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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantitative temporally and spatially resolved X-ray fluorescence microprobe characterization of the manganese dissolution-deposition mechanism in aqueous Zn/α-MnO 2 batteries

Rechargeable aqueous Zn/α-MnO 2 batteries are a possible alternative to lithium ion batteries for scalable stationary energy storage applications due to their low cost, safety and environmentally benign components. A critical need for advancement of this battery system is a full understanding of the electrochemical reaction mechanisms, which remain unclear. In this report, operando , spatiotemporal resolved synchrotron X-ray fluorescence mapping measurements on a custom aqueous Zn/α-MnO 2 cell provided direct evidence of a Mn dissolution-deposition faradaic mechanism that governs the electrochemistry. Simultaneous visualization and quantification of the Mn distribution in the electrolyte revealed the formation of aqueous Mn species during discharge and depletion on charge. The findings are supported by ex situ transmission electron microscopy (TEM), X-ray diffraction, Mn K-edge X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) measurements. The elucidated mechanism is fundamentally different from the previously proposed Zn 2+ insertion or conversion reactions. These findings provide a foundation for developing dissolution- deposition chemistries suitable for scalable stationary energy storage with aqueous electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2022

Tracer-field cross-correlations with k -nearest neighbour distributions

ABSTRACT In astronomy and cosmology significant effort is devoted to characterizing and understanding spatial cross-correlations between points – e.g galaxy positions, high energy neutrino arrival directions, X-ray and AGN sources, and continuous fields – e.g. weak lensing meiand Cosmic Microwave Background maps. Recently, we introduced the k-nearest neighbour (kNN) formalism to better characterize the clustering of discrete (point) data sets. Here, we extend it to the point – field cross-correlations analysis. It combines kNN measurements of the point data set with measurements of the field smoothed at many scales. The resulting statistics are sensitive to all orders in the joint clustering of the points and the field. We demonstrate that this approach, unlike the 2-pt cross-correlation, can measure the statistical dependence of two data sets even when there are no linear (Gaussian) correlations between them. We further demonstrate that this framework is far more effective than the two point function in detecting cross-correlations when the continuous field is contaminated by high levels of noise. For a particularly high level of noise, the cross-correlation between haloes and the underlying matter field in a cosmological simulation, between 10 h−1 Mpc and 30 h−1 Mpc, is detected at >5σ significance using the technique presented here, when the two-point cross-correlation significance is ∼1σ. Finally, we show that kNN cross-correlations of haloes and the matter field can be well modelled on quasi-linear scales using the Hybrid Effective Field Theory (HEFT) framework, with the same set of bias parameters as are used for 2-pt cross-correlations. The substantial improvement in the statistical power of detecting cross-correlations using this method makes it a promising tool for various cosmological applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Space-time generalization of mutual information

The mutual information characterizes correlations between spatially separated regions of a system. Yet, in experiments we often measure dynamical correlations, which involve probing operators that are also separated in time. Here, we introduce a space-time generalization of mutual information which, by construction, satisfies several natural properties of the mutual information and at the same time characterizes correlations across subsystems that are separated in time. In particular, this quantity, that we call the space-time mutual information, bounds all dynamical correlations. We construct this quantity based on the idea of the quantum hypothesis testing. As a by-product, our definition provides a transparent interpretation in terms of an experimentally accessible setup. We draw connections with other notions in quantum information theory, such as quantum channel discrimination. Finally, we study the behavior of the space-time mutual information in several settings and contrast its long-time behavior in many-body localizing and thermalizing systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Associated Particle Imaging of Neutron Inelastic Scatter: 3-D Reconstruction, Capabilities, and Challenges

Associated particle imaging (API) offers unique advantages for 3-D imaging of neutron inelastic scatter, including single-view tomographic imaging and data acquisition when access is limited to only one side of the interrogated object. However, widespread adoption of neutron inelastic scatter imaging has been impeded by several inherent challenges, most prominently spatial resolution, self-attenuation, and statistical noise. Here, in this work, the capabilities and challenges of neutron inelastic scatter imaging are investigated. Instead of focusing on a single imaging application, we identify imaging principles that hold for various neutron inelastic scatter imaging techniques. The primary challenges for 3-D imaging are characterized. The inherent spatial resolution in the time-of-flight (TOF) dimension is derived based on the known system timing resolution and scan geometry. Three reconstruction algorithms are described and demonstrated, including the introduction of modern iterative reconstruction incorporating a physics-based system model. Simulation is leveraged to demonstrate imaging capability with varying coincidence count levels and system timing resolution. An example of measured data with both back-scatter and forward-scatter detector positioning is presented. System design characteristics and their effects on image quality are identified. The imaging framework presented in this article has the potential to facilitate growth of 3-D neutron inelastic scatter API by identifying applications that are a good match for the technique and by targeting system development resources toward the requirements of a specific imaging task.

Associated particle imaging (API)↗
DOE OSTI2020

Advanced Characterization of Thin Film Solar Cells

Polycrystalline thin-film solar cells have reached a levelized cost of energy that is competitive with all other sources of electricity. The technology has significantly improved in recent years, with laboratory cell efficiencies for cadmium telluride (CdTe), perovskites, and copper indium gallium diselenide (CIGS) each exceeding 22 percent. Both CdTe and CIGS solar panels are now produced at the gigawatt scale. However, there are ongoing challenges, including the continued need to improve performance and stability while reducing cost. Advancing polycrystalline solar cell technology demands an in-depth understanding of efficiency, scaling, and degradation mechanisms, which requires sophisticated characterization methods. These methods will enable reseachers and manufacturers to improve future solar modules and systems. This work provides researchers with a concise overview of the status of thin-film solar cell technology and characterization. Chapters describe material systems and their properties and then provide an in-depth look at relevant characterization methods and the learning facilitated by each of these. Following an introductory chapter, the book provides systematic and thorough coverage of the following topics: trends to improve CdTe solar cell performance; Cu(In,Ga)Se2 and related materials; perovskite solar cells; photovoltaic device modelling; luminescence and thermal imaging of thin-film photovoltaic materials, devices, and modules; application of spatially resolved spectroscopy characterization techniques on Cu2ZnSnSe4 solar cells; time-resolved photoluminescence characterization of polycrystalline thin-film solar cells; fundamentals of electrical material and device spectroscopies applied to thin-film polycrystalline chalcogenide solar cells; nanometer-scale characterization of thin-film solar cells by atomic force microscopy-based electrical probes; scanning transmission electron microscopy characterization of solar cells; photoelectron spectroscopy methods in solar cell research; time-of-flight secondary-ion mass spectrometry and atom probe tomography; and solid-state nuclear magnetic resonance characterization for photovoltaic applications. The final chapter provides an overview and describes future prospects.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Development of a Novel Electrical Characterization Technique for Measuring Hidden Joint Contacts in Weapons Cavities (LDRD Final Report 218470)

This report summarizes research performed in the context of a REHEDS LDRD project that explores methods for measuring electrical properties of vessel joints. These properties, which include contact points and associated contact resistance, are “hidden” in the sense that they are not apparent from a computer-assisted design (CAD) description or visual inspection. As is demonstrated herein, the impact of this project is the development of electromagnetic near-field scanning capabilities that allow weapon cavity joints to be characterized with high spatial and/or temporal resolution. Such scans provide insight on the hidden electrical properties of the joint, allowing more detailed and accurate models of joints to be developed, and ultimately providing higher fidelity shielding effectiveness (SE) predictions. The capability to perform high-resolution temporal scanning of joints under vibration is also explored, using a multitone probing concept, allowing time-varying properties of joints to be characterized and the associated modulation to SE to be quantified.

42 ENGINEERING↗
DOE OSTI2021

A digital holography ex situ measurement characterization of plasma-exposed surface erosion from an electrothermal arc source

Digital holography has been proposed to fulfill a need for an imaging diagnostic capable of in situ monitoring of surface erosion caused by plasma–material interaction in nuclear fusion devices. A digital holography diagnostic for 3D surface erosion measurement has been developed at Oak Ridge National Laboratory with the goal of deployment on a plasma device. A proof-of-concept in situ demonstration is planned which would involve measurement of plasma erosion on targets exposed to an electrothermal arc source. This work presents the results of an ex situ characterization of the capability and limitations of holographic imaging of targets exposed to the arc source. Targets were designed to provide a fiducial for comparison of deformed and unaffected areas. The results indicated that the average net erosion was ~150 nm/plasma exposure, which is expected to be within the diagnostic’s measurement capacity. Surface roughness averages determined by holographic image analysis showed good agreement with measurements taken with a profilometer. Finally, the limit of the holography diagnostic’s x–y spatial resolution was characterized by comparison with scanning electron microscope imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Desorption Electrospray Ionization–Mass Spectrometry Imaging Provides Spatiochemical Information on Potential Biocontrol Agents against Phytophthora capsici Infection in Tomato Plants

Biological control agents can offer an eco-friendly and more sustainable alternative to conventional chemical pesticides, providing protection against destructive pathogens, such as Phytophthora capsici, while reducing potential environmental harm associated with synthetic pesticide use in agricultural systems. This work evaluates the biocontrol effectiveness of Bacillus vallismortis, Bacillus amyloliquefaciens, Bacillus thuringiensis, and Bacillus subtilis, against the widespread plant pathogen Phytophthora capsici. Our studies showed that Bacillus thuringiensis and Bacillus subtilis promote plant growth and provide protection against Phytophthora capsici in both in vitro and in vivo greenhouse studies, while Bacillus vallismortis and Bacillus amyloliquefaciens were effective in vitro but not in vivo. Specifically, Bacillus thuringiensis was observed to both hinder the growth of Phytophthora capsici and enhance plant resilience to this pathogen, with B. thuringiensis-treated, pathogen-exposed plants displaying a 94.4% increase in root length and a 74.0% increase in shoot height compared to plants with only oomycete exposure. To probe the molecular interactions between the biocontrol agent and pathogen, a dual culture of Bacillus thuringiensis and Phytophthora capsici was analyzed in situ using a desorption electrospray ionization–mass spectrometry imaging (DESI-MSI) workflow. This approach interrogated the spatially oriented biochemical interactions that may serve as the molecular foundation for the effectiveness of these biological control agents in crop protection, identifying seven unique phenotypic regions within the dual culture. Herein, we demonstrate the benefits of biological control agent application in tomato cultivation and showcase the strengths of desorption electrospray ionization–mass spectrometry imaging when applied to the spatially resolved molecular characterization of agriculturally relevant microorganisms.

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

The fluid definition of the ‘waters of the United States’: Non-uniform effects of regulation on US wetland protections

Recent revisions to the definition of the ‘waters of the United States’ (WOTUS) have considerably altered how wetlands are federally regulated under the Clean Water Act. The two most recent modifications to WOTUS, the Clean Water Rule (CWR) and the Navigable Waters Protection Rule (NWPR), represent two opposing approaches to the federal wetland policy. The impacts of these two rules on the regulation of wetlands have as of yet been poorly characterized at broad spatial scales. Using New York State (NYS) as a case study, we evaluated the jurisdictional statuses of more than 253 000 wetlands under the CWR and the NWPR to assess the landscape-scale effects of WOTUS re-definitions. Here, we found that statewide and within each of NYS's hydrologic regions, the NWPR protects fewer wetlands and less total wetland area than the CWR. The efficacy of the two regulations varied considerably in space across NYS, highlighting the need for comprehensive, nationwide assessments of wetland policy outcomes. We also observed that both rules produced non-uniform patterns in jurisdiction across a range of landscape positions and wetland sizes, preferentially protecting large wetlands close to the stream network. This effect was particularly pronounced under the NWPR, which excludes all geographically isolated wetlands from protection. Our findings in NYS emphasize the existence of unique patterns in protected wetlands across spatial scales, highlighting the value in applying geospatial analyses to evaluate environmental policy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗
DOE OSTI2021

Nucleon clustering at kinetic freezeout of heavy-ion collisions via path-integral Monte Carlo

Clustering of the four-nucleon system at kinetic freezeout conditions is studied using path-integral Monte Carlo techniques. This method seeks to improve upon previous calculations which relied on approximate semiclassical methods or few-body quantum mechanics. Estimates are given for the decay probabilities of the 4N system into various light nuclei decay channels and the strength of spatial correlations is characterized. Additionally, a simple model is presented to describe the impact of this clustering on nucleon multiplicity distributions. Additionally, the effects of a possible modification of the inter-nucleon interaction due to the close critical line (and hypothetical QCD critical point) on the clustering are also studied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Advancing Battery Manufacturing: Synchrotron Characterization for Industry

Large-scale battery manufacturing requires understanding the fundamental principles of materials and interfaces and relies on advanced techniques for detailed interrogation. Despite advancements in the industrial scale production and their associated quality control tools, challenges such as electrode heterogeneity, internal defects, and largescale material waste (e.g., scrap) can hamper manufacturing. Synchrotron X-ray characterization techniques offer spatial, temporal, and chemical resolution that can provide diagnostic insights for metrology across various manufacturing steps. This review examines the use of synchrotron tools to advance understanding of key steps in the battery manufacturing process. Recent examples demonstrate how synchrotron methods resolve manufacturing challenges and uncover degradation pathways that are otherwise inaccessible. Future directions for advancing battery manufacturing emphasize collaboration between academia and industry through the use of synchrotron X-ray techniques.

Batteries↗
DOE OSTI2025

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗
DOE OSTI2020

Robustness of slow contraction to cosmic initial conditions

We present numerical relativity simulations of cosmological scenarios in which the universe is smoothed and flattened by undergoing a phase of slow contraction and test their sensitivity to a wide range of initial conditions. Our numerical scheme enables the variation of all freely specifiable physical quantities that characterize the initial spatial hypersurface, such as the initial shear and spatial curvature contributions as well as the initial field and velocity distributions of the scalar that drives the cosmological evolution. In particular, we include initial conditions that are far outside the perturbative regime of the well-known attractor scaling solution. We complement our numerical results by analytically performing a complete dynamical systems analysis and show that the two approaches yield consistent results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Finite-momentum instability of a dynamical axion insulator

Due to the chiral anomaly, Weyl semimetals can exhibit a signature topological magnetoelectric response known as an axion term which is determined by the microscopic band structure. In the presence of strong interactions Weyl fermions may form a chiral condensate, with the intrinsic dynamics and fluctuations of the associated condensate phase producing a dynamical contribution to the axion response. Here we show that an imbalance in the density of right- and left-handed electrons drives an instability of the chiral condensate towards finite momentum and leads to strong fluctuations in the axion response. We derive a long-wavelength theory of Lifschitz type governing the dynamics of the Goldstone mode and use this to characterize its associated spatial fluctuations, which manifest as an inhomogeneous anomalous Hall effect. In conclusion, we show that these fluctuations produce signatures in inelastic light-scattering experiments across a broad spectrum of frequencies, and can be used to determine the structure factor for the axionic collective mode.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Generalized hydrodynamic analysis of transport through a finite open nanopore for two-component single-file systems

Single-file diffusion (SFD) in finite open nanopores is characterized by nonzero spatially varying tracer diffusion coefficients within a generalized hydrodynamic description. This contrasts with infinite SFD systems where tracer diffusivity vanishes. In standard tracer counterpermeation (TCP) analysis, two reservoirs, each containing a different species, are connected to opposite ends of a finite pore. Here, we implement an extended TCP analysis to allow the two reservoirs to contain slightly different mixtures of the two species. Then, determination of diffusion fluxes through the pore allows extraction of diffusion coefficients for near-constant partial concentrations of the two species. This analysis is applied for a lattice-gas model describing two-component SFD through a finite linear pore represented by a one-dimensional array of cells. Two types of particles, A and B, can hop only to adjacent empty cells with generally different rates, $h_A$ and $h_B$. Particles are noninteracting other than exclusion of multiple cell occupancy. Results reveal generalized hydrodynamic tracer diffusion coefficients which adopt small values inversely proportional to pore length in the pore center, but which are strongly enhanced near pore openings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Evaluation of an LED Simulator for Single- and Multi-Junction PV Cell Performance Testing

We present the evaluation of a solar simulator comprising a Light Emitting Diode (LED) array as its light source. While multiple applications can be envisioned for such a light source, here we focus on its use for performance testing of solar cells at Standard Test Conditions. With this in mind, we present characterization of the spatial uniformity of the irradiance and its temporal stability as well as the spectral range and spectral class. For a multisource simulator, the spectral uniformity across the test plane should also be evaluated and we discuss a method for performing this evaluation that is well suited to a solar cell performance testing application. One major advantage of this simulator is the ability to easily adjust the spectral output as needed in multijunction PV cell measurements and we also discuss this application here.

LED↗