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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗
DOE OSTI2023

Accelerated fission rate irradiation design, pre-irradiation characterization, and adaptation of conventional PIE methods for U-10Mo and U-17Mo

Metallic U alloys have high U density and thermal conductivity and thus have been explored since the beginning of nuclear power research. Alloys of U with modest amounts of Mo, such as U-10 wt % Mo (U-10Mo), are of particular interest because the γ-U crystal structure in this alloying addition shows prolonged stability in reactor service. Historically, radiation data on U-10Mo fuels were collected in Na fast reactors or lower temperature research reactor conditions, but little is known about irradiation behavior, particularly swelling and creep, at irradiation temperatures between 250 and 500°C. This work discusses the methodology and pre-irradiation characterization results from a U-Mo irradiation campaign performed in the High Flux Isotope Reactor at Oak Ridge National Laboratory. U-10Mo and U-17Mo samples irradiations are being completed at temperatures ranging from 250 to 500°C to three targeted fission densities between 2 × 10 20 and 1.5 × 10 21 fissions per cubic centimeter. Swelling measurement of the specimen sizes studied here required development and assessment of new methods for volume determination before and after irradiation. Laser profilometry and X-ray computation tomography (XCT) were used to provide preirradiation characterization of samples to determine the error and applicability of each to determine swelling following irradiation. These outcomes are contextualized through use of BISON simulations performed to assess the predicted expansion of U-Mo fuels subjected to the irradiation conditions of this work. Use of existing BISON fuel performance models predicted a maximum of 7% swelling under the irradiation conditions of this study. Pre-irradiation characterization revealed the as-cast U-Mo fuel samples were uniformly large-grained fully cubic U crystals with small U-C/N bearing precipitates and pores distributed throughout. Samples were found to contain a bulk porosity between .4 and 3% because of the casting process. Local porosity in areas far from large, interconnected pores was found by Slice-and-View to be under .2%. Nanometer-sized precipitates rich in C and N were identified in all samples, likely because of impurities during the fabrication process. Dendritic bands were also observed throughout the samples. These bands were characterized by variable Mo content that deviated from the overall Mo content by 2–3 wt %. No other microstructural features were correlated to these bands. Mechanical properties were found to be slightly strengthened compared to literature reports of bulk U-Mo fuels due to the nano-scale precipitates throughout the sample.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

GPU Acceleration in SRW: Design and Considerations

Synchrotron Radiation Workshop (SRW) is a powerful tool for simulation synchrotron radiation emission and propagation through beamline elements, enabling advanced beamline design and experimental optimization. Recently, GPU acceleration has been developed for SRW to support highly detailed end-to-end simulations of experiments at synchrotron light sources. This work documents the design and implementation of this GPU acceleration support, addressing the complexities of adapting CPU-based components to heterogeneous computing architectures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Synergistic Integration of Multiple Wave Energy Converters with Adaptive Resonance and Offshore Floating Wind Turbines through Bayesian Optimization

We developed a synergistic ocean renewable system where an array of Wave Energy Converters (WEC) with adaptive resonance was collocated with a Floating Offshore Wind Turbine (FOWT) such that the WECs, capturing wave energy through the resonance adapting to varying irregular waves, consequently reduced FOWFT loads and turbine motions. Combining Surface-Riding WECs (SR-WEC) individually designed to feasibly relocate their natural frequency at the peak of the wave excitation spectrum for each sea state, and to obtain the highest capture width ratio at one of the frequent sea states for annual average power in a tens of kilowatts scale with a 15 MW FOWT based on a semi-submersible, Bayesian Optimization is implemented to determine the arrangement of WECs that minimize the annual representation of FOWT’s wave excitation spectra. The time-domain simulation of the system in the optimized arrangement is performed, including two sets of interactions: one set is the wind turbine dynamics, mooring lines, and floating body dynamics for FOWT, and the other set is the nonlinear power-take-off dynamics, linear mooring, and individual WECs’ floating body dynamics. Those two sets of interactions are further coupled through the hydrodynamics of diffraction and radiation. For sea states comprising Annual Energy Production, we investigate the capture width ratio of WECs, wave excitation on FOWT, and nacelle acceleration of the turbine compared to their single unit operations. We find that the optimally arranged SR-WECs reduce the wave excitation spectral area of FOWT by up to 60% and lower the turbine’s peak nacelle acceleration by nearly 44% in highly occurring sea states, while multiple WECs often produce more than the single operation, achieving adaptive resonance with a larger wave excitation spectra for those sea states. The synergistic system improves the total Annual Energy Production (AEP) by 1440 MWh, and we address which costs of Levelized Cost Of Energy (LCOE) can be reduced by the collocation.

Engineering↗
DOE OSTI2023

Nuclear Smuggling Detection and Deterrence (NA-213) [Slides]

The risk of a terrorist group acquiring radioactive/nuclear materials requires NSDD's continuous efforts to build capacity of partner countries to deter, detect, and investigate acts of nuclear smuggling. Over the past 25 years, NSDD has and continues to deploy radiation detection equipment tailored to operational requirements with the goal of developing a layered, flexible, varied, and unpredictable nuclear detection architecture. An effective counter nuclear smuggling strategy considers both technical and operational challenges to develop the tools necessary to achieve the mission. LANL provides expert support to the NSDD mission to constantly improve and adapt to any future challenges.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy

Abstract Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation quality and speed, creating an unmet need for the acceleration of Monte Carlo (MC) dose calculation. Existing deep learning approaches to denoise the final plan MC dose fail to achieve the accuracy and speed requirements of large-scale beamlet dose calculation in the presence of a strong magnetic field for online adaptive radiotherapy planning. Our deep learning dose calculation method, DeepMC, addresses these needs by predicting low-noise dose from extremely noisy (but fast) MC-simulated dose and anatomical inputs, thus enabling significant acceleration. DeepMC simultaneously reduces MC sampling noise and predicts corrupted dose buildup at tissue-air material interfaces resulting from MR-field induced electron return effects. Here we demonstrate our model’s ability to accelerate dose calculation for daily treatment planning by a factor of 38 over traditional low-noise MC simulation with clinically meaningful accuracy in deliverable dose and treatment delivery parameters. As a post-processing approach, DeepMC provides compounded acceleration of large-scale dose calculation when used alongside established MC acceleration techniques in variance reduction and graphics processing unit-based MC simulation.

Engineering↗
DOE OSTI2020

Functional and genetic markers of niche partitioning among enigmatic members of the human oral microbiome

Abstract Introduction Microbial residents of the human oral cavity have long been a major focus of microbiology due to their influence on host health and intriguing patterns of site specificity amidst the lack of dispersal limitation. However, the determinants of niche partitioning in this habitat are yet to be fully understood, especially among taxa that belong to recently discovered branches of microbial life. Results Here, we assemble metagenomes from tongue and dental plaque samples from multiple individuals and reconstruct 790 non-redundant genomes, 43 of which resolve to TM7, a member of the Candidate Phyla Radiation, forming six monophyletic clades that distinctly associate with either plaque or tongue. Both pangenomic and phylogenomic analyses group tongue-specific clades with other host-associated TM7 genomes. In contrast, plaque-specific TM7 group with environmental TM7 genomes. Besides offering deeper insights into the ecology, evolution, and mobilome of cryptic members of the oral microbiome, our study reveals an intriguing resemblance between dental plaque and non-host environments indicated by the TM7 evolution, suggesting that plaque may have served as a stepping stone for environmental microbes to adapt to host environments for some clades of microbes. Additionally, we report that prophages are widespread among oral-associated TM7, while absent from environmental TM7, suggesting that prophages may have played a role in adaptation of TM7 to the host environment. Conclusions Our data illuminate niche partitioning of enigmatic members of the oral cavity, including TM7, SR1, and GN02, and provide genomes for poorly characterized yet prevalent members of this biome, such as uncultivated Flavobacteriaceae.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Physical effects on compact high-velocity clouds in the circumgalactic medium

ABSTRACT We numerically investigate the evolution of compact high-velocity clouds (CHVCs) passing through a hot, tenuous gas representing the highly ionized circumgalactic medium (CGM) by applying the adaptive-mesh refinement code flash. The model clouds start from both hydrostatic and thermal equilibrium and are in pressure balance with the CGM. Here, we present 14 models, divided into two mass categories and two metallicities each and different velocities. We allow for self-gravity and thermal conduction or not. All models experience mass diffusion, radiative cooling, and external heating leading to dissociation and ionization. Our main findings are (1) self-gravity stabilizes clouds against Rayleigh–Taylor instability, which is disrupted within 10 sound-crossing times without; (2) clouds can develop Jeans-instable regions internally even though they are initially below Jeans mass; (3) all clouds lose mass by ram pressure and Kelvin–Helmholtz instability; (4) thermal conduction substantially lowers mass-loss rates, by this, extending the clouds’ lifetimes, particularly, more than doubling the lifetime of low-mass clouds; (5) thermal conduction leads to continuous, filamentary stripping, while the removed gas is heated up quickly and mixes efficiently with the ambient CGM; (6) without thermal conduction the removed gas consists of dense, cool, clumpy fragments; (7) thermal conduction might prevent CHVCs from forming stars; and (8) clouds decelerated by means of drag from the ambient CGM form head-tail shapes and collapse after they reach velocities characteristic for intermediate-velocity clouds. Conclusively, only sophisticated modelling of CHVCs as non-homogeneous and non-isothermal clouds with thermal conduction and self-gravity explains observed morphologies and naturally leads to the suppression of star formation.

Sander, Bastian↗
DOE OSTI2021

Application of Markov Chain Monte Carlo Methods for Uncertainty Quantification in Inverse Transport Problems

Determination of the components of a radioactive source/shield system using the system’s radiation signature is of great importance in homeland security, material safeguards, and waste management. Although significant progress has been made toward solving this inverse transport problem in recent years, work remains to be done to quantify the uncertainty in reconstructed results. In this article we apply two Markov chain Monte Carlo (MCMC) approaches, the delayed rejection adaptive metropolis (DRAM) and differential evolution adaptive metropolis (DREAM) methods, to solve inverse problems and quantify uncertainty. The DRAM method uses delayed rejection combined with global adaptation of the proposal covariance matrix. Furthermore, the DREAM method hybridizes MCMC sampling with the differential evolution (DE) algorithm. In numerical test cases, the DRAM and DREAM methods are shown to be superior to a first-order inverse Hessian approach for problems with noisy data and multiple unknown quantities, with DREAM converging to the posterior distribution more quickly than DRAM. The DREAM and DRAM results indicate that a full posterior distribution is required to quantify uncertainty in many inverse transport problems.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Fabrication of Flexible Perovskite Solar Cells via Rapid Thermal Annealing

Adaptability, lightweight, and low cost of materials make flexible perovskite solar cells essential for the perovskite technology to breach commercial photovoltaic market. Roll-to-roll manufacturing has great potential for high-throughput perovskite manufacturing; however, conventional annealing methods are not capable of producing flexible perovskite solar cells at scale. Rapid thermal annealing (RTA), a radiative method, is utilized on roll-to-roll lines within many different industries and has shown promising potential for perovskite annealing. Here, we introduce a blade-coated perovskite thin film on flexible ITO-coated PET annealed via RTA that reduces post-deposition processing time from ~150 seconds to ~14 seconds. Performance was not sacrificed for scalability as a perovskite solar cell was produced with a power conversion efficiency (PCE) of 14.58%.

Martin, Blake↗
DOE OSTI2022

Role of chemical disorder on radiation-induced defect production and damage evolution in NiFeCoCr

Understanding chemical disorder in many concentrated solid solution alloys (CSAs) at the levels of electrons and atoms has attracted increasing attention as a path forward to reveal and identify underlying mechanisms for extraordinary mechanical properties and improved radiation tolerance. Single-phase NiFeCoCr CSA is a common base for many high-entropy alloys (HEAs) that have shown improved mechanical strength and radiation tolerance. In this study, defect production and damage evolution in NiFeCoCr under ion irradiation at room temperature to dose over 20 dpa are determined using ion channeling technique along both <100> and <110> directions utilizing multiple probing beam energies. The results obtained from the multi-axial and multi-energy channeling analysis are compared with those previously obtained for Ni crystals irradiated under similar conditions. The influence of chemical complexity on defect production and clustering at early-stage under room temperature irradiation up to dose of 1 dpa is discussed based on positron annihilation spectroscopy results. Defect structure evaluation in Ni and NiFeCoCr is also discussed based on transmission electron microscopy results over a prolonged irradiation at both room and elevated temperatures. Compared with chemically complex NiFeCoCr, larger dislocation loops thus less lattice strain are expected to form in pure Ni. Moreover, the role of chemical disorder in this CSA is also investigated based on ab initio calculations using large supercells. Finally, to understand the impact of chemical complexity effect on defect structure evolution, this integrated research effort attempts to link the relatively large charge redistribution due to difference in valence electron counts resulting from alloying different 3d transition metal elements, moderate lattice distortion arising from similar adaptable atomic size, and notable suppressed or delayed damage evolution in NiFeCoCr.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An adaptive masking method for beam halo measurement by a digital micro mirror device

We report that in high intensity particle beams, irregularities in cathode emission, scattering effects, dark current and space charge forces can lead to a common phenomenon termed beam halo with associated emittance growth, beam loss and overall beam quality degradation. It is of fundamental interest and practical importance to precisely monitor such beam halo, which could offer valuable insights into the experimental strategy for the suppression of this undesired feature. A Digital Micro mirror Device (DMD) is a computer-controlled micro-electrical-mechanical system that contains a compact array of physically independent reflective mirrors. Using a standard DMD, we come up with an adaptive masking method for halo measurement, which demonstrates superior robustness and efficiency comparing to the conventional approaches as confirmed by simulation and experimental results. Our development includes an integrated package of hardware, software and a graphic user interface (GUI) that is robust and portable and can be applied as a beam halo diagnostic for electron guns or radiating charged particle beams in general.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Standardizing experimental approaches to investigate interactions between bacteria and ectomycorrhizal fungi

Bacteria and ectomycorrhizal fungi (EcMF) represent two of the most dominant plant root-associated microbial groups on Earth, and their interactions continue to gain recognition as significant factors that shape forest health and resilience. Yet, we currently lack a focused review that explains the state of bacteria-EcMF interaction research in the context of experimental approaches and technological advancements. To these ends, we illustrate the utility of studying bacteria-EcMF interactions, detail outstanding questions, outline research priorities in the field, and provide a suite of approaches that can be used to promote experimental reproducibility, field advancement, and collaboration. Though this review centers on the ecology of bacteria, EcMF, and trees, it by default offers experimental and conceptual insights that can be adapted to various subfields of microbiology and microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Bayesian Exploration and Surrogate Emulation of Nonlinear Beam-Response Geometry in the LBNF Beamline

Next-generation long-baseline neutrino experiments aim to achieve multi-MW proton beam power while reducing accelerator-induced systematic uncertainties. At Fermilab, the LBNF beamline is designed for 1.2 MW operation with PIP-II and is upgradeable to 2.4 MW. DUNE will probe the three-flavor neutrino paradigm and search for CP violation, requiring precise neutrino-flux normalization and improved control of accelerator-related uncertainties. Within the LBNF beamline, the System for On-Axis Neutrino Detection (SAND) will constrain flux uncertainties using precision near-detector measurements, while the Muon Monitor System (MuMS) will provide beamline diagnostics sensitive to the proton beam, target, and horn configuration. However, the pion phase space relevant for DUNE depends simultaneously on many correlated parameters, including beam centroid, beam width, horn current and alignment, target position, optics shifts, and radiation-induced changes. Consequently, MuMS observables exhibit nonlinear and coupled responses that are difficult to characterize using traditional one-parameter scans. To address this challenge, we are developing a Bayesian Exploration framework coupled to physics-informed surrogate emulators trained on Geant4 beamline simulations. Gaussian-process emulators provide both fast predictions and uncertainty estimates, enabling adaptive selection of new simulation points in beam-parameter space. As an initial demonstration, we construct surrogate emulators for MuMS response observables using a verified simulation campaign spanning proton-beam steering conditions. The emulators reproduce the simulated dependence of MuMS centroid and gradient observables while providing predictive uncertainties, and serve as the foundation for future multidimensional exploration including beam width, horn current, and additional beamline parameters. This work establishes a framework for uncertainty-aware beam monitoring, adaptive simulation campaigns, and rapid beam-response inference for future DUNE operations.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗
DOE OSTI2022

The effect of saturated thermal conduction on clouds in a hot plasma

We numerically investigate the internal evolution of multiphase clouds, which are at rest with respect to an ambient, highly ionized medium (HIM) representing the hot component of the circumgalactic medium. Time-dependent saturated thermal conduction and its implications like condensation rates and mixing efficiency are assessed in multiphase clouds. Our simulations are carried out by using the adaptive mesh refinement code FLASH. The model clouds are initially in both hydrostatic and thermal equilibrium and are in pressure balance with the HIM. Thus, they have steep gradients in both temperature and density at the interface to HIM leading to non-negligible thermal conduction. Several physical processes are considered numerically or semi-analytically: thermal conduction, radiative cooling and external heating of gas, self-gravity, mass diffusion, and dissociation of molecules and ionization of atoms. It turns out that saturated thermal conduction triggers a continuous condensation irrespective of cloud mass. Dynamical interactions with ambient HIM all relate to the radial density gradient in the clouds: (1) mass flux due to condensation is the higher the more homogeneous the clouds are; (2) mixing of condensed gas with cloud gas is easier in low-mass clouds, because of their shallower radial density gradient; and thus (3) accreted gas is distributed more efficiently. A distinct and sub-structured transition zone forms at the interface between cloud and HIM, which starts at smaller radii and is much narrower as deduced from analytical theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Advanced Reactors Integrated Energy System: Thermal Energy Storage Island Design

The main topic of this research is integrated energy systems (IES) designed for pairing industrial thermal energy loads with advanced reactors (ARs). The Idaho National Laboratory (INL) Crosscutting Technology Development IES program and the National Reactor Innovation Center (NRIC) are seeking to develop, design, and construct an AR-IES demonstration platform that couples the thermal output from an AR operating at the INL/NRIC Demonstration of Microreactor Experiments (DOME) test bed in the Experimental Breeder II dome to a variable capacity load emulator (i.e., air-cooled radiator) and sensible thermal energy storage (TES) via a molten salt thermal energy transfer fluid. In the rapidly evolving landscape of energy supply and distribution, flexibility has emerged as a prized attribute, surpassing the traditional notions of stability and baseload generation capability. This shift in priorities is particularly evident in the context of nuclear power plants (NPPs), where adaptability over constant output is becoming more important. As our energy infrastructure and resources embraces the rise of distributed energy generation, the inherent variability in net demand continues to grow. Moreover, the use of nuclear energy as a source of heat for decarbonizing the industrial sector is becoming a very pressing topic. In such environment, advanced NPPs are poised to enter a more competitive energy market, delivering both, flexible electricity and heat. This shift motivates the exploration of TES systems, designed to empower NPPs with nimble responsiveness to market fluctuations, flexible heat delivery capabilities, and redefine their role in the energy field. TES systems offer the unique advantage of storing nuclear energy in its original form as heat, thereby affording unparalleled flexibility in its subsequent utilization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Adapting confocal Raman microscopy for in situ studies of redox transformations at electrode-electrolyte interfaces

Confocal Raman microscopy was applied to quantify redox species present within the diffusion layer adjacent to an electrode surface under potentiostatic control. A glass microscope coverslip with a thin indium tin oxide (ITO) coating served as both the working electrode and optical window for a microscope-stage mountable spectroelectrochemical cell. A high numerical aperture objective mounted in an inverted microscope frame just below the stage brought excitation radiation through the coverslip window and to a tight focus a few micrometers above the ITO film surface. Species diffusing into the confocal probe volume defined by the excitation beam focus and the collected light region were detected, identified and quantified based on their Raman scattering frequencies and intensities. Here, in measurements that interrogated the interconversion of ferrocyanide and ferricyanide ions as a function of applied voltage, least-squares regression analysis of spectral datasets predicted the formal potential and relative surface concentrations of the ions in good agreement with the expected Nernstian response. Preliminary studies of methyl viologen reduction at an ITO film/Nafion membrane interface were conducted and show the possibility for estimation of mass transport coefficients of redox species within ionic polymer materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗