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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗
DOE OSTI2025

Computational Modeling of Molten Salt Infiltration and Oxidation in Nuclear Graphite

Graphite is utilized as a moderator and reflector in advanced nuclear reactor designs due to its high thermal conductivity, neutron moderation properties, and resistance to radiation damage. However, its longterm performance and reliability are challenged by degradation mechanisms such as molten salt infiltration in molten salt reactors (MSRs) and oxidation in gas-cooled reactors (GCRs). These mechanisms can compromise the structural integrity and operational lifetime of graphite components, necessitating a more detailed assessment of their physical behavior. This report focuses on the development of computational models for molten salt infiltration and oxidation of graphite to aid the design and performance analysis of graphite components. For molten salt infiltration, a computational framework is developed that couples incompressible Navier-Stokes and phase-field model to simulate the penetration of molten salt into graphite?s interconnected pore structure. Initial model verification is performed using two-phase flows in two dimensions, demonstrating the models ability to capture fundamental physical behavior and agree with analytical solution. This framework is then applied to a realistic IG110 nuclear graphite , where a computed tomography extracted pore geometry is used to analyse the infiltration behavior of FLiNaK molten salt. This model provides insights into how the microstructure and other relevant parameters influence the transport pathways of molten salt into graphite, potentially offering a means to rapidly evaluate a graphite grade?s resistance to infiltration. For oxidation, the report details pore-scale mass and heat transport models, describing the diffusion of gases, reaction kinetics, and thermal effects. Additionally, this report highlights inconsistencies in the existing volume-averaged macroscopic model, particularly in upscaling of reaction kinetics and flux terms, and surface to volume transformations. These inconsistencies suggest that current formulations may not accurately capture the experimentally observed graphite oxidation process, highlighting the need for improved model development. This work advances the development of physics-based computational models for graphite degradation, contributing to improved predictive models for next-generation nuclear reactor designs. Future efforts will focus on refining the infiltration model to address non-physical behaviors and enhance its robustness. Additionally, for oxidation, further studies will employ the principles of volume averaging to rigorously derive the upscaled equations, potentially in collaboration with subject matter experts.

Computational Modeling of Molten Salt Infiltration↗
DOE OSTI2018

Discovery and Structure-Based Optimization of Benzimidazole-Derived Activators of SOS1-Mediated Nucleotide Exchange on RAS

Son of sevenless homologue 1 (SOS1) is a guanine nucleotide exchange factor that catalyzes the exchange of GDP for GTP on RAS. In its active form, GTP-bound RAS is responsible for numerous critical cellular processes. Aberrant RAS activity is involved in ~30% of all human cancers; hence, SOS1 is an attractive therapeutic target for its role in modulating RAS activation. In this paper, we describe a new series of benzimidazole-derived SOS1 agonists. Using structure-guided design, we discovered small molecules that increase nucleotide exchange on RAS in vitro at submicromolar concentrations, bind to SOS1 with low double-digit nanomolar affinity, rapidly enhance cellular RAS-GTP levels, and invoke biphasic signaling changes in phosphorylation of ERK 1/2. These compounds represent the most potent series of SOS1 agonists reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Iron Redox Chemistry and Its Environmental Impact: A Virtual Special Issue

Special Editorial Issue. Iron (Fe) is the most abundant redox-active element at the Earth’s surface. It occurs in diverse host rock lithologies, sediments, and soils as accessory oxide and oxyhydroxide minerals and nanoparticles that can dominate the reactive mineral/water interfacial area. Furthermore, designer Fe oxide nanoparticles produced to exploit the catalytic properties of specific mineral surfaces continue to undergo rapid development and deployment for a variety of purposes, including environmental remediation. The structure, charge, and chemical dynamics at these interfaces with aqueous solutions strongly impacts their interaction with other elements, organics, and contaminants. The influence of important environmental factors, especially oxygen concentration, natural organic matter, microbes, etc. remain poorly understood. Key interfacial processes can be driven by both biotic and abiotic mechanisms.

Iron redox, special issue, mechanisms, biogeochemi↗
DOE OSTI2020

NISQ+: Boosting quantum computing power by approximating quantum error correction

Quantum computers are growing in size, and design decisions are being made now that attempt to squeeze more computation out of these machines. In this spirit, we design a method to boost the computational power of near-term quantum computers by adapting protocols used in quantum error correction to implement "Approximate Quantum Error Correction (AQEC)." By approximating fully-fledged error correction mechanisms, we can increase the compute volume (qubits × gates, or "Simple Quantum Volume (SQV)") of near-term machines. The crux of our design is a fast hardware decoder that can approximately decode detected error syndromes rapidly. Specifically, we demonstrate a proof-of-concept that approximate error decoding can be accomplished online in near-term quantum systems by designing and implementing a novel algorithm in Single-Flux Quantum (SFQ) superconducting logic technology. This avoids a critical decoding backlog, hidden in all offline decoding schemes, that leads to idle time exponential in the number of T gates in a program. Our design utilizes one SFQ processing module per physical qubit. Employing state-of-the-art SFQ synthesis tools, we show that the circuit area, power, and latency are within the constraints of contemporary quantum system designs. Under pure dephasing error models, the proposed accelerator and AQEC solution is able to expand SQV by factors between 3,402 and 11,163 on expected near-term machines. The decoder achieves a 5% accuracy-threshold and pseudo-thresholds of ~ 5%,4.75%,4.5%, and 3.5% physical error-rates for code distances 3,5,7, and 9. Decoding solutions are achieved in a maximum of ~20 nanoseconds on the largest code distances studied. By avoiding the exponential idle time in offline decoders, we achieve a 10x reduction in required code distances to achieve the same logical performance as alternative designs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Efficient Scheduling of Recursive Control Flow on GPUs

Graphics processing units (GPUs) have rapidly emerged as a very significant player in high performance computing. Single instruction multiple thread (SIMT) pipelines are typically used in GPUs to exploit parallelism and maximize performance. Although support for unstructured control flow has been included in GPUs, efficiently managing thread divergence for arbitrary parallel programs remains a critical challenge. In this paper, we focus on the problem of supporting recursion in modern GPUs. We design and comparatively evaluate various algorithms to manage thread divergence encountered in recursive programs. The results improve upon traditional post-dominator based reconvergence mechanisms designed to handle thread divergence due to control flow within a procedure.

GPUs↗
NASA NTRS1991

Precision metering of microliter volumes of biological fluids in micro-gravity

Concepts were demonstrated and investigated for transferring accurately known and reproducible microliter volumes of biological fluids from sample container onto dry chemistry slides in microgravity environment. Specific liquid transfer tip designs were compared. Information was obtained for design of a liquid sample handling system to enable clinical chemical analysis in microgravity. Disposable pipet tips and pipet devices that were designed to transfer microliter volumes of biological fluid from a (test tube) sample container in 1-G environment were used during microgravity periods of parabolic trajectories of the KC-135 aircraft. The transfer process was recorded using charge coupled device camera and video cassette equipment. Metering behavior of water, a synthetic aqueous protein solution, and anticoagulated human blood was compared. Transfer of these liquids to 2 substrate materials representative of rapidly wettable and slowly wettable dry chemistry slide surface was compared.

Columbus, Richard L.↗
NASA NTRS1992

Generating the complete control environment interface for EASIE

The Environment for Application Software Integration and Execution (EASIE) was designed to meet the needs of conceptual design engineers that face the task of integrating the results of many stand alone engineering analysis programs. EASIE is a set of utility programs which supports rapid integration and execution of programs about a central relational database, and it provides users with two basic modes of executing operations: Application Derived Executive (ADE), a menu-driven execution mode which provides users with sufficient guidance to quickly review data, select menu action items, and execute application programs, and Complete Control Executive (CCE), which provides a full executive interface, allowing users in-depth control of the design process. Users can switch between these modes as needed. This project will consider the CCE mode interface. Two objectives of this project are to redesign the selecting menus by using a windowing system and to reorganize the selecting structures of the selecting menus. The project will be implemented in the C window system, OSF/Motif version.

Tsai, Chia-Lin↗
NASA NTRS2003

Process-Based Cost Estimation for Ramjet/Scramjet Engines

Process-based cost estimation plays a key role in effecting cultural change that integrates distributed science, technology and engineering teams to rapidly create innovative and affordable products. Working together, NASA Glenn Research Center and Boeing Canoga Park have developed a methodology of process-based cost estimation bridging the methodologies of high-level parametric models and detailed bottoms-up estimation. The NASA GRC/Boeing CP process-based cost model provides a probabilistic structure of layered cost drivers. High-level inputs characterize mission requirements, system performance, and relevant economic factors. Design alternatives are extracted from a standard, product-specific work breakdown structure to pre-load lower-level cost driver inputs and generate the cost-risk analysis. As product design progresses and matures the lower level more detailed cost drivers can be re-accessed and the projected variation of input values narrowed, thereby generating a progressively more accurate estimate of cost-risk. Incorporated into the process-based cost model are techniques for decision analysis, specifically, the analytic hierarchy process (AHP) and functional utility analysis. Design alternatives may then be evaluated not just on cost-risk, but also user defined performance and schedule criteria. This implementation of full-trade study support contributes significantly to the realization of the integrated development environment. The process-based cost estimation model generates development and manufacturing cost estimates. The development team plans to expand the manufacturing process base from approximately 80 manufacturing processes to over 250 processes. Operation and support cost modeling is also envisioned. Process-based estimation considers the materials, resources, and processes in establishing cost-risk and rather depending on weight as an input, actually estimates weight along with cost and schedule.

Singh, Brijendra↗
NASA NTRS2003

Development of a Thin Film Solar Cell Interconnect for the Powersphere Concept

Progressive development of microsatellite technologies has resulted in increased demand for lightweight electrical power subsystems including solar arrays. The use of thin film photovoltaics has been recognized as a key solution to meet the power needs. The lightweight cells can generate sufficient power and still meet critical mass requirements. Commercially available solar cells produced on lightweight substrates are being studied as an option to fulfill the power needs. The commercially available solar cells are relatively inexpensive and have a high payoff potential. Commercially available thin film solar cells are primarily being produced for terrestrial applications. The need to convert the solar cell from a terrestrial to a space compatible application is the primary challenge. Solar cell contacts, grids and interconnects need to be designed to be atomic oxygen resistant and withstand rapid thermal cycling environments. A mechanically robust solar cell interconnect is also required in order to withstand handling during fabrication and survive during launch. The need to produce the solar cell interconnects has been identified as a primary goal of the Powersphere program and is the topic of this paper. Details of the trade study leading to the final design involving the solar cell wrap around contact, flex blanket, welding process, and frame will be presented at the conference.

Simburger, Edward J.↗
NASA NTRS2008

Innovative Applications of Laser Scanning and Rapid Prototype Printing to Rock Breakdown Experiments

We present the novel application of two technologies for use in rock breakdown experiments, i.e. close-range, ground-based 3D triangulation scanning and rapid prototype printing. These techniques aid analyses of form-process interactions across the range of scales relevant to breakdown (micron-m). This is achieved through (a) the creation of DEMs (which permit quantitative description and analysis of rock surface morphology and morphological change) and (b) the production of more realistically-shaped experimental blocks. We illustrate the use of these techniques, alongside appropriate data analysis routines, in experiments designed to investigate the persistence of fluvially-derived features in the face of subsequent wind abrasion and weathering. These techniques have a range of potential applications in experimental field and lab-based geomorphic studies beyond those specifically outlined here.

Bourke, Mary↗
NASA NTRS2014

Hurricane Imaging Radiometer

The Hurricane Imaging Radiometer (HIRAD) is a synthetic thinned array passive microwave radiometer designed to allow retrieval of surface wind speed in hurricanes, up through category five intensity. The retrieval technology follows the Stepped Frequency Microwave Radiometer (SFMR), which measures surface wind speed in hurricanes along a narrow strip beneath the aircraft. HIRAD maps wind speeds in a swath below the aircraft, about 50-60 km wide when flown in the lower stratosphere. HIRAD has flown in the NASA Genesis and Rapid Intensification Processes (GRIP) experiment in 2010 on a WB-57 aircraft, and on a Global Hawk unmanned aircraft system (UAS) in 2012 and 2013 as part of NASA's Hurricane and Severe Storms Sentinel (HS3) program. The GRIP program included flights over Hurricanes Earl and Karl (2010). The 2012 HS3 deployment did not include any hurricane flights for the UAS carrying HIRAD. The 2013 HS3 flights included one flight over the predecessor to TS Gabrielle, and one flight over Hurricane Ingrid. This presentation will describe the HIRAD instrument, its results from the 2010 and 2013 flights, and potential future developments.

Cecil, Daniel J.↗
NASA NTRS2017

Aeroelastic Uncertainty Quantification Studies Using the S4T Wind Tunnel Model

This paper originates from the joint efforts of an aeroelastic study team in the Applied Vehicle Technology Panel from NATO Science and Technology Organization, with the Task Group number AVT-191, titled "Application of Sensitivity Analysis and Uncertainty Quantification to Military Vehicle Design." We present aeroelastic uncertainty quantification studies using the SemiSpan Supersonic Transport wind tunnel model at the NASA Langley Research Center. The aeroelastic study team decided treat both structural and aerodynamic input parameters as uncertain and represent them as samples drawn from statistical distributions, propagating them through aeroelastic analysis frameworks. Uncertainty quantification processes require many function evaluations to asses the impact of variations in numerous parameters on the vehicle characteristics, rapidly increasing the computational time requirement relative to that required to assess a system deterministically. The increased computational time is particularly prohibitive if high-fidelity analyses are employed. As a remedy, the Istanbul Technical University team employed an Euler solver in an aeroelastic analysis framework, and implemented reduced order modeling with Polynomial Chaos Expansion and Proper Orthogonal Decomposition to perform the uncertainty propagation. The NASA team chose to reduce the prohibitive computational time by employing linear solution processes. The NASA team also focused on determining input sample distributions.

Nikbay, Melike↗
NASA NTRS1994

Development of a Prototype Real-Time Automated Filter for Operational Deep Space Navigation

Operational deep space navigation has in the past, and is currently, performed using systems whose architecture was designed to accommodate tape data transfers and computing environments with a tiny fraction of the current capability. Additionally, this architecture requires constant human supervision and intervention. A prototype for a system which allows relatively automated processing of radio metric data received in near real-time from NASA's Deep Space Network (DSN) without any redesign of the existing operational flow has been developed. This system will allow for more rapid response as well as much reduced staffing to support mission navigation operations.

deep↗
DOE OSTI2024

CH 3 Radical Generation in Microplasmas for Up-Conversion of Methane

The conversion of methane, CH 4 , into higher value chemicals using low temperature plasmas is challenged by both improving efficiency and selectivity. One path towards selectivity is capturing plasma produced methyl radicals, CH 3 , in a solvent for aqueous processing. Due to the rapid reactions of methyl radicals in the gas phase, the transport distance from production of the CH 3 to its solvation should be short, which then motivates the use of microplasmas. The generation of CH 3 in Ar/CH 4 /H 2 O plasmas produced in nanosecond pulsed dielectric barrier discharge microplasmas is discussed using results from a computational investigation. The microplasma is sustained in the channel of a microfluidic chip in which the solvent flows along one wall or in droplets. CH 3 is primarily produced by electron-impact of and dissociative excitation transfer to CH 4 , as well as CH 2 reacting with CH 4 . CH 3 is rapidly consumed to form C 2 H 6 which, in spite of being subject to these same dissociative processes, accumulates over time, as do other stable products including C 3 H 8 and CH 3 OH. The gas mixture and electrical properties were varied to assess their effects on CH 3 production. CH 3 production is largest with 5% CH 4 in the Ar/CH 4 /H 2 O mixture due to an optimal balance of electron-impact dissociation, which increases with CH 4 percentage, and dissociative excitation transfer and CH 2 reacting with CH 4 , which decrease with CH 4 percentage. Design parameters of the microchannels were also investigated. Increasing the permittivity of the dielectrics in contact with the plasma increased the ionization wave intensity which increased CH 3 production. Increased energy deposition per pulse generally increased CH 3 production as does lengthening pulse length up to a certain point. The arrangement of the solvent flow in the microchannel can also affect the CH 3 density and fluence to the solvent. The fluence of CH 3 to the liquid solvent is increased if the liquid is immersed in the plasma as a droplet or is a layer on the wall where the ionization wave terminates. The solvation dynamics of CH 3 with varying numbers of droplets was also examined. Here, the maximum density of solvated methyl radicals CH 3aq occurs with a large number of droplets in the plasma. However, the solvated CH 3aq density can rapidly decrease due to desolvation, emphasizing the need to quickly react the solvated species in the solvent.

03 NATURAL GAS↗
DOE OSTI2024

Deep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition

Abstract Materials synthesis platforms that are designed for autonomous experimentation are capable of collecting multimodal diagnostic data that can be utilized for feedback to optimize material properties. Pulsed laser deposition (PLD) is emerging as a viable autonomous synthesis tool, and so the need arises to develop machine learning (ML) techniques that are capable of extracting information from in situ diagnostics. Here, we demonstrate that intensified-CCD image sequences of the plasma plume generated during PLD can be used for anomaly detection and the prediction of thin film growth kinetics. We develop multi-output (2 + 1)D convolutional neural network regression models that extract deep features from plume dynamics that not only correlate with the measured chamber pressure and incident laser energy, but more importantly, predict parameters of an auto-catalytic film growth model derived from in situ laser reflectivity experiments. Our results demonstrate how ML with in situ plume diagnostics data in PLD can be utilized to maintain deposition conditions in an optimal regime. Further, the predictive capabilities of plume dynamics on the kinetics of film growth or other film properties prior to deposition provides a means for rapid pre-screening of growth conditions for the non-expert, which promises to accelerate materials optimization with PLD.

36 MATERIALS SCIENCE↗
DOE OSTI2022

ClusterCAD 2.0: an updated computational platform for chimeric type I polyketide synthase and nonribosomal peptide synthetase design

Abstract Megasynthase enzymes such as type I modular polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs) play a central role in microbial chemical warfare because they can evolve rapidly by shuffling parts (catalytic domains) to produce novel chemicals. If we can understand the design rules to reshuffle these parts, PKSs and NRPSs will provide a systematic and modular way to synthesize millions of molecules including pharmaceuticals, biomaterials, and biofuels. However, PKS and NRPS engineering remains difficult due to a limited understanding of the determinants of PKS and NRPS fold and function. We developed ClusterCAD to streamline and simplify the process of designing and testing engineered PKS variants. Here, we present the highly improved ClusterCAD 2.0 release, available at https://clustercad.jbei.org. ClusterCAD 2.0 boasts support for PKS-NRPS hybrid and NRPS clusters in addition to PKS clusters; a vastly enlarged database of curated PKS, PKS-NRPS hybrid, and NRPS clusters; a diverse set of chemical ‘starters’ and loading modules; the new Domain Architecture Cluster Search Tool; and an offline Jupyter Notebook workspace, among other improvements. Together these features massively expand the chemical space that can be accessed by enzymes engineered with ClusterCAD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Application of Raman Spectroscopy to Determine Uranium Content in ADUN Solution

The work presented in this report is part of the ongoing efforts to address the nuclear material control and accounting needs for advanced reactor fuel fabrication facilities. This work was supported by the Materials Protection, Accounting, and Control Technologies (MPACT) program under the US Department of Energy Office of Nuclear Energy‘s Nuclear Fuel Cycle and Supply Chain program. The activities and engagements under the MPACT program are designed to support a robust US civilian nuclear energy enterprise. In the work described in this report, we supported MPACT objectives by developing measurement techniques that could be used for material accounting and process monitoring and by working with industry partners to identify existing gaps and areas for improvement. Oak Ridge National Laboratory has been working with commercial tristructural isotropic (TRISO) fuel fabricators such as Standard Nuclear to develop technology for rapid and cost-effective uranium content assessment. This work has focused on demonstrating advanced measurement techniques (e.g., Raman spectroscopy) that can be used for rapid, reliable, and cost-effective routine measurements of uranium content in feed solutions and liquid waste streams as well as for monitoring in-line process measurements and product streams. Specifically, this report explores techniques for accurately determining uranium content in acid-deficient uranyl nitrate (ADUN) solutions and detecting low uranium concentrations in ammonia solutions. Developing such measurement techniques will benefit TRISO fuel fabrication facilities, facilities involved in other parts of the fuel cycle that require online monitoring of aqueous solutions, and potentially molten salt fuel reactors. This work supports developing Raman spectroscopy procedures to determine uranium concentrations in ADUN solutions, which are used as feedstock in the sol–gel process for creating TRISO fuel. Some additional benefits of using Raman spectroscopy for uranium quantification in fabrication facilities include enabling online monitoring of the chemical process, which would provide near real-time feedback; eliminating the need for sample transfers, preparation, or dilution; providing nondestructive measurements; and user friendliness. In this fiscal year, FY25, we determined the identity of the unknown Raman band at approximately 853 cm−1 that was discovered in ADUN Raman spectra in FY24, created calibration curves and determined uranium concentrations of two ADUN solutions, and compared the Raman results to results obtained from inductively coupled plasma mass spectrometry and Davies–Gray titration. Furthermore, we have identified focus areas for experimentation in future fiscal years. A key result is that the accuracy of using Raman can provide accuracy comparable to destructive analysist techniques, With a well-developed calibration curve, using standards and a large number of samples (more than five samples), uncertainty on the order of 1%–3% is achievable. Given that the uncertainties achieved by Raman spectroscopy were on the order of the uncertainties achieved using ICP-MS, we conclude that with a well-developed procedure Raman spectroscopy can be used to determine uranium concentrations in ADUN solutions for NMC&A applications. The benefits of such an approach are that the time and effort will be less than that of comparable destructive analysis techniques, with approximately the same level of technical expertise. This will be attractive to operators of fuel fabrication facilities as it will lower costs and improve efficiencies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗