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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster

ABSTRACT The Fornax galaxy cluster is the richest nearby (D ∼ 20 Mpc) galaxy association in the southern sky. As such, it provides a wealth of opportunities to elucidate on the processes where environment holds a key role in transforming galaxies. Although it has been the focus of many studies, Fornax has never been explored with contiguous homogeneous wide-field imaging in 12 photometric narrow and broad bands like those provided by the Southern Photometric Local Universe Survey (S-PLUS). In this paper, we present the S-PLUS Fornax Project (S+FP) that aims to comprehensively analyse the galaxy content of the Fornax cluster using S-PLUS. Our data set consists of 106 S-PLUS wide-field frames (FoV∼1.4 × 1.4 deg2) observed in five Sloan Digital Sky Survey-like ugriz broad bands and seven narrow bands covering specific spectroscopic features like [O ii], Ca ii H+K, Hδ, G band, Mg b triplet, Hα, and the Ca ii triplet. Based on S-PLUS specific automated photometry, aimed at correctly detecting Fornax galaxies and globular clusters in S-PLUS images, our data set provides the community with catalogues containing homogeneous 12-band photometry for ∼3 × 106 resolved and unresolved objects within a region extending over ∼208 deg2 (∼5 Rvir in RA) around Fornax’ central galaxy, NGC 1399. We further explore the eagle and IllustrisTNG cosmological simulations to identify 45 Fornax-like clusters and generate mock images on all 12 S-PLUS bands of these structures down to galaxies with M⋆ ≥ 108 M⊙. The S+FP data set we put forward in this first paper of a series will enable a variety of studies some of which are briefly presented.

Astronomy & Astrophysics↗
DOE OSTI2024

Utah FORGE: Updated FMI Fracture Log from Well 16A(78)-32

This dataset consists of an Excel spreadsheet detailing the fracture picks from a reinterpretation of the formation micro-imaging (FMI) log from Utah FORGE well 16A(78)-32. The provided information details fracture location, geometry, and type. Also included here is a link to the original raw and processed FMI logs, as well as other data from the 2021 well logging.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Overview on the theory and phenomenology of generalized parton distributions

We give a brief overview on the theory and phenomenology of generalized parton distributions (GPDs), including the recently developed framework of single-diffractive hard exclusive process for matching GPDs to experimental observables. We concentrate on the extraction of GPDs from experimental processes, especially on the challenges and potential solutions regarding the separation of different GPDs and the extraction of $x$-dependence of GPDs, which is critically important for constructing the tomographic images and matching the $x$-moments of GPDs to various emergent hadron properties.

Qiu, Jianwei↗
DOE OSTI2025

Control of machining-induced residual stress via tool geometry and process parameter modification

Distortion generated in machined, monolithic, thin-walled aerospace components due to residual stresses leads to significant material and economic waste in the manufacturing industry. Inherent residual stress (IRS) present in stock materials combines with machining-induced residual stress (MIRS) to influence the final machined part distortion. It is hypothesized that MIRS can be controlled, based on the part geometry, through deliberate cutting tool geometry and process parameter modifications to negate the effect of IRS on distortion, consequently resulting in distortion-free parts. A finite element (FE) orthogonal cutting model is developed to study how tool geometry and process parameters influence machining-induced residual stress (MIRS). Orthogonal cutting experiments are performed on Al 7075-T651 samples to measure cutting forces and MIRS. A cutting force dynamometer is used to measure forces during cutting and a novel digital image correlation (DIC) based hole drilling technique is employed to measure the near-surface residual stress (RS) in the cut samples. These data are subsequently utilized to validate the FE prediction model. Various cases of cutting simulations involving different depths of cut, tool tip radii, and rake angles are performed to study their effects on RS. Similar to prior literature, increasing the depth of cut, tool tip radius, or rake angle is found to promote the formation of near-surface tensile stresses. The competing effects of material plowing and temperature are shown to determine the type of RS at the end of the cut. Moreover, a window of variation of RS (up to ± 400 MPa) is estimated within the given range of conditions, allowing for the control of MIRS through tool and process modification.

Mathews, Ritin [ORNL] (ORCID:0000000301440828)↗
DOE OSTI2025

Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components

X-ray computed tomography (XCT) is essential for nondestructive evaluation and quality control of large-scale metal components. XCT imaging, however, faces significant challenges from metal artifacts, particularly those caused by Compton scattering, which degrade image quality and obscure critical details. Hardware-based solutions (e.g. scatterControl) offer advancements by intercepting scattered photons and reducing artifacts, but they can be time-consuming and require additional processing. Here, we propose modifying and leveraging a novel deep learning (DL) framework, Simurgh, to enhance and accelerate scatter correction in XCT. By combining scatterControl with DL-based artifact removal, we demonstrate significant reduction in scan time while producing high-quality reconstructions. Through extensive evaluation on industrial XCT data, we show that our methods reduce scan time by up to more than 10 x while preserving flaw detectability. Quantitative analysis across multiple segmentation techniques confirms that Simurgh-based reconstructions consistently outperform traditional Feldkamp-Davis-Kress, model-based iterative reconstruction, and commercial DL models in both pixel-level and task-specific evaluations, enabling scalable, high-throughput XCT workflows for characterization of large scale components in applications such as casting and metal additive manufacturing.

Complex metal parts↗
DOE OSTI2025

Giant Enhancement of Four-Wave Mixing by Doubly Zone-Folded Nonlocal Metasurfaces

Resonant optical metasurfaces hold promise for enhancing nonlinear optical signals and manipulating their fundamental properties. However, they rarely excel at amplifying signals from nonlinear processes with two incident pump beams, such as four-wave mixing (FWM) or sum-frequency generation. Frequency-mixing experiments impose challenging requirements for metasurface design due to the need to support multiple optical resonances with compatible field profiles at specified resonant wavelengths, often across a substantial spectral separation. Here, in this work, we introduce nonlocal ‘quadromer’ metasurfaces containing four nanostructures per unit cell as the key to unlocking configurable, multiresonant metasurfaces that enhance frequency-mixing processes. As a proof of concept, we experimentally demonstrate enhanced FWM using quadromer metasurfaces made of silicon and silicon-rich silicon nitride. The results are relevant for applications such as imaging of infrared light upconverted into the visible spectrum and the generation of quantum light via spontaneous FWM.

four-wave mixing↗
DOE OSTI2025

Sequence Diagrams & PFMEA Table - VGI [SWR-25-107]

As part of the VGI work under the National Charging Experience (ChargeX) Consortium, reliability analysis of communication interfaces for multiple SCM/VGI use-cases was performed using a Process Failure Modes and Analysis (PFMEA) style framework. This repository hosts all the relevant files for each of these use-cases which include: *A visual representation of their communication architecture: Image file (.png) *UML sequence diagram: Plant-UML source file (.puml). Visio file (.vsdx) and image file (.png) derived from the UML sourceX` *The PFMEA table: Excel file (.xlsx) These files are meant to serve as a starting point and can be adapted to company / organization specific SCM implementation.

Gadamsetty, Pranav [National Renewable Energy Labo↗
DOE OSTI2024

Infrared Imaging Using Thermally Stable HgTe/CdS Nanocrystals

Transferring nanocrystals (NCs) from the laboratory environment toward practical applications has raised new challenges. HgTe appears as the most spectrally tunable infrared colloidal platform. Its low-temperature synthesis reduces the growth energy cost yet also favors sintering. Once coupled to a read-out circuit, the Joule effect aggregates the particles, leading to a poorly defined optical edge and large dark current. Here, in this study, we demonstrate that CdS shells bring the expected thermal stability (no redshift upon annealing, reduced tendency to form amalgams, and preservation of photoconduction after an atomic layer deposition process). The electronic structure of these confined particles is unveiled using k.p self-consistent simulations showing a significant exciton binding energy of ~ 200 meV. After shelling, the material displays a p-type behavior that favors the generation of photoconductive gain. The latter is then used to increase the external quantum efficiency of an infrared imager, which now reaches 40% while presenting long-term stability.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Formation of zinc carbonate phases on dissolving calcite, aragonite, and vaterite in acidic aqueous solutions

Calcium carbonate (CaCO 3 ) minerals serve as a major sink to retain metal ions through mineral-water interfacial reactions in which the capacity and long-term stability of contaminant uptake are influenced by coupled dissolution and precipitation reactions of both primary and secondary carbonate minerals (i.e., mineral replacement). Notably, recent studies of calcite reactivity in acidic solutions containing high levels of metal ions demonstrated complex behavior under conditions of sustained disequilibrium. Here, we explored the reactivity of three CaCO 3 polymorphs (calcite, aragonite, and vaterite) with acidic Zn 2+ -containing aqueous solutions using a suite of imaging techniques including optical and scanning electron microscopies, synchrotron-based micro X-ray fluorescence, and transmission X-ray microscopy. Zn uptake by calcite occurred through a two-step process: the formation of a thin layer of the zinc precipitate on the substrate surface followed by the growth of fibrous and radiating hydrozincite particles from the layer. In contrast, Zn uptake by aragonite occurred by mineral replacement where the secondary Zn carbonate phase preserved the external morphology of the original crystal (i.e., a pseudomorph). The replacement of vaterite by hydrozincite occurred within the confined space beneath the porous shell of vaterite, signifying that the primary mechanism driving Zn carbonate precipitation was chemical exchange through the pores. When multiple CaCO 3 polymorphs coexisted, the replacement of aragonite and vaterite occurred preferentially over that of calcite. These results demonstrate the distinct morphological and mineralogical controls over the reactivities of calcium carbonate minerals with Zn 2+ under acidic conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Co-orchestration of multiple instruments to uncover structure–property relationships in combinatorial libraries

The rapid growth of automated and autonomous instrumentation brings forth opportunities for the co-orchestration of multimodal tools that are equipped with multiple sequential detection methods or several characterization techniques to explore identical samples. This is exemplified by combinatorial libraries that can be explored in multiple locations via multiple tools simultaneously or downstream characterization in automated synthesis systems. In co-orchestration approaches, information gained in one modality should accelerate the discovery of other modalities. Correspondingly, an orchestrating agent should select the measurement modality based on the anticipated knowledge gain and measurement cost. Herein, we propose and implement a co-orchestration approach for conducting measurements with complex observables, such as spectra or images. The method relies on combining dimensionality reduction by variational autoencoders with representation learning for control over the latent space structure and integration into an iterative workflow via multi-task Gaussian Processes (GPs). This approach further allows for the native incorporation of the system's physics via a probabilistic model as a mean function of the GPs. We illustrate this method for different modes of piezoresponse force microscopy and micro-Raman spectroscopy on a combinatorial Sm-BiFeO3 library. However, the proposed framework is general and can be extended to multiple measurement modalities and arbitrary dimensionality of the measured signals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Mixed Element Microparticle Characterization by Electron Probe Microanalysis

Abstract Microparticle compositional characterization for nuclear forensics has traditionally been achieved by “gold-standard” destructive analytical techniques such as large geometry-secondary ion mass spectrometry and fission track-thermal ionization mass spectrometry, but long processing times and total sample consumption eliminate the option of subsequent analysis by other methods. Electron probe microanalysis has long been widely employed for rapid, nondestructive, micrometer-scale compositional measurements and imaging in fields such as material science and geology and may therefore need to be reevaluated as an alternative tool for microparticle analysis for the nuclear forensics community. This study presents the use of electron probe microanalysis for imaging and quantitative characterization of homogeneous microparticles utilizing a calibration curve based on high-precision quadrupole-inductively coupled plasma-mass spectrometry analyses. Samples of opportunity synthesized at Savannah River National Laboratory, nickel-doped cerium oxide microparticles, were selected as analogs for plutonium-doped uranium oxide microparticles. Positive detection and accurate quantification of variable amounts of nickel dopant down to trace levels (10s of parts per million) suggest applicability of this technique to other mixed element systems (e.g., actinides). Quantitative single-particle characterization via electron probe microanalyzer may thus provide a high fidelity, nondestructive complement to techniques currently in use.

Riche, Alexis T. (ORCID:0009000121978126)↗
DOE OSTI2024

Investigation of the cesium activation of Ga⁢N photocathodes by low-energy electron microscopy

Low-energy electron microscopy (LEEM) was performed on p-Ga⁢N samples during in situ cesium deposition. LEEM images of electron reflectivity recorded as a function of the incident electron energy at different Cs coverages allowed to spatially resolve the evolution of the local work function (WF) during the activation process. While the average WF drops by more than 3 eV, the local WF remains quite uniform across the surface throughout the activation process. Maximum fluctuations of less than 0.2 eV were observed in the WF maps for Cs coverage of a fraction of a monolayer. These fluctuations are mainly related to the surface topography, in particular, to the atomic steps’ structure, which replicates the substrate miscut. Apart from these weak spatial fluctuations, no Cs clusters that would induce strong local WF contrast were observed at the scale of the 20-nm resolution of the measurements. These observations agree with the simple model of semiconductor activation to negative electron affinity that describes the formation of a dipole layer as responsible for the lowering of the WF. Additionally, at complete Cs coverage, the WF becomes fully homogeneous over the surface, smoothing out features originating from defects and topography.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Revealing multiscale competing processes in the solid-state synthesis of single-crystalline layered oxide positive electrodes

Solid-state synthesis involves a web of coupled chemical reactions and physical changes that unfold across multiple scales. Efforts to fine-tune its parameters have historically followed heuristic, trial-driven workflows that demand significant time and resources. In this study, we aimed to open this black box by employing multiscale in situ synchrotron imaging and diffraction. Using LiNi 0.5 Mn 0.3 Co 0.2 O 2 battery positive electrode material as a model system and Ba-based sintering aids, we reveal dopant segregation, intergranular mass transport, and porosity evolution as key drivers of single-crystalline particle formation. Notably, we uncovered a dynamic competition between particle-level grain coalescence and atomic-scale cation disordering, both of which are thermally activated yet have opposing impacts on battery performance. These findings highlight the coupled, multiscale nature of structure development and offer a mechanistic basis for optimizing the solid-state synthesis process. This framework provides a path toward more controlled, efficient, and scalable production of high-performance battery positive electrode materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Process control-enabled mitigation of microstructural and plastic heterogeneities in additively manufactured Grade 91 steel

Synergizing wire arc-directed energy deposition (WA-DED) additive manufacturing (AM) with particle-strengthened creep strength-enhanced ferritic (CSEF) steels enables fabrication and repair of critical power-plant components. Investigations focused on fusion-welded particle-strengthened CSEF steels, such as Grade 91 steel, have linked microstructurally heterogeneous regions—forming due to heat affected zones (HAZ)—with premature failure during elevated temperature service. Fusion-based AM, including WA-DED, likewise generates microstructurally and plastically heterogeneous regions due to spatiotemporally varying thermokinetics during deposition. However, works investigating such microstructural heterogeneities, their implications for mechanical behavior, and strategies to mitigate their formation remain scarce. This work identifies microstructurally and plastically heterogeneous regions within the WA-DED-processed Grade 91 steel. Spatial microhardness variations in the as-fabricated specimen correlate with the variation in the attributes of grain, martensitic microstructure, and precipitates across the fusion zone and HAZ. Digital image correlation-enabled tensile tests performed at 500 °C revealed pronounced deformation localization and a wave-like strain distribution, with wavelength close to the melt pool depth, indicating susceptibility of the as-fabricated components to premature creep failure. Such heterogeneity in microstructural and mechanical behavior was attributed to recurring solid-state phase transformations. Subsequently, an interlayer temperature control strategy was implemented, wherein maintaining interlayer temperature above the martensitic start temperature mitigated the heterogeneous microstructural and plastic response in the as-fabricated condition. Findings open pathways to achieving deformation-localization- and creep-resistant microstructures in WA-DED fabricated particle-strengthened CSEF steel components, reducing reliance on post-welding heat treatments—conventionally required to enhance creep resistance—and enabling on-demand, short lead-time fabrication of next-generation power-plant components.

Heat affected zones↗
DOE OSTI2024

Infrared phase-change chiral metasurfaces with tunable circular dichroism

Integrating phase-change materials in metasurfaces has emerged as a powerful strategy to realize optical devices with tunable electromagnetic responses. Here, phase-change chiral metasurfaces based on GST-225 material with the designed trapezoid-shaped resonators are demonstrated to achieve tunable circular dichroism (CD) responses in the infrared regime. The asymmetric trapezoid-shaped resonators are designed to support two chiral plasmonic resonances with opposite CD responses for realizing switchable CD between negative and positive values using the GST phase change from amorphous to crystalline. The electromagnetic field distributions of the chiral plasmonic resonant modes are analyzed to understand the chiroptical responses of the metasurface. Furthermore, the variations in the absorption spectrum and CD value for the metasurface as a function of the baking time during the GST phase transition are analyzed to reveal the underlying thermal tuning process of the metasurface. The demonstrated phase-change metasurfaces with tunable CD responses hold significant promise in enabling many applications in the infrared regime such as chiral sensing, encrypted communication, and thermal imaging.

42 ENGINEERING↗
DOE OSTI2025

Rare Earth Element-Induced Condensation of the Block V of the Repeats-in-Toxin Domain from CyaA from Bordetella pertussis for Separations

Rare earth elements (REEs) are critical for the development of a range of new technologies. However, the current industrial separation processes of these metals from natural sources, recycled materials, and industrial effluents involve the large consumption of organic solvents, resulting in a sizable environmental footprint. We aim to exploit the high affinity of the block V peptide of the repeats-in-toxin (RTX) domain of the adenylate cyclase protein from Bordetella pertussis for the separation of REEs. This peptide selectively binds with lanthanide (Ln) cations and can undergo Ln-induced phase separation, which can be used in bioseparation processes. Here, we evaluated the self-assembling structures of complexes of the RTX domain peptide folded in the presence of Ln 3+ cations. Size distribution and surface potential measurements of complexes were taken to understand the Ln-induced changes in the complexed peptide. Transmission electron microscopy imaging was used to explore the structures of complexes, while anomalous small-angle X-ray scattering measurements were used to determine the distribution of Ln 3+ ions within the protein-based macrostructures. In the presence of excess Ln 3+ , we observed the formation of coral-like cylindrical structures comprised of Ln 3+ -RTX complexes, with approximately eight trivalent metals per peptide within the nanosized assemblies. These findings provide new insights into the structural organization of assembled RTX domains and their ability to coordinate with REEs, forming nanosized, metal-rich structures that naturally condense, providing a proof-of-concept for protein-based separation processes of these critical materials.

chemical structure↗