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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Defect Thermodynamics and Transport Properties of Proton Conducting Perovskite Electrode and Electrolyte Materials Evaluated Based on Density Functional Theory Modeling

Both electron-rich and electron-poor perovskite oxides have been used in solid oxide cell applications as electrode and electrolyte materials. The rich oxygen defect chemistry and its coupling to temperature, hydrogen-steam or oxygen-steam gas pressure, or to the applied potentials creates enormous complexities for modeling performance and degradation of the materials. Herein, density functional theory-based thermodynamic modeling was carried out to describe the defect chemistry and transport properties of the proton-conducting electrolyte BaZr1-xYxO3-δ (x≤0.1) and of the triple-conducting perovskite (La,Ba)(Fe,M)O3-δ (M=Y and Zr). The defect thermodynamics of intrinsic point defects and the hydrogen-related defect reactions were solved in integrated defect models and further used to predict the Brouwer diagram and the transport properties of the functional perovskites. For the electron-poor electrolytes BaZr0.9Y0.1O3-δ, the developed model has been used to describe the experimental transport properties in the SOC operating conditions. Specifically, the roles played by the acceptor-bound holes and the intrinsic and hydrogen point defects upon the conductivities of holes, protons, and oxygen vacancies under the hydrogen-rich and oxygen-rich conditions at various humidity levels were demonstrated. A defect modeling tool was also developed for the triple-conducting perovskite (La,Ba)(Fe,M)O3-δ (M=Y and Zr) to examine magnetic effects and hydride defects in defect equilibria.

defect thermodynamics↗
DOE OSTI2020

Self-assembly of solid nanoclusters in molybdenum under gas ion implantation

The self-assembly of defects in materials could create unique physical and chemical properties. In nuclear fuels, the formation of self-assembled fission products mitigates fission-gas-release and swelling. In this work, we report the formation of a solid nanocluster superlattice in molybdenum, an important constituent in metallic fuels, under krypton gas ion implantation. X-ray absorption near edge structure measurements coupled with density functional theory calculations show that the pressure of krypton nanoclusters in molybdenum is ~2 GPa and molecular dynamic simulations reveal that the krypton atoms are solid in the nanoclusters with a krypton-to-vacancy ratio of ~0.28 at 300 K.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

On the surface passivating principle of functional thiol towards efficient and stable perovskite nanocrystal solar cells

Inorganic halide perovskite nanocrystals (PNCs) have demonstrated promising potential for solar cell applications. However, the lability of photoactive CsPbI3 phase under ambient conditions, coupled with considerable amounts of surface defects induced during solidification process, have impeded achieving high performances and longevities of the PNC-based solar cells. Post-treatment of the PNCs with organic ligands has been proposed as an efficient strategy for surface passivation, which, however, still relies on the binding actions of typical functional groups towards surface defects (especially, carboxylates onto iodine vacancies). Herein, we uncover that thiolate, a deprotonated form of thiol, renders distinctive binding feasibility towards iodine vacancies at the CsPbI3 PNC surface, compared with those of typical functional groups. By treating the PNC solid with deprotonated cysteine as a ligand, the surface defects are comprehensively passivated. The solar cells with the modified PNC films demonstrate an excellent PCE of 15.5 % and improved device longevity (77 % of initial PCE over 2 months) under ambient conditions. Our work not only elucidates the chemical principles of thiol on the binding with PNC surface, but also corroborates the power of thiolate as a promising strategy to develop high performances and improved longevity of solar cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling the electrical double layer at solid-state electrochemical interfaces

Models of the electrical double layer (EDL) at electrode/liquid-electrolyte interfaces no longer hold for all-solid-state electrochemistry. Here we show a more general model for the EDL at a solid-state electrochemical interface based on the Poisson–Fermi–Dirac equation. By combining this model with density functional theory predictions, the interconnected electronic and ionic degrees of freedom in all-solid-state batteries, including the electronic band bending and defect concentration variation in the space-charge layer, are captured self-consistently. Along with a general mathematical solution, the EDL structure is presented in various materials that are thermodynamically stable in contact with a lithium metal anode: the solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) and the solid interlayer materials LiF, Li 2 O and Li 2 CO 3 . Here, the model further allows design of the optimum interlayer thicknesses to minimize the electrostatic barrier for lithium ion transport at relevant solid-state battery interfaces.

25 ENERGY STORAGE↗
DOE OSTI2021

High Throughput In-Line Coating Metrology Development for Solid Oxide Fuel Cell Manufacturing

Coatings play key roles in solid oxide fuel cell (SOFC) stack durability. For example, diffusion barrier coatings on Cr-containing interconnect and balance of plant (BOP) components protect electrodes from Cr poisoning over the long operational lifetimes (>10,000 hours) of the fuel cell stack. Common defects in coatings, such as cracks, pinholes, and porosity, result in a failure to protect the electrodes, resulting in shorter operational lifetime and thus higher cost. It is very unlikely, even in the best coating process, that all these defects can be mitigated, hence identifying critical defects in parts, and removing defective parts from production before they can damage the stack, becomes paramount. Furthermore, these quality control techniques must be operational in the production/assembly line (in-line), i.e., high throughput and non-destructive, and cost effective. Redox Power Systems, LLC (Redox) together with the National Renewable Energy Laboratory (NREL) developed much needed high throughput, in-line metrology techniques for protective coatings. The overall goal of the project is to lower cost while increasing robustness, reliability, and endurance of SOFC stacks. To accomplish this, we had several objectives, including: to identify key coating and substrate defects that lead to coating failure through the use of detailed characterization methods (e.g., microscopy, XRD, EDS, electrochemistry); to assess capabilities of in-line metrology techniques, e.g., optical profilometry (Redox) and thermography (NREL), to probe these defects, or evidence thereof; demonstrate long-term performance of “defect-free” protective coatings, as identified by in-line metrology, in solid oxide fuel cell (SOFC) stack operation. In the first part of this project, the ability to identify key defects expected to lead to coating and SOFC degradation using in-line metrology tools were evaluated. Coated interconnect samples with controlled defect types and populations were tested under conditions similar to SOFC operation, followed by detailed post-test analysis to reveal the defects responsible for observed degradation. In the second part of the project, the optimal in-line metrology techniques and methodologies were used to map the defect distribution in full-size interconnects with critical defects intentionally allowed to exist in some cases. These interconnects underwent SOFC testing for extended periods (up to ~3,000 hours) followed by post-test analysis to evaluate the effectiveness of in-line metrology techniques in mitigating MCO coating related degradation. Key accomplishments in this project included the following: Demonstrated ASR of < 0.05 ohm-cm 2 at 650 °C for 1,000 hours with low defect (determined by in-line metrology) interconnect samples (average ASR=37 milliohms-cm 2 after over 1,000 hours). Demonstrated that low defect coatings on interconnects (as screened using in-line metrology) have low volatilization of chromium at ~650 °C for 1,000 hours as detected using Cr-getter material (< 5 at% increase above baseline); 1022 hour duration tests under humidified, elevated temperature (750 °C rather than 650 °C) compared a base case against different coating thicknesses. Demonstrated capability to identify initial key defects of interest with in-line metrology techniques using up to 8 cm by 10 cm having coatings with and without intentional defects of interest using thermal imaging and optical profilometry. Correlated key defects identified using metrology techniques with observed coating performance (e.g., ASR and Cr volatility). Conducted several 4 cm by 4 cm cell tests using MCO-interconnects that were pre-screened using some of the metrology techniques developed in the project (e.g., optical profilometry). An analysis of ASR measurements were able to show that defect-free coatings resulted in the anticipated performance in the cell tests.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Finding the perfect imperfection: Accelerated, computationally driven discovery and design of quantum defects

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.

Xiong, Yihuang [Dartmouth College, Hanover, NH (Un↗
DOE OSTI2021

Photoluminescence spectra of point defects in semiconductors: Validation of first-principles calculations

Optically and magnetically active point defects in semiconductors are interesting platforms for the development of solid state quantum technologies. Their optical properties are usually probed by measuring photoluminescence spectra, which provide information on excitation energies and on the interaction of electrons with lattice vibrations. We present a combined computational and experimental study of photoluminescence spectra of defects in diamond and SiC, aimed at assessing the validity of theoretical and numerical approximations used in first-principles calculations, including the use of the Franck-Condon principle and the displaced harmonic oscillator approximation. We focus on prototypical examples of solid state qubits, the divacancy centers in SiC and the nitrogen-vacancy in diamond, and we report computed photoluminescence spectra as a function of temperature that are in very good agreement with the measured ones. As expected we find that the use of hybrid functionals leads to more accurate results than semilocal functionals. Interestingly our calculations show that constrained density functional theory (CDFT) and time-dependent hybrid DFT perform equally well in describing the excited state potential energy surface of triplet states; our findings indicate that CDFT, a relatively cheap computational approach, is sufficiently accurate for the calculations of photoluminescence spectra of the defects studied here. Finally, we find that only by correcting for finite-size effects and extrapolating to the dilute limit can one obtain a good agreement between theory and experiment. Our results provide a detailed validation protocol of first-principles calculations of photoluminescence spectra, necessary both for the interpretation of experiments and for robust predictions of the electronic properties of point defects in semiconductors.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Nondestructive Visualization of Defects and Crack Propagation of Shuttle-Foam

Shuttle insulating foam is a low-density closed-cell solid-gas composite. A chief barrier to understanding foam loss has been extreme difficulties in nondestructively visualizing defects of the foam that is almost transparent to x-rays. Here we show that defects, crack propagation, and cell structure can be clearly and nondestructively observed by turning the density inhomogeneity across foam structures into a source for phase contrast imaging. This provides a new powerful way to help understand foam loss.

Hu, Zheng-Wei↗
NASA NTRS2000

Temperature Distribution Within a Defect-Free Silicon Carbide Diode Predicted by a Computational Model

Most solid-state electronic devices diodes, transistors, and integrated circuits are based on silicon. Although this material works well for many applications, its properties limit its ability to function under extreme high-temperature or high-power operating conditions. Silicon carbide (SiC), with its desirable physical properties, could someday replace silicon for these types of applications. A major roadblock to realizing this potential is the quality of SiC material that can currently be produced. Semiconductors require very uniform, high-quality material, and commercially available SiC tends to suffer from defects in the crystalline structure that have largely been eliminated in silicon. In some power circuits, these defects can focus energy into an extremely small area, leading to overheating that can damage the device. In an effort to better understand the way that these defects affect the electrical performance and reliability of an SiC device in a power circuit, the NASA Glenn Research Center at Lewis Field began an in-house three-dimensional computational modeling effort. The goal is to predict the temperature distributions within a SiC diode structure subjected to the various transient overvoltage breakdown stresses that occur in power management circuits. A commercial computational fluid dynamics computer program (FLUENT-Fluent, Inc., Lebanon, New Hampshire) was used to build a model of a defect-free SiC diode and generate a computational mesh. A typical breakdown power density was applied over 0.5 msec in a heated layer at the junction between the p-type SiC and n-type SiC, and the temperature distribution throughout the diode was then calculated. The peak temperature extracted from the computational model agreed well (within 6 percent) with previous first-order calculations of the maximum expected temperature at the end of the breakdown pulse. This level of agreement is excellent for a model of this type and indicates that three-dimensional computational modeling can provide useful predictions for this class of problem. The model is now being extended to include the effects of crystal defects. The model will provide unique insights into how high the temperature rises in the vicinity of the defects in a diode at various power densities and pulse durations. This information also will help researchers in understanding and designing SiC devices for safe and reliable operation in high-power circuits.

Kuczmarski, Maria A.↗
DOE OSTI2024

Research Progress and Perspectives on Pre‐Sodiation Strategies for Sodium‐Ion Batteries

Sodium‐ion batteries (SIBs) with abundant elements have garnered significant attention from researches as a promise compensation to lithium‐ion batteries (LIBs). However, the large‐scale commercial application of SIBs is partially hindered by the limited initial coulombic efficiency (ICE) due to the irreversible formation of solid electrolyte interphase (SEI) and intercalation into the defects in the anode. Similar to pre‐lithiation techniques, pre‐sodiation approaches are considered to be one of the most direct and effective way to compensate for the loss of active sodium at the anode side of SIBs during the initial cycle. In this context, additional sodium ions are pre‐injected to the cathode/anode material by chemical/electrochemical methods, aiming to improve battery span life and energy density. Here, this review delves into the necessity and impact of pre‐sodiation techniques, compiling the latest research progress, for instance, self‐sacrificing cathode additives, over‐sodiated cathode materials, direct contact and solution chemical pre‐sodiation. Notably, the research mechanisms underlying solution chemical pre‐sodiation are highlighted. This comprehensive overview aims to foster a deeper understanding of the pre‐sodiation techniques and expects to provide guidance for realizing the commercial application of high energy density sodium‐ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Compositionally graded aluminum-silicon alloy fabricated via friction extrusion

Herein, a novel solid-phase gradient alloying technique was developed for a high throughput composition-microstructure-mechanical property assessment. Friction extrusion of a two-piece billet setup facilitated the formation of a seamless compositionally graded aluminum (Al)-silicon (Si) extrudate rod, with Si concentration in Al matrix gradually increasing from ~1 at% at one end to ~7 at% at the other end of the rod. We observed a strong dependence of the Al grain size, morphology, and texture on the Si concentration. The Si particles pinned the recrystallized grain boundaries resulting in refined (< 10 µm) and textured grains in the high Si content region, while the Al grains in the low Si region are equiaxed, randomly textured, and with a larger average size (~50 µm). The hardness of Al-Si gradient extrudate increases by ~50% percent with a 6 at% increase in Si content due to Hall Petch and particle strengthening effects. Our approach demonstrates the use of a solid phase processing technique to successfully produce a defect-free continuously compositionally graded bulk components thus overcoming the limitations of porosity and material heterogeneities commonly observed in other techniques such as by additive laser deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Automated discovery of a robust interatomic potential for aluminum

Machine learning, trained on quantum mechanics (QM) calculations, is a powerful tool for modeling potential energy surfaces. A critical factor is the quality and diversity of the training dataset. Here we present a highly automated approach to dataset construction and demonstrate the method by building a potential for elemental aluminum (ANI-Al). In our active learning scheme, the ML potential under development is used to drive non-equilibrium molecular dynamics simulations with time-varying applied temperatures. Whenever a configuration is reached for which the ML uncertainty is large, new QM data is collected. The ML model is periodically retrained on all available QM data. The final ANI-Al potential makes very accurate predictions of radial distribution function in melt, liquid-solid coexistence curve, and crystal properties such as defect energies and barriers. We perform a 1.3M atom shock simulation and show that ANI-Al force predictions shine in their agreement with new reference DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

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↗
DOE OSTI2024

Compensating for Sintering Distortion in Additively Manufactured Shaped Charge Liners using Physics-Informed Machine Learning

Copper is a challenging material to process using laser-based additive manufacturing due to its high reflectivity and high thermal conductivity. Sintering-based processes can produce solid copper parts without the processing challenges and defects associated with laser melting; however, sintering can also cause distortion in copper parts, especially those with thin walls. In this study, we use physics-informed Gaussian process regression to predict and compensate for sintering distortion in thin-walled copper parts produced using a Markforged Metal X bound powder extrusion (BPE) additive manufacturing system. Through experimental characterization and computational simulation of copper’s viscoelastic sintering behavior, we can predict sintering deformation. We can then manufacture, simulate, and test parts with various compensation scaling factors to inform Gaussian process regression and predict a compensated as-printed (pre-sintered) part geometry that produces the desired final (post-sintered) part.

36 MATERIALS SCIENCE↗
NASA NTRS1983

Studies of convection in a solidifying binary mixture at reduced gravity

A great deal of interest was generated recently in the possibility of producing new materials in the reduced gravity environment provided during the forthcoming missions of Spacelab. The range of possibilities extend from producing large crystals of uniform properties to manufacturing materials with unique properties. Most of these processes involve the solidification of materials from the liquid state. Convective motions within the liquid during solidification can influence the local material composite and the shape of the solid-liquid interface which may result in solids with non-uniform properties and crystal defects. The microgravity environment of Spacelab is being viewed as one in which the buoyancy forces are eliminated so that convection driven by thermal gradients does occur, resulting in an improved solidification process. However, convection may occur for other reasons and whether convection is negligible or not during solidification constitutes processing in low-gravity environment. Little information exists presently on convection during solidification under such circumstances. A continuation of an analytical investigation into the nature of convective motion in a binary liquid layer due to surface tension forces during its solidification is reported. The onset of convection will be determined through a stability analysis which is described.

Antar, B. N.↗
NASA NTRS1989

Thermographic detection of disbonds

The presence of disbonds significantly decreases the integrity of many laminated structures used in aerospace applications. A thermographic technique is presented which is able to detect subsurface delamination. The technique uses one of several heat sources (such as hot water, hot air, IR lamps, etc.) to increase the surface temperature of the structure. The subsequent temperature profiles of the surface are detected with an IR camera. A novel spatial filter developed at NASA-Langley eliminates the effects of uneven heating to give clear images of the subsurface delaminations. Defects are detectable in samples as diverse as solid rocket motor samples and laminated wood for wind tunnel blades. Numerical simulations are presented for comparison with experiment results.

Winfree, William P.↗
DOE OSTI2022

Dislocation-position fluctuations in solid 4He as collective variables in a quantum crystal

Abstract Quantum behavior at mesoscopic length scales is of significant interest, both from a fundamental-physics standpoint, as well as in the context of technological advances. In this light, the description of collective variables comprising large numbers of atoms, but nevertheless displaying non-classical behavior, is a fundamental problem. Here, we show that an effective-Hamiltonian approach for such variables, as has been applied to describe the quantum behavior of coupled qubit/oscillator systems, can also be very useful in understanding intrinsic behavior of quantum materials. We consider lattice dislocations – naturally occurring mesoscopic line defects in crystals – in the prototypical bosonic quantum crystal, solid 4 He. For this purpose, we map fully atomistic quantum simulations onto effective one-dimensional Hamiltonians in which the collective dislocation-position variables are represented as interacting, massive quantum particles. The results provide quantitative understanding of several experimental observations in solid 4 He.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Influence of Superlattice Structure on V-Defect Distribution, External Quantum Efficiency and Electroluminescence for Red InGaN Based µLEDs on Silicon

Achieving high quantum efficiency in long-wavelength LEDs has posed a significant challenge to the solid-state lighting and display industries. In this article, we use V-defect engineering as a technique to achieve higher efficiencies in red InGaN LEDs on (111) Si through lateral injection. We investigate the effects of superlattice structure on the V-defect distribution, the electroluminescence properties, and the external quantum efficiency. Increasing the relative thickness of In in the InGaN/GaN superlattice and the total superlattice thickness correlate with a reduction of active region defects and increased external quantum efficiencies. The highest measured on-chip EQE was 0.15% and based on Monte-Carlo ray tracing simulations for light extraction we project this would correspond to a flip-chip EQE of ~2.5%.

36 MATERIALS SCIENCE↗