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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Development of Surface Grain Relief on Self-Ion Irradiated Copper

The development of surface grain relief has been observed on self-ion irradiated pure polycrystalline copper. However, the mechanistic origin of this feature has yet to be determined. Two possible mechanisms, anisotropic creep relaxation of void swelling induced stresses and crystallographic orientation-dependent sputtering rate differences, are being investigated as the cause of this evolution. This work focuses on characterizing the surface development and investigating the mechanism of orientation-dependent sputtering. Based on the conditions under which these specimens were irradiated, preferential sputtering is not likely to be the cause of the observed grain relief. Surface grain relief can greatly influence the ability to non-destructively detect irradiation-induced effects in polycrystalline metals. Determining the origin of grain relief development is necessary before this surface feature can be used an indicator of irradiation-induced effects in pure copper and other alloys. The development of surface grain relief has been observed on self-ion irradiated pure polycrystalline copper irradiated to 100 dpa. This surface feature was first noted by measuring samples using transient grating spectroscopy and later confirmed using scanning electron microscopy. Calculations of single-crystal sputtering rates show that the difference in sputtering yields between a randomly-oriented solid and a low-index plane is not sufficient to account for the observed height difference. SEM images appear to show a maximum step-height difference of around 100 nm and differential sputtering can only account for differences on the order of 10 nm at most. This determination indicates that anisotropic creep relaxation may be the mechanistic origin of the observed surface features. If this is the case, which will be confirmed by future work, then TG spectroscopy may be an effective tool for the determination of the onset of certain radiation-damage evolution. For example, if the onset of creep relaxation is strongly correlated to a specific level of void swelling and if the surface features present as a result of creep relaxation can be observed using TG spectroscopy, then accurate determinations of particular levels of void swelling may be made. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mapping Rare Earths and Toxics in E-Waste via Hyperspectral Imaging and Machine Learning

Electronic waste (e-waste) presents a mounting challenge to environmental sustainability due to its complex composition, which includes high-value rare earth elements, hazardous organic compounds, and non-recyclable plastics. Accurate and scalable material classification is essential for enabling efficient resource recovery and safe recycling practices. This study introduces a confidence-aware classification pipeline that combines mid-infrared hyperspectral imaging (HSI), spectral angle mapping (SAM), and iterative machine learning to perform pixel-level material identification across e-waste devices. A curated spectral library encompassing artificial materials (e.g., plastic iron oxide, galvanized metals), minerals (e.g., allanite, hematite), and organic compounds (e.g., benzanthracene, toluene) was used to generate pseudo-labels, each assigned a confidence score based on SAM-derived spectral similarity. High-confidence samples from seven consumer electronics—digital cameras, keyboards, laptop fans, modems, motherboards, TV remotes, and speakers—were iteratively expanded and classified using models such as Support Vector Machine (SVM), Random Forest, Gradient Boosting Classifier, Partial Least Squares Discriminant Analysis (PLSDA) and Logistic Regression. The best-performing classifiers achieved macro F1 scores approaching 1.0. Results revealed widespread plastic content (dominated by plastic iron oxide), the presence of rare earth-bearing minerals like cerium-containing allanite, and pervasive detection of hazardous organics such as benzanthracene. Principal Component Analysis (PCA) visualizations and confusion matrices confirmed high separability and robust classification performance. This methodology enables precise, non-destructive, and scalable classification of heterogeneous e-waste streams. It supports automated, hazard-aware sorting in recycling workflows, facilitating selective recovery of critical materials and compliance with circular economy goals. The confidence-aware framework provides a foundation for real-time deployment in industrial settings, offering significant implications for smart e-recycling infrastructure and policy-driven material stewardship.

Circular economy↗
DOE OSTI2019

Multi-scale structural analysis of proteins by deep semantic segmentation

Abstract Motivation Recent advances in computational methods have facilitated large-scale sampling of protein structures, leading to breakthroughs in protein structural prediction and enabling de novo protein design. Establishing methods to identify candidate structures that can lead to native folds or designable structures remains a challenge, since few existing metrics capture high-level structural features such as architectures, folds and conformity to conserved structural motifs. Convolutional Neural Networks (CNNs) have been successfully used in semantic segmentation—a subfield of image classification in which a class label is predicted for every pixel. Here, we apply semantic segmentation to protein structures as a novel strategy for fold identification and structure quality assessment. Results We train a CNN that assigns each residue in a multi-domain protein to one of 38 architecture classes designated by the CATH database. Our model achieves a high per-residue accuracy of 90.8% on the test set (95.0% average per-class accuracy; 87.8% average per-structure accuracy). We demonstrate that individual class probabilities can be used as a metric that indicates the degree to which a randomly generated structure assumes a specific fold, as well as a metric that highlights non-conformative regions of a protein belonging to a known class. These capabilities yield a powerful tool for guiding structural sampling for both structural prediction and design. Availability and implementation The trained classifier network, parser network, and entropy calculation scripts are available for download at https://git.io/fp6bd, with detailed usage instructions provided at the download page. A step-by-step tutorial for setup is provided at https://goo.gl/e8GB2S. All Rosetta commands, RosettaRemodel blueprints, and predictions for all datasets used in the study are available in the Supplementary Information. Supplementary information Supplementary data are available at Bioinformatics online.

Eguchi, Raphael R.↗
DOE OSTI2015

Mechanical anisotropy at the nanoscale in amorphous solids

Amorphous solids are randomly disordered without any long-range periodic atomic arrangement and thus appear isotropic. Here, we show in metallic glasses that this view does not hold at small scales: Strong mechanical anisotropy emerges when the sample size decreases below about 15 nm as shown by the marked deviation in stress-strain relations as well as elastic modulus along different loading directions. The size induced mechanical anisotropy is naturally related to structural anisotropy that is absent before loading. The anisotropic stress and modulus versus the size yield different scaling exponents in different stages of deformation, hinting at different deformation mechanisms. The size effect discovered here points to the existence of intrinsic heterogeneity defined by the anisotropy, which may play an important role in structure-property relations in amorphous solids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Mapping growth windows in quaternary perovskite oxide systems by hybrid molecular beam epitaxy

Requisite to growing stoichiometric perovskite thin films of the solid-solution A ' 1-x A x B O 3 by hybrid molecular beam epitaxy is understanding how the growth conditions interpolate between the end members A'B O 3 and AB O 3 , which can be grown in a self-regulated fashion, but under different conditions. Using the example of La 1-x Sr x VO 3 , the two-dimensional growth parameter space that is spanned by the flux of the metal-organic precursor vanadium oxytriisopropoxide and composition, x , was mapped out. The evolution of the adsorption-controlled growth window was obtained using a combination of X-ray diffraction, atomic force microscopy, reflection high-energy electron-diffraction (RHEED), and Rutherford backscattering spectroscopy. It is found that the stoichiometric growth conditions can be mapped out quickly with a single calibration sample using RHEED. Once stoichiometric conditions have been identified, the out-of-plane lattice parameter can be utilized to precisely determine the composition x . This strategy enables the identification of growth conditions that allow the deposition of stoichiometric perovskite oxide films with random A-site cation mixing, which is relevant to a large number of perovskite materials with interesting properties, e.g., high-temperature superconductivity and colossal magnetoresistance, that emerge in solid solution A ' 1-x A x B O 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2017

INFLUENCE OF THE GALACTIC GRAVITATIONAL FIELD ON THE POSITIONAL ACCURACY OF EXTRAGALACTIC SOURCES

We investigate the influence of random variations of the Galactic gravitational field on the apparent celestial positions of extragalactic sources. The basic statistical characteristics of a stochastic process (first-order moments, an autocorrelation function and a power spectral density) are used to describe a light ray deflection in a gravitational field of randomly moving point masses as a function of the source coordinates. We map a 2D distribution of the standard deviation of the angular shifts in positions of distant sources (including reference sources of the International Celestial Reference Frame) with respect to their true positions. For different Galactic matter distributions the standard deviation of the offset angle can reach several tens of μ as (microarcsecond) toward the Galactic center, decreasing down to 4–6 μ as at high galactic latitudes. The conditional standard deviation (“jitter”) of 2.5 μ as is reached within 10 years at high galactic latitudes and within a few months toward the inner part of the Galaxy. The photometric microlensing events are not expected to be disturbed by astrometric random variations anywhere except the inner part of the Galaxy as the Einstein–Chvolson times are typically much shorter than the jittering timescale. While a jitter of a single reference source can be up to dozens of μ as over some reasonable observational time, using a sample of reference sources would reduce the error in relative astrometry. The obtained results can be used for estimating the physical upper limits on the time-dependent accuracy of astrometric measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Analyzing the Validity of Brazilian Testing Using Digital Image Correlation and Numerical Simulation Techniques

Characterizing the mechanical behavior of rocks plays a crucial role to optimize the fracturing process in unconventional reservoirs. However, due to the intrinsic anisotropy and heterogeneity in unconventional resources, fracture process prediction remains the most significant challenge for sustainable and economic hydrocarbon production. During the deformation tracking under compression, deploying conventional methods (strain gauge, extensometer, etc.) is insufficient to measure the deformation since the physical attachment of the device is restricted to the size of the sample, monitoring limited point-wise deformation, producing difficulties in data retrieval, and a tendency to lose track in failure points, etc. Where conventional methods are limited, the application of digital image correlation (DIC) provides detailed and additional information of strain evolution and fracture patterns under loading. DIC is an image-based optical method that records an object with a camera and monitors the random contrast speckle pattern painted on the facing surface of the specimen. To overcome the existing limitations, this paper presents numerical modeling of Brazilian disc tests under quasi-static conditions to understand the full-field deformation behaviors and finally, it is validated by DIC. As the direct tensile test has limitations in sample preparation and test execution, the Brazilian testing principle is commonly used to evaluate indirectly the tensile strength of rocks. The two-dimensional numerical model was built to predict the stress distribution and full-field deformation on Brazilian disc under compression based on the assumptions of a homogenous, isotropic and linear elastic material. The uniaxial compression test was conducted using the DIC technique to determine the elastic properties of Spider Berea sandstone, which were used as inputs for the simulation model. The model was verified by the analytical solution and compared with the digital image correlation. The numerical simulation results showed that the solutions matched reasonably with the analytical solutions where the maximum deviation of stress distribution was obtained as 14.59%. The strain evolution (normal and shear strains) and displacements along the central horizontal and vertical planes were investigated in three distinguishable percentages of peak loads (20%, 40%, and 90%) to understand the deformation behaviors in rock. The simulation results demonstrated that the strain evolution contours consistently matched with DIC generated contours with a reasonable agreement. The changes in displacement along the central horizontal and vertical planes showed that numerical simulation and DIC generated experimental results were repeatable and matched closely. In terms of validation, Brazilian testing to measure the indirect tensile strength of rocks is still an issue of debate. The numerical model of fracture propagation supported by digital image correlation from this study can be used to explain the fracturing process in the homogeneous material and can be extended to non-homogeneous cases by incorporating heterogeneity, which is essential for rock mechanics field applications.

58 GEOSCIENCES↗
NASA NTRS1998

BIGEL analysis of gene expression in HL60 cells exposed to X rays or 60 Hz magnetic fields

We screened a panel of 1,920 randomly selected cDNAs to discover genes that are differentially expressed in HL60 cells exposed to 60 Hz magnetic fields (2 mT) or X rays (5 Gy) compared to unexposed cells. Identification of these clones was accomplished using our two-gel cDNA library screening method (BIGEL). Eighteen cDNAs differentially expressed in X-irradiated compared to control HL60 cells were recovered from a panel of 1,920 clones. Differential expression in experimental compared to control cells was confirmed independently by Northern blotting of paired total RNA samples hybridized to each of the 18 clone-specific cDNA probes. DNA sequencing revealed that 15 of the 18 cDNA clones produced matches with the database for genes related to cell growth, protein synthesis, energy metabolism, oxidative stress or apoptosis (including MYC, neuroleukin, copper zinc-dependent superoxide dismutase, TC4 RAS-like protein, peptide elongation factor 1alpha, BNIP3, GATA3, NF45, cytochrome c oxidase II and triosephosphate isomerase mRNAs). In contrast, BIGEL analysis of the same 1,920 cDNAs revealed no differences greater than 1.5-fold in expression levels in magnetic-field compared to sham-exposed cells. Magnetic-field-exposed and control samples were analyzed further for the presence of mRNA encoding X-ray-responsive genes by hybridization of the 18 specific cDNA probes to RNA from exposed and control HL60 cells. Our results suggest that differential gene expression is induced in approximately 1% of a random pool of cDNAs by ionizing radiation but not by 60 Hz magnetic fields under the present experimental conditions.

Non-NASA Center↗
DOE OSTI2017

A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media

A new computational method is proposed for efficient uncertainty quantification of multiphase flow in porous media with stochastic permeability. For pressure estimation, it combines the dimension-adaptive stochastic collocation method on Smolyak sparse grids and the Kronrod–Patterson–Hermite nested quadrature formulas. For saturation estimation, an additional stage is developed, in which the pressure and velocity samples are first generated by the sparse grid interpolation and then substituted into the transport equation to solve for the saturation samples, to address the low regularity problem of the saturation. Numerical examples are presented for multiphase flow with stochastic permeability fields to demonstrate accuracy and efficiency of the proposed two-stage adaptive stochastic collocation method on nested sparse grids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Failure behavior after stepwise uniaxial extension of entangled polymer melts

This paper studies how stepwise extension of various well-entangled polymer melts produce mechanical/structural breakdowns during stress relaxation. Depending on how stepwise extension is imposed on five different styrene-butadiene random copolymers, two different forms of specimen failure are observed. When a step extension is produced with a low Hencky rate or to a low strain below some thresholds, the sample breaks up rather sharply after an appreciable period of induction during which the stress relaxes quiescently. After step extension, the sample draws and undergoes unsustainable necking due to shear yielding, if the step extension is produced with a Hencky rate higher than the Rouse relaxation rate and the magnitude is beyond a Hencky strain of 1.5. Moreover, introduction of long-chain branching suppresses the elastic breakup, postponing it to Hencky strains beyond 2.5. The clearly identifiable characteristics of the elastic yielding may be understood in terms of some speculative interpretations. Finally, more convincing explanations have yet to come from future computer experiments that hopefully the present work is able to motivate.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
NASA NTRS1974

Design of state-feedback controllers including sensitivity reduction, with applications to precision pointing

The design procedure of feedback controllers was described and the considerations for the selection of the design parameters were given. The frequency domain properties of single-input single-output systems using state feedback controllers are analyzed, and desirable phase and gain margin properties are demonstrated. Special consideration is given to the design of controllers for tracking systems, especially those designed to track polynomial commands. As an example, a controller was designed for a tracking telescope with a polynomial tracking requirement and some special features such as actuator saturation and multiple measurements, one of which is sampled. The resulting system has a tracking performance comparing favorably with a much more complicated digital aided tracker. The parameter sensitivity reduction was treated by considering the variable parameters as random variables. A performance index is defined as a weighted sum of the state and control convariances that sum from both the random system disturbances and the parameter uncertainties, and is minimized numerically by adjusting a set of free parameters.

Hadass, Z.↗
NASA NTRS1978

Origin of magnetization in lunar breccias - An example of thermal overprinting

Twenty six samples from seven hand specimens, collected from the station 6 boulder at the Apollo 17 landing site, were studied magnetically. The boulder is a breccia consisting of three lithologic units distinguished by their clast population. The direction of magnetization of samples from unit B which is almost devoid of large clasts cluster fairly well after alternating field demagnetization. Samples from unit C which is characterized by abundant large clasts up to 1 m in size do not contain a uniform direction of magnetization but the distribution is not random. Based on these data we propose that the natural remanent magnetization (NRM) in these breccias is the vector sum of two magnetizations, a pre-impact magnetization and a partial thermoremanence acquired during breccia formation. The relative contribution of the two components is controlled by the thermal history of the ejecta, which in turn is determined by its clast population. Depending on the clast population, the NRM can be a total thermoremanence, a partial thermoremanence plus a pre-impact magnetization, or a pre-impact magnetization. This model of thermal overprinting might be applicable to all lunar breccias of medium and higher metamorphic grade.

Gose, W. A.↗
NASA NTRS1989

Fatigue crack growth model RANDOM2 user manual, appendix 1

The FORTRAN program RANDOM2 is documented. RANDOM2 is based on fracture mechanics using a probabilistic fatigue crack growth model. It predicts the random lifetime of an engine component to reach a given crack size. Included in this user manual are details regarding the theoretical background of RANDOM2, input data, instructions and a sample problem illustrating the use of RANDOM2. Appendix A gives information on the physical quantities, their symbols, FORTRAN names, and both SI and U.S. Customary units. Appendix B includes photocopies of the actual computer printout corresponding to the sample problem. Appendices C and D detail the IMSL, Ver. 10(1), subroutines and functions called by RANDOM2 and a SAS/GRAPH(2) program that can be used to plot both the probability density function (p.d.f.) and the cumulative distribution function (c.d.f.).

Boyce, Lola↗
NASA NTRS2000

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

Bell, Thomas L.↗
NASA NTRS2010

Mimas: Preliminary Evidence For Amorphous Water Ice from VIMS

We have conducted a statistical clustering analysis (1,2) on a mosaic of VIMS data cubes obtained on February 13, 2010, for Saturn s satellite Mimas. Seven VIMS cubes were geometrically projected and re-sampled to a common spatial resolution. The clustering technique consists of a partitioning algorithm coupled to a criterion that prevents sub-optimal solutions and tests for the influence of random noise in the measurements. The clustering technique is agnostic about the meaning of the clusters, and scientific interpretation requires their a posteriori evaluation. The preliminary results yielded five clusters, demonstrating that spectral variability across Mimas surface is statistically significant. The ratios of the means calculated for each of the clusters show structure within the 1.6- micron water ice band, as well as the shape and the central wavelength of the strong ice band at 2 micron, that map spatially in patterns apparently related to the topography of Mimas, in particular certain regions in and around Herschel crater. The mean spectra of the five clusters, show similarities with laboratory spectra of amorphous and crystalline H2O ice (3) that are suggestive of the presence of an amorphous ice component in certain regions of Mimas, notably on the central peak of Herschel, on the crater floor, and in faults surrounding the crater. This may represent a mixture of both ice phases, or perhaps a layer of amorphous ice on a base of crystalline ice. Another possible occurrence of amorphous ice appears southwest of Herschel, close to the south pole.

Cruikshank, Dale P.↗
NASA NTRS2022

Simulating the Diffusion of Hydrogen in Amorphous Silicates: A ‘Jumping’ Migration Process and its Implications for Solar Wind Implanted Lunar Volatiles

We use molecular dynamics (MD) simulations to better explain the movement of atomic hydrogen in amorphous silica and quantify the planetary science implications of these findings. Previous MD simulations had a large range of predicted values and did not agree well with experiment. Our simulations sample atomic motion for a longer duration and consider a wider range of temperatures than previous simulations. In contrast to constant atomic motion, the hydrogen atoms were shown to undergo random intermittent jumps from one oxygen atom to another, the number of which increase with temperature. Predicted diffusion coefficients had a better agreement to experimental values than previous MD simulations, suggesting the importance of longer simulation durations for better statistics. The low activation energy and jumps observed at lunar temperatures do not support the theory of diurnal variations in OH content for an undamaged amorphous silica surface. Instead, we conclude that energetic solar wind impacts can induce two competing atomic hydrogen motion processes in the exposed surface: A prompt effect that induces jumps in the temperature spike volume, but also a long term effect of damage in the structure that traps atomic hydrogen. We then use SDTrimSP to quantify the damage created during exposure and MD to demonstrate the H retention and trapping near these defects. Damage was shown to be dependent on impact energy, with defects easily retaining implanted hydrogen. MD results like those presented herein on unweathered surfaces are therefore most relevant to magnetic anomalies. As a result, we demonstrate the importance of lunar volatile models to account for the damage state of the substrate when modelling hydrogen diffusion, retention, and subsequent OH/water production.

Liam S. Morrissey↗