Structure-property defect models for materials discovery in high-temperature energy applications
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Microelectronic and photonic systems in the natural space environment are bombarded by a variety of charged particles including electrons, trapped protons, cosmic rays, and solar particles (protons and other heavy ions). These incident particles cause both ionizing and non-ionizing effects when traversing a device, and the effects can be either transient or permanent. The vast majority of the kinetic energy of an incident proton is lost to ionization, creating the single event effects (SEES) and total ionizing dose (TID) effects described in section IVA. However, the small portion of energy lost in non-ionizing processes causes atoms to be removed from their lattice sites and form permanent electrically active defects in semiconductor materials. These defects, i.e., "displacement damage," can significantly degrade device performance. In general, most of the displacement damage effects in the natural space environment can be attributed to protons since they are plentiful and extremely energetic (and therefore not readily shielded against). For this reason, we consider only proton induced displacement damage in this course. (Nevertheless, we identify solar cells as an important example of a case where both electron and proton damage can be important since only very light shielding is feasible.) The interested reader is encouraged to explore the three previous NSREC and RADECS short courses [Srou88a, Summ92, Hopk97] which also treat displacement damage issues for satellite applications. Part A of this segment of the short course introduces the space environment, proton shielding issues, and requirements specifications for proton-rich environments. In order to exercise the displacement damage analysis tools for on-orbit performance predictions, the requirements document must provide the relevant proton spectra in addition to the usual total ionizing dose-depth curves.
Microelectronic and photonic systems in the natural space environment are bombarded by a variety of charged particles including electrons, trapped protons, cosmic rays, and solar particles (protons and other heavy ions). These incident particles cause both ionizing and non-ionizing effects when traversing a device, and the effects can be either transient or permanent. The vast majority of the kinetic energy of an incident proton is lost to ionization, creating the single event effects (SEES) and total ionizing dose (TID) effects. However, the small portion of energy lost in non-ionizing processes causes atoms to be removed from their lattice sites and form permanent electrically active defects in semiconductor materials. These defects, i.e., "displacement damage," can significantly degrade device performance. In general, most of the displacement damage effects in the natural space environment can be attributed to protons since they are plentiful and extremely energetic (and therefore not readily shielded against). For this reason, we consider only proton induced displacement damage in this course. (Nevertheless, we identify solar cells as an important example of a case where both electron and proton damage can be important since only very light shielding is feasible.) The interested reader is encouraged to explore the three previous NSREC and RADECS short courses which also treat displacement damage issues for satellite applications. Part A of this segment of the short course introduces the space environment, proton shielding issues, and requirements specifications for proton-rich environments. In order to exercise the displacement damage analysis tools for on-orbit performance predictions, the requirements document must provide the relevant proton spectra in addition to the usual total ionizing dose-depth curves. Ion-solid interactions and the nature of the displacement damage they generate have been studied extensively for over half a century, yet they still remain a subject of investigation. In this section, a description of the mechanisms by which displacement damage is produced will be followed by a summary of the major consequences for device performance in a space environment. Often the degradation of a device parameter can be characterized by a damage factor (measured in a laboratory using monoenergetic protons) that is simply the change in a particular electrical or optical parameter per unit proton fluence. In addition, we will describe the concept of a non-ionizing energy loss rate (NIEL) which quantifies that portion of the energy lost by an incident ion that goes into displacements. It has been calculated as a function of proton energy, and is analogous to (and has the same units as) the linear energy transfer (LET) for ionizing energy. We will discover that, to first order, the calculated NIEL describes the energy dependence of the measured device damage factors. This observation provides the basis for predicting proton induced device degradation in a space environment based on both the calculated NIEL and relatively few laboratory test measurements. The methodology of such on-orbit device performance predictions will be described, as well as the limitations. Several classes of devices for which displacement damage is a significant (if not the dominant) mode of radiation induced degradation will be presented.
This document contains the proceedings of the Training Workshop on Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems held at NASA Langley Research Center, Hampton, Virginia, March 5 - 6, 2002. The workshop was jointly sponsored by Old Dominion University's Center for Advanced Engineering Environments and NASA. Workshop attendees were from NASA, other government agencies, industry, and universities. The objectives of the workshop were to give overviews of the diverse activities in hierarchical approach to material modeling from continuum to atomistics; applications of multiscale modeling to advanced and improved material synthesis; defects, dislocations, and material deformation; fracture and friction; thin-film growth; characterization at nano and micro scales; and, verification and validation of numerical simulations, and to identify their potential for future aerospace systems.
The phenomenon of Leaky Lamb Wave (LLW) in composite materials was first observed in 1982 using a Schlieren system. It has been studied extensively by numerous investigators and successfully shown to be an effective quantitative NDE tool.
Point defect formation associated with early stages of optical damage was observed unexpectedly in two, and possibly three, different optical materials subjected to short-duration space exposure. Three calcium fluoride, two lithium fluoride, and three magnesium fluoride samples were flown on Space Shuttle flight STS-46 as part of the Evaluation of Oxygen Interactions with Materials - Third Phase experiment. One each of the calcium and magnesium fluoride samples was held at a fixed temperature of 60 C during the space exposure, while the temperatures of the other samples were allowed to vary with the ambient temperature of the shuttle cargo bay. Pre-flight and post-flight optical absorption measurements were performed on all of the samples. With the possible exception of the magnesium fluoride samples, every sample clearly showed the formation of F-centers in that section of the sample that was exposed to the low earth orbit environment. Solar vacuum ultraviolet radiation is the most probable primary cause of the defect formation; however, the resulting surface metallization may be synergistically altered by the atomic oxygen environment.
The project has evolved to that of using Green's functions to predict properties of deep defects in narrow gap materials. Deep defects are now defined as originating from short range potentials and are often located near the middle of the energy gap. They are important because they affect the lifetime of charge carriers and hence the switching time of transistors. We are now moving into the arena of predicting formation energies of deep defects. This will also allow us to make predictions about the relative concentrations of the defects that could be expected at a given temperature. The narrow gap materials mercury cadmium telluride (MCT), mercury zinc telluride (MZT), and mercury zinc selenide (MZS) are of interest to NASA because they have commercial value for infrared detecting materials, and because there is a good possibility that they can be grown better in a microgravity environment. The uniform growth of these crystals on earth is difficult because of convection (caused by solute depletion just ahead of the growing interface, and also due to thermal gradients). In general it is very difficult to grow crystals with both radial and axial homogeneity.
Transmission electron microscopy was used to investigate the defect structure of edge defined film growth (EFG) material, web dentritic ribbons (WEB), and ribbon to ribbon recrystallized material (RTR). The most common defects in all these materials are coherent first order twin boundaries. These coherent twins can be very thin, a few atomic layers. Bundles of the twins which contain odd numbers of twins will in optical images appear as a seemingly single first twin boundary. First-order coherent twin boundaries are not electrically active, except at locations where they contain intrinsic (grain boundary) dislocations. These dislocations take up small deviations from the ideal twin relation and play the same role in twin boundaries as conventional and play the some role in twin boundaries as conventional edge and screw dislocations in small angle tilt and twist boundaries.
To develop fast and low cost all optical methods to estimate defects in sensor materials.
Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.
Optically addressable spin defects have emerged as the leading platforms for quantum sensing and communication in solid-state systems. While traditional efforts have concentrated on a focused set of well-studied defects, recent advances in high-throughput computational methods have shown promise for large-scale exploration of defects across diverse semiconductor hosts. By cataloging key properties of quantum defects in computational databases, high-throughput screening techniques can systematically suggest and design novel candidates. In this article, we highlight recent advances in data-driven quantum defect design aimed at addressing critical materials science challenges such as host materials selection, defect stability, and desirable electronic and optical properties. Here, we emphasize the importance of electronic-structure-guided searches across various materials and illustrate how high-throughput computations contribute to our understanding of design principles for quantum defects. Additionally, we outline ongoing challenges and emerging opportunities in this rapidly developing field.
Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .
In ab initio studies of carrier-capture processes in defective semiconductor materials, the single-effective-mode formalism and the static-coupling approximation have become the predominant theoretical approaches for determining carrier-capture coefficients. The single-mode formalism relies on accurate nonequilibrium defect energies obtained from density-functional theory (DFT), where required inputs are a series of configurationally displaced, defect-containing supercells obtained using an interpolative ansatz, and where the DFT outputs are corresponding total energies that have traditionally been postprocessed using a long-established ground-state formulation of finite-size corrections and defect-formation energies. This formulation remains commonly used even though the defects that form a configuration-coordinate (CC) diagram typically exist as structures that are displaced from the ground state. To remedy this inconsistency, Kumagai has recently proposed novel methods for implementing finite-size corrections specifically intended for DFT calculations of the defect energies used to construct CC diagrams and implement the single-mode formalism [Y. Kumagai, Phys. Rev. B 107, L220101 (2023)]. Kumagai's approach builds on the latest finite-size-correction methods introduced to describe vertical charge-state transitions for charge-localizing point defects in semiconductors and insulators [T. Gake et al., Phys. Rev. B 101, 020102 (2020); S. Falletta et al., Phys. Rev. B 102, 041115 (2020)]. The newly identified finite-size artifact treated in these studies is the polarization charge induced on a configurationally frozen defect and its subsequent interaction with a vertical transition in charge state. In this work, we evaluate Kumagai's proposed methodology by applying it in a high-precision DFT study of carrier capture by substitutional C N in GaN, a well-characterized and technologically relevant defect and material. We have rigorously calculated C N defect energies across various supercell sizes for each defect configuration and charge state on the hole-capture CC diagram of C N (𝑞=−1), enabling a direct comparison of the slopes of the defect energies versus inverse cell size with those predicted by Kumagai. The most consequential prediction of Kumagai's method is that these slopes distinctly vary as the square of the linear-interpolation parameter used to construct the nonequilibrium defect configurations. Our results quantitatively support this prediction. Moreover, with these new finite-size corrections and multiple-cell-size DFT calculations in place, we find that the classical energy barrier for hole capture by C N (𝑞=−1) in GaN decreases to 0.092–0.127 eV. This finding confirms the recent ≈ 0.1 eV prediction of Reshchikov based on the weak temperature dependence for hole capture observed in photoluminescence experiments [M. A. Reshchikov, J. Appl. Phys. 129, 121101 (2021)]. These results stand in stark contrast to previously calculated barriers of 0.486 and 0.73 eV, which also used the single-mode formalism but were obtained by instead using ground-state-based finite-size corrections. Our reduced classical barrier for capture increases the temperature-dependent hole-capture coefficient of a C N (𝑞=−1) defect by more than two to four orders of magnitude for temperatures of 100–600 K, compared to the previous 0.486 eV results. While other defects may not be as dramatically affected as here, we suggest that incorporating proper finite-size corrections for the vertical-transition-like states embedded within CC diagrams is an essential, yet previously unrecognized, component of accurate modeling of carrier-capture when using the single-effective-mode formalism.
Nondestructive evaluation by Thermography (TNDE) is generally classified into two categories, the passive approach and the active approach. The passive approach is usually performed by measuring the natural temperature difference between the ambient and the material or structure to be tested. The active approach, on the other hand, requires the application of an external energy source to stimulate the material for inspection. A laser, a heater, a hot air blower, a high power thermal pulse, mechanical, or electromagnetic energy may provide the energy sources. For the external heating method to inspect materials for defects and imperfection at ambient temperature, a very short burst of heat can be introduced to one of the surfaces or slow heating of the side opposite to the side being observed. Due to the interruption of the heat flow through the defects, the thermal images will reveal the defective area by contrasting against the surrounding good materials. This technique is called transient Thermography, pulse video Thermography, or thermal wave imaging. As an empirical rule, the radius of the smallest defect should be at least one to two times larger than its depth under the surface. Thermography is being used to inspect void, debond, impact damage, and porosity in composite materials. It has been shown that most of the defects and imperfection can be detected. However, the current method of inspection using thermographic technique is more of an art than a practical scientific and engineering approach. The success rate of determining the defect location and defect type is largely depend on the experience of the person who operates thermography system and performs the inspection. The operator has to try different type of heat source, different duration of its application time, as well as experimenting with the thermal image acquisition time and interval during the inspection process. Further-more, the complexity of the lay-up and structure of composites makes it more difficult to determine the optimal operating condition for revealing the defects. In order to develop an optimal thermography inspection procedure, we must understand the thermal behavior inside the material subjected to transient heat in order to interpret the thermal images correctly. Fabrication of finite element models of characteristic defects in composite materials subjected to transient heat will enable the development of appropriate procedure for thermography inspection. Design of phantom defects could be modeled and behavior characterized prior to physically building these test parts. Since production of phantom test parts can be very time consuming and laborious, it is important to design good representative defects.
In materials, point defects often control or modify functional properties. To predict the performance of materials intended for application in optoelectronic devices, it is imperative to understand the properties of those point defects. For the first time, all six intrinsic defects of GaAs, a key optoelectronics material, and their charge transition levels are calculated using density functional theory with the HSE06 functional. For comparison, both PBE and r 2 SCAN calculations are also carried out. The HSE06 results are found to be in better agreement with experimental data than previous calculations. In conclusion, the importance of using the exact electron exchange present in hybrid functionals and larger supercells to accurately determine defect levels and ground state defect configurations is demonstrated.
Some background information on intrinsic point defects is provided and on carbon and oxygen in silicon in so far as it may be relevant for the efficiency of solar cells fabricated from EFG ribbon material. The co-precipitation of carbon and oxygen and especially of carbon and silicon self interstitials are discussed. A simple model for the electrical activity of carbon-self-interstitial agglomerates is presented. The self-interstitial content of these agglomerates is assumed to determine their electrical activity and that both compressive stresses (high self-interstitial content) and tensile stresses (low self-interstitial content) give rise to electrical activity of the agglomerates. The self-interstitial content of these carbon-related agglomerates may be reduced by an appropriate high temperature treatment and enhanced by a supersaturation of self-interstitials generated during formation of the p-n junction of solar cells. Oxygen present in supersaturation in carbon-rich silicon may be induced to form SiO, precipitates by self-interstitials generated during phosphorus diffusion. It is proposed that the SiO2-Si interface of the precipates gives rise to a continuum of donor stables and that these interface states are responsible for at least part of the light inhancement effects observed in oxygen containing EFG silicon after phosphorus diffusion.
The leaky Lamb waves (LLW) technique is approaching a maturity level that is making it attractive quantitative NDE tool for composites and bonded joints.