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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 OSTI2015

Topological defect dynamics in operando battery nanoparticles

Topological defects can markedly alter nanomaterial properties. This presents opportunities for "defect engineering," where desired functionalities are generated through defect manipulation. However, imaging defects in working devices with nanoscale resolution remains elusive. We report three-dimensional imaging of dislocation dynamics in individual battery cathode nanoparticles under operando conditions using Bragg coherent diffractive imaging. Dislocations are static at room temperature and mobile during charge transport. During the structural phase transformation, the lithium-rich phase nucleates near the dislocation and spreads inhomogeneously. The dislocation field is a local probe of elastic properties, and we find that a region of the material exhibits a negative Poisson's ratio at high voltage. Operando dislocation imaging thus opens a powerful avenue for facilitating improvement and rational design of nanostructured materials.

25 ENERGY STORAGE↗
DOE OSTI2017

Application of photoluminescence imaging and laser-beam-induced-current mapping in thin film solar cell characterization

My research projects are focused on application of photonics, optics and micro- fabrication technology in energy related fields. Photonic crystal fabrication research has the potential to help us generate and use light more efficiently. In order to fabricate active 3D woodpile photonic structure devices, a woodpile template is needed to enable the crystal growth process. We developed a silica woodpile template fabrication process based on two polymer transfer molding technique. A silica woodpile template is demonstrated to work with temperature up to 900 C. It provides a more economical way to explore making better 3D active woodpile photonic devices like 3D photonic light emitting diodes (LED). Optical research on solar cell testing has the potential to make our energy generation more e cient and greener. PL imaging and LBIC mapping are used to measure CdTe solar cells with different back contacts. A strong correlation between PL image defects and LBIC map defects is observed. This opens up potential application for PL imaging in fast solar cell inspection. 2D laser IV scan shows its usage in 2D parameter mapping. We show its ability to generate important information about solar cell performance locally around PL image defects.

14 SOLAR ENERGY↗
NASA NTRS2001

Phase sensitive x-ray diffraction imaging of defects in biological macromolecular crystals

Conventional x-ray diffraction topography is currently used to map defects in the bulk of protein crystals, but the lack of sufficient contrast is frequently a limiting factor. We experimentally demonstrate that this barrier can be circumvented using a method that combines phase sensitive and diffraction imaging principles. Details of defects revealed in tetragonal lysozyme and cubic ferritin crystals are presented and discussed. The approach enabling the detection of the phase changes of diffracted x rays should prove to be useful in the study of defect structures in a broad range of biological macromolecular crystals.

Muramidase/chemistry↗
NASA NTRS2002

Phase Sensitive X-Ray Diffraction Imaging of Defects in Biological Macromolecular Crystals

Characterization of defects and/or disorder in biological macromolecular crystals presents much greater challenges than in conventional small-molecule crystals. The lack of sufficient contrast of defects is often a limiting factor in x-ray diffraction topography of protein crystals. This has seriously hampered efforts to understand mechanisms and origins of formation of imperfections, and the role of defects as essential entities in the bulk of macromolecular crystals. In this report, we employ a phase sensitive x-ray diffraction imaging approach for augmenting the contrast of defects in protein crystals.

Hu, Z. W.↗
DOE OSTI2019

Automated Quantitative Analysis of Extended Irradiation Defects - Dislocations, Voids and Precipitates in Neutron Irradiated HT-9 Steel

Structural alloys that make up the core components of nuclear reactors are exposed to radiation that can substantially alter the microstructure and mechanical properties of the material. Irradiation can cause the formation of extended defects including dislocation line and loops, voids and various types of precipitates. To understand the irradiation effects, it is critical to characterize these defects individually and collectively to quantify how they evolve throughout irradiation stages. Transmission electron microscopy (TEM) is a standard tool for providing extensive size, number density and spatial distribution of extended irradiation defects, however, manual measurement of defect size and number density requires time-intensive effort to analyze enough defects that provide a statistically meaningful result and are prone to errors of subjectivity. In this work, we developed a set of MATLAB algorithms offering robust and automated identification and quantification of extended irradiation defects like dislocation lines, voids and precipitates commonly observed in neutron irradiated cladding alloys [1]. Using a neutron-irradiated HT-9 martensitic alloy irradiated at 412°C to 111.8 dpa, we demonstrate the capability of these algorithms for quantitative defect analysis. Figure 1 presents defect images of the HT-9 using an advanced diffraction contrast imaging scanning transmission electron microscopy (DCI STEM) that suppresses bend contours and provides better defect contrast compared to conventional TEM [2]. The first step of defect analysis is defect identification, a process that can be digitally achieved by contrast thresholding (for simple defect contrast) and by machine learning computer vision for defect semantic segmentation [3]. Here, labeled binary defect images (Figures 2a and 2c) were used. For dislocation density quantification, we employed an optimized circular-grid intersection method first introduced by Dr. John Steeds [4]. This method is shown in Figures 2a and 2b, where the number of intersections of dislocation lines with circular traces was measured. This produces an unbiased sampling of dislocation lines, regardless of their orientation. This process was optimized with automated digital intersection number and grid length registration. Interestingly, it was found that a relatively large number of circles in a set circular gird is was needed to produce an invariant result (Figure 2b), with a low systematic measurement error. This demonstrates the main advantage of computer-based defect analysis, in performing repetitive operations quickly with a reduced systematic error. For the quantitative analysis of voids and precipitates a challenge encountered with automated defect analysis is feature overlap, particularly when the density of voids/precipitates is high. To mitigate this problem, as shown in Figure 2d, we modified the popular circular Hough transformation and treated ‘circular shape’ as the particle descriptor for voids/precipitates, efficiently resolving the overlapping particles. In summary, this automated digital quantification together with machine learning enabled defect identification [3] opens new opportunities for standardizing the characterization workflow for quantitative analysis of extended irradiation defects.

Sainju, Rajat↗
DOE OSTI2022

X-ray nano-imaging of defects in thin film catalysts via cluster analysis

Functional properties of transition-metal oxides strongly depend on crystallographic defects; crystallographic lattice deviations can affect ionic diffusion and adsorbate binding energies. Scanning x-ray nanodiffraction enables imaging of local structural distortions across an extended spatial region of thin samples. Yet, localized lattice distortions remain challenging to detect and localize using nanodiffraction, due to their weak diffuse scattering. Here, in this study, we apply an unsupervised machine learning clustering algorithm to isolate the low-intensity diffuse scattering in as-grown and alkaline-treated thin epitaxially strained SrIrO 3 films. We pinpoint the defect locations, find additional strain variation in the morphology of electrochemically cycled SrIrO 3 , and interpret the defect type by analyzing the diffraction profile through clustering. Our findings demonstrate the use of a machine learning clustering algorithm for identifying and characterizing hard-to-find crystallographic defects in thin films of electrocatalysts and highlight the potential to study electrochemical reactions at defect sites in operando experiments.

42 ENGINEERING↗
DOE OSTI2019

ADVANCED-STEM-BASED DEEP LEARNING FOR SEMANTIC SEGMENTATION OF DEFECTS IN STEELS

In this work, we developed a novel deep convolutional neural network (DCNN) model, called DefectNet, for robust and automated semantic segmentation of three crystallographic defects including line dislocations, precipitates and voids commonly observed in structural metals and alloys. In previous work, we established an experimental protocol for a diffraction contrast imaging scanning transmission electron microscopy (DCI STEM) technique and tailored it specifically for imaging defects in popular iron-based structural alloy. Thus, the DefectNet was trained over a small but high-quality DCI STEM defect image sets of a HT-9 martensitic steel before and after neutron irradiation for 111.8 dpa at 412°C. For the defect quantification that typically takes at least half an hour even for an expert, with a good model the machine learning algorithm can produce more reproducible and reliable quantification in a few seconds. This work demonstrates the feasibility of using deep learning algorithms for fast and accurate defect quantitative analysis.

Machine Learning, Radiation effects, Image analysi↗
NASA NTRS1989

Acoustical Imaging Of Defects In Ceramics

Because of their brittle nature, ceramics are extremely sensitive to even slight variations in microstructure. Direct observations show importance of kinds of defects by identifying them as sites of localized failures. Sites cannot be determined priori by optical and x-ray methods. Color images obtained from precise acoustic measurements reveal subtle variations in porosity fractions and mean sizes of pores in ceramics. Velocity and attenuation of ultrasound found related directly to density and mean size of pores, respectively.

Generazio, Edward R.↗
DOE OSTI2024

Molecular-Resolution Electron Imaging of Defects and Dynamics at the Ice-Water Interface

Water crystallization into hexagonal ice (type I h ) is one of the most critical processes relevant to the Earth’s environment and human activities. However, despite recent breakthroughs in imaging non-equilibrium condensed ice structures, the ice-water interface has never been imaged at a molecular resolution. This is primarily due to the low stability of the hydrogen bonds in ice under high-resolution microscopy conditions and a lack of methods to prepare compatible samples. Here, this presentation describes the first molecular-resolution imaging of ice crystallized from liquid water and the ice-water interface using high-resolution transmission electron microscopy (HRTEM). By encapsulating deionized (DI) water between two amorphous carbon (a-C) TEM grids and subsequently freezing it with liquid N 2 on a cryo sample stage, we generated two types of ice: non-equilibrium, condensed ice from the atmosphere and encapsulated ice from the DI water (Fig. 1A). Condensed ice usually shows irregular, spherulitic shapes (Fig. 1B). Selected area electron diffraction (SAED) shows that they are a mixture of cubic and hexagonal crystals (Fig. 1C). On the contrary, encapsulated ice forms thin films that contain large-area single-crystalline regions of hexagonal ice oriented along the [0001] zone axis (Fig. 1D). Differential electron energy-loss spectroscopy (EELS) confirmed the high purity of the encapsulated ice free from organic contaminations that are common in other encapsulation methods for HRTEM such as graphene liquid cells. These single-crystalline areas are robust under the electron beam up to ~100 e/Å 2 s. Aberration-corrected HRTEM imaging in these areas achieved a line resolution of ~1.3 Å (Fig. 1E and F). This platform allows us to study near-equilibrium ice structures and dynamics at an unprecedented spatial resolution (Fig. 2). For example, we discovered subdomain-rich regions near the defective crystal edges despite the structure appearing single-crystalline according to diffraction criteria. These subdomains connect via low-angle grain boundaries with flat energy landscapes as a function of tilt angles (according to simulations), showing the high tolerance of ice to defect structures. When we tuned the sample temperature and electron flux rate, we observed radiolysis-controlled bubble generation and dissolution in ice single crystals near a steady state of bubble dynamics. Furthermore, rich beam-induced melting and recrystallization dynamics were observed at the ice-water interface with lattice resolution. These data represent the first observation of the ice-water phase transformation at the sub-nanometer level. In summary, the methods developed in this work enabled molecular-resolution observations of ice and the ice-water interface and shed light on the microstructures and phase transformation pathways. Finer control on the temperature, electron irradiation profile, and imaging detector could eventually lead to real-time observation of ice nucleation in water and address long-standing questions in the nucleation pathways.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1992

Near-infrared cathodoluminescence imaging of defect distributions in In(0.2)Ga(0.8)As/GaAs multiple quantum wells grown on prepatterned GaAs

The defect distribution in a highly strained In(0.2)Ga(0.8)As/GaAs multiple-quantum-well (MQW) structure grown on a patterned GaAs substrate is examined with cathodoluminescence imaging and spectroscopy in the near IR. By spatially correlating the luminescence arising from the MQW exciton recombination (950 nm) with the longer wavelength (1000-1200 nm) luminescence arising from the defect-induced recombination, it is demonstrated that it is possible to determine the regions of highest film quality in both the mesa and valley regions. The present approach enables a judicious determination of the optimal regions to be used for active pixels in InGaAs/GaAs spatial light modulators.

Rich, D. H.↗
DOE OSTI2025

Longitudinal position dependence of dark line defect growth rate in high-power diode lasers at 790 nm

Using a nondestructive, in situ near-infrared defect imaging technique, we obtained time-resolved images of dark line defect (DLD) growth in the cavities of several high-power 790-nm diode lasers and calculated individual DLD growth rates. A clear longitudinal spatial dependence in the DLD growth rate was observed, in which the DLD growth rate was faster near the anti-reflective (AR) facet. Longitudinal spatial hole burning simulation results indicate that the total photon density increases toward the AR facet, while the carrier density decreases toward the AR facet. Here, these results suggest that photon absorption plays a key role in enhancing DLD growth beyond the contribution of the traditional carrier capture mechanism. Asymmetric DLD growth that was preferentially directed toward the high-reflectivity facet was also observed, providing further support for the role of photon absorption in the growth process. To account for these findings, we propose a photon-accelerated mechanism for the enhancement of DLD growth in which the slower carrier capture process in the traditional recombination-enhanced dislocation glide mechanism is replaced by a faster photon absorption process.

Engineering - Electronic and electrical engineerin↗