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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Microstructural and infiltration properties of woven preforms during chemical vapor infiltration

Interface-resolved direct numerical simulations (DNSs) of chemical vapor infiltration (CVI) have been performed over a range of furnace-operating conditions (Thiele moduli) and for practical woven preform geometries. A level-set method is used to resolve the geometry of the initial preform at tow scale. The interface between the vapor and solid phase is then evolved in time through the entire CVI densification cycle, fully resolving the time-varying topology between the two phases. In contrast to previous level-set methods for CVI simulation, the physical reaction and diffusion processes govern the level-set movement in the current approach. The surface deposition kinetics is described by the usual one-step model. In this paper, the DNS data are used to study the evolving porosity, surface-to-volume ratio, and flow infiltration properties (permeability and effective diffusivities). Additionally, comparisons are made to popularly-assumed structure functions and the standard, Kozeny–Carmen porous media model commonly employed in modeled CFD simulations of CVI. The virtual DNS experiments reveal a Thiele modulus and preform geometry (fabric layup) dependence which the existing microstructural and infiltration models are not able to describe throughout the entire densification process. The DNS-based, woven geometry-specific correlations can be applied directly to mean-field, furnace-scale CFD simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Thermophysical Properties of High-Frequency Induction Heat Sintered Graphene Nanoplatelets/Alumina Ceramic Functional Nanocomposites

This paper concerns the thermophysical properties of high-frequency induction heat (HFIH) sintered alumina ceramic nanocomposites containing various graphene nanoplatelets (GNP) concentrations. The GNP/alumina nanocomposites demonstrated high densities, fine-grained microstructures, highest fracture toughness and hardness values of 5.7 MPa m{sup 1/2} and 18.4 GPa, which found 72 and 8%, superior to the benchmarked monolithic alumina, respectively. We determine the role of GNP in tuning the microstructure and inducing toughening mechanisms in the nanocomposites. The sintered monolithic alumina exhibited thermal conductivity value of 24.8 W/mK; however, steady drops of 2, 15 and 19% were recorded after adding respective GNP contents of 0.25, 0.5 and 1.0 wt.% in the nanocomposites. In addition, a dwindling trend in thermal conductions with increasing temperatures was recorded for all sintered samples. Simulation of experimental results with proven theoretical thermal models showed the dominant role of GNP dispersions, microstructural porosity, elastic modulus and grain size in controlling the thermal transport properties of the GNP/alumina nanocomposites. Thermogravimetric analysis showed that the nanocomposite with up to 0.5 mass% of GNP is thermally stable at the temperatures greater than 875 °C. The GNP/alumina nanocomposites owning a distinctive combination of mechanical and thermal properties are promising contenders for the specific components of the aerospace engine and electronic devices having contact with elevated temperatures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗
NASA NTRS2021

An Investigation of the Grain Size and Adhesion Strength of High-Speed Impact Ice

Ice accumulation on aircraft from supercooled water droplets (impact icing) can increase drag and decrease lift, leading to a decrease in fuel efficiency and a potential for unsafe situations. Anti-icing materials and coatings are of high interest to prevent aircraft icing. Because no anti-icing material suitable for in-flight situations has been realized, icing models aim to predict the accumulation and shape of the ice to understand its effects. In both cases, understanding the physical mechanism behind ice adhesion and shedding is necessary. A recent literature review has shown that the apparent ice adhesion strength to any specific material varies over several orders of magnitude across studies and test methods. One of the reasons for this high variance is likely to be the varying microstructure of the ice used for different studies. Although the microstructure of impact ice has been studied in the past, those conditions were not relevant to that of in-flight aircraft icing. The microstructure of the ice formed will determine both its bulk and surface properties, yet it has been overlooked in the ice adhesion community. Here, we use optical microscopy to study the non-uniform ice crystal grain size in impact ice accreted in NASA Glenn Research Center’s Icing Research Tunnel at various icing conditions. Similar to other environmental conditions studied in the literature, we show an increase in grain size at larger distances from the growth interface; however, the data shows substantially larger grains than what was expected from the prior literature. Ice accrued at lower temperatures has a smaller grain size at all distances from the growth interface. No change in grain size was noticed when varying only the wind speed. A correlational analysis shows that smaller grain sizes at the growth interface corresponded to an increase in the apparent ice adhesion strength when the adhesive failure was interfacial, but not when the failure was cohesive. These results may explain the overall trend in the literature of increasing apparent adhesion strength with decreasing temperature. Incorporating microstructure trends for various environmental conditions in icing models may increase the certainty in predicting ice adhesion strength and shedding, and will provide a better basis for comparison between adhesive tests on ice produced in different facilities and at different storage times.

• Ice Fabric↗
DOE OSTI2023

Modeling shock-induced void collapse in single-crystal Ta systems at the mesoscales

Understanding the role of microstructural heterogeneities on the shock wave propagation and defect evolution behavior is essential to predicting the dynamic response of metals. Heterogeneities, such as voids, provide challenges to understanding the wave propagation behavior as the shock-void interaction can collapse the void and result in large plastic strains and significant heating (hot spot formation) in the metal. Accurate modeling of this phenomenon requires predicting the void collapse mechanisms and the related heat generation and dissipation mechanisms (hotspot formation) that determine the microstructure evolution. While molecular dynamics (MD) simulations can model the void collapse behavior, the time/length scale capabilities pose a challenge to connect with continuum models or the experimental scales. Here, this study presents the capability of the newly developed quasi-coarse-grained dynamics (QCGD) method that extends the MD simulations to larger system sizes and longer times to model this phenomenon. This study uses QCGD simulations to investigate the mechanisms of shock wave interactions with pre-existing voids in single-crystal Ta microstructures for variations in shock pressures, void size, and loading orientations. For a given orientation, the plasticity contributions and rates of void collapse are observed to vary with shock pressures and void size. The larger void sizes and higher pressures result in increased temperatures (hot spots) and faster void collapse rates and unravel the variations in the plasticity contributions. In addition, QCGD simulations investigate the post-collapse microstructure evolution as a release wave travels through the hot spot region. The simulations reveal that the reduction in temperatures due to heat dissipation initiates the dynamic recrystallization behavior in the hotspot regions.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Uncertainty Reduction With Multi-Model Monte Carlo for Crystal Plasticity Simulations of Additively Manufactured Metals

In this work, multi-model Monte Carlo estimators are developed to reduce uncertainty in quantities of interest (QoIs) extracted from crystal plasticity simulations of additively manufactured (AM) metals. A significant concern in AM parts is uncertainty in mechanical properties caused in part by complex microstructures that arise from the AM process. Quantifying uncertainty in microstructure-sensitive behavior using experiments alone is costly, especially when mechanical allowables must be established. Quantitative relationships among microstructure, micromechanical metrics like slip accumulation, crack initiation, and failure are also difficult to capture with limited experiments. Crystal plasticity material models instead enable computational prediction of micromechanical stress and strain fields given a discretized microstructure. However, high-fidelity finely discretized crystal plasticity simulations are computationally expensive, while lower-fidelity models are less accurate and generally biased, making uncertainty quantification and reduction computationally difficult as well. Multi-model Monte Carlo methods leverage correlations between high- and low-fidelity models to produce unbiased estimators for QoIs with reduced uncertainty relative to standard Monte Carlo. Crystal plasticity QoIs considered in this work include yield strength and the mean and extreme values of micromechanical fields that are relevant to crack initiation. Multi-model Monte Carlo estimators are developed for each individual QoI and several groups of QoIs. The results of this work establish relationships among model correlations, sample allocation, and uncertainty reduction for different combinations of QoIs and demonstrate a trend of less uncertainty reduction as QoIs become more sensitive to local microstructure. Limitations from using pilot samples to estimate model covariances and train low-fidelity models are also addressed. The uncertainty reduction achieved by multi-model Monte Carlo is an important step toward using computational mechanics models to predict microstructure-sensitive crack initiation and failure in AM parts.

uncertainty quantification↗
DOE OSTI2025

Mechanistic Fission Gas Release Uncertainty Induced by Microstructure Data

Fission Gas Release (FGR) is an important engineering safety parameter for nuclear fuel. While fuel performance modeling with BISON currently relies on mechanistic models to predict it, comparison with experimental data shows both under or over prediction depending on operation mode (steady or transient).Predicting microstructure data is essential to accurately predicts the engineering scale parameters. An important source of uncertainty in mechanistic models arises from the missing captured physics. Continuous validation and refinement of these models against experimental data are also necessary to ensure their reliability and accuracy in predicting engineering parameters.

36 - MATERIALS SCIENCE↗
DOE OSTI2019

Controlling the extent of atomic ordering in intermetallic alloys through additive manufacturing

Control of the atomic structure, as measured by the extent of the embrittling B2 chemically ordered phase, is demonstrated in intermetallic alloys through additive manufacturing (AM) and characterized using high fidelity neutron diffraction. As a layer-by-layer rapid solidification process, AM was employed to suppress the extent of chemically ordered B2 phases in a soft ferromagnetic Fe-Co alloy, as a model material system of interest to electromagnetic applications. The extent of atomic ordering was found to be insensitive to the spatial location within specimens and insinuates that the thermal conditions within only a few AM layers were most influential in controlling the microstructure, in agreement with the predictions from a thermal model for welding. Analysis of process parameter effects on ordering found that suppression of B2 phase was the result of an increased average cooling rate during processing. AM processing parameters, namely interlayer interval time and build velocity, were used to systematically control the relative fraction of ordered B2 phase in specimens from 0.49 to 0.72. Hardness of AM specimens was more than 150% higher than conventionally processed bulk material. Implications for tailoring microstructures of intermetallic alloys are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Linking process and structure in the friction stir scribe joining of dissimilar materials: A computational approach with experimental support

We present that friction stir welding (FSW) is a popular technique to join dissimilar materials in numerous applications. The solid state nature of the process enables joining materials with strikingly different physical properties. For welds in lap configuration, an enhancement to this technology is made by introducing a short, hard insert, referred to as a cutting-scribe, at the bottom of the tool pin. The cutting-scribe induces deformation in the bottom plate which leads to the formation of mechanical interlocks or hook like structures at the interface of two materials. A thermo-mechanical computational model employing a coupled Eulerian-Lagrangian approach is developed to quantitatively capture the morphology of these interlocks during the FSW process. Simulations using this model are validated by experimental observations. In conclusion, the identified interface morphology coupled with the predicted temperature field from this process–structure model can be used to estimate the post-weld microstructure and joint strength.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Final Report: Improving the understanding of the coupled thermal-mechanical-hydrologic behavior of consolidating granular salt

The goal of this project is to improve the understanding of key aspects of the coupled thermal-mechanical-hydrologic response of granular (or crushed) salt used as a seal material for shafts, drifts, and boreholes in mined repositories in salt. The project is organized into three tasks to accomplish this goal: laboratory measurements of granular salt consolidation (Task 1), microstructural observations on consolidated samples (Task 2), and constitutive model development and evaluation (Task 3). Task 1 involves laboratory measurements of salt consolidation along with thermal properties and permeability measurements conducted under a range of temperatures and stresses expected for potential mined repositories in salt. Testing focused on the role of moisture, temperature and stress state on the hydrologic (permeability) and thermal properties of consolidating granular salt at high fractional densities. Task 2 consists of microstructural observations made on samples after they have been consolidated to interpret deformation mechanisms and evaluate the ability of the constitutive model to predict operative mechanisms under different conditions. Task 3 concerns the development of the coupled thermal-mechanical-hydrologic constitutive model for granular salt consolidation. The measurements and observations in Tasks 1 and 2 were used to develop a thermal-mechanical constitutive model. Accomplishments and status from each of these efforts is reported in subsequent sections of this report

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Deep-freeze graph training for latent learning

Scientific and engineering advances are primarily driven by multi-tier conceptual constructs and conditional theoretical frameworks. The theories allow predictions of hypothetical system responses, given a set of approximate conditions (ranges of applicability) imposed on latent parameters that cannot be measured directly. Learning to estimate the latent variables (Latent Learning) helps to pinpoint the anticipated range-edge anomalies and improves the confidence in interpretation, interpolation and extrapolation of limited experimental data. Due to high dimensionality and extreme non-linearity of the materials science problems, very large datasets are typically required for conventional data-driven model development. The vital experimental data collection, particularly on microstructural phases, is very challenging, which makes it difficult to compile a high-quality database. Incorporation of the domain knowledge into the computational graph structure, initialization and optimization processes presents a viable mechanism for developing accurate models, with limited datasets. Furthermore, this study successfully utilized the approach to build the Deep Freeze Graph (DeepFreG) by mapping known causality relationships and by digitizing empirical domain knowledge for Latent Learning (LL), with specific applications in materials science.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Prebiotic Synthesis of Autocatalytic Products From Formaldehyde-Derived Sugars as the Carbon and Energy Source

Our research objective is to understand and model the chemical processes on the primitive Earth that generated the first autocatalytic molecules and microstructures involved in the origin of life. Our approach involves: (a) investigation of a model origin-of-life process named the Sugar Model that is based on the reaction of formaldehyde- derived sugars (trioses and tetroses) with ammonia, and (b) elucidation of the constraints imposed on the chemistry of the origin of life by the fixed energies and rates of C,H,O-organic reactions under mild aqueous conditions. Recently, we demonstrated that under mild aqueous conditions the Sugar Model process yields autocatalytic products, and generates organic micropherules (2-20 micron dia.) that exhibit budding, size uniformity, and chain formation. We also discovered that the sugar substrates of the Sugar Model are capable of reducing nitrite to ammonia under mild aqueous conditions. In addition studies done in collaboration with Sandra Pizzarrello (Arizona State University) revealed that chiral amino acids (including meteoritic isovaline) catalyze both the synthesis and specific handedness of chiral sugars. Our systematic survey of the energies and rates of reactions of C,H,O-organic substrates under mild aqueous conditions revealed several general principles (rules) that govern the direction and rate of organic reactions. These reactivity principles constrain the structure of chemical pathways used in the origin of life, and in modern and primitive metabolism.

Weber, Arthur L.↗
DOE OSTI2020

Microstructure Experiments-Enabled MARMOT Simulations of SiC/SiC-based Accident Tolerant Nuclear Fuel System

We have undertaken an experimental-computational project that addresses a few key technology gaps associated with the use of SiC/SiC composites for light water reactor fuel cladding. Two principal endeavors in this project are to assess the irradiation-induced microstructural changes and swelling in SiC/SiC composites, and to characterize and model the porous oxide surface layer (when exposed to steam) along SiC recession that is detrimental to the clad integrity under accident conditions. The project tasks are: (i) ion irradiation and characterization (University of Tennessee, Knoxville), (ii) mechanical tests and analysis (University of South Carolina), (iii) steam exposure tests (Oak Ridge National Laboratory), (iv) electron microscopy and spectroscopic characterization (NC State University), (v) x-ray microscopy and reconstruction (University of South Carolina and NC State University), (vi) phase field modeling and simulations (NC State University and Idaho National Laboratory). The effects of 10 MeV Au ion irradiation at 350°C on the microstructure evolution in SiC/SiC composites are investigated at doses up to 400 displacements per atom (dpa) at the University of Tennessee, Knoxville. Atomic force microscopy and optical profilometry reveal irradiation induced axial and radial shrinkage of the fibers for doses greater than 10 dpa. Based on detailed electron microscopy characterization, the primary cause of the fiber shrinkage is attributed to irradiation-induced loss of carbon packets. Additionally, the multilayer PyC interface is observed to portray high resistance to irradiation damage. The mechanical response and failure mechanisms of un-irradiated samples is also assessed through loading tests and X-ray imaging at the University of South Carolina. Steam exposure tests are performed at the Oak Ridge National Laboratory in a facility that represents a reactor pressure vessel under a loss-of-coolant-accident scenario. The samples that are analyzed methodically in this report are tested for 32/31 hours at 1200°C with a velocity of 0.25 cm/s for the pressures: 0.1 MPa, 0.45 MPa, 0.92 MPa and 1.38 MPa. Scanning/transmission electron microscopy analysis conducted at the NC State University (NCSU) shows that the oxide layer thickness increases with the steam pressure. While the oxide layer is crystalline (α- cristobalite) for the pressures 0.45 MPa, 0.92 MPa and 1.38 MPa, the layer is amorphous at 0.1 MPa. Results from Raman spectroscopy have also confirmed the formation of α-cristobalite phase of SiO₂. The abrupt increase in the integrated Raman intensity ratio between steam pressures 0.1 and 0.45 MPa suggests the onset of accelerated crystallization. Non-destructive three dimensional X-ray microscopy/tomography (XCT) and computational image processing techniques are employed by the University of South Carolina to probe the porous oxidation features on SiC samples at varying pressures. Interestingly, most pores are observed to be located away from the surface as well as the oxide-SiC interface. The average oxide layer thickness assessed from the XCT analysis is seen to be in excellent agreement with the values determined through scanning electron microscopy analysis for the highest pressures where the oxide layer is relatively more uniform. A phase-field model developed by the NC State University and Idaho National Laboratory for simulating oxidation of SiC by steam captures the paralinear kinetics of SiC oxidation with a high degree of fidelity. Results from quasi-one-dimensional and two dimensional simulations show that the pores with oxidizing species lead to a higher volatilization rate. These simulations indicate that the enhanced apparent volatilization rates at higher pressures observed in experiments can be rationalized by the increased volatilization from the pores. The project team has also successfully developed the capability to import images from experiments for realistic evolution of the oxidizing microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Iridescence from Total Internal Reflection at 3D Microscale Interfaces: Mechanistic Insights and Spectral Analysis

An experimental investigation and the optical modeling of the structural coloration produced from total internal reflection interference within 3D microstructures are described. Ray-tracing simulations coupled with color visualization and spectral analysis techniques are used to model, examine, and rationalize the iridescence generated for a range of microgeometries, including hemicylinders and truncated hemispheres, under varying illumination conditions. An approach to deconstruct the observed iridescence and complex far-field spectral features into its elementary components and systematically link them to ray trajectories that emanate from the illuminated microstructures is demonstrated. The results are compared with experiments, wherein microstructures are fabricated with methods such as chemical etching, multiphoton lithography, and grayscale lithography. Microstructure arrays patterned on surfaces with varying orientation and size lead to unique color-traveling optical effects and highlight opportunities for how total internal reflection interference can be used to create customizable reflective iridescence. The findings herein provide a robust conceptual framework for rationalizing this multibounce interference mechanism and establish approaches for characterizing and tailoring the optical and iridescent properties of microstructured surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chromium Poisoning ERMINE Model Data

This is the data from the paper "Systematic and Predictive Trends to Chromium Poisoning in Solid Oxide Fuel Cell Cathodes" by Hokon Kim et al., appearing in the Journal of Power Sources. The files here are the microstructures, mesh files, and outputs from the ERMINE finite element model of chromium poisoning in SOFC cathodes. Further description can be found in Readme.rtf and in the paper..

Chromium,SOFC↗
DOE OSTI2026

Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor.

25 ENERGY STORAGE↗
DOE OSTI2017

Reprint of: Microstructural evolution of neutron irradiated 3C-SiC

The microstructural response of neutron irradiated 3C-SiC have been investigated over a wide irradiation temperature and fluence range via qualitative and quantitative synchrotron-based X-ray diffraction characterization. Additionally, we identify several neutron fluence- and irradiation temperature-dependent changes in the microstructure, and directly highlight the specific defects introduced through the course of irradiation. By quantifying the microstructure, we aim to develop a more detailed understanding of the radiation response of SiC. Such studies are important to build mechanistic models of material performance and to understand the susceptibility of various microstructures to radiation damage for advanced energy applications.

36 MATERIALS SCIENCE↗