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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ultrasparse View X-ray Computed Tomography for 4D Imaging

X-ray computed tomography (CT) is a noninvasive, nondestructive approach to imaging materials, material systems, and engineered components in two and three dimensions. Acquisition of three-dimensional (3D) images requires the collection of hundreds or thousands of through-thickness X-ray radiographic images from different angles. Such 3D data acquisition strategies commonly involve suboptimal temporal sampling for in situ and operando studies (4D imaging). Herein, we introduce a sparse-view imaging approach, Tomo-NeRF, which is capable of reconstructing high-fidelity 3D images from <10 twodimensional radiographic images. Experimental 2D and 3D X-ray images were used to test the reconstruction capability in two-view, four-view, and six-view scenarios. Tomo-NeRF is capable of reconstructing 3D images with a structural similarity of 0.9971–0.9975 and a voxel-wise accuracy of 81.83–89.59% from 2D experimentally obtained images. Furthermore, the reconstruction accuracy for the experimentally obtained images is less than the synthetic structures. Experimentally obtained images demonstrate a similarity of 0.9973–0.9984 and a voxelwise accuracy of 84.31–95.77%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Using Digital Image Correlation for Material Testing at Cryogenic Temperatures

Recent efforts were made to parametrize an aluminum alloy at cryogenic temperatures to calibrate finite element models simulating material deformation. Digital image correlation (DIC) was used to measure material properties using front/back strains of specimens during tensile tests. Data acquired from DIC was compared to physical extensometer measurements. Two camera pairs (front and back) were mounted via aluminum extrusion to the exterior of an environmental chamber of a hydraulic test stand. Images were taken through single-pane optical glass windows of the environment chamber. Positive pressure bags encased the cameras, attaching to the perimeter of the glass to keep out moisture and prevent windows from frosting. Figure 1 shows the environmental setup and the camera setup during cryogenic testing. Some of the challenges during testing at cryogenic temperatures include the gaseous flow of liquid nitrogen in the optical path of the mounted cameras, frost buildup on the windows as seen in Figure 1b, and frost on the test coupon. The temperature gradient present during the introduction of liquid nitrogen into the chamber can increase the projection error of images captured of the specimen. Figure 2 shows the estimated projection error from DIC as a function of temperature during the cool down process. This presentation addresses some of the concerns and observations when using DIC for testing at cryogenic temperatures using methods of isolated camera system and techniques for maintaining the glass panel clear from frost.

Joseph Cochran↗
DOE OSTI2022

Bridging Nano- and Microscale X-Ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray computed tomography (CT) is a non-destructive imaging technique in which contrast originates from the materials' absorption coefficient. The recent development of laboratory nanoscale CT (nano-CT) systems has pushed the spatial resolution for battery material imaging to voxel sizes of 50 nm, a limit previously achievable only with synchrotron facilities. Given the non-destructive nature of CT, in situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area and volume expansion, during battery operation or cycling. Combined with artificial intelligence and machine learning analysis techniques, nano-CT has enabled the development of predictive models to analyse the impact of the electrode microstructure on cell performances or the influence of material heterogeneities on electrochemical responses. In this Review, we discuss the role of X-ray CT and nano-CT experimentation in the battery field, discuss the incorporation of artificial intelligence and machine learning analyses and provide a perspective on how the combination of multiscale CT imaging techniques can expand the development of predictive multiscale battery behavioural models.

diagnostics↗
DOE OSTI2023

Stochastic generation of electrolyzer anode catalyst layers

Here, we introduce a stochastic methodology to reproduce the complex pore structure observed in commercial iridium catalyst layers. This method preserves the α pore (pores smaller than 250 nm) and β pore (pores greater than or equal to 250 nm) regions of the catalyst layer. The morphology of the generated materials was validated by comparing the pore size distributions of generated materials against those obtained from commercial materials imaged using x-ray nano computed tomography. We further demonstrate that the pore size distributions of the generated materials are statistically indistinguishable from the imaged catalyst layers, indicating that the stochastic methodology is capable of accurately reproducing catalyst layer morphology. Pore network modelling was conducted on the generated catalyst materials to simulate single-phase permeability, electrical conductivity, and ionic conductivity, and these properties were found to be within experimentally measured ranges for electrolyzer catalyst layers. Additionally, simulations were performed on the generated materials with varying ionomer and iridium catalyst loadings. As the ionomer loading is added, proton conductivity increases exponentially, which demonstrates the importance of optimizing ionomer loading, considering that these effects will be exacerbated in the hydration and temperature conditions of operating electrolyzers. The stochastic material generation method presented in this work is a powerful tool for the development of novel low loading catalyst layers, where the effect of various structural parameters on electrolyzer performance characteristics can be explored.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Terahertz Nanoimaging of Perovskite Solar Cell Materials

Direct visualization and quantitative evaluation of charge filling in grain boundary (GB) traps of hybrid metal halide perovskites require dynamic conductivity imaging simultaneously at the terahertz (THz) frequency and nanometer (nm) spatial scales not accessible by conventional transport and imaging methods used thus far. Here, in this study, we apply a THz near-field nanoconductivity mapping to the archetypal metal halide perovskite photovoltaic films and demonstrate that it is a powerful tool to reveal distinct dielectric heterogeneity due to charge trapping and degradation at the single GB level. Our approach visualizes the filled defect ion traps by local THz charge conductivity and allows for extracting a quantitative profile of trapping density in the vicinity of GBs with sub-20 nm resolution. Furthermore, imaging material degradation by tracking local nanodefect distributions overtime identifies a distinct degradation pathway that starts from the GBs and propagates inside the grains over time. The single GB, nano-THz conductivity imaging demonstrated here can be extended to benchmark various perovskite materials and devices for their global photoenergy conversion performance and local charge transfer proprieties of absorbers and interfaces.

14 SOLAR ENERGY↗
DOE OSTI2024

Polarization-dependent photoemission electron microscopy for domain imaging of inorganic and molecular materials

Polarization-dependent photoemission electron microscopy (PD-PEEM) exploits spatial variation in the optical selection rules of materials to image domain formation and material organization on the nanoscale. In this Perspective, we discuss the mechanism of PD-PEEM that results in the observed image contrast in experiments and provide examples of a wide range of material domain structures that PD-PEEM has been able to elucidate, including molecular and polymer domains, local electronic structure and defect symmetry, (anti)ferroelectricity, and ferromagnetism. As a result, we discuss challenges and new directions that are possible with this tool for probing domain structure in materials, including investigating the formation of transient ordered states, multiferroics, and the influence of molecular and polymer order and disorder on excited state dynamics and charge transport.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cladding Ring Tension Testing (RTT) of unirradiated cladding materials using Digital Image Correlation (DIC)

Cladding Ring Tension Testing (RTT) of unirradiated cladding materials using Digital Image Correlation (DIC). RTT is an important tool for determining hoop strength of thin-walled tubing, especially in anisotropic materials such as zirconium fuel cladding. The goal is to set up a DIC system to a tensile test on these RTT specimens and study the mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Multi-Objective Bayesian Optimized Human Assessed Multi-Target Generated Spectral Recommender System for Rapid Pareto Discoveries of Material Properties

Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.

Biswas, Arpan↗
NASA NTRS1981

Landsat classification of coastal wetlands in Texas

Through a multiagency study of Landsat imagery applications, an analysis of Texas coastal wetlands shows that five Level III categories of wetlands can be delineated using image interpretation: topographically low marshes, topographically high marshes, tidal flats, sea grass and algal flats, and vegetated dredged material. Image interpretation involves optical enlargement of 1:1,000,000 scale, Landsat transparencies to a scale of 1:125,000 and mapping on a stable film base. Digital classification procedures, resulting in 1:24,000 scale line printer maps as output, require several iterations to display welands effectively. Accuracies of 65% were achieved for all wetland categories combined.

Finley, R. J.↗
DOE OSTI2020

Biomedical Integration of Metal–Organic Frameworks

Metal–organic frameworks (MOFs) have recently been demonstrated to be excellent platforms for biomedical applications. On account of their porous nature and modular structure, MOFs have served as bioactive-compound carriers, cell-imaging materials, and therapeutic agents. MOF cavities allow the encapsulation of a variety of guest molecules, facilitating controllable drug release and optical imaging. The metal components of MOFs make them suitable for magnetic resonance imaging (MRI) and computed tomography (CT). Further, MOF-embedded therapeutic agents have demonstrated promise in photodynamic and photothermal therapies. In this review, we describe several advanced examples that utilize MOFs in these cutting-edge applications. Investigation of the relationship between their structure and designated application will enable future, informed exploration of MOFs for biomedical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Characterization of Novel Spacecraft Materials aboard the Materials International Space Station Experiment-Flight Facility (Preliminary Results)

This work will encompass the preflight characterization of 15 novel and heritage materials currently under observation on the Materials International Space Station Experiment-Flight Facility (MISSE-FF). MISSE-FF has been upgraded to perform active reflectance measurements of the materials. Images taken in RGB/IR colors are compared to results from an extensive ground testing campaign to obtain quantitative on-orbit material evolution data. Identical materials samples are to be flown on the ram, wake, and zenith faces of MISSE-FF, enabling deconvolution of the energetic electron, proton, atomic oxygen, and ultraviolet damage pathways. Energy deposition from the space environment leads to chemical changes in the material that in turn alter the optical properties. The same chemical damage that manifests as changes in optical reflectance and absorptance also leads to changes in myriad physical properties such as mechanical strength, electrical conductivity, and chemical reactivity. Therefore, flight materials are able to be characterized based on their unique reflectance spectra by comparing on-orbit measurements of optical reflectance with extensive terrestrial experiments, which help to correlate changes in reflectance with respect to changes in other material properties. The MISSE program has been a part of the International Space Station National Laboratory for many years and has been instrumental in understanding space weather modification of material properties. However, MISSE-FF has been limited to passive experiments with only pre/post flight material studies possible. In advance of the MISSE-16 experiment, the flight facility has received a major upgrade to provide daily spectral observations by way of a RGB/IR camera and a tunable light source. The MISSE-16 mission launched in February 2022 and carries 15 material samples for 6 months of the low Earth orbital exposure. Identical materials samples are to be flown on the ram, wake, and zenith faces of MISSE-FF, enabling deconvolution of the energetic electron, proton, atomic oxygen, and ultraviolet damage pathways. This paper discusses the MISSE-16 experiment, highlights the first use of the facility upgrades, and presents results from the extensive preflight material characterization that includes directional hemispherical reflectance, bidirectional reflectance, AFM, SEM, and electrical conductivity. Additionally, data showing the modification of these properties by ground-based exposure to space-like electron and atomic oxygen flux will be discussed. Finally, updates on deployment and initial check-out of the experiment on MISSE-FF will be presented. It is the ultimate goal of this program to provide validation for the development of ground based space weather simulation facilities and techniques.

Ryan Hoffman↗
NASA NTRS1988

Applications of synchrotron radiation to materials science: Diffraction imaging (topography) and microradiography

Synchrotron radiation sources are now available throughout the world. The use of hard X-ray radiation from these sources for materials science is described with emphasis on diffraction imaging for material characterization. With the availability of synchrotron radiation, real-time in situ measurements of dynamic microstructural phenomena have been started. This is a new area where traditional application of X-rays has been superseded. Examples are chosen from limited areas and are by no means exhaustive. The new emerging information will, no doubt, have great impact on materials science and engineering.

Kuriyama, Masao↗
DOE OSTI2023

Making and breaking terahertz waves with fluid plasmas

Vigorous research efforts during the past several decades have successfully closed the “terahertz gap” between microwaves and infrared light, offering new and increasingly efficient ways to produce, detect, and manipulate radiation fields in the terahertz (THz) frequency range. In our laboratory, THz time-domain spectroscopy (THz-TDS) and optical-pump THz-probe (OPTP) experiments have been routinely utilized as ultrafast spectroscopy tools to investigate a variety of emerging quantum materials and metamaterials. The ultrafast THz pulses are produced by femtosecond laser excitation of photoconductive antennas, semiconductor surfaces (InAs), and nonlinear crystals (ZnTe, GaSe, and LiNbO 3 ). Photoconductive antennas and nonlinear crystals also allow for the coherent detection of these pulses in the time domain, with amplitude and phase spectra obtained in the frequency domain via fast Fourier transform. Although such solid-state schemes are highly desirable in many aspects and thus also commonly utilized in many research laboratories and industrial applications, they typically suffer from limited bandwidths due to the absorption and frequency dispersion induced primarily by phonon resonances, limiting THz applications such as spectroscopy of emerging materials, imaging and detection, and biomedical characterization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

In Situ Transmission Electron Microscopy: Signal processing challenges and examples

Transmission electron microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TEM have enabled high-volume and high-resolution data collection at a microsecond frame rate. Here, taking advantage of these advances in data collection rates requires the development and application of data processing tools, including image analysis, feature extraction, and streaming data processing techniques. In this article, we highlight a few areas in materials science that have benefited from combining signal processing and statistical analysis with data collection capabilities in TEM and present a future outlook on opportunities of integrating signal processing with automated TEM data analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Annealing of focused ion beam damage in gold microcrystals: an in situ Bragg coherent X-ray diffraction imaging study

Focused ion beam (FIB) techniques are commonly used to machine, analyse and image materials at the micro- and nanoscale. However, FIB modifies the integrity of the sample by creating defects that cause lattice distortions. Methods have been developed to reduce FIB-induced strain; however, these protocols need to be evaluated for their effectiveness. Here, non-destructive Bragg coherent X-ray diffraction imaging is used to study the in situ annealing of FIB-milled gold microcrystals. Two non-collinear reflections are simultaneously measured for two different crystals during a single annealing cycle, demonstrating the ability to reliably track the location of multiple Bragg peaks during thermal annealing. The thermal lattice expansion of each crystal is used to calculate the local temperature. This is compared with thermocouple readings, which are shown to be substantially affected by thermal resistance. To evaluate the annealing process, each reflection is analysed by considering facet area evolution, cross-correlation maps of the displacement field and binarized morphology, and average strain plots. The crystal's strain and morphology evolve with increasing temperature, which is likely to be caused by the diffusion of gallium in gold below ~280°C and the self-diffusion of gold above ~280°C. The majority of FIB-induced strains are removed by 380–410°C, depending on which reflection is being considered. These observations highlight the importance of measuring multiple reflections to unambiguously interpret material behaviour.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1996

Method of Poisson's ratio imaging within a material part

The present invention is directed to a method of displaying the Poisson's ratio image of a material part. In the present invention longitudinal data is produced using a longitudinal wave transducer and shear wave data is produced using a shear wave transducer. The respective data is then used to calculate the Poisson's ratio for the entire material part. The Poisson's ratio approximations are then used to displayed the image.

Roth, Don J.↗
DOE OSTI2023

Demonstration of an AI-driven workflow for autonomous high-resolution scanning microscopy

Abstract Modern scanning microscopes can image materials with up to sub-atomic spatial and sub-picosecond time resolutions, but these capabilities come with large volumes of data, which can be difficult to store and analyze. We report the Fast Autonomous Scanning Toolkit (FAST) that addresses this challenge by combining a neural network, route optimization, and efficient hardware controls to enable a self-driving experiment that actively identifies and measures a sparse but representative data subset in lieu of the full dataset. FAST requires no prior information about the sample, is computationally efficient, and uses generic hardware controls with minimal experiment-specific wrapping. We test FAST in simulations and a dark-field X-ray microscopy experiment of a WSe 2 film. Our studies show that a FAST scan of <25% is sufficient to accurately image and analyze the sample. FAST is easy to adapt for any scanning microscope; its broad adoption will empower general multi-level studies of materials evolution with respect to time, temperature, or other parameters.

47 OTHER INSTRUMENTATION↗