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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Perfect Strain Relaxation in Metamorphic Epitaxial Aluminum on Silicon through Primary and Secondary Interface Misfit Dislocation Arrays

Understanding the atomically precise arrangement of atoms at epitaxial interfaces is important for emerging technologies such as quantum materials that have function and performance dictated by bonds and defects that are energetically active on the micro-electronvolt scale. A combination of atomistic modeling and dislocation theory analysis describes both primary and secondary dislocation networks at the metamorphic Al/Si (111) interface, which is experimentally validated by atomic resolution scanning transmission electron microscopy. The electron microscopy images show primary misfit dislocations for the majority of the strain relief and evidence of a secondary structure allowing for complete relaxation of the Al–Si misfit strain. Finally, this study demonstrates the equilibrium interface that represents the lowest energy structure of a highly mismatched and semicoherent single-crystal interface with complete strain relief in an atomically abrupt structure.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Thermal conductivity of GaN single crystals: Influence of impurities incorporated in different growth processes

The thermal conductivity of GaN crystals grown by different techniques is analyzed using the 3ω method in the temperature range of 30 K to 295 K. GaN wafers grown by the ammonothermal method show a significant variation in thermal conductivity at room temperature with values ranging between 164 W m -1 K -1 and 196 W m -1 K -1 . GaN crystals produced with the sodium flux and hydride vapor phase epitaxy methods show results of 211 W m -1 K -1 and 224 W m -1 K -1 , respectively, at room temperature. Analysis using secondary ion mass spectrometry indicates varying amounts of impurities between the respective crystals and explains the behavior of thermal conductivity trends in the samples. The observed difference between thermal conductivity curves suggests that scattering of phonons at point defects dominates the thermal conductivity of GaN within the investigated temperature range. Finally, deviations of model curves from thermal conductivity measurements and disparities between modelled characteristic lengths and actual sample thicknesses indicate that phonon resonances are active in GaN.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Efficient ab initio calculations of electron-defect scattering and defect-limited carrier mobility

Electron-defect ($e - \mathrm{d}$) interactions govern charge carrier dynamics at low temperature, where they limit the carrier mobility and give rise to phenomena of broad relevance in condensed matter physics. Ab initio calculations of $e - \mathrm{d}$ interactions are still in their infancy, mainly because they require large supercells and computationally expensive workflows. Here we develop an efficient ab initio approach for computing elastic $e - \mathrm{d}$ interactions, their associated $e - \mathrm{d}$ relaxation times (RTs), and the low-temperature defect-limited carrier mobility. The method is applied to silicon with simple neutral defects, such as vacancies and interstitials. Contrary to conventional wisdom, the computed $e - \mathrm{d}$ RTs depend strongly on carrier energy and defect type, and the defect-limited mobility is temperature dependent. These results highlight the shortcomings of widely employed heuristic models of $e - \mathrm{d}$ interactions in materials. Finally, our method opens avenues for studying $e - \mathrm{d}$ scattering and low-temperature charge transport from first principles.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interstitial solute segregation at triple junctions: Implications for nanomaterials and a case study of hydrogen in palladium

At very fine grain sizes, grain boundary segregation can deviate from conventional behavior due to triple junction effects. While this issue has been addressed in prior work for substitutional alloys, here we develop a framework that accounts for interstitial sites in the grains, grain boundaries, and triple junctions of model Pd(H) polycrystals. This approach allows computation of interstitial segregation spectra separately at both defect types, which permits an understanding of segregation at all grain sizes via a size-scaling spectral isotherm. Here, the size dependencies of dilute Pd(H) are found to be influenced not only by the triple junction content, but also by grain size–dependent lattice strains; the latter effect is evidenced by size dependencies of individual grain boundary and junction subspectra. The framework proposed here is applicable to interstitial alloys in general and may serve as a basis for interfacial engineering in interstitial nanocrystalline alloys. As an example, we show that using the dilute limit isotherm, hydrogen density can triple in nanocrystalline vis-à-vis microcrystalline Pd due to hydrogen adsorption at intergranular defect sites.

Alloys↗
DOE OSTI2019

Development and Demonstration of an In-Situ Tritium Scavenger

The objective of this project was to use an inherent feature of salt-cooled reactors towards the capture and removal of tritium from the primary coolant system: the presence of the graphite moderator. The fuel elements fluoride-salt cooled high-temperature (FHR) reactors consist of a graphite matrix that encapsulates TRISO fuel particles, and the total fuel element surface area of Mark I PB-FHR is 7780 m 2 . Therefore the FHR fuel inherently provides removable graphite of high surface area. The goal of this project was to understand the transport of tritium across the salt-graphite interface. The following was achieved: 1. Electrochemical techniques were demonstrated for studying the entry, diffusion, and trapping of hydrogen isotopes in graphite. 2. Electrochemical techniques were used to demonstrate the relationship between galvanic corrosion between graphite and stainless steel 316 and hydrogen uptake in graphite. 3. Electrochemical techniques were demonstrated for studying the dissolution and diffusion of hydrogen isotopes in molten FLiBe. 4. Thermodynamic reference electrodes were tested for FLiBe and FLiNaK. 5. Electrochemical techniques were demonstrated as an in-salt hydrogen thermal desorption measurement, which had previously only been achieved in gas environments. 6. FLiBe exposure of graphite lead to graphite fluorination and an increase of defects, which indicate an increase of reactive carbon sites available for tritium uptake. 7. TRIDENT modeling was used to perform sensitivity analysis of FHR design parameters on tritium uptake fraction in graphite, showing high sensitivity to tritium diffusivity and solubility. 8. A cross-cutting effort with another NEUP-funded project was initiated for application of the SAM mass-transport module to system-scale tritium modeling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗
DOE OSTI2025

Fused Deposition Modeling Additive Manufacturing of Carbonized Structures via Waste-Enhanced Filaments

This report details the development, characterization, and use of coal-enhanced composite materials in additive manufacturing applications. High coal loading formulations—containing up to 70 wt.% coal—were successfully extruded and processed using commercially available 3D printers. Extensive experimental testing was conducted to assess the mechanical, thermal, and microstructural properties of the composites. In parallel, multi-scale computational modeling was employed to elucidate atomistic interactions and evaluate the effects of printing-induced defects on structural performance. Large-scale printability trials demonstrated the feasibility of fabricating complex components for tooling and construction applications, including wind turbine blade molds and modular wall sections. Techno-economic analyses demonstrated the cost-effectiveness and scalability of coal-enhanced composites for large-scale additive manufacturing applications such as wind turbine blade tooling.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

As‐Doped Polycrystalline CdSeTe: Localized Defects, Carrier Mobility and Lifetimes, and Impact on High‐Efficiency Solar Cells

Abstract The efficiency potential for single‐junction photovoltaics (PV) is described by the detailed balance model, which requires the elimination of nonradiative recombination and perfect minority carrier collection. Improvements in GaAs, Si, and perovskite PV follow this model. It might be more complex for CdTe, a leading thin‐film PV technology. While lifetime, passivation, and doping goals for 25% efficient CdTe solar cells are largely reached, voltage is ≈20% below the detailed balance limit. Why is that? In Se‐alloyed CdSe x Te 1‐x (Se is required for >20% efficiency) additional losses can occur due to electrostatic and bandgap fluctuations and due to electronic trap states. To understand mechanisms limiting CdSeTe solar cell performance and to suggest improvements, carrier dynamics, and transport in CdSe x Te 1‐x with variation in Se composition and as doping is analyzed. It is shown that trapping, likely due to anion‐site defects and their complexes, is correlated with low charge carrier mobility of 0.1–0.6 cm 2 (Vs) −1 . Even with 1000 ns charge carrier lifetimes, carrier diffusion length is less than the absorber thickness, reducing efficiency to ≈23%. Device simulations are used to analyze the performance of CdSe x Te 1‐x solar cells; thermodynamic models are not sufficient for absorbers with electronic disorder and trapping.

14 SOLAR ENERGY↗
DOE OSTI2025

Tiny Bubbles: Combined HR(S)TEM and 4D-STEM Analysis of Sub-Nanometer He Bubbles in Au

Irradiation produces a distribution of defect sizes in materials, with the smallest defects often below one nanometer in size and approaching the scale of a single unit cell in metals. While high-resolution scanning transmission electron microscopy (STEM)-based imaging can directly image structures at this level, techniques such as four-dimensional STEM (4D-STEM) enable characterization of materials across large fields of view, capturing a more representative volume that can be valuable for quantifying defects, their distributions, and the associated strain fields. Here we present a combined HRSTEM and 4D-STEM approach to study the model system of He bubble implantation in an Au thin film. The present work is of general interest for the study of materials in extreme environments, as it demonstrates an effective way to characterize even the tiniest sub-nanometer sized He bubbles in addition to larger irradiation defects.

atomic-resolution STEM↗
DOE OSTI2022

The role of deviatoric stress and dislocations on the α to ω phase transformation in Ti

Under extreme conditions, α-Ti becomes unstable and transforms either into β-Ti at high temperature or into ω-Ti at high pressure. In what concerns the α to ω phase transformation (PT), there has been a wide range of experimentally reported transition pressures from approximately 2 to 15 GPa at room temperature. Deviatoric stresses and internal defects are often assumed to be the root cause of this variation. Here, in this study, these postulates are revisited using both continuum mechanics and molecular dynamics (MD) simulations. First, a simple continuum model, assuming linear elasticity and isotropic plasticity, is developed to describe the effects of applied stress and dislocations on the stability of an ω nucleus in an infinite α domain. Second, a new MD simulation method is developed to generate an ω nucleus in the α domain utilizing the displacement field identified from the topological analysis. Results from MD simulations show that despite the fact that phase diagrams typically delineate the limits between two phases in terms of only P and T, deviatoric stress promotes the α to ω phase transformation by reducing the critical radius above which an ω nucleus is stable. Furthermore, the required deviatoric stress to nucleate and stabilize a nanoscale ω nucleus is likely emanating from the internal stress of defects such as dislocations. The MD-informed micromechanics models are used to identify favorable configurations where dislocations help favor the α to ω transformation. These configurations show that the interaction with a basal or prismatic dislocation reduces the critical radius of a ω nucleus by about 10 or 16 %, respectively. In addition, prismatic edge dislocations are found to promote the growth of ω nucleus when interacting with the ($\bar{1}$$\bar{1}$20) α //(0001) ω interface. Importantly, a simple model of the arrival of dislocation at an ω nucleus suggests that PT does not necessarily require a pile-up to be present but could alternatively be mediated by a constant rapid flow of dislocations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Overexpression of microRNA-26a protects against deficient β-cell function via targeting phosphatase with tensin homology in mouse models of type 2 diabetes

The prevalence of type 2 diabetes mellitus (T2DM) increased rapidly in the world. The development of β-cell dysfunction is the quintessential defects in T2DM patients However, the pathogenesis of β-cell dysfunction is still unclear. MicroRNAs are short non-coding RNAs and has been reported to be involved in pathogenesis of β-cell dysfunction and T2DM. Here, we investigated the mechanisms by which miR-26a regulate β-cell function and insulin signaling pathway in high fat diet (HFD) fed and db/db T2DM mice model. The expression of miR-26a was down-regulated dramatically in the serum and islets of both HFD and db/db mice model. miR-26a overexpression protected against HFD-induced diabetes and maintained prolonged normoglycemic time in HFD fed mice. Overexpression of miR-26a improved β-cell dysfunction in T2DM mice. Further, we identified that PTEN is a direct target gene of miR-26a. Overexpression of miR-26a significantly inhibited the luciferase activity of hPTEN 3′-UTR, while the effect of miR-26a disappeared when the miR-26a potential binding site within the PTEN 3′-UTR was mutated. Overexpression of miR-26a reduced both the mRNA and protein levels of PTEN in vitro and in vivo. We also found that miR-26a overexpression increased the expression of p-Akt and p-FoxO-1, while the effect of miR-26a was blocked by PTEN overexpression. In conclusion, our data indicated that miR-26a potentially contributes to the β-cell dysfunction in T2DM, and miR-26a may be a new therapeutic strategy against T2DM.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Anisotropic shock response of single-crystalline β-phase tin shock physics, molecular dynamics, plasticity

Mesoscale simulations of the dynamic response of polycrystalline metals to shockwave compression can provide unique insight in to the nature of the various physical mechanisms responsible for material failure. This approach requires a constitutive description for individual grains and boundaries, including defects such as dislocations, within an explicit representation of the microstructure geometry and evolving deformation fields. Computational models of the single-crystal constituents cannot be unambiguously constrained by traditional measurements of the shock or stress-strain response of polycrystalline metals. Instead, these models require comprehensive measurements of the anisotropic shock response of single crystals for their calibration and validation. We present a coordinated experimental and simulation campaign on the shock response of single-crystalline β-phase tin demonstrating a remarkable anisotropic elastic-plastic response of the metal. This anisotropy will be explained with the help of molecular dynamics simulations that show preferred twinning in one orientation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Combining phase-field crystal methods with a Cahn-Hilliard model for binary alloys

Diffusion-induced phase transitions typically change the lattice symmetry of the host material. In battery electrodes, for example, Li ions (diffusing species) are inserted between layers in a crystalline electrode material (host). This diffusion induces lattice distortions and defect formations in the electrode. The structural changes to the lattice symmetry affect the host material’s properties. We propose a 2D theoretical framework that couples a Cahn-Hilliard (CH) model, which describes the composition field of a diffusing species, with a phase-field crystal (PFC) model, which describes the host-material lattice symmetry. We couple the two continuum models via coordinate transformation coefficients. We introduce the transformation coefficients in the PFC method to describe affine lattice deformations. These transformation coefficients are modeled as functions of the composition field. Using this coupled approach, we explore the effects of coarse-grained lattice symmetry and distortions on a diffusion-induced phase transition process. In this paper, we demonstrate the working of the CH-PFC model through three representative examples: First, we describe base cases with hexagonal and square symmetries for two composition fields. Next, we illustrate how the CH-PFC method interpolates lattice symmetry across a diffuse phase boundary. Finally, we compute a Cahn-Hilliard type of diffusion and model the accompanying changes to lattice symmetry during a phase transition process.

25 ENERGY STORAGE↗
DOE OSTI2023

Towards deep computer vision for in-line defect detection in polymer electrolyte membrane fuel cell materials

Polymer Electrolyte Membrane (PEM) fuel cells are a promising source of alternative energy. However, their production is limited by a lack of well-established methods for quality control of their constituent materials like the membrane-electrode assembly during roll-to-roll manufacturing. One potential solution is the implementation of deep learning methods to detect unwanted defects through their detection in scanned images. Here we explore the detection of defects like scratches, pinholes, and scuffs in a sample dataset of PEM optical images using two deep learning algorithms: Patch Distribution Modeling (PaDiM) for unsupervised anomaly detection and Faster-RCNN for supervised object detection. Both methods achieve scores on performance metrics (ROC-AUC and PRO-AUC for PaDiM and AP for Faster-RCNN) that are comparable to their scores on benchmark datasets. These methods also have the potential to detect a wider range of defects compared to IR thermography and previous optical inspection methods. Overall, deep learning shows promise at detecting relevant defects of interest and has the potential to achieve real-time defect detection.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Temporal and spatial laser intensification within nodular defects overcoated with multilayer dielectric mirrors over a wide range of defect geometries

The nodular defect shape and the laser incidence angle have a dramatic impact on the spatial distribution of light intensification within the nodule as well as how the laser light is drained from the defect. Nodular defect geometries unique to ion beam sputtering, ion-assisted deposition, and electron-beam (e-beam) deposition, respectively, are modeled in this parametric study over a wide range of nodular inclusion diameters and layer count for optical interference mirror coatings constructed with quarter-wave thicknesses and capped with a half wave of the low index material. It was found for hafnia ($n$=1.9) and silica ($n$=1.45) multilayer mirrors that the light intensification in nodular defects with a $C$ factor of 8, typical of e-beam deposited coatings deposited with a wide range of deposition angles, was maximized for a 24-layer design. For intermediate size inclusion diameters, increasing the layer count for normal incidence multilayer mirrors reduced the light intensification within the nodular defect. A second parametric study explored the impact of the nodule shape on the light intensification for a fixed number of layers. In this case, there is a strong temporal trend for the different nodule shapes. Narrow nodules tend to drain more laser energy through the bottom of the nodule into the substrate while wide nodules tend to drain more laser energy through the top of the nodule when irradiated at normal incidence. Further, at a 45° incidence angle, waveguiding is an additional method to drain laser energy from the nodular defect. Finally, laser light resonates within nodular defects longer than within the adjacent nondefective multilayer structure.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Engineering quantum-coherent defects: The role of substrate miscut in chemical vapor deposition diamond growth

The engineering of defects in diamond, particularly nitrogen-vacancy (NV) centers, is important for many applications in quantum science. A materials science approach based on chemical vapor deposition (CVD) growth of diamond and in situ nitrogen doping is a promising path toward tuning and optimizing the desired properties of the embedded defects. Herein, with the coherence of the embedded defects in mind, we explore the effects of substrate miscut on the diamond growth rate, nitrogen density, and hillock defect density, and we report an optimal angle range for the purposes of engineering coherent ensembles of NV centers in diamond according to our growth parameters. We provide a model that quantitatively describes hillock nucleation in the step-flow regime of CVD growth, shedding insight on the physics of hillock formation. We also report significantly enhanced incorporation of nitrogen at hillock defects, opening the possibility for templating hillock-defect-localized NV center ensembles for quantum applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗