of) features.

Computational Complexity↗

Formation and coarsening of epitaxially-supported metal nanoclusters

This mini-review describes developments over the last ~30 years in characterizing the nucleation & growth of epitaxially-supported metal nanoclusters (NCs) or islands during vapor deposition, as well as their post-deposition coarsening. A beyond-mean-field treatment for homogeneous nucleation & growth corrects the deficiencies of traditional treatments in describing, e.g., the island size distribution, but also necessitates consideration of the spatial distribution of islands and their capture zones. We discuss advances in modeling capabilities, including those based upon on an ab-initio level treatment of periphery diffusion kinetics, for description of the non-equilibrium growth shapes of these NCs, focusing on 2D NCs. For post-deposition coarsening of arrays of NCs, there is generally a competition between Ostwald Ripening (OR) and Smoluchowski Ripening (SR). SR is also known as Particle Migration & Coalescence. For 2D NCs in homoepitaxial systems, conventional OR is observed on pristine fcc(111) surfaces, dramatically enhanced OR in the presence of even trace amounts of chalcogens for Cu(111) and Ag(111), and anomalous OR on anisotropic fcc(110) surfaces. The unexpected discovery of SR for fcc(100) homoepitaxial systems prompted extensive analysis of the underlying diffusivities of 2D NCs as a function of size, as well as of NC coalescence dynamics. A comprehensive understanding of these processes is now available. Self-assembly of 3D NCs during deposition, issues related to heterogeneous nucleation, directed assembly, NC growth structure selection, and coarsening are addressed. Finally, for SR of 3D epitaxial NCs, recent insights into the size-dependence of diffusivity are described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stabilizing alkaline fuel cells with a niobium-doped brookite titanium dioxide catalyst support

Anion-exchange membrane fuel cells represent a promising and scalable approach for hydrogen energy utilization. However, their development is hindered by the weak bonding between metal catalysts and carbon supports, along with challenges in fabricating electronically/ionically conductive electrodes. Here, we report a composite cathode of Nb-doped brookite TiO 2 nanorods that have robust stability when combined with Pt nanoscale catalysts in an alkaline fuel cell. The composite cathode, fabricated without the addition of an ionomer, delivers a power density of 419 mW cm −2 at a current density of 650 mA cm −2 and a voltage retention of 81% at 100 mA cm −2 after 25 h, substantially outperforming a cathode fabricated from commercial Pt/C. Further investigations of the chemical structure, anion exchange capacity, and mass transfer resistance reveal that a solvent residue derived from N-methylpyrrolidone plays an important role in charge transfer and mass transport in the alkaline fuel cell.

alkaline fuel cell↗

Silver(I) Supported Liquid Membranes for Selective Ethylene Recovery from Mixed-Gas Streams of Tandem CO 2 Electrolysis

Large-scale olefin separations from unreacted paraffins and other byproduct gases are primarily done by energy-intensive cryogenic distillation processes at refineries. Silver(I) supported liquid membranes (Ag SLMs) can be implemented at smaller production scales of ethylene (C 2 H 4 ), a critical industrial chemical, such as its electrocatalytic (EC) production from CO 2 . Challenges of EC C 2 H 4 production mainly stem from reducing gases like hydrogen (H 2 ), where the redox reactions pertinent to Ag(I) facilitators diminish olefin transport. Herein we report that aqueous Ag(I) solution in a composite Ag SLM can operate in mixed-gas conditions containing H 2 gas utilizing reduced titania compounds, such as titanium(III) oxide (Ti 2 O 3 ). Embedding Ti 2 O 3 in the polydimethylsiloxane layer of Ag SLM assisted in selectively separating C 2 H 4 from mixed-gas feed streams related to CO 2 electrolysis containing H 2 . The direct exposure of a mixed-gas stream containing C 2 H 4 , CO 2 , CO, N 2 , and CH 4 with as high as 50 vol % H 2 maintained excellent C 2 H 4 separations for 7 days of continuous operation. The Ag SLM provided effective separations of C 2 H 4 from CO (at detection limits), CH 4 (selectivity ratio (α) = 20–30), and H 2 (α = ∼20), but C 2 H 4 from CO 2 (α = 2–4) revealed a slightly lower separation. These data show that aqueous Ag(I) solution(s) used in the SLMs can separate C 2 H 4 for extended periods, even under highly reducing gas conditions. Also, we report C 2 H 4 recovery from the gas mixture produced in the EC CO 2 reduction process. In conclusion, the Ag SLM gave C 2 H 4 selective separation from a five-component complex mixed-gas stream, relevant to tandem CO 2 electrolysis.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Engineering CoO x ‑Based Self-Supported Anodes for Pure-Water-Fed Anion-Exchange-Membrane Electrolysis

Commercial membrane electrolyzers rely on acidic fluorocarbon membranes and ionomers, requiring the use of expensive IrO x -based oxygen-evolution catalysts. Anion-exchange-membrane water electrolyzers (AEMWEs) operate in an alkaline environment, enabling the use of non-precious-metal catalysts. Here, we study and engineer CoO x -based catalyst-coated anodes deposited via hydrothermal synthesis directly onto porous transport layers both with and without thermal annealing. The self-supported, nanoneedle-structured Co3O4 anode, formed by annealing the as-synthesized cobalt carbonate hydroxide, Co­(CO3) x (OH) y , outperforms the baseline Co3O4 nanoparticle ink-based anode in pure-water-fed AEMWE due to the improved catalyst-layer continuity and thus number of electroactive Co species. The as-synthesized and unannealed Co­(CO3) x (OH) y , however, appears to undergo substantial conversion to a more-active CoO x (OH) y phase predominantly at the surface, with nominal Co3+ present and higher electrical conductivity, lowering the cell voltage to ∼200 mV at 1.0 A·cm–2 in pure-water-fed AEMWE compared to the conventional Co3O4 nanoparticle anodes. We analyze the differences in electrode electrochemical response between pure-water and KOH feed modes, finding distinct activation and degradation modes. The Co­(CO3) x (OH) y anode shows significant activation and slower degradation linked to the conversion to oxyhydroxide. We propose catalyst layer designs that promote both hydroxide and electron transport, alongside interfacial engineering strategies to obtain high performance while mitigating anode degradation.

anion-exchange-membrane water electrolysis↗

Hourly Load Profile Dataset for Electric Airport Ground Support Equipment in the United States

Currently, there are limited data on the magnitude and timing of electricity demand from electric ground support equipment (eGSE) across U.S. airports. To address this gap, this study presents a modeling approach for estimating hourly annual electricity demand from eGSE at the 50 largest U.S. commercial airports. These datasets, accessible at data.nrel.gov/submissions/279, provide critical insights into the potential grid impacts and electricity demand associated with eGSE adoption.

33 ADVANCED PROPULSION SYSTEMS↗