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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 487 records · Page 27

X-ray topography as a process control tool in semiconductor and microcircuit manufacture

A bent wafer camera, designed to identify crystal lattice defects in semiconductor materials, was investigated. The camera makes use of conventional X-ray topographs and an innovative slightly bent wafer which allows rays from the point source to strike all portions of the wafer simultaneously. In addition to being utilized in solving production process control problems, this camera design substantially reduces the cost per topograph.

Parker, D. L.↗

The effect of oxidation-expanded defects upon MOS parameters

Implantation of Ne ions was chosen as a means of introducing a uniformly distributed quantitatively controllable and reproducible amount of microdefects at the silicon surface. Each wafer was ion-implanted on one half of its surface, the other half remaining as a control. Seven implant fluences from 1 trillion to 5 by 10 to the 14th power Ne ions/sq cm were used. The fluences, as well as the concentrations of defects expanded by the subsequent gate oxidation, were correlated with seven different MOS parameters. For implant fluences of 10 to the 14th power per sq cm and above, increasing stacking-fault densities were found. The oxide defect density associated with time-dependent breakdown increased significantly with Ne dose. The presence of oxidation-expanded defects drastically increases the surface-generation velocity and decreases the bulk lifetime. Slight increases in flatband voltage and surface-state density occurred only for the wafers having the greatest defect concentrations. Oxidation of a P-containing damaged silicon surface results in a greater pileup of P at the surface than occurs for the oxidation of a similar but undamaged surface. It appears that the expanding defects restrain the diffusion of P inward from the surface.

Prussin, S.↗

Point defects in semiconductors: Friends and foes for quantum technologies

Point defects in semiconductors are both a curse and a blessing in microelectronics: they enable the control of electrical conductivity through doping, yet can also act as trapping and recombination centers that degrade device performance. In quantum information science, defects play a similarly dual role. They can be harnessed as spin–photon interfaces enabling the coupling of electronic and nuclear spins to light and the creation of distributed entanglement for quantum networks or used as atomistic scale sensors for quantum sensing. At the same time, defects are a major source of decoherence for superconducting qubits, one of the leading quantum computing platforms. This article discusses how a deeper materials-level understanding of defects can guide the design of improved quantum devices for communication, sensing, and computation.

Zhu, Yizhi [Rice University, Houston, TX (United S↗

NDE of Friction Stir Welds in Aerospace Applications

Friction Stir Welding (FSW) is a solid state joining process, which utilizes a cylindrical, shouldered pin tool with a radiused tip that is rotated and plunged into the weld joint. Frictional heating beneath the shoulder, and surrounding the pin tip causes the material to plasticize, intermix and consolidate into a weldment without melting the parent material. FSW in aluminum alloys has many advantages such as low distortion and shrinkage, excellent mechanical properties, and no porosity. However, the propensity of the FSW process to create detrimental defects does exist, and is dependent on FSW parameter limits and controls. Inspection processes for FSW must also be selected and implemented concurrent with the new weld process. This paper describes the efforts by Lockheed Martin and NASA to find proper NDE techniques for detecting and characterizing the anomalies that may be caused by operating outside the envelope of optimized FSW parameters. Potential defects are identified and the results of the exploration of numerous NDE techniques including visual, liquid penetrant, multiple ultrasonic methods, eddy current and conductivity are discussed.

Kinchen, David G.↗

Mechanistic Insights into Defect-Mediated Crystallization Revealed by Lattice Strain Evolution

Structural defects and lattice strain are intrinsic to many crystalline materials, yet their roles in controlling chemical reaction mechanisms and directing crystallization pathways remain poorly understood. Here, in this study, we revealed the three-dimensional evolution of strain and dislocation defects at the nanoscale during the growth of heterogeneously nucleated barite (BaSO 4 ) and calcite (CaCO 3 ) crystals by using coherent X-ray scattering, electron microscopy, and molecular simulations. Unlike barite, which formed with minimal internal strain, calcite developed dislocation defects and exhibited spatially varying strain that increased during growth. During growth in Sr-rich solutions, calcite likely incorporates Sr 2+ into the defects, which further modulates the local lattice structure and increases both the compressive and tensile strain. These findings suggest that calcite crystallization was likely dominated by attachment of precursor phases, which gave rise to defect-enriched domain structures not predicted by classical growth models. By linking defect formation to ion incorporation and growth dynamics, this work provides fundamental insight into how lattice-level strain heterogeneity governs the chemical reactivity of ionic crystals.

Bragg coherent diffractive imaging↗

High-Throughput Uniformity and Defect Monitoring in Low-Temperature Electrolysis Porous Transport Layers Using X-Ray Radiography

Effective quality control (QC) for manufacturing proton exchange membrane water electrolysis (PEMWE) components is critical to enabling widespread adoption of the technology for hydrogen generation. This study investigates X-ray radiography as a novel, high-throughput, potentially in-line QC technique for detecting defects and assessing material property distributions in titanium-based porous transport layers (PTLs) which constitute a crucial component of low temperature PEMWE stacks. We obtain radiographs of a set of fifteen PTLs and model their absorbance of the broadband radiation as a second-order polynomial to account for the non-monoenergetic radiation source used in this study. The resulting model serves as a basis for predicting the areal density and porosity distributions of the PTLs. We find radiography successful in detecting multiple instances of defects, including holes/depressions, cracks, and excess material on the surface or in the pores of the material, demonstrating its potential as a robust in-line QC tool for PTL manufacturing.

08 HYDROGEN↗

Defect Termination in the UiO-66 Family of Metal–Organic Frameworks: The Role of Water and Modulator

The defect concentration in the prototypical metal–organic framework UiO-66 can be well controlled during synthesis, leading to precisely tunable physicochemical properties for this structure. However, there has been a long-standing debate regarding the nature of the compensating species present at the defective sites. Here, we present unambiguous spectroscopic evidence that the missing-linker defect sites in an ambient environment are compensated with both carboxylate and water (bound through intermolecular hydrogen bonding), which is further supported by ab initio calculations. In contrast to the prevailing assumption that the monocarboxylate groups (COO – ) of the modulators form bidentate bonding with two Zr 4+ sites, COO – is found to coordinate to an open Zr 4+ site in an unidentate mode. The neighboring Zr 4+ site is terminated by a coordinating H 2 O molecule, which helps to stabilize the COO – group. Lastly, this finding not only provides a new understanding of defect termination in UiO-66, but also sheds light on the origin of its catalytic activity.

36 MATERIALS SCIENCE↗

Three-Dimensional Reconstruction of Defects and Structures in Additively Manufactured Parts with Automated Serial Sectioning

Metal additive manufacturing (AM) processes have been demonstrated to be effective at reducing costs and lead times associated with complex components for space flight applications. Laser powderbed fusion (L-PBF) is a commonly used AM technology due to the ability to produce complex parts with fine feature resolution in a wide variety of alloys and applications. L-PBF, like many other manufacturing processes, can produce minor flaws in parts when in nominal operation as well as process-escape defects when process abnormalities occur. The effects of the flaws and methods of detecting the flaws are a subject of interest to understand the difficulties in detecting these flaws with current technology and how much risk the flaws or defects pose to potential flight parts. Using a RoboMet.3D automated serial sectioning system, seeded defects as well as minor process flaws can be imaged and reconstructed in three dimensions to compare to non-destructive evaluation (NDE) techniques, such as x-ray computed tomography (CT), neutron CT, and in-situ monitoring. The RoboMet automates the metallography process by automatically grinding, polishing, and imaging samples in a single system and providing the control data for NDE comparisons to know the real size of defects built into coupons. These comparisons provide an understanding behind the technological limitations of the NDE techniques for different alloys. The same serial sectioning methods have also been utilized to characterize the surfaces of parts to reconstruct the surfaces and take measurements of internal features not easily examined with non-destructive methods. Using the RoboMet, fine lattice structures built with L-PBF have been characterized to determine the actual thicknesses of struts and density of the lattice structures. These structures have been used as finer build supports for the L-PBF process, designs for fine catalysts, and other design considerations for small components. The RoboMet data helps to inform the modeling and design efforts around these fine components.

additive manufacturing↗

Defect Study of Group V Doped CdTe By Thermoelectric Effect Spectroscopy

Shallow acceptors in single crystal CdTe induced by Group V (P, As, and Sb) doping are identified by thermoelectric effect spectroscopy (TEES). Understanding defects in Group V doped CdTe is critical to improving and controlling the acceptor density and lifetime in the absorber material which is an important factor determining the open circuit voltage and efficiency in CdTe solar cells.

14 SOLAR ENERGY↗

Detecting defects that reduce breakdown voltage using machine learning and optical profilometry

Abstract Semiconductor wafer manufacturing relies on the precise control of various performance metrics to ensure the quality and reliability of integrated circuits. In particular, GaN has properties that are advantageous for high voltage and high frequency power devices; however, defects in the substrate growth and manufacturing are preventing vertical devices from performing optimally. This paper explores the application of machine learning techniques utilizing data obtained from optical profilometry as input variables to predict the probability of a wafer meeting performance metrics, specifically the breakdown voltage (V bk ). By incorporating machine learning techniques, it is possible to reliably predict performance metrics that cause devices to fail at low voltage. For diodes that fail at a higher (but still below theoretical) breakdown voltage, alternative inspection methods or a combination of several experimental techniques may be necessary.

42 ENGINEERING↗

Coherent control and high-fidelity readout of chromium ions in commercial silicon carbide

Abstract Transition metal ions provide a rich set of optically active defect spins in wide bandgap semiconductors. Chromium (Cr 4+ ) in silicon-carbide (SiC) produces a spin-1 ground state with a narrow, spectrally isolated, spin-selective, near-telecom optical interface. However, previous studies were hindered by material quality resulting in limited coherent control. In this work, we implant Cr into commercial 4H-SiC and show optimal defect activation after annealing above 1600 °C. We measure an ensemble optical hole linewidth of 31 MHz, an order of magnitude improvement compared to as-grown samples. An in-depth exploration of optical and spin dynamics reveals efficient spin polarization, coherent control, and readout with high fidelity (79%). We report T 1 times greater than 1 s at cryogenic temperatures (15 K) with a T 2 * = 317 ns and a T 2 = 81 μs, where spin dephasing times are currently limited by spin–spin interactions within the defect ensemble. Our results demonstrate the potential of Cr 4+ in SiC as an extrinsic, optically active spin qubit.

74 ATOMIC AND MOLECULAR PHYSICS↗

Enhanced extreme ultraviolet high-harmonic generation from chromium-doped magnesium oxide

High-order harmonic generation (HHG) from crystals is emerging as a new ultrashort source of coherent extreme ultraviolet (XUV) light. Doping the crystal structure can offer a new way to control the source properties. Here, we present a study of HHG enhancement in the XUV spectral region from an ionic crystal, using dopant-induced vacancy defects, driven by a laser centered at a wavelength of 1.55 μm. Our numerical simulations based on solutions of the semiconductor Bloch equations and density-functional theory are supported by our experimental observations and demonstrate an increase in the XUV high harmonic yield from doped bulk magnesium oxide (MgO) compared to undoped MgO, even at a low defect concentration. The anisotropy of the harmonic emission as a function of the laser polarization shows that the pristine crystal's symmetry is preserved. Our study paves the way toward the control of HHG in solids with complex defects caused by transition-metal doping.

36 MATERIALS SCIENCE↗

Infrared thermography NDT for in-situ defect detection in sandwich composite panel manufacturing

Composite manufacturing presents numerous challenges, as defects can arise from various sources throughout the process. In sandwich composite structures, the integration of a foam core introduces additional complexity and increases the likelihood of defect formation like delamination. To mitigate these issues and reduce the risk of future structural failures, in-situ monitoring during manufacturing is essential. This study investigates infrared (IR) thermography as a non-destructive technique for detecting manufacturing defects in foam-core sandwich composite panels under thermally excited conditions representative of in-situ processing. A stationary FLIR A8590 IR camera (640 × 512 pixels, 30Hz, 17mm lens, 9 ft stand-off distance) was used to monitor prefabricated panels subjected to controlled external heating simulating compression molding and resin cure exotherm. Interlaminar delamination defects with characteristic sizes ranging from 0.25 × 0.25in² to 5 × 5in² produced measurable surface temperature depressions of approximately 4–10°C during transient cooling, exceeding the effective noise floor of the camera by more than two standard deviations. Thicker laminates exhibited prolonged defect detectability windows due to increased thermal diffusion time. In contrast, embedded Teflon inclusions generated weak thermal contrasts of ≤ 3°C, approaching the measurement noise floor, due to limited thermal property contrast with the surrounding glass fiber composite. These results establish quantitative detectability limits for stationary thermographic inspection of sandwich composite panels under manufacturing-representative thermal cycles.

Barakat, Abdallah [ORNL] (ORCID:0000000296141398)↗

The Application of Convolutional Neural Networks (CNNs) to Recognize Defects in 3D-Printed Parts

Cracks and pores are two common defects in metallic additive manufacturing (AM) parts. In this paper, deep learning-based image analysis is performed for defect (cracks and pores) classification/detection based on SEM images of metallic AM parts. Three different levels of complexities, namely, defect classification, defect detection and defect image segmentation, are successfully achieved using a simple CNN model, the YOLOv4 model and the Detectron2 object detection library, respectively. The tuned CNN model can classify any single defect as either a crack or pore at almost 100% accuracy. The other two models can identify more than 90% of the cracks and pores in the testing images. In addition to the application of static image analysis, defect detection is also successfully applied on a video which mimics the AM process control images. The trained Detectron2 model can identify almost all the pores and cracks that exist in the original video. This study lays a foundation for future in situ process monitoring of the 3D printing process.

36 MATERIALS SCIENCE↗

Calcium-Magnesium-Alumino-Silicates (CMAS) Reaction Mechanisms and Resistance of Advanced Turbine Environmental Barrier Coatings for SiC/SiC Ceramic Matrix Composites

Environmental barrier coatings (EBCs) and SiC/SiC ceramic matrix composites (CMCs) systems will play a crucial role in future turbine engines for hot-section component applications because of their ability to significantly increase engine operating temperatures, reduce engine weight and cooling requirements. The development of prime-reliant environmental barrier coatings is an essential requirement to enable the applications of the 2700-3000 F EBC - CMC systems. This presentation primarily focuses on the reaction mechanisms of advanced NASA environmental barrier coating systems, when in contact with Calcium-Magnesium Alumino-Silicates (CMAS) at high temperatures. Advanced oxide-silicate defect cluster environmental barrier coatings are being designed for ultimate balanced controls of the EBC temperature capability and CMAS reactivity, thus improving the CMAS resistance. Further CMAS mitigation strategies are also discussed.

Environmental barrier coatings (EBCs)↗

High-throughput spin-bath characterization of spin defects in semiconductors

Detailed knowledge of the local environments of spin defects in semiconductors, such as nitrogenvacancy (NV) centers in diamond or divacancies in silicon carbide, is crucial for optimizing control and entanglement protocols in quantum sensing and information applications. However, at present a direct experimental characterization of individual defect environments is not scalable, as conventional spin-bath measurements are time consuming and difficult to automate. Achieving high-throughput characterization requires short experiments to probe the spin bath. However, with fewer and noisier measurements, the inverse problem of recovering spin-bath properties from measured data becomes ill posed, with multiple spin baths having a high likelihood of yielding the same data. In this work, we present a set of computational tools to resolve the ill-posed inverse problem of recovering the atomic positions and hyperfine couplings of random nuclei surrounding spin defects from sparse, noisy experimental coherence data, which can be obtained in hours. Here, we use a trans-dimensional Bayesian approach that incorporates ab initio data to yield full posterior distributions over nuclear spin environments, enabling robust recovery from limited data. We also provide practical tools and guidelines to determine the limits of detectability for hyperfine couplings under specific dynamical decoupling sequences and sampling conditions. In addition, we demonstrate how the tools developed here, in combination with ab initio simulations of spin baths, can guide the design of efficient experimental protocols for application-specific high-throughput screening. To showcase the utility of our approach, we apply it to design fast dynamical decoupling experiments to characterize the spin baths often individual NV centers in diamond. While the primary focus is on accelerating spin-bath characterization of spin defects, this Bayesian approach also lays the foundation for digital-twin studies of spin defects, where a virtual model of the spin-defect system evolves in real time with ongoing experimental measurements. Together, the set of tools we designed and applied paves the way for scalable deployment of spin defects in semiconductors for quantum sensing and information applications.

Bayesian methods↗

Coriolis-force-induced trajectory and endpoint deviations in the reaching movements of labyrinthine-defective subjects

When reaching movements are made during passive constant velocity body rotation, inertial Coriolis accelerations are generated that displace both movement paths and endpoints in their direction. These findings directly contradict equilibrium point theories of movement control. However, it has been argued that these movement errors relate to subjects sensing their body rotation through continuing vestibular activity and making corrective movements. In the present study, we evaluated the reaching movements of five labyrinthine-defective subjects (lacking both semicircular canal and otolith function) who cannot sense passive body rotation in the dark and five age-matched, normal control subjects. Each pointed 40 times in complete darkness to the location of a just extinguished visual target before, during, and after constant velocity rotation at 10 rpm in the center of a fully enclosed slow rotation room. All subjects, including the normal controls, always felt completely stationary when making their movements. During rotation, both groups initially showed large deviations of their movement paths and endpoints in the direction of the transient Coriolis forces generated by their movements. With additional per-rotation movements, both groups showed complete adaptation of movement curvature (restoration of straight-line reaches) during rotation. The labyrinthine-defective subjects, however, failed to regain fully accurate movement endpoints after 40 reaches, unlike the control subjects who did so within 11 reaches. Postrotation, both groups' movements initially had mirror image curvatures to their initial per-rotation reaches; the endpoint aftereffects were significantly different from prerotation baseline for the control subjects but not for the labyrinthine-defective subjects reflecting the smaller amount of endpoint adaptation they achieved during rotation. The labyrinthine-defective subjects' movements had significantly lower peak velocity, higher peak elevation, lower terminal velocity, and a more vertical touchdown than those of the control subjects. Thus the way their reaches terminated denied them the somatosensory contact cues necessary for full endpoint adaptation. These findings fully contradict equilibrium point theories of movement control. They emphasize the importance of contact cues in adaptive movement control and indicate that movement errors generated by Coriolis perturbations of limb movements reveal characteristics of motor planning and adaptation in both healthy and clinical populations.

NASA Discipline Neuroscience↗

Distinctive molecular configuration of nanostructured silica deposited at a glancing angle

Glancing-angle deposition (GLAD) produces nanostructured silica, showcasing form birefringence, an attractive alternative to traditionally used crystalline materials for polarization control. This work aims to enhance the understanding of its internal structure and associated defects in its native form and after laser processing. Our observations show, for the first time, that the GLAD silica exhibits a unique Raman signature that converges to a typical silica spectrum following laser melting. Defects were also investigated with fluorescence spectroscopy. The new insight provided by this work informs our understanding of this birefringent material and drives optimization of its performance in GLAD-based polarization control devices.

36 MATERIALS SCIENCE↗