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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Imaging antiferromagnetic domain fluctuations and the effect of atomic scale disorder in a doped spin-orbit Mott insulator

Correlated oxides can exhibit complex magnetic patterns. Understanding how magnetic domains form in the presence of disorder and their robustness to temperature variations has been of particular interest, but atomic scale insight has been limited. We use spin-polarized scanning tunneling microscopy to image the evolution of spin-resolved modulations originating from antiferromagnetic (AF) ordering in a spin-orbit Mott insulator perovskite iridate Sr 3 Ir 2 O 7 as a function of chemical composition and temperature. We find that replacing only several percent of lanthanum for strontium leaves behind nanometer-scale AF puddles clustering away from lanthanum substitutions preferentially located in the middle strontium oxide layer. Thermal erasure and reentry into the low-temperature ground state leads to a spatial reorganization of the AF puddles, which nevertheless maintain scale-invariant fractal geometry in each configuration. Our experiments reveal multiple stable AF configurations at low temperature and shed light onto spatial fluctuations of the AF order around atomic scale disorder in electron-doped Sr 3 Ir 2 O 7 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Exploring Sustainability in Scientific Software through Code Quality & Test Coverage Metrics

Context: Scientific open-source software (SciOSS) plays a foundational role in research and engineering, yet its long-term sustainability has often been overlooked and remains a significant concern. Objective: This study investigates the long-term sustainability of SciOSS through code and test quality metrics. Method: We analyze CASS Software Portfolio projects, classifying them by sustainability and comparing their code structure, test coverage, and links between code quality and testing across the dataset. Results: Sustainable projects show higher, more consistent test coverage and clearer code-test correlations, while unsustainable ones show weaker patterns. Overall, test coverage is low in scientific software, and high complexity and coupling reduce testability. Conclusion: In this study, we present a practical, data-driven approach for assessing sustainability in scientific software, offering a foundation for evaluating long-term software health and supporting future efforts in quality assurance and sustainability monitoring.

Md mushfiqur rahman, Sheikh [University of Tenness↗
DOE OSTI2025

VISIONARY: Virtual Intelligence System for Optimizing Novel Analytical Research Yields

VISIONARY is an AI system that accelerates energy materials discovery by automatically generating hypotheses about structure-property relationships. It analyzes patterns in materials data, identifies promising correlations, and proposes testable scientific hypotheses without human intervention. By streamlining this reasoning process, VISIONARY helps researchers efficiently identify candidate materials with desired properties, significantly speeding up the materials development pipeline for energy applications. During the project, we developed a standalone application. The application uses a combination of papers provided by the user and data collected from FutureHouse’s dataset to build an understanding of the background that the user wants to explore for the hypothesis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nuclear Uncertainties Associated with the Nucleosynthesis in Ejecta of a Black Hole Accretion Disk

Abstract The simulation of heavy element nucleosynthesis requires input from yet-to-be-measured nuclear properties. The uncertainty in the values of these off-stability nuclear properties propagates to uncertainties in the predictions of elemental and isotopic abundances. However, for any given astrophysical explosion, there are many different trajectories, i.e., temperature and density histories, experienced by outflowing material, and thus different nuclear properties can come into play. We consider combined nucleosynthesis results from 460,000 trajectories from a black hole accretion disk and find the spread in elemental predictions due solely to unknown nuclear properties to be a factor of a few. We analyze this relative spread in model predictions due to nuclear variations and conclude that the uncertainties can be attributed to a combination of properties in a given region of the abundance pattern. We calculate a cross-correlation between mass changes and abundance changes to show how variations among the properties of participating nuclei may be explored. Our results provide further impetus for measurements of multiple quantities on individual short-lived neutron-rich isotopes at modern experimental facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Laser-induced digital oxidation for copper-based flexible photodetectors

Copper oxide compounds (Cu x O) with bandgaps of 1.3–2.1 eV (CuO) and 2.1–2.6 eV (Cu 2 O) have been investigated as promising p-type semiconducting materials. Cu x O is generally obtained by deposition or thermal oxidation, but those methods are not optimal for flexible substrates. Furthermore, additional patterning steps are required to fabricate devices. In this work, we present an easy, controllable method to fabricate a metal-semiconductor-metal (MSM) photodetector using laser-induced oxidation of a thin Cu film. After laser irradiation, the Cu film is heated under ambient conditions, and this leads to a thermal oxidation reaction, in which Cu oxide is monolithically formed in the Cu film and a Cu-Cu x O-Cu MSM structure is produced. Since the laser offers localized heating, an arbitrary CuxO pattern can be written in the Cu film by spatially controlled heating. In addition, by optimizing the heating time, the laser-induced oxidation can be successfully performed even on a flexible substrate. To study the laser-induced oxidation, we examined the correlation between laser parameters and the oxidation pattern and analyzed the composition using scanning electron microscopy, Raman spectroscopy, and X-ray photoemission spectroscopy. Furthermore, we measured the transient photoresponse and employed scanning photocurrent microscopy to investigate the mechanism of carrier transport behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Correcting for digital image correlation speckle inversion at high temperature using color cameras

Digital image correlation (DIC) is a popular, noncontacting technique to measure full-field deformation by using cameras to track the motion of an applied surface pattern. Because it is noncontacting, DIC can be performed for extreme temperature applications (e.g., hot-fire rocket testing of carbon composite rocket nozzles) under harsh conditions during which bonded gauges are damaged. Speckle pattern inversion is a phenomenon that sometimes occurs while performing high-temperature DIC. During speckle pattern inversion, portions of the surface pattern that were initially darker at room temperature (e.g., graphite) may emit more light due to blackbody radiation than the portions that were initially paler, thereby producing images in which the pattern appears inverted at high temperature relative to the initial pattern at room temperature. This phenomenon can prevent the correlation algorithm from being able to resolve the displacements between images. This work compares three methods to mitigate speckle pattern inversion: (A) the subtraction method, a recently-published technique in which two high-temperature images are subtracted to remove unwanted light; (B) the filtering method, a popular technique in which optical bandpass filters screen out unwanted light; and (C) the histogram rescaling method, a proposed new method that pairs a color camera with a blue light source and uses information from the green sensor of the camera to correct against inversion in the blue sensor through postprocessing. The histogram rescaling method is shown to successfully eliminate speckle pattern inversion and has the added advantages that it does not require quasi-static loading to be able to compensate for speckle pattern inversion, nor does it impose thick-glass distortions caused by the optical filter.

Rowley, Lindsey J.↗
DOE OSTI2021

Incorporating space and time into random forest models for analyzing geospatial patterns of drug-related crime incidents in a major U.S. metropolitan area

The opioid crisis has hit American cities hard, and research on spatial and temporal patterns of drug-related activities including detecting and predicting clusters of crime incidents involving particular types of drugs is useful for distinguishing hot zones where drugs are present that in turn can further provide a basis for assessing and providing related treatment services. In this study, we investigated spatiotemporal patterns of more than 52,000 reported incidents of drug-related crime at block group granularity in Chicago, IL between 2016 and 2019. We applied a space-time analysis framework and machine learning approaches to build a model using training data that identified whether certain locations and built environment and sociodemographic factors were correlated with drug-related crime incident patterns, and establish the top contributing factors that underlaid the trends. Space and time, together with multiple driving factors, were incorporated into a random forest model to analyze these changing patterns. We accommodated both spatial and temporal autocorrelation in the model learning process to assist with capturing the changes over time and tested the capabilities of the space-time random forest model by predicting drug-related activity hot zones. Overall, we focused particularly on crime incidents that involved heroin and synthetic drugs as these have been key drug types that have highly impacted cities during the opioid crisis in the U.S.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Propagation of statistical uncertainties of Skyrme mass models to simulations of r -process nucleosynthesis

Uncertainties in nuclear models have a major impact on simulations that aim at understanding the origin of heavy elements in the universe through the rapid neutron capture process ( r process) of nucleosynthesis. Within the framework of the nuclear density functional theory, we use results of Bayesian statistical analysis to propagate uncertainties in the parameters of energy density functionals to the predicted r -process abundance pattern, by way not only of the nuclear masses but also through the influence of the masses on β -decay and neutron capture rates. We point out the importance of the nonequilibrium end stage of the r process in determining the width of the resulting abundance pattern uncertainty bands. We additionally make the first identifications of specific parameters of Skyrme-like energy density functionals which show tentative correlations with particular aspects of the r -process abundance pattern. While previous studies have explored the reduction in the abundance pattern uncertainties due to anticipated new measurements of neutron-rich nuclei, here we point out that an even larger reduction will occur when these new measurements are used to reduce the uncertainty of model predictions of masses, which are then propagated through to the abundance pattern. We make a quantitative prediction for how large this reduction will be.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Decomposition of liquid-liquid extraction organic phase structure into critical and pre-peak contributions

Solution nanostructure induced by amphiphile self-association plays an important role in various chemical and physical processes, including liquid-liquid extraction (LLE). Small angle scattering techniques are an essential means of probing this structure, but, due to non-uniqueness of scattering patterns, their interpretation is not trivial. Here, in this study, we decompose small angle x-ray scattering (SAXS) patterns for a range of binary LLE organic phases into two components: Ornstein-Zernike and pre-peak contributions resulting from, respectively, critical concentration fluctuations and packing of the amphiphilic extractant molecules in the nonpolar aliphatic diluent. While we previously applied Ornstein-Zernike scattering models to similar organic phases, including the pre-peak explicitly in the fit allows us to measure weak fluctuations at high extractant concentration and simultaneously obtain information on the position and intensity of the correlation peak related to amphiphile packing. Scattering patterns and partial structure factors calculated from molecular dynamics simulations support this interpretation. We demonstrate how this minimal scattering model describes nanostructuring for a large number of extractant types over their entire extractant/diluent composition ranges, suggesting simple and universal behavior. The straightforward assignment of these structural contributions facilitates the comparison of these features between different classes of extractant molecules and will enable further studies of organic phase aggregation. Applicability to more complex, process-relevant organic phases is illustrated with post-contact organic phases containing significant quantities of extracted lanthanide nitrate salt, which we find are readily described by this model.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

The R-Process Alliance: Abundance Universality among Some Elements at and between the First and Second R-Process Peaks*

Abstract We present new observational benchmarks of rapid neutron-capture process ( r -process) nucleosynthesis for elements at and between the first ( A ∼ 80) and second ( A ∼ 130) peaks. Our analysis is based on archival ultraviolet and optical spectroscopy of eight metal-poor stars with Se ( Z = 34) or Te ( Z = 52) detections, whose r -process enhancement varies by more than a factor of 30 (−0.22 ≤ [Eu/Fe] ≤ +1.32). We calculate ratios among the abundances of Se, Sr through Mo (38 ≤ Z ≤ 42), and Te. These benchmarks may offer a new empirical alternative to the predicted solar system r -process residual pattern. The Te abundances in these stars correlate more closely with the lighter r -process elements than the heavier ones, contradicting and superseding previous findings. The small star-to-star dispersion among the abundances of Se, Sr, Y, Zr, Nb, Mo, and Te (≤0.13 dex, or 26%) matches that observed among the abundances of the lanthanides and third r -process-peak elements. The concept of r -process universality that is recognized among the lanthanide and third-peak elements in r -process-enhanced stars may also apply to Se, Sr, Y, Zr, Nb, Mo, and Te, provided the overall abundances of the lighter r -process elements are scaled independently of the heavier ones. The abundance behavior of the elements Ru through Sn (44 ≤ Z ≤ 50) requires further study. Our results suggest that at least one relatively common source in the early Universe produced a consistent abundance pattern among some elements spanning the first and second r -process peaks.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Measurement of Convective Heat Transfer Coefficients with Supercritical CO2 in Novel Additively Manufactured Helically Patterned Pin Fin Tubes Using the Wilson Plot Technique

This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO2 flowing in pin-fin patterned pipes in the Heat Exchange and Experimental Testing (HEET) facility at the US DoE’s National Energy Technology Laboratory (NETL) in Morgantown, WV. The measurement procedures in the HEET rig were validated by conducting benchmark tests with smooth stainless-steel tube and comparing the results with published correlations for Nusselt number (Nu) and friction factor. Over typical Reynolds number range in sCO2, the measured Nu and friction factors were within 7% of classical correlations for smooth tube flow.The candidate pin fin patterned pipes were additively manufactured (AM) at the Oak Ridge National Laboratory. The pins were circular or elliptical in cross-section. Pin length to diameter aspect ratios were 1.33 and 2, while the pin diameter to tube diameter ratio was 0.188 and 0.125. Tests were performed for ReD varying from 6.9×104 to 2.2×105 and at conditions equivalent to the low pressure outlet (8.69 MPa, 361 K) of the low temperature recuperator (LTR) in an indirect sCO2 power cycle. The Wilson plot technique was utilized to measure the bulk heat transfer coefficients.For the better performing design (tube A, pin length to tube diameter ratio: 1.33, pin diameter to tube diameter ratio: 0.188), the local heat transfer coefficient increased by 112% relative to the Dittus-Boelter correlation at the LTR low pressure outlet. This corresponded to a 282% increase in the product of the heat transfer coefficient and the surface area. Large pressure drops across the test articles were observed.

Searle, Matthew↗
DOE OSTI2023

Quantum textures of the many-body wavefunctions in magic-angle graphene

Interactions among electrons create novel many-body quantum phases of matter with wavefunctions that often reflect electronic correlation effects, broken symmetries, and novel collective excitations. A wide range of quantum phases has been discovered in MATBG, including correlated insulating, unconventional superconducting, and magnetic topological phases. The lack of microscopic information, including precise knowledge of possible broken symmetries, has thus far hampered our understanding of MATBG's correlated phases. Here we use high-resolution scanning tunneling microscopy to directly probe the wavefunctions of the correlated phases in MATBG. The squares of the wavefunctions of gapped phases, including those of the correlated insulators, pseudogap, and superconducting phases, show distinct patterns of broken symmetry with a √3 x √3 super-periodicity on the graphene atomic lattice that has a complex spatial dependence on the moiré superlattice scale. We introduce a symmetry-based analysis to describe our measurements of the wavefunctions of MATBG's correlated phases with a set of complex-valued local order parameters. For the correlated insulators in MATBG, at fillings of ±2 electrons per moiré unit cell relative to charge neutrality, we compare the observed quantum textures to those expected for proposed theoretical ground states. In typical MATBG devices, the textures of correlated insulators' wavefunctions closely match those of the theoretically proposed IKS order, while in ultra-low-strain samples our data has local symmetries like those of a T-IVC phase. Here, we also study the wavefunction of MATBG's superconducting state, revealing strong signatures of intervalley coherence that can only be distinguished from those of the insulator with our phase-sensitive measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Heat Transfer Coefficients of Additively Manufactured Tubes with Internal Pin Fins for Supercritical Carbon Dioxide Cycle Recuperators

This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO 2 flowing in additively manufactured tubes with internal pin fins at the US DOE’s National Energy Technology Laboratory in Morgantown, WV. The measurement procedures were validated by conducting benchmark tests with smooth stainless-steel tube and comparing the results with published correlations for Nusselt number (Nu) and friction factor. Over Reynolds numbers (ReD) ranging from 5 × 10 4 to 2.5 × 10 5 , measured Nu was within 5% of the Dittus-Boelter correlation and measured friction factors were within 5% of the McAdams correlation for smooth tube flow. The candidate pin fin patterned pipes were additively manufactured (AM) at the Oak Ridge National Laboratory. The pins were circular or elliptical in cross-section and were printed at a 30⁰ angle relative to the inner wall (to meet AM constraints). The pin arrangement was helical to promote enhanced heat transfer due to swirl flow. Pin length to diameter aspect ratio was 1.33, 2, and 8, while the pin diameter to tube diameter ratio was 0.188, 0.125, and 0.063. Tests were performed for ReD varying from 6.9 × 10 4 to 2.2 × 10 5 and at conditions equivalent to the low pressure (LP) outlet (8.69 MPa, 361 K) and the high pressure (HP) inlet (20.7 MPa, 350 K) of the low temperature recuperator (LTR) in an indirect sCO 2 cycle. The Wilson plot technique was utilized to measure the bulk heat transfer coefficients. For the best performing design (tube A, pin length to tube diameter ratio: 1.33, pin diameter to tube diameter ratio: 0.19), the local heat transfer coefficient increased by 136% relative to the Dittus-Boelter correlation at the LTR low pressure outlet and 194% at the LTR high pressure inlet. These correspond to a 282% and a 271% increase in the product of the heat transfer coefficient and surface area (adjusted for fin efficiency) product, respectively. Large pressure drops across the test articles were observed. For Tube Design A, the average friction factor, across the range of ReD considered, was significantly larger than the McAdams correlation at both the LTR LP outlet and the LTR HP inlet. A thermal performance factor was utilized to express the ratio of material required to build a finned heat exchanger relative to a finless heat exchanger with the same heat duty and pumping power. Tube Design A was estimated to decrease the required heat exchanger material by 13%.

Searle, Matthew↗
DOE OSTI2026

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗
DOE OSTI2023

The local ordering of polar solvents around crystalline carbon nitride nanosheets in solution

The crystalline graphitic carbon nitride, poly-triazine imide (PTI) is highly unusual among layered materials since it is spontaneously soluble in aprotic, polar solvents including dimethylformamide (DMF). The PTI material consists of layers of carbon nitride intercalated with LiBr. When dissolved, the resulting solutions consist of dissolved, luminescent single to multilayer nanosheets of around 60–125 nm in diameter and Li+ and Br- ions originating from the intercalating salt. To understand this unique solubility, the structure of these solutions has been investigated by high-energy X-ray and neutron diffraction. Although the diffraction patterns are dominated by inter-solvent correlations there are clear differences between the X-ray diffraction data of the PTI solution and the solvent in the 4–6 Å -1 range, with real space differences persisting to at least 10 Å. Structural modelling using both neutron and X-ray datasets as a constraint reveal the formation of distinct, dense solvation shells surrounding the nanoparticles with a layer of Br - close to the PTI-solvent interface. This solvent ordering provides a configuration that is energetically favourable underpinning thermodynamically driven PTI dissolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ultra-Structural Imaging Provides 3D Organization of 46 Chromosomes of a Human Lymphocyte Prophase Nucleus

Three dimensional (3D) ultra-structural imaging is an important tool for unraveling the organizational structure of individual chromosomes at various stages of the cell cycle. Performing hitherto uninvestigated ultra-structural analysis of the human genome at prophase, we used serial block-face scanning electron microscopy (SBFSEM) to understand chromosomal architectural organization within 3D nuclear space. Acquired images allowed us to segment, reconstruct, and extract quantitative 3D structural information about the prophase nucleus and the preserved, intact individual chromosomes within it. Our data demonstrate that each chromosome can be identified with its homolog and classified into respective cytogenetic groups. Thereby, we present the first 3D karyotype built from the compact axial structure seen on the core of all prophase chromosomes. The chromosomes display parallel-aligned sister chromatids with familiar chromosome morphologies with no crossovers. Furthermore, the spatial positions of all 46 chromosomes revealed a pattern showing a gene density-based correlation and a neighborhood map of individual chromosomes based on their relative spatial positioning. A comprehensive picture of 3D chromosomal organization at the nanometer level in a single human lymphocyte cell is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Optical Variability of ICRF3 Quasars in the Pan-STARRS 3Pi Survey with Functional Principal Component Analysis

We make use of individual (epoch) detection data from the Pan-STARRS “3π” survey for 2863 optical ICRF3 counterparts in the five wavelength bands g, r, i, z, and y, published as part of the Data Release 2. A dedicated method based on the Functional Principal Component Analysis is developed for these sparse and irregularly sampled data. With certain regularization and normalization constraints, it allows us to obtain uniform and compatible estimates of the variability amplitudes and average magnitudes between the passbands and objects. We find that the starting assumption of affinity of the light curves for a given object at different wavelengths is violated for several percent of the sample. The distributions of rms variability amplitudes are strongly skewed toward small values, peaking at ∼0.1 mag with tails stretching to 2 mag. Statistically, the lowest variability is found for the r band and the largest for the reddest y band. A small “brighter-redder” effect is present, with amplitudes in y greater than amplitudes in g in 57% of the sample. The variability versus redshift dependence shows a strong decline with z toward redshift 3, which we interpret as the time dilation of the dominant time frequencies. The colors of radio-loud ICRF3 quasars are correlated with redshift in a complicated, wavy pattern governed by the emergence of brightest emission lines within the five passbands.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Low flow characteristics for regulated and unregulated streams in North Carolina and prediction using climate signals

In this work, low flow statistics of regulated and unregulated streams in the state of North Carolina were updated with streamflow data through 2019. About 22% of the streams considered show a significant downward trend, but considerable low-frequency variability confounding trends. The relationship between regional index time series of groundwater-depth low flow and the Atlantic Multidecadal Oscillation (AMO) was examined to determine whether low-frequency climate modes can account for the long-term pattern in low flows. Consequently, a significant correlation was found between AMO and groundwater-depth low flow, such that positive AMO is associated with lower groundwater-depth low flow and vice versa, particularly for the Piedmont region. Predictive equations for annual low flows at the ecoregion level shows that springtime average streamflow and AMO were selected as the primary predictors of low flow for coastal and Piedmont regions, whereas springtime average streamflow and the November–December–January average Oceanic Niño Index were used as the primary predictors for the mountain region. The relative root mean square error (RMSE) of the disaggregated predictions to US Geologic Survey gauge locations was <23% at 79% of the stations, between 24% and 43% at 10% of the stations, and greater than 44% at 1% of the stations. The remaining 10% of stations showed large RMSEs. This latter percentage is characterized by smaller drainage basins and intermittent flows, suggesting the prediction models are not applicable to drainage basins smaller than roughly 20 square km and intermittent streams.

54 ENVIRONMENTAL SCIENCES↗