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NASA NTRSDate not supplied

Scalar Atomic Defect-Based Solid-State Self-calibrating Magnetometer (3SM) for Space Plasma Analysis

The Earth’s magnetosphere is a system of multiple, co-located particle populations interacting via plasma waves. Things to understand are driving processes, radiation belt and ring current issues, auroral physics, internal plasma processes, and magnetosphere-ionosphere mapping issues. These plasma-physics processes enable the Earth’s magnetosphere to evolve in response to temporal changes in the solar wind and they underlie the phenomena of space weather, which impacts spacecraft systems, astronauts, radio communications, and ground based electric-power grids. The objective of 3SM is to measure magnetic field strength and to calibrate the Vector Magnetometer (VM) device to maintain absolute accuracy during a mission. The 3SM features make the instrument preferably suited not only for the traditional role of scalar magnetometers as absolute references for the calibration of the on-board vector instruments, but also for extended operational capacities, such as higher frequency scalar measurements (of potential interest for magnetosphere studies for the low frequency part of the spectrum) or autonomous scalar / vector operations. Diamond has been the solid-state platform of choice for quantum device technologies for some time, however, it suffers from difficulties such as scalability, integration, and cost. While the diamond platform is very useful for quantum technologies, further development is needed to make it viable. The material platform of choice for NASA Glenn’s Quantum Sensing And Spin Physics (Q-SASP) is silicon carbide (SiC). This is due to the much higher industry development of the SiC material platform for high-power and high-temperature electronics. It leverages both the decades-long SiC development expertise and infrastructure at NASA Glenn and its growing capabilities in quantum metrology. To make SiC devices usable for quantum technologies such as quantum sources, a much deeper understanding of defects is needed. Q-SASP is developing quantum metrology capabilities to evaluate the energy structure, defect formation energy, band structure augmentation, generation/recombination rates, and limits of dipole-dipole coupling in non-metal implanted SiC devices. This can be achieved by analysis of zero-field splitting, low-field resonance, and singlet-triplet mixing through various forms of Electrically Detectable Magnetic Resonance (EDMR) and Near-Zero Field Magnetic Resonance (NZFMR) spectroscopy. This work will discuss recent system developments, device developments, computational modeling, and spectroscopy results and analysis of defects created by non-metal implantations in SiC devices. The defect formation energies of V Si ,V C , V C V Si , N C V Si , N Si , N C in 4H-SiC are previously reported values in other research [2]-[3]. The defect formation energies of PSi and PC were calculated in GPAW [fig 1A]. The basic underlying mechanism of the zero-field phenomenon is the mixing of singlet and triplet states [4]-[5]. In most spin-dependent transport, two electron spins are involved, and thus one must consider each of their interactions with the field. We investigated the electronic and magnetic properties of 4H-SiC and 6H-SiC. The defect formation energy helps us determine what types of defects we are observing in the SiC EDMR experiment. They have very low formation energy (it is negative). The phosphorus substitution in 4H-SiC is a very stable defect. The band diagrams provide us with vital information about how the electronic properties of SiC (such as band gap) change as we add non-metal defects. The zero-field splitting parameters allow us to study the inflection point in the NZFMR [fig 1B]. We clearly observed zero-field splitting. We also noted that the zero-field splitting remained constant with changing bias. We aspect it zero-field splitting to remain constant while the hyperfine and exchange interaction perturbations shift under the influence of an external magnetic field. This is the essence of quantum magnetometry and self-calibration.

space plasma↗
DOE OSTI2019

Diffusion of point defects in ordered and disordered Ni–Fe alloys

We present how the ordered and disordered arrangement of elements can affect the transport properties of point defects in Ni–Fe metallic alloys using atomistic simulations. With molecular dynamics (MD) based on both first-principles calculations and empirical potentials, we show that defect diffusion slows down in the ordered Ni–Fe phases due to the decrease of effective coordination number for nearest-neighbor defect jumps. Thus, the disorder-order transition influences defect migration by changing the local atomic environment. We further elucidate that the defect diffusion in ordered and disordered phases is a result of the interplay between preferential defect diffusion and defect stability that relate to the defect energetics. These results indicate that defect evolution may be significantly delayed by embedding certain ordered structures into bulk disordered alloys, which are important to the understanding of the role of disorder in metallic alloys and provide insights on materials engineering by tuning the disorder/order level.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Photoluminescence Dynamics of Aryl sp 3 Defect States in Single-Walled Carbon Nanotubes

Photoluminescent defect states introduced by sp 3 functionalization of semiconducting carbon nanotubes are rapidly emerging as important routes for boosting emission quantum yields and introducing new functionality. Knowledge of the relaxation dynamics of these states is required for understanding how functionalizing agents (molecular dopants) may be designed to access specific behaviors. We measure photoluminescence (PL) decay dynamics of sp 3 defect states introduced by aryl functionalization of the carbon nanotube surface. Results are given for five different nanotube chiralities, each doped with a range of aryl functionality. We find the PL decays of these sp 3 defect states are biexponential, with both components relaxing on timescales of ~ 100 ps. Exciton trapping at defects is found to increases PL lifetimes by a factor of 5-10, in comparison to those for the free exciton. A significant chirality dependence is observed in the decay times, ranging from 77 ps for (7,5) nanotubes to > 600 ps for (5,4) structures. The strong correlation of time constants with emission energy indicates relaxation occurs via multiphonon decay processes, with close agreement to theoretical expectations. Variation of the aryl dopant further modulates decay times by 10-15%. The aryl defects also affect PL lifetimes of the free E 11 exciton. Shortening of the E 11 bright state lifetime as defect density increases provides further confirmation that defects act as exciton traps. A similar shortening of the E11 dark exciton lifetime is found as defect density increases, providing strong experimental evidence that dark excitons are also trapped at such defect sites.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Tuning Electronic Structure of Single Layer MoS 2 through Defect and Interface Engineering

Transition-metal dichalcogenides (TMDs) have emerged in recent years as a special group of two-dimensional materials and have attracted tremendous attention. Among these TMD materials, molybdenum disulfide (MoS 2 ) has shown promising applications in electronics, photonics, energy, and electrochemistry. In particular, the defects in MoS 2 play an essential role in altering the electronic, magnetic, optical, and catalytic properties of MoS 2 , presenting a useful way to engineer the performance of MoS 2 . The mechanisms by which lattice defects affect the MoS 2 properties are unsettled. In this work, we reveal systematically how lattice defects and substrate interface affect MoS 2 electronic structure. We fabricated single-layer MoS 2 by chemical vapor deposition and then transferred onto Au, single-layer graphene, hexagonal boron nitride, and CeO 2 as substrates and created defects in MoS 2 by ion irradiation. Here, we assessed how these defects and substrates affect the electronic structure of MoS 2 by performing X-ray photoelectron spectroscopy, Raman and photoluminescence spectroscopies, and scanning tunneling microscopy/spectroscopy measurements. Molecular dynamics and first-principles based simulations allowed us to conclude the predominant lattice defects upon ion irradiation and associate those with the experimentally obtained electronic structure. We found that the substrates can tune the electronic energy levels in MoS 2 due to charge transfer at the interface. Furthermore, the reduction state of CeO 2 as an oxide substrate affects the interface charge transfer with MoS 2 . The irradiated MoS 2 had a faster hydrogen evolution kinetics compared to the as-prepared MoS 2 , demonstrating the concept of defect controlled reactivity in this phase. Our findings provide effective probes for energy band and defects in MoS 2 and show the importance of defect engineering in tuning the functionalities of MoS 2 and other TMDs in electronics, optoelectronics, and electrochemistry.

42 ENGINEERING↗
DOE OSTI2024

Ultrafast formation of topological defects in a two-dimensional charge density wave

Topological defects play a central role in dynamical systems undergoing a non-adiabatic transition. In solids, topological defects as a result of femtosecond laser excitation have attracted increasing interest not only because they are key to understanding phase transitions but also because they can generate a variety of hidden orders that are not accessible in thermal equilibrium. Despite the common occurrence of these defects in a non-equilibrium system, the fundamental limit on how fast they can emerge in solids and the generic pathway for defect creation at such fast timescales have remained open questions. Here we apply ultrafast electron diffraction to study the reciprocal-space signatures of transient defects in a two-dimensional charge density wave, where simultaneous measurements of both defect and phonon dynamics yield a microscopic view of defect formation in the femtosecond regime. We find that one-dimensional domain walls are generated well within 1 ps following photoexcitation, during which the defect growth is not dictated by the amplitude of the order parameter but is mediated by a non-thermal population of longitudinal optical phonons. In conclusion, our work provides a framework for the ultrafast engineering of topological defects that are coupled to specific collective modes, which will prove useful for the dynamical control of non-equilibrium phases in correlated materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels

Crystalline materials exhibit long-range ordered lattice unit, within which resides nonperiodic structural features called defects. These crystallographic defects play a vital role in determining the physical and mechanical properties of a wide range of material systems. While computer vision has demonstrated success in recognizing feature patterns in images with well defined contrast, automated identification of nanometer scale crystallographic defects in electron micrographs governed by complex contrast mechanism is still a challenging task. Here, building upon an advanced defect imaging mode that offers high feature clarity, we introduce DefectSegNet - a new convolutional neural network (CNN) architecture that performs semantic segmentation of three common crystallographic defects in structural alloys: dislocation lines, precipitates and voids. Results from supervised training of a small set of high-quality defect images of steels show high pixel-wise accuracy across all three types of defects: 91.60 ± 1.77% on dislocations, 93.39 ± 1.00% on precipitates, and 98.85 ± 0.56% on voids. We discuss the sources of uncertainties in CNN prediction, and the training data in terms of feature density, representation and homogeneity and their effects on deep learning performance. Further defect quantification using DefectSegNet prediction outperforms human expert average, presenting a promising new workflow for fast and statistically meaningful quantification of materials defects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Elucidating correlated defects in metal organic frameworks using theory-guided inelastic neutron scattering spectroscopy

Metal organic frameworks (MOFs) that incorporate metal oxide cluster nodes, exemplified by UiO-66, have been widely studied, especially in terms of their deviations from the ideal, defect-free crystalline structures. Although defects such as missing linkers, missing nodes, and the presence of adventitious synthesis-derived node ligands (such as acetates and formates) have been proposed, their exact structures remain unknown. Previously, it was demonstrated that defects are correlated and span multiple unit cells. The highly specialized techniques used in these studies are not easily applicable to other MOFs. Thus, there is a need to develop new experimental and computational approaches to understand the structure and properties of defects in a wider variety of MOFs. Here, we show how low-frequency phonon modes measured by inelastic neutron scattering (INS) spectroscopy can be combined with density functional theory (DFT) simulations to provide unprecedented insights into the defect structure of UiO-66. We are able to identify and assign peaks in the fingerprint region (<100 cm –1 ) which correspond to phonon modes only present in certain defective topologies. Specifically, this analysis suggests that our sample of UiO-66 consists of predominantly defect-free fcu regions with smaller domains corresponding to a defective bcu topology with 4 and 2 acetate ligands bound to the Zr 6 O 8 nodes. Importantly, the INS/DFT approach provides detailed structural insights (e.g., relative positions and numbers of acetate ligands) that are not accessible with microscopy-based techniques. Furthermore, the quantitative agreement between DFT simulations and the experimental INS spectrum combined with the relative simplicity of sample preparation, suggests that this methodology may become part of the standard and preferred protocol for the characterization of MOFs, and, in particular, for elucidating the structure defects in these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

First-principles elucidation of defect-mediated Li transport in hexagonal boron nitride

Hexagonal boron nitride (hBN) is a promising candidate as a protective membrane or separator in Li-ion and Li–S batteries, given its excellent chemical stability, mechanical robustness, and high thermal conductivity. In addition, hBN can be functionalized by introducing defects and dopants, or be directly integrated into other active components of batteries, which further augments its appeal to the field. Here, we use first-principles simulations to evaluate the role of atomic defects in hBN in regulating the Li-ion diffusion mechanism and associated kinetics. Specifically, the following four distinct types of vacancy defects are considered: isolated single B and N vacancies, a B–N vacancy pair, and a B 3 N vacancy cluster. It is found that these defect sites generally favor Li intercalation and out-of-plane diffusion but slow down in-plane Li-ion diffusion due to a strong Li trapping effect at the defect sites. Such a trapping effect is, however, highly local such that it does not necessarily affect the overall Li-ion conductivity in defected hBN layers. The present systematic evaluation of the impact of atomic defects on Li ion migration and accompanied charge analysis of hBN lattice in response to Li-ion diffusion provide a mechanistic understanding of Li-ion transport behavior in defected hBN and highlight the potential of defect engineering to achieve optimal material performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Impact of noise sources and optical design on defect detection sensitivity in extreme ultraviolet actinic pattern inspection tool

Here, we discuss the impact of various noise sources and the optical design in bright field extreme ultraviolet (EUV) actinic inspection of mask features for defects in the patterned absorber. It is shown that an optimum pixel size is needed to maximize the defect signal-to-noise ratio (SNR) to balance the trade-off in increasing signal strength with shot noise from defect signal and the background pattern intensity (mask layout image) and speckle noise from the mask blank roughness. Moreover, we consider defocus showing that the EUV mask phase effect has an asymmetric impact on pattern defect SNR's through-focus behavior. The impact of defocus limits inspection performance based on defect SNR. Using critical defect sizes in a case study, we show the defect SNR performance of the limiting case and discuss the possibility of utilizing a nominal defocus in the inspection system to leverage the phase effect of EUV mask absorber to improve the defect SNR. A 50% improvement in defect SNR is shown to be possible by introducing a -50 nm nominal defocus into the bright field inspection system.

42 ENGINEERING↗
DOE OSTI2023

Graph-based machine learning improves just-in-time defect prediction

The increasing complexity of today’s software requires the contribution of thousands of developers. This complex collaboration structure makes developers more likely to introduce defect-prone changes that lead to software faults. Determining when these defect-prone changes are introduced has proven challenging, and using traditional machine learning (ML) methods to make these determinations seems to have reached a plateau. In this work, we build contribution graphs consisting of developers and source files to capture the nuanced complexity of changes required to build software. By leveraging these contribution graphs, our research shows the potential of using graph-based ML to improve Just-In-Time (JIT) defect prediction. We hypothesize that features extracted from the contribution graphs may be better predictors of defect-prone changes than intrinsic features derived from software characteristics. We corroborate our hypothesis using graph-based ML for classifying edges that represent defect-prone changes. This new framing of the JIT defect prediction problem leads to remarkably better results. We test our approach on 14 open-source projects and show that our best model can predict whether or not a code change will lead to a defect with an F1 score as high as 77.55% and a Matthews correlation coefficient (MCC) as high as 53.16%. This represents a 152% higher F1 score and a 3% higher MCC over the state-of-the-art JIT defect prediction. We describe limitations, open challenges, and how this method can be used for operational JIT defect prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Transport-reaction model for defect and carrier behavior within displacement cascades in gallium arsenide

A model is presented for recombination of charge carriers at displacement damage in gallium arsenide, which includes clustering of the defects in atomic displacement cascades produced by neutron or ion irradiation. The carrier recombination model is based on an atomistic description of capture and emission of carriers by the defects with time evolution resulting from the migration and reaction of the defects. The physics and equations on which the model is based are presented, along with details of the numerical methods used for their solution. The model uses a continuum description of diffusion, field-drift and reaction of carriers and defects within a representative spherically symmetric cluster. The initial radial defect profiles within the cluster were chosen through pair-correlation-function analysis of the spatial distribution of defects obtained from the binary-collision code MARLOWE, using recoil energies for fission neutrons. Charging of the defects can produce high electric fields within the cluster which may influence transport and reaction of carriers and defects, and which may enhance carrier recombination through band-to-trap tunneling. Properties of the defects are discussed and values for their parameters are given, many of which were obtained from density functional theory. The model provides a basis for predicting the transient response of III-V heterojunction bipolar transistors to pulsed neutron irradiation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Simple self-consistent method for excited states in density functional theory to characterize defect-derived behavior in wide-band-gap-based microelectronic materials

This final report summarizes the results of the Laboratory Direct Research and Development (LDRD) Project Number 229740. Wide band gap semiconductors such as gallium nitride (GaN) have features highly desirable for multiple mission electronic applications. Realization of their potential requires atomic-scale understanding of electronic behavior. The principal experimental tools for electronically probing defects in GaN are chemically undifferentiating and lack a practical theoretical counterpart needed to identify and characterize specific defects. This project investigated whether a simple idea for modeling defect excited states and their associated photoluminescence (PL) energies is viable, as a path to accelerate the understanding of defect behavior and gain valuable insights into engineering new electronic materials and devices. The research implemented a non-self-consistent total-energy evaluation of a Koopmans-type estimation of an excited electronic state energy in density functional theory (DFT) calculations, and proceeded to design, implement, and assess a self-consistent method for computing excited states based upon an OCcupation-Constrained-DFT (occ-DFT). The occ-DFT was verified in test calculations of defect excited states and validated against well-characterized PL data for 3d transition metal defects in GaN. The method proved stable and robust in computing excited states and gave accurate predictions compared to experimental PL data. The combined ground state/excited-state capability proved capable of chemically differentiating defect species in GaN. In application to 3d dopants in GaN, we reinterpreted extensive experimental literature, proposed new defects as prospective candidates for use in quantum information applications, and outlined design strategies to create and exploit these potentially useful functional defects in GaN.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Prediction of Performance Variation Caused by Manufacturing Tolerances and Defects in Gas Diffusion Electrodes of Phosphoric Acid (PA)–Doped Polybenzimidazole (PBI)-Based High-Temperature Proton Exchange Membrane Fuel Cells

The automated process of coating catalyst layers on gas diffusion electrodes (GDEs) for high-temperature proton exchange membrane fuel cells results inherently into a number of defects. These defects consist of agglomerates in which the platinum sites cannot be accessed by phosphoric acid and which are the consequence of an inconsistent coating, uncoated regions, scratches, knots, blemishes, folds, or attached fine particles—all ranging from μm to mm size. These electrochemically inactive spots cause a reduction of the effective catalyst area per unit volume (cm2/cm3) and determine a drop in fuel cell performance. A computational fluid dynamics (CFD) model is presented that predicts performance variation caused by manufacturing tolerances and defects of the GDE and which enables the creation of a six-sigma product specification for Advent phosphoric acid (PA)-doped polybenzimidazole (PBI)-based membrane electrode assemblies (MEAs). The model was used to predict the total volume of defects that would cause a 10% drop in performance. It was found that a 10% performance drop at the nominal operating regime would be caused by uniformly distributed defects totaling 39% of the catalyst layer volume (~0.5 defects/μm2). The study provides an upper bound for the estimation of the impact of the defect location on performance drop. It was found that the impact on the local current density is higher when the defect is located closer to the interface with the membrane. The local current density decays less than 2% in the presence of an isolated defect, regardless of its location along the active area of the catalyst layer.

Gurau, Vladimir (ORCID:0000000327429061)↗
NASA NTRS1982

Reduction of solar cell efficiency by bulk defects across the back-surface-field junction

The degradation of solar cell performance due to bulk defects distributed across the back-surface field junction is analyzed in terms of a three-region developed-perimeter model. Families of curves are computed and their physical significance is discussed in detail with reference to three parameters used to characterize the defects: defect area, defect density, and defect surface recombination velocity. A reduction in the open-circuit voltage due to the presence of a defect is expressed as a function of the defect area, density, cell thickness, and defect surface recombination velocity. Numerical examples are presented to illustrate the importance of the particular defect parameters.

Sah, C. T.↗
NASA NTRS2004

Identification and Control of Gravity Related Defect Formation During Melt Growth of Electro-Optic Single Crystals Bismuth Silicate(Bi12SiO20)

A research carried out under Award Number NAG8-1487 was aimed at to the design, conduct and analysis of experiments directed at the identification and control of gravitational effects on crystal growth, segregation and defect formation in the Sillenite system: bismuth silicate (Bi(12)SiO(20)). Correlation analyses was conducted in order to establish the influence of gravity related defects introduced during crystal growth on critical, application specific properties. Achievement of the states objective was conducted during the period from Feb. 01, 1998 to Dec. 31, 2003 with the following anticipated milestones: 1. Establishment of capabilities for (a) reproducible Czochralski and Bridgman-type growth of BSO single crystals and (b) for comprehensive analysis of crystalline and chemical defects as well as for selective property characterization of grown crystals (year 1). 2. Design and execution of critical space growth experiment(s) based on analyses of prefatory space results (experiments aimed at establishing the viability of planned approaches and procedures) and on unresolved issues related to growth, segregation and defect formation associated with conventional growth in Bridgman geometries. Comparative analysis of growth under conventional and under mu-g conditions; identification of gravity related defect formation during conventional Bridgman growth and formulation of approaches for their control (years 2 and 3). Development of charge confinement system which permits growth interface demarcation (in a mu-g environment) as well as minimization of confinement related stress and contamination during growth; design of complementary mu-g growth experiments aimed at quantitative mu-g growth and segregation analyses (year 4). 3. Conduct of quantitative mu-g growth experiments directed at: (a) identification and control of gravity related crystalline and chemical defect formation during single crystal growth of Bi(12)SiO(20) and at (b) defect engineering -the development of approaches to the controlled generation during crystal growth of specified point defects in homogeneous distribution (year 5). The proposed research places focus on a class of materials which have outstanding electrical and optical properties but have so far failed to reach their potential, primarily because of our inability to control adequately their stoichiometry and crystal defect formation as well as confinement related contamination and lattice stress.

Becia, Piotr↗
NASA NTRS2011

Fracture Mechanics Analyses of Subsurface Defects in Reinforced Carbon-Carbon Joggles Subjected to Thermo-Mechanical Loads

Coating spallation events have been observed along the slip-side joggle region of the Space Shuttle Orbiter wing-leading-edge panels. One potential contributor to the spallation event is a pressure build up within subsurface voids or defects due to volatiles or water vapor entrapped during fabrication, refurbishment, or normal operational use. The influence of entrapped pressure on the thermo-mechanical fracture-mechanics response of reinforced carbon-carbon with subsurface defects is studied. Plane-strain simulations with embedded subsurface defects are performed to characterize the fracture mechanics response for a given defect length when subjected to combined elevated-temperature and subsurface-defect pressure loadings to simulate the unvented defect condition. Various subsurface defect locations of a fixed-length substrate defect are examined for elevated temperature conditions. Fracture mechanics results suggest that entrapped pressure combined with local elevated temperatures have the potential to cause subsurface defect growth and possibly contribute to further material separation or even spallation. For this anomaly to occur, several unusual circumstances would be required making such an outcome unlikely but plausible.

Knight, Norman F., Jr.↗
DOE OSTI2018

Nanotube/Nanowire as Effective Defect Sinks in Metals—Atomistic Simulations and In Situ Ion Radiation Transmission Electron Microscopy

The accumulation of defects during irradiation leads to material property degradation modes such as embrittlement and swelling, eventually causing material failure. Effective and efficient removal of defects is of crucial importance to design radiation damage-tolerant materials. Here, by biasing defect migration pathways via carbon nanotube (CNT) infiltration, we present a greatly enhanced damage-tolerant Al-CNT composite with defect storage measured to be one order of magnitude lower than that in pure, irradiated Al. Furthermore, extreme-value statistics (largest size) of defect clusters are significantly changed in the presence of CNT. In situ ion irradiation transmission electron microscopy (TEM) experiments and atomistic simulations together reveal the dynamic evolution and convergent diffusion of radiation-induced defects to CNTs, facilitating defect recombination and enhancing radiation tolerance. The occurrence of CNT-biased defect convergent migration is tuned by the thermodynamic driving force of stress gradient in Al matrix due to the CNT phase transformation. This approach to controlling defect migration using 1D interface engineering creates a new opportunity to enhance the properties of nuclear materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Multi-scan computed tomography defect detectability

Systems and methods for representing internal defects of an object to determine defect detectability using a multi-scan computed tomography (CT) approach are disclosed. A defect-free object may be scanned using a CT machine. In one or more separate scans, phantom defects may be imaged and the resulting projections combined and reconstructed to represent internal defects. The air-normalized intensities of the object and the phantom defect may be used to represent voids and inclusions. Subtraction of materials may be represented by the quotient of the air-normalized intensities thereof, and the addition of materials may be represented by the product of the air-normalized intensities thereof. A void may be represented by subtracting a phantom defect scan from the object scan. An inclusion may be represented by creating a void, scanning an additional phantom defect, and adding the additional phantom defect in the volume created by the void.

Schiefelbein, Bryan E.↗