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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

In-situ microstructure observation of oxidized SiC layer in surrogate TRISO fuel particles under krypton ion irradiation

In accidental scenarios of high temperature gas-cooled reactors, both oxidation of and irradiation to the SiC layer in tri-structural-isotropic (TRISO) fuel particles can change the microstructure and integrity of the fuel elements. Here, in the present study, microstructure and defect evolution in the oxidized SiC layer of surrogate TRISO fuel particles under 1.2 MeV krypton ion irradiation was observed by in-situ transmission electron microscopy. The SiC layers oxidized in water vapor at 1200 °C were irradiated azt room temperature and 800 °C and at damage levels of 0.28–11.2 dpa, respectively. SiC and SiO 2 were found to still be in their crystal structures at the damage level of 11.2 dpa at 800 °C, while SiC was observed to have been amorphized at only 0.56 dpa irradiation at room temperature. The defect number density at 800 °C was an order of magnitude lower than that in the sample irradiated at room temperature. Also, crystalline SiO 2 had higher radiation resistance compared to SiC. A defect reaction rate theory was utilized to understand the fundamental defect evolution process and irradiation resistance difference.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A concurrent irradiation-mechanics multiscale coupling model

The vast majority of our current knowledge regarding the basic mechanisms controlling irradiation effect on mechanical properties is based almost entirely on the results of post-irradiation experiments or theoretical models. However, the concurrent effects of irradiation, mechanical stress, and thermal damage on the failure phenomena of materials and components remain largely unexplored due to its internal multiscale-multiphysics coupling nature. Here, we present here a concurrent irradiation-mechanics multiscale coupling model. The concurrent evolutions of nanoscale irradiation defect clusters, microscale dislocation configurations, and mechanical responses are well captured based on coupling cluster dynamics, discrete dislocation dynamics, and the finite element methods using an effective time marching scheme. Model predictions of defect densities and size are in general agreement with experimental observations. Irradiation hardening is shown to take place also in samples undergoing concurrent irradiation-mechanical loading, similar to samples tested post-irradiation. However, the occurrence of plastic flow localization and dislocation channel formation is not accompanied with apparent yield drop (softening) under concurrent irradiation-mechanical loading conditions, which is different from the post-irradiation case.

42 ENGINEERING↗
DOE OSTI2024

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗
DOE OSTI2021

Mitigation of J–V distortion in CdTe solar cells by Ga-doping of MgZnO emitter

Distortions in the current–voltage curves of CdTe-based thin-film solar cells with MgZnO emitter layers are not uncommon. Even when such distortions are very subtle with standard sunlight, they can be greatly accentuated by the removal of short-wavelength photons with optical filters, and the dark-curve turn-on voltage can be noticeably increased. The strong suggestion is that good J–V curves with full-spectrum light often rely on photogeneration of electrons from trap states in the MgZnO emitter. When the carrier concentration of the CdTe absorber is increased with external doping, there is a corresponding need for a larger MgZnO carrier concentration. Based on the assumption that the emitter carrier concentration needs to be comparable to that of the absorber, Ga-doping of the MgZnO was shown to very nearly eliminate the large filtered-light distortions and is arguably superior to MgZnO that relies on photogeneration. In addition, it was shown that photogeneration and recovery in MgZnO is relatively slow, so that without Ga-doping, the cell efficiency improves gradually for most of an hour in the light, and the turn-on voltage of the dark curve increases on a similar time scale when the light is removed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Triple ionic–electronic conducting oxides for next-generation electrochemical devices

Triple ionic–electronic conductors (TIECs) are materials that can simultaneously transport electronic species alongside two ionic species. The recent emergence of TIECs provides intriguing opportunities to maximize performance in a variety of electrochemical devices, including fuel cells, membrane reactors and electrolysis cells. However, the potential application of these nascent materials is limited by lack of fundamental knowledge of their transport properties and electrocatalytic activity. The goal of this Review is to summarize and analyse the current understanding of TIEC transport and electrochemistry in single-phase materials, including defect formation and conduction mechanisms. In this work, we particularly focus on the discovery criteria (for example, crystal structure and ion electronegativity), design principles (for example, cation and anion substitution chemistry) and operating conditions (for example, atmosphere) of materials that enable deliberate tuning of the conductivity of each charge carrier. Lastly, we identify important areas for further advances, including higher chemical stability, lower operating temperatures and discovery of n-type TIEC materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Electron Beam Powder Bed Fusion Additive Manufacturing of Refractory Metals

The processing of refractory metals via additive manufacturing (AM) presents an opportunity to fabricatecomponents not possible through traditional powder metallurgy techniques. However, processing via AM isextremely challenging and there exist a host of technological limitations still unaddressed. Molybdenumand tungsten are two materials of particular interest for nuclear energy generation applications. Themajority of existing work on the processing of these materials is focused on laser powder bed fusion whereasa smaller body of work exists for electron beam melting AM. In general, material with acceptable densitycan be obtained via both routes however cracking is much more difficult to mitigate against. Strongcrystallographic fiber textures have been observed across a range of refractory systems. In this work wepresent our recent findings on electron beam melting AM of pure tungsten and molybdenum. Wedemonstrate that defect-free material can be obtained in both systems with appropriate processing. Strongbuild direction crystallographic texture fibers are observed in both systems. In molybdenum the fibertexture has direct impact on the resulting tensile behavior. These results demonstrate that electron beamAM is a suitable technology for processing these difficult to fabricate materials.

Fernandez-Zelaia, Patxi↗
DOE OSTI2023

High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications

Abstract Calculations of point defect energetics with Density Functional Theory (DFT) can provide valuable insight into several optoelectronic, thermodynamic, and kinetic properties. These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches. For applications of DFT-based high-throughput computation for data-driven materials discovery, point defect properties are of interest, yet are currently excluded from available materials databases. This work presents a benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We consider three different a-posteriori correction sets implemented in an automated workflow, and evaluate the qualitative and quantitative differences among four different categories of defect information: thermodynamic transition levels, formation energies, Fermi levels, and dopability limits. We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Improvement of Front-Junction GaInP by Point-Defect Injection and Annealing

Traditional front junction GaInP solar cells are radiation tolerant and can have good diffusion length, but have limited voltage and thus efficiency. Here, we investigate the impact of annealing on GaInP device performance. First, Zn-doped GaInP/AlGaInP double heterojunction structures are studied in order to investigate the impact of annealing in a simple structure. While standard anneals lower diffusion length and lifetime, annealing after injecting point-defects improves material quality, presumably by eliminating sources of non-radiative recombination. Atomic ordering is reduced by the anneal, which raises the device bandgap and requires consideration. These results can be used to improve front junction device performance while controlling the bandgap. Then, GaInP front-junction devices are created using anneals with and without point-defect injection. Voc and EQE trends follow the diffusion length and lifetime trends from the DH structures. Baseline devices have Woc of 0.484 V, raising to 0.504 V after a high temperature anneal. However, injecting point defects prior to the anneal results in a front junction device with Woc of 0.405 V and a diffusion length greater than 8 micrometers. Optimized front-junction GaInP devices with an ARC have ~20% efficiency without a rear reflector.

anneal↗
DOE OSTI2021

Improvement of Front-Junction GaInP by Point-Defect Injection and Annealing: Preprint

Traditional front junction GaInP solar cells are radiation tolerant and can have good diffusion length, but have limited voltage and thus efficiency. Here, we investigate the impact of annealing on GaInP device performance. First, Zn-doped GaInP/AlGaInP double heterojunction structures are studied in order to investigate the impact of annealing in a simple structure. While standard anneals lower diffusion length and lifetime, annealing after injecting point-defects improves material quality, presumably by eliminating sources of non-radiative recombination. Atomic ordering is reduced by the anneal, which raises the device bandgap and requires consideration. These results can be used to improve front junction device performance while controlling the bandgap. Then, GaInP front-junction devices are created using anneals with and without point-defect injection. Voc and EQE trends follow the diffusion length and lifetime trends from the DH structures. Baseline devices have Woc of 0.484 V, raising to 0.504 V after a high temperature anneal. However, injecting point defects prior to the anneal results in a front junction device with Woc of 0.405 V and a diffusion length greater than 8 micrometers. Optimized front-junction GaInP devices with an ARC have ~20% efficiency without a rear reflector.

anneal↗
DOE OSTI2024

Diffuse scattering from dynamically compressed single-crystal zirconium following the pressure-induced α → ω phase transition

The prototypical α → ω phase transition in zirconium is an ideal test bed for our understanding of polymorphism under extreme loading conditions. After half a century of study, a consensus had emerged that the transition is realized via one of two distinct displacive mechanisms, depending on the nature of the compression path. However, recent dynamic-compression experiments equipped with diffraction diagnostics performed in the past few years have revealed new transition mechanisms, demonstrating that our understanding of the underlying atomistic dynamics and transition kinetics is in fact far from complete. We present classical molecular dynamics simulations of the α → ω phase transition in single-crystal zirconium shock compressed along the [0001] axis using a machine-learning-class potential. The transition is predicted to proceed primarily via a modified version of the two-stage Usikov-Zilberstein mechanism, whereby the high-pressure ω phase heterogeneously nucleates at boundaries between grains of an intermediate β phase. We further observe the fomentation of atomistic disorder at the junctions between β grains, leading to the formation of highly defective interstitial material between the ω grains. We directly compare synthetic x-ray diffraction patterns generated from our simulations with those obtained using femtosecond diffraction in recent dynamic-compression experiments, and show that the simulations produce the same unique, anisotropic diffuse scattering signal unlike any previously seen from an elemental metal. Our simulations suggest that the diffuse signal arises from a combination of thermal diffuse scattering, nanoparticlelike scattering from residual kinetically stabilized α and β grains, and scattering from interstitial defective structures. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of point defect accumulation on in-pile thermal conductivity degradation: Fuel rod defect distribution and deviation between in-pile and post irradiation thermal conductivity

As nuclear fuel burn-up increases, its thermal conductivity degrades due to the accumulation of defects that lead to increased phonon scattering rates. This results in a rise in the centerline temperature of the fuel rod, whereby heat generation must be decreased to avoid undesired behavior such as fuel melting and extensive fission gas release. Fuel performance codes are utilized to optimize the fuel's operational conditions; while they are based on established physical principles, their empirical nature limits their predictive capabilities. Recently, an effort has been made to develop predictive fuel performance codes for commonly used nuclear fuels, as well as accelerated qualification of advanced nuclear fuels. In this report, we elaborate on the importance of careful analysis of point defects’ impact on thermal conductivity in fuel performance analysis. Further, a model is presented where point defect concentration is estimated based on Rate Theory modeling and used as input to the Klemens-Callaway model to calculate their contribution to the degradation of thermal conductivity in UO 2 under prototypical irradiation conditions. This analysis suggests that point defect concentration is significant at the rim of the fuel pellet and neglecting this leads to underestimation of the centerline temperature, which may have consequences on fission gas behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

FAIR Data and Interpretable AI Framework for Architectured Metamaterials (Final Report)

This research program established a transformative framework for the discovery and design of mechanical metamaterials, which are architected structures engineered to control physical phenomena like sound and vibration in ways natural materials cannot. To overcome the traditional reliance on trial-and-error, the project developed an interpretable Artificial Intelligence (AI) framework that moves beyond "black box" models to reveal the specific geometric patterns—such as "unit-cell templates"—that govern a material’s performance. A major breakthrough was the development of a hierarchical design method, which allows a single material to block vibrations across multiple frequency ranges simultaneously by layering patterns at different scales without them interfering with one another. This was further expanded to include irregular, graph-based designs that use spanning tree algorithms to ensure structural connectivity while allowing for customized, direction-dependent properties like stiffness and acoustic impedance. Beyond design, the project addressed the practicalities of real-world production by developing uncertainty quantification techniques that account for manufacturing defects and material variability, reducing the need for expensive physical testing by orders of magnitude. To speed up the discovery process, the team implemented Gaussian Process Regression and other surrogate models that provide accurate performance predictions at a fraction of the traditional computational cost. The AI-generated designs were successfully validated through fabrication of physical samples and wave propagation experiments, confirming their ability to accurately guide or reflect waves as predicted. By contributing these tools and high-quality FAIR benchmark datasets to the wider scientific community, this work provides a scalable foundation for advancing technologies in aerospace vibration control, medical imaging, and noise reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Site-Selective Atomic Layer Deposition at Thermally Generated Surface Oxygen Vacancies on Rutile TiO 2

Unique atomic arrangements (i.e., defects) on material surfaces may exhibit distinctive reactivity that affords opportunities for selective surface chemistry exclusively at those sites. While theoretically appealing, site-selective atomic layer deposition (ALD) processes remain largely unrealized experimentally. Here we provide evidence for site-selective ALD that exclusively targets oxygen vacancies thermally generated at the surface of TiO 2 single crystals. High-resolution in situ ellipsometry reveals the nucleation behavior of dimethylaluminum isopropoxide (DMAI) and water at process conditions precisely tuned for selective hydroxylation of surface defects. An island growth model for nucleation and atomic force microscopy (AFM) imaging are consistent with a site-selective growth mechanism that depends on the surface oxygen vacancy density. This approach to direct ALD reactions at defective surface sites may provide future opportunities for targeted remediation of electronically imperfect interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Detection of Defects in Additively Manufactured Metallic Materials with Machine Learning of Pulsed Thermography Images

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Quality control (QC) requires nondestructive evaluation (NDE) of actual AM structures. Pulsed thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, detection sensitivity of this method is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. The ML methods with higher accuracy require longer run time. However, this runtime is sufficiently short to perform QC within a realistic time frame.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Impacts of PTL coating gaps on cell performance for PEM water electrolyzer

The anode porous transport layer (PTL) is a critical component of polymer electrolyte membrane (PEM) water electrolyzers, providing electrical conduction and water/oxygen transport to the anode catalyst layer. Platinum group metal (PGM) coatings are applied to titanium PTLs to prevent oxidation and preserve conductivity. To implement PEM water electrolysis on a large scale, it is essential to minimize the cost of mass-manufactured cell components while ensuring that defects in materials and components do not adversely affect the performance of the cell. In this study, we created gaps in the Pt coatings that are typically applied to PTLs to understand their effects on cell performance and inform on fabrication tolerances. The PTL coatings were fabricated by sputter deposition of Pt, intentionally leaving uncoated regions in either large patches or thin strips. For either geometry, the cell performance decreased with the increasing fraction of the uncoated regions. However, PTLs containing multiple thin uncoated strips caused a less severe performance effect than PTLs with continuous uncoated regions of the same relative total area. Through analysis of cell performance, impedance, and 3D charge transport modelling, here we demonstrate that both the anode catalyst layer and membrane play a role in distributing current to mitigate the impact of coating defects at a short length scale. These results allow to draw conclusions about the tolerance requirements with regards to PTL coating uniformity in terms of both the size and total area of defects.

08 HYDROGEN↗
DOE OSTI2024

Enhanced superconducting qubit performance through ammonium fluoride etch

The performance of superconducting qubits is often limited by dissipation and two-level systems (TLS) losses. The dominant sources of these losses are believed to originate from amorphous materials and defects at interfaces and surfaces, likely as a result of fabrication processes or ambient exposure. Here, we explore a novel wet chemical surface treatment at the Josephson junction-substrate and the substrate-air interfaces by replacing a buffered oxide etch (BOE) cleaning process with one that uses hydrofluoric acid followed by aqueous ammonium fluoride. We show that the ammonium fluoride etch process results in a statistically significant improvement in median $\text{T}_1$ by $\sim22\%$ (p = 0.002), and a reduction in the number of strongly-coupled TLS in the tunable frequency range. Microwave resonator measurements on samples treated with the ammonium fluoride etch after niobium deposition and etching also show $\sim33\%$ lower TLS-induced loss tangent compared to the BOE treated samples. As the chemical treatment primarily modifies the Josephson junction-substrate interface and substrate-air interface, we perform targeted chemical and structural characterizations to examine materials differences at these interfaces and identify multiple microscopic changes that could contribute to decreased TLS losses.

36 MATERIALS SCIENCE↗