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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
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Additive Manufacturing Model-Based Process Metrics: Reduced Order Modeling of the Laser Powder Bed Fusion Process

The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. In this work, we describe a fully parallel reduced order modeling approach that has been developed to evaluate the evolution of AM processes, termed the AM moment measure method. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology and terminology of the approach will be described, and computed build maps will be calculated and compared for various laser powder bed fusion (LPBF) builds of Ti-6Al-4V. Such comparative results develop understanding of how the sequential process actions can affect the LPBF-AM build quality and microstructure variability.

Laser Powder Bed Fusion↗
DOE OSTI2021

A Range and Performance Optimized Version of the Computer-Aided Speckle Interferometry Algorithm for Real-Time Displacement-Strain Field Monitoring

Abstract This work presents an optimized implementation of the Computer-Aided Speckle Interferometry algorithm which enables full-field determination of displacements and strains on commodity Graphics Processing Units at high resolution and frame rates. By combining careful control of the average speckle size in a laser speckle pattern with a simple sampling rate conversion scheme, a compact representation of the optical speckle is achieved. This allows for optimal use of Graphics Processing Unit architecture with robust range extension. The optimal mapping of the Computer-Aided Speckle Interferometry algorithm to Graphics Processing Unit architecture is shown in detail, and a straightforward method for disambiguating large displacements is illustrated. Lastly, this paper demonstrates a two-step subimage-tapering modification to the original algorithm that enables robust range enhancement while maintaining resolution. Results from numerical simulations on synthetic speckle patterns are shown, and runtime performance metrics are provided, with performance ranging up to 60 frames per second in some cases. The method is suitable for interactive experimental mechanics research, process and testing or any application where real-time high-resolution displacement-strain monitoring is needed. A .NET Framework class library enabling the incorporation of the algorithm into 3rd -party applications is available for download.

42 ENGINEERING↗
NASA NTRS1982

Image Analysis for Facility Siting: a Comparison of Lowand High-altitude Image Interpretability for Land Use/land Cover Mapping

For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both 'area-weighted' and 'by-class' accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was more accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs.

Borella, H. M.↗
NASA NTRS2006

Integrating Terrain Maps Into a Reactive Navigation Strategy

An improved method of processing information for autonomous navigation of a robotic vehicle across rough terrain involves the integration of terrain maps into a reactive navigation strategy. Somewhat more precisely, the method involves the incorporation, into navigation logic, of data equivalent to regional traversability maps. The terrain characteristic is mapped using a fuzzy-logic representation of the difficulty of traversing the terrain. The method is robust in that it integrates a global path-planning strategy with sensor-based regional and local navigation strategies to ensure a high probability of success in reaching a destination and avoiding obstacles along the way. The sensor-based strategies use cameras aboard the vehicle to observe the regional terrain, defined as the area of the terrain that covers the immediate vicinity near the vehicle to a specified distance a few meters away.

Howard, Ayanna↗
DOE OSTI2018

Mapping Benthic Habitat Conditions and Seafloor Deposits using Sediment Profile Imaging and a Semiautomated Image Processing System

Objectives/Scope: Sediment profile imaging (SPI) technology characterizes in situ physical, geochemical, and biological seafloor features. SPI was required by Mexico’s Agency for Safety, Energy, and Environment in 2017 for environmental baseline surveys (EBS) of oil lease blocks in the southern Gulf of Mexico. Because of its ability to provide information on benthic community health and the distribution of very thin (down to the centimeter scale) layers of deposited materials, SPI technology is highly effective for mapping drill cuttings or drilling muds released around wellheads during exploration or production and documenting their ecological impacts. SPI technology has not been widely used in the oil and gas industry for EBS or other monitoring activities. A primary objective of this work is to improve the transparency and consistency of the SPI data generation and data management process. Methods, Procedures, Process: The SPI camera works like an inverted periscope and obtains an undisturbed 21x15-cm cross-sectional image of the upper sediment column. The camera is internally powered and can be deployed rapidly from a standard winch in depths to 4,000 m. Many stations can be sampled in a single day by “pogo-sticking” across a survey area. Sediment grain size, penetration depth, surface boundary roughness, natural and anthropogenic depositional layers, depth of the oxidized surface sediment layer, maximum biogenic mixing depth, and infaunal successional stage can be directly measured at sea or immediately following the cruise. Final SPI data sets can be provided within a few weeks of the survey. Results, Observations, Conclusions: Details on the features measured in SPI images and the underlying interpretive paradigms are presented. To standardize the SPI data generation process, Integral Consulting Inc. has developed 1) a semiautomated image analysis platform, and 2) a SPI data-specific database architecture that allows both numerical and non-numerical metrics to be incorporated into a standard database structure. An integrated, software-based SPI analysis platform has been developed that imports image files and metadata and provides a graphical user interface. The software automatically stores the data, which can then be reviewed for quality assurance, plotted, statistically analyzed, and mapped or exported to other platforms (e.g., Esri ArcGIS©) for further evaluation. Image processing algorithms have been developed using a combination of open-source and commercially available software packages (e.g., MATLAB® and OpenCV) to automatically quantify key parameters. Novel/Additive Information: SPI technology’s underutilization in the oil and gas industry may be in part due to a lack of standardization in the measurement of basic features in SPI images. A primary objective of this work is to develop a streamlined, standardized, and transparent process for generating and managing SPI data.

02 PETROLEUM↗
DOE OSTI2018

Competing Grain Boundary and Interior Deformation Mechanisms with Varying Sizes

In typical coarse-grained alloys, the dominant plastic deformations are dislocation gliding or climbing, and material strengths can be tuned by dislocation interactions with grain boundaries, precipitates, solid solutions, and other defects. With the reduction of grain size, the increase of material strengths follows the classic Hall-Petch relationship up to nano-grained materials. Even at room temperatures, nano-grained materials exhibit strength softening, or called the inverse Hall-Petch effect, as grain boundary processes take over as the dominant deformation mechanisms. On the other hand, at elevated temperatures, grain boundary processes compete with grain interior deformation mechanisms over a wide range of the applied stress and grain sizes. This book chapter reviews and compares the rate equation model and the microstructure-based finite element simulations. The latter explicitly accounts for the grain boundary sliding, grain boundary diffusion and migration, as well as the grain interior dislocation creep. Therefore the explicit finite element method has clear advantages in problems where microstructural heterogeneities play a critical role, such as in the gradient microstructure in shot peening or weldment. Furthermore, combined with the Hall-Petch effect and its breakdown, the above competing processes help construct deformation mechanism maps by extending from the classic Frost-Ashby type to the ones with the dependence of grain size.

Zhang, Wei↗
DOE OSTI2017

Revisiting the conversion reaction voltage and the reversibility of the CuF2 electrode in Li-ion batteries

Deviation between thermodynamic and experimental voltages is one of the key issues in Li-ion conversion-type electrode materials; the factor that affects this phenomenon has not been understood well in spite of its importance. In this work, we combine first principles calculations and electrochemical experiments with characterization tools to probe the conversion reaction voltage of transition metal difluorides MF2 (M = Fe, Ni, and Cu). We find that the conversion reaction voltage is heavily dependent on the size of the metal nanoparticles generated. The surface energy of metal nanoparticles appears to penalize the reaction energy, which results in a lower voltage compared to the thermodynamic voltage of a bulk-phase reaction. Furthermore, we develop a reversible CuF2 electrode coated with NiO. Electron energy loss spectroscopy (EELS) elemental maps demonstrate that the lithiation process mostly occurs in the area of high NiO content. This suggests that NiO can be considered a suitable artificial solid electrolyte interphase that prevents direct contact between Cu nanoparticles and the electrolyte. Thus, it alleviates Cu dissolution into the electrolyte and improves the reversibility of CuF2.

Seo, Joon Kyo↗
DOE OSTI2021

Manifold learning for coarse-graining atomistic simulations: Application to amorphous solids

In this work, we introduce a generalized machine learning framework to probabilistically parameterize upper-scale models in the form of nonlinear PDEs consistent with a continuum theory, based on coarse-grained atomistic simulation data of mechanical deformation and flow processes. The proposed framework utilizes a hypothesized coarse-graining methodology with manifold learning and surrogate-based optimization techniques. Coarse-grained high-dimensional data describing quantities of interest of the multiscale models are projected onto a nonlinear manifold whose geometric and topological structure is exploited for measuring behavioral discrepancies in the form of manifold distances. A surrogate model is constructed using Gaussian process regression to identify a mapping between stochastic parameters and distances. Derivative-free optimization is employed to adaptively identify a unique set of parameters of the upper-scale model capable of rapidly reproducing the system's behavior while maintaining consistency with coarse-grained atomic-level simulations. The proposed method is applied to learn the parameters of the shear transformation zone (STZ) theory of plasticity that describes plastic deformation in amorphous solids as well as coarse-graining parameters needed to translate between atomistic and continuum representations. We show that the methodology is able to successfully link coarse-grained microscale simulations to macroscale observables and achieve a high-level of parity between the models across scales.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Proteomic profile changes associated with diminished expression of T-cell intracellular antigens reveal a hormesis response

T-cell intracellular antigen (TIA) proteins function as regulators of cell homeostasis by controlling global gene expression in response to dynamic regulatory changes and environmental stress. Here, we used two-dimensional differential in-gel electrophoresis (2D-DIGE) and mass spectrometry (MALDI-TOF/TOF) to identify protein changes associated with the down-regulated expression of TIA proteins. We detected 30 differentially expressed proteins (DEPs), 24 of which were identified, and some of these DEPs were validated by western blotting. In silico analysis showed that DEPs were associated with metabolic processes, detoxification and proteostasis. We mapped the DEPs to the available biological pathways and networks, which included the metabolism of small molecules such as sugars, lipids, amino acids, and nucleotides. Our findings support previous studies and suggest that low expression of TIA proteins might act as a potential adaptive switch to link gene expression reprogramming to a proliferative phenotype mediated by a hormesis phenomenon.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI

We introduce GenAI4UQ, a software package for forward and inverse uncertainty quantification in model calibration, parameter estimation, and ensemble forecasting. GenAI4UQ leverages a generative AI-based conditional modeling framework to address limitations of traditional inverse modeling techniques, such as Markov Chain Monte Carlo (MCMC) methods. By replacing computationally intensive iterative processes with a direct, learned mapping, GenAI4UQ enables efficient calibration of input parameters and generation of predictions directly from observations. The software supports rapid ensemble forecasting with robust uncertainty quantification while maintaining computational and storage efficiency. Built-in auto-tuning of hyperparameters simplifies model training, ensuring accessibility for users with varying expertise. Its versatile conditional generative framework is applicable across diverse scientific domains. While GenAI4UQ offers significant advantages in flexibility and efficiency, users should interpret its uncertainty estimates with caution in data-sparse scenarios, as the model may overestimate uncertainty—an effect common to all surrogate-based approaches including MCMC with surrogate models. Despite this, GenAI4UQ transforms inverse modeling by providing a fast, reliable, and user-friendly solution. It empowers researchers and practitioners to quickly estimate parameter distributions and generate model predictions for new observations, facilitating efficient decision-making and advancing the state of uncertainty quantification in computational modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN’s ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Lastly, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Hierarchical Self-Assembly of Carbon Dots into High-Aspect-Ratio Nanowires

Here, we report a spontaneous and hierarchical self-assembly mechanism of carbon dots prepared from citric acid and urea into nanowire structures with large aspect ratios (>50). Scattering-type scanning near-field optical microscopy (s-SNOM) with broadly tunable mid-IR excitation was used to interrogate details of the self-assembly process by generating nanoscopic chemical maps of local wire morphology and composition. s-SNOM images capture the evolution of wire formation and the complex interplay between different chemical constituents directing assembly over the nano- to microscopic length scales. We propose that residual citrate promotes tautomerization of melamine surface functionalities to produce supramolecular shape synthons comprised of melamine-cyanurate adducts capable of forming long-range and highly directional hydrogen-bonding networks. This intrinsic, heterogeneity-driven self-assembly mechanism reflects synergistic combinations of high chemical specificity and long-range cooperativity that may be harnessed to reproducibly fabricate functional structures on arbitrary surfaces.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Electroluminescence from Single-Walled Carbon Nanotubes with Quantum Defects

Individual single-walled carbon nanotubes with covalent sidewall defects have emerged as a class of photon sources whose photoluminescence spectra can be tailored by the carbon nanotube chirality and the attached functional group/molecule. Here we present electroluminescence spectroscopy data from single-tube devices based on (7, 5) carbon nanotubes, functionalized with dichlorobenzene molecules, and wired to graphene electrodes. We observe electrically generated, defect-induced emissions that are controllable by electrostatic gating and strongly red-shifted compared to emissions from pristine nanotubes. The defect-induced emissions are assigned to excitonic and trionic recombination processes by correlating electroluminescence excitation maps with electrical transport and photoluminescence data. At cryogenic conditions, additional gate-dependent emission lines appear, which are assigned to phonon-assisted hot-exciton electroluminescence from quasi-levels. Similar results were obtained with functionalized (6, 5) nanotubes. We also compare functionalized (7, 5) electroluminescence data with photoluminescence of pristine and functionalized (7, 5) nanotubes redox-doped using gold(III) chloride solution. This work shows that electroluminescence excitation is selective toward neutral defect-state configurations with the lowest transition energy, which in combination with gate-control over neutral versus charged defect-state emission leads to high spectral purity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Overlapping qubits from non-isometric maps and de Sitter tensor networks

The emergence of a local effective theory from a more fundamental theory of quantum gravity with seemingly fewer degrees of freedom is a major puzzle of theoretical physics. A recent approach to this problem is to consider general features of the Hilbert space maps relating these theories. In this work, we construct approximately local observables, or overlapping qubits, from such non-isometric maps. We show that local processes in effective theories can be spoofed with a quantum system with fewer degrees of freedom, with deviations from actual locality identifiable as features of quantum gravity. For a concrete example, we construct two tensor network models of de Sitter space-time, demonstrating how exponential expansion and local physics can be spoofed for a long period before breaking down. Our results highlight the connection between overlapping qubits, Hilbert space dimension verification, degree-of-freedom counting in black holes, holography, and approximate locality in quantum gravity.

Quantum information↗
DOE OSTI2021

Inverse design of two-dimensional materials with invertible neural networks

The ability to readily design novel materials with chosen functional properties on-demand represents a next frontier in materials discovery. However, thoroughly and efficiently sampling the entire design space in a computationally tractable manner remains a highly challenging task. To tackle this problem, we propose an inverse design framework (MatDesINNe) utilizing invertible neural networks which can map both forward and reverse processes between the design space and target property. This approach can be used to generate materials candidates for a designated property, thereby satisfying the highly sought-after goal of inverse design. We then apply this framework to the task of band gap engineering in two-dimensional materials, starting with MoS 2 . Within the design space encompassing six degrees of freedom in applied tensile, compressive and shear strain plus an external electric field, we show the framework can generate novel, high fidelity, and diverse candidates with near-chemical accuracy. We extend this generative capability further to provide insights regarding metal-insulator transition in MoS 2 which are important for memristive neuromorphic applications, among others. This approach is general and can be directly extended to other materials and their corresponding design spaces and target properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hemispherical power asymmetry in intensity and polarization for Planck PR4 data

Abstract One of the foundations of the Standard Model of Cosmology is statistical isotropy, which can be tested, among other probes, through the study of the Cosmic Microwave Background (CMB). However, a hemispherical power asymmetry on large scales has been reported for WMAP and Planck data by different works.The statistical significance is above 3σfor temperature, suggesting a directional dependence of the local power spectrum, and thus a feature beyond the ΛCDM model. With the third release of the Planck data (PR3), a new analysis was performed including the E-mode polarization maps, finding an asymmetry at a modest level of significance. In this work, we perform an asymmetry analysis in intensity and polarization maps for the latest Planck processing pipeline (PR4). We obtain similar results to those obtained with PR3, with a slightly lower significance (2.8% for the Sevem method)for the amplitude of the E-mode local variance dipole as well as a significant variability with the considered mask.In addition, a hint of a possible T-E alignment between the asymmetry axes is found at the level of ∼ 5%. For the analysis, we have implemented an alternative inpainting approach in order to get an accurate reconstruction of the E-modes. More sensitive all-sky CMB polarization data, such as those expected from the future LiteBIRD experiment, are needed to reach a more robust conclusion on the possible existence of deviations from statistical isotropy in the form of a hemispherical power asymmetry.

Astronomy & Astrophysics↗
DOE OSTI2022

Perovskite grain wrapping by converting interfaces and grain boundaries into robust and water-insoluble low-dimensional perovskites

Stabilizing perovskite solar cells requires consideration of all defective sites in the devices. Substantial efforts have been devoted to interfaces, while stabilization of grain boundaries received less attention. Here, we report on a molecule tributyl(methyl)phosphonium iodide (TPI), which can convert perovskite into a wide bandgap one-dimensional (1D) perovskite that is mechanically robust and water insoluble. Mixing TPI with perovskite precursor results in a wrapping of perovskite grains with both grain surfaces and grain boundaries converted into several nanometer-thick 1D perovskites during the grain formation process as observed by direct mapping. The grain wrapping passivates the grain boundaries, enhances their resistance to moisture, and reduces the iodine released during light soaking. The perovskite films with wrapped grains are more stable under heat and light. The best device with wrapped grains maintained 92.2% of its highest efficiency after light soaking under 1-sun illumination for 1900 hours at 55°C open-circuit condition.

14 SOLAR ENERGY↗
DOE OSTI2023

QASMTrans

A transpiler that incorporates several key features. It includes a mapping and routing method, a process for decomposing gates into basis gates compatible with IBM machines, and a remapping method designed to enhance simulation performance. Compared to the state-of-art transpiler qiskit, we have dramatically speed up in various benchmarks.

Hua,, Fei↗