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At least 757 records · Page 42

Process-Induced Morphological Defects in Epitaxial CVD Silicon Carbide

Silicon carbide (SiC) semiconductor technology has been advancing rapidly, but there are numerous crystal growth problems that need to be solved before SiC can reach its full potential. Among these problems is a need for an improvement in the surface morphology of epitaxial films that are grown to produce device structures. Various processes before and during epilayer growth lead to the formation of morphological defects observed in SiC epilayers grown on SiC substrates. In studies of both 6H and 4H-SiC epilayers, atomic force microscopy (AFM) and other techniques have been used to characterize SiC epilayer surface morphology. In addition to the well-known micropipe defect, SiC epilayers contain growth pits, triangular features (primarily) in 4H-SiC, and macro step due to step bunching. In work at NASA Lewis, it has been found that factors contributing to the formation of some morphological defects include: defects in the substrate bulk, defects in the substrate surface caused by cutting and polishing the wafer, the tilt angle of the wafer surface relative to the basal plane, and growth conditions. Some of these findings confirm results of other research groups. This paper presents a review of published and unpublished investigations into processes that are relevant to epitaxial film morphology.

Powell, J. A.↗

Thermographic Imaging of Defects in Anisotropic Composites

Composite materials are of increasing interest to the aerospace industry as a result of their weight versus performance characteristics. One of the disadvantages of composites is the high cost of fabrication and post inspection with conventional ultrasonic scanning systems. The high cost of inspection is driven by the need for scanning systems which can follow large curve surfaces. Additionally, either large water tanks or water squirters are required to couple the ultrasonics into the part. Thermographic techniques offer significant advantages over conventional ultrasonics by not requiring physical coupling between the part and sensor. The thermographic system can easily inspect large curved surface without requiring a surface following scanner. However, implementation of Thermal Nondestructive Evaluations (TNDE) for flaw detection in composite materials and structures requires determining its limit. Advanced algorithms have been developed to enable locating and sizing defects in carbon fiber reinforced plastic (CFRP). Thermal Tomography is a very promising method for visualizing the size and location of defects in materials such as CFRP. However, further investigations are required to determine its capabilities for inspection of thick composites. In present work we have studied influence of the anisotropy on the reconstructed image of a defect generated by an inversion technique. The composite material is considered as homogeneous with macro properties: thermal conductivity K, specific heat c, and density rho. The simulation process involves two sequential steps: solving the three dimensional transient heat diffusion equation for a sample with a defect, then estimating the defect location and size from the surface spatial and temporal thermal distributions (inverse problem), calculated from the simulations.

Plotnikov, Y. A.↗

Application of Hilbert-Huang Transform for Improved Defect Detection in Terahertz NDE of Shuttle Tiles

Terahertz NDE is being examined as a method to inspect the adhesive bond-line of Space Shuttle tiles for defects. Terahertz signals are generated and detected, using optical excitation of biased semiconductors with femtosecond laser pulses. Shuttle tile samples were manufactured with defects that included repair regions unbond regions, and other conditions that occur in Shuttle structures. These samples were inspected with a commercial terahertz NDE system that scanned a tile and generated a data set of RF signals. The signals were post processed to generate C-scan type images that are typically seen in ultrasonic NDE. To improve defect visualization the Hilbert-Huang Transform, a transform that decomposes a signal into oscillating components called intrinsic mode functions, was applied to test signals identified as being in and out of the defect regions and then on a complete data set. As expected with this transform, the results showed that the decomposed low-order modes correspond to signal noise while the high-order modes correspond to low frequency oscillations in the signal and mid-order modes correspond to local signal oscillations. The local oscillations compare well with various reflection interfaces and the defect locations in the original signal.

Anastasi, Robert F.↗

System and process for detecting and monitoring surface defects

A system and process for detecting and monitoring defects in large surfaces such as the field joints of the container segments of a space shuttle booster motor. Beams of semi-collimated light from three non-parallel fiber optic light panels are directed at a region of the surface at non-normal angles of expected incidence. A video camera gathers some portion of the light that is reflected at an angle other than the angle of expected reflectance, and generates signals which are analyzed to discern defects in the surface. The analysis may be performed by visual inspection of an image on a video monitor, or by inspection of filtered or otherwise processed images. In one alternative embodiment, successive predetermined regions of the surface are aligned with the light source before illumination, thereby permitting efficient detection of defects in a large surface. Such alignment is performed by using a line scan gauge to sense the light which passes through an aperture in the surface. In another embodiment a digital map of the surface is created, thereby permitting the maintenance of records detailing changes in the location or size of defects as the container segment is refurbished and re-used. The defect detection apparatus may also be advantageously mounted on a fixture which engages the edge of a container segment.

Mueller, Mark K.↗

Toward Intelligent Software Defect Detection

Source code level software defect detection has gone from state of the art to a software engineering best practice. Automated code analysis tools streamline many of the aspects of formal code inspections but have the drawback of being difficult to construct and either prone to false positives or severely limited in the set of defects that can be detected. Machine learning technology provides the promise of learning software defects by example, easing construction of detectors and broadening the range of defects that can be found. Pinpointing software defects with the same level of granularity as prominent source code analysis tools distinguishes this research from past efforts, which focused on analyzing software engineering metrics data with granularity limited to that of a particular function rather than a line of code.

Benson, Markland J.↗

An Experimental Investigation concerning the Effects of AFP Defects on Progressive Failure of Tensile Coupons

This paper discusses characterization approaches for the evaluation of potential defects that may occur during the automated fiber placement (AFP) process. Two nondestructive evaluation techniques were utilized simultaneously, acoustic emission (AE) and digital image correlation (DIC), to investigate correlations between mechanical properties and damage propagation during tension tests. The layup configuration is designed with the defect running across the width, and the stacking sequence with seven layers is produced: [−45/0/45/̅9̅̅0̅]s. A total of 3 panels were manufactured: one containing a gap defect in the middle layer, another one with an overlap defect, and a pristine panel for baseline comparison. Each panel accommodates six coupons having dimensions of 20” x 2”. The results indicate that defects caused during the manufacturing process affect damage initiation and growth.

Anay, Rafal↗

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↗

Athermal annealing of pre-existing defects in crystalline silicon

Systematic investigations of electronic energy loss (S e ) effects on pre-existing defects in crystalline silicon (Si) are crucial to provide reliance on the use of ionizing irradiation to anneal pre-existing defects, leading to successful implementation of this technology in the fabrication of Si-based devices. In this regard, the S e effects on nonequilibrium defect evolution in pre-damaged Si single crystals at 300 K has been investigated using intermediate-energy ions (12 MeV O and Si ions) that interact with the pre-damaged surface layers of Si mainly by ionization, except at the end of their range where the nuclear energy loss (S n ) is no longer negligible. Furthermore, under these irradiation conditions, experimental results and molecular dynamics simulations have revealed that pre-existing disorder in Si can be almost fully annealed by subsequent irradiation with intermediate-energy incident ions with S e values as low as 1.5–3.0 keV/nm. Selective annealing of pre-existing defect levels in Si at room temperature can be considered as an effective strategy to mediate the transient enhanced diffusion of dopants in Si. This approach is more desirable than the regular thermal annealing, which is not compatible with the processing requirements that fall below the typical thermal budget.

36 MATERIALS SCIENCE↗

Impacts of point defects on shallow doping in cubic boron arsenide: A first principles study

Cubic boron arsenide (BAs) stands out as a promising material for advanced electronics, thanks to its exceptional thermal conductivity and ambipolar mobility. However, effective control of p- and n-type doping in BAs poses a significant challenge, mostly as a result of the influence of defects. In the present study, we employed density functional theory (DFT) to explore the impacts of the common point defects and impurities on p-type doping of Be B and Si As , and on n-type doping of Si B and Se As . We found that the most favorable point defects formed by C, O, and Si are C As , O B O As , Si As , C As Si B , and O B Si As , which have formation energies of less than 1.5 eV. While the O impurity detrimentally affects both p- and n-type dopings, C and Si impurities are harmful for n-type dopings, making n-type doping a potential challenge. Interestingly, the antisite defect pair A s B B As benefits both p- and n-type doping. Finally, the doping limitation analysis presented in this study can potentially pave the way for strategic development in the area of BAs-based electronics.

36 MATERIALS SCIENCE↗

Enhanced defect annihilation capability of the graphene/copper interface: An in situ study

It is well known that energetic heavy ion irradiations can often induce defects and ultimately lead to material degradations. Interfaces, such as high-angle grain boundaries (HAGBs), are generally used as defect sinks for alleviating the irradiation damage. However, HAGBs are often unstable during radiation. Here we investigate the interfacial irradiation responses of the graphene (Gr)/Cu composites by using in situ Kr ++ ions irradiation under transmission electron microscopy. The results revealed that the Gr/Cu interface exhibits higher defect annihilation capability compared to the HAGBs in Cu. Moreover, the atomistic simulations suggested a slightly higher and larger range of stress field for the Gr/Cu interface, which contributes to the enhanced defects absorption capability. The present findings are essential to understand and design a new class of carbon/metal composites with superior irradiation tolerance.

36 MATERIALS SCIENCE↗

Correctly Assessing Defect Tolerance in Halide Perovskites

The notion of “defect tolerance” has often been invoked to explain the excellent performance of halide perovskites in optoelectronic applications. However, this concept has not been rigorously defined or assessed. A common interpretation is that all of the energetically favorable intrinsic defects are shallow. On the basis of examples in the prototypical halide perovskite CsPbI 3 , we show that this is not the case. The antisite defects Pb I and I Pb are energetically favorable, but also have levels deep in the band gap. Still, because of strong anharmonicity, they are not efficient nonradiative recombination centers. Here, our study demonstrates how to correctly evaluate the “defect tolerance” of halide perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect Stability in CdTe Based on Formation Energies and Migration Barriers

Native point defects are thought to play a key role in CdTe, either as compensation centers in intentionally doped material, as a source of conductivity in nominally undoped material, or as electron–hole recombination centers. Here, the discussion of their concentration and impact has often centered only on formation energies and transition levels. Using hybrid density functional calculations, including the effects of spin–orbit coupling (SOC), we discuss the stability of native point defects in CdTe based on their formation energies and migration barriers. We show that although Cd interstitials are the lowest energy donor defects, they are unstable at room temperature due to a low migration barrier. They are important for maintaining charge neutrality during growth or annealing at high temperatures, but once the material is brought to room temperature, they are not frozen in as often assumed and are expected to anneal out, leaving the other more stable defects to determine the conductivity. Taking this into account in the solution of the charge neutrality equation, we are able to predict the conductivity type and carrier concentrations that are in good agreement with experimental observations.

14 SOLAR ENERGY↗

A first-principles understanding of point defects and impurities in GaN

Attaining control over the electrical conductivity of gallium nitride through impurity doping is one of the foremost achievements in semiconductor science. Yet, unwanted contaminants and point defects continue to limit device performance, and experimental techniques alone are insufficient for elucidating the behavior of these unintentionally incorporated species. Methodological advancements have made first-principles calculations more powerful than ever and capable of quantitative predictions, though care must still be taken in comparing results from theory and experiment. In this Tutorial, we explain the basic concepts that define the behavior of dopants, unintentional impurities, and point defects in GaN. We also describe how to interpret experimental results in the context of theoretical calculations and also discuss how the properties of defects and impurities vary in III-nitride alloys. Lastly, we examine how the physics of defects and impurities in GaN is relevant for understanding other wide-bandgap semiconductor materials, such as the II–IV-nitrides, boron nitride, and the transition metal nitrides.

36 MATERIALS SCIENCE↗

First-principles calculations of defects and electron–phonon interactions: Seminal contributions of Audrius Alkauskas to the understanding of recombination processes

First-principles calculations of defects and electron–phonon interactions play a critical role in the design and optimization of materials for electronic and optoelectronic devices. The late Audrius Alkauskas made seminal contributions to developing rigorous first-principles methodologies for the computation of defects and electron–phonon interactions, especially in the context of understanding the fundamental mechanisms of carrier recombination in semiconductors. Alkauskas was also a pioneer in the field of quantum defects, helping to build a first-principles understanding of the prototype nitrogen-vacancy center in diamond, as well as identifying novel defects. Here, we describe the important contributions made by Alkauskas and his collaborators and outline fruitful research directions that Alkauskas would have been keen to pursue. Audrius Alkauskas’ scientific achievements and insights highlighted in this article will inspire and guide future developments and advances in the field.

36 MATERIALS SCIENCE↗

Defect-induced phonon-resonant scattering and its influence on thermal transport of irradiated thorium-dioxide

Thermal transport in proton irradiated thorium-dioxide (ThO 2 ) is investigated. Using a combination of experiments and first-principles computational framework, the role of lattice defects on thermal conductivity is analyzed. A resonant-phonon scattering mechanism beyond the traditionally considered Rayleigh scattering is found to significantly influence low-temperature thermal transport in the presence of irradiation-induced point defects. The existence of localized phonon modes associated with irradiation-induced defects is suggested by the inability of the first-principles based thermal conductivity model—which considers only three-phonon interactions and phonon-defects scattering using the Tamura formalism—to predict the experimental results, unless a resonant scattering mechanism is included. The emergence of additional peaks in the Raman spectra in the proximity of phonon-resonant frequency provides further evidence for the existence of localized modes. Coupled with a microstructure evolution model, this analysis enables more accurate analysis for contrasting the contributions of different phonon scattering mechanisms across all irradiation doses and temperatures.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantifying the dislocation content of atomically resolved grain boundary line defects using the Nye tensor

The Nye tensor, which quantifies the density of Burgers vector for a given dislocation line direction, can be effectively used to characterize dislocation content in bulk crystals from atomic-resolution transmission electron microscopy images. The Nye tensor can be calculated from these images, in part because the reference state is simply defined by the lattice of the perfect crystal. The application of the Nye tensor to interfacial line defects, for which the natural reference state is the dichromatic pattern of the two grains in their reference orientation, poses additional challenges. In this work, we present a method that employs the Nye tensor to characterize the edge dislocation content of line defects at grain boundaries from atomic-resolution images. This approach enables us to rapidly characterize all edge dislocation content along a grain boundary. Additionally, the Nye tensor provides information about line defect core structure. Finally, we demonstrate this method on two exemplar defects: a twin boundary disconnection and a facet junction in face-centered cubic Au.

Crystallographic defects↗

Point defects, compositional fluctuations, and secondary phases in non-stoichiometric kesterites

The efficiency of kesterite-based solar cells is limited by various non-ideal recombination paths, amongst other by a high density of defect states and by the presence of binary or ternary secondary phases within the absorber layer. Pronounced compositional variations and secondary phase segregations are indeed typical features of non-stoichiometric kesterite materials. Certainly kesterite-based thin film solar cells with an off-stoichiometric absorber layer composition, especially Cu-poor/Zn-rich, achieved the highest efficiencies, but deviations from the stoichiometric composition lead to the formation of intrinsic point defects (vacancies, anti-sites, and interstitials) in the kesterite-type material. In addition, a non-stoichiometric composition is usually associated with the formation of undesirable side-phase (secondary phases). Thus the correlation between off-stoichiometry and intrinsic point defects as well as the identification and quantification of secondary phases and compositional fluctuations in non-stoichiometric kesterite materials is of great importance for the understanding and rational design of solar cell devices. Here, this paper summarizes the latest achievements in the investigation of identification and quantification of intrinsic point defects, compositional fluctuations and secondary phases in non-stoichiometric kesterite-type materials.

14 SOLAR ENERGY↗

The Effect of Dose of Nitrogen-Ion Implantation on the Concentration of Point Defects Introduced into GaAs Layers

Secondary-ion mass spectrometry and Rutherford proton backscattering have been used to measure the concentration profiles of nitrogen atoms and examine the defect structure of epitaxial GaAs layers implanted with 250-keV N{sup +} ions at doses of 5 × 10{sup 14}–5 × 10{sup 16} cm{sup –2}. It was found that no amorphization of the layers being implanted occurs at doses exceeding the calculated amorphization threshold, a concentration of point defects that is formed is substantially lower than the calculated value, and a characteristic specific feature of the defect concentration profiles is the high defect concentration in the surface layer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗