SEARCH · Search NASA

Results for “microstructure design”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Atom Probe Tomography Investigation of Clustering in Model P 2 O 5 -Doped Borosilicate Glasses for Nuclear Waste Vitrification

Atom probe tomography (APT) has been utilized to investigate the microstructure of two model borosilicate glasses designed to understand the solubility limits of phosphorous pentoxide (P 2 O 5 ). This component is found in certain high-level radioactive defence wastes destined for vitrification, where phase separation can potentially lead to a number of issues relating to the processing of the glass and its long-term chemical and structural stability. The development of suitable focused ion beam (FIB)-preparation routes and APT analysis conditions were initially determined for the model glasses, before examining their detailed microstructures. In a 3.0 mol% P 2 O 5 -doped glass, both visual inspection and sensitive statistical analysis of the APT data show homogeneous microstructures, while raising the content to 4.0 mol% initiates the formation of phosphorus-enriched nanoscale precipitates. This study confirms the expected inhomogeneities and phase separation of these glasses and offers routes to characterizing these at near-atomic scale resolution using APT.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Modeling microstructural evolution in irradiated materials with cluster dynamics methods: A review

As both the design of material systems for nuclear energy applications and the number of reactor designs being proposed increase the need for material models predicting the evolution of microstructures as a function of chemistry, texture, grain size, precipitate content, etc., and irradiation conditions is steadily increasing. Here, this manuscript aims at presenting a review of the different cluster dynamics modeling schemes that have emerged worldwide over the past decade(s). Additionally, the manuscript also critically discusses limitations in existing approaches and identifies potential routes for future developments.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Hydrogen charging and desorption from microstructural viewpoint: A method for deconvoluting hydrogen desorption spectra and unveiling the hydrogen-microstructure interaction

Understanding the interaction of hydrogen with microstructural features in metallic materials is crucial for designing hydrogen-resistant alloys. Although thermal desorption spectroscopy (TDS) is widely used for investigating the hydrogen binding behavior of various microstructural features, its application to face-centered cubic (fcc) metals and alloys that exhibit low hydrogen diffusivity is limited due to the lumped TDS desorption signals. This paper shows that, by coupling a Sofronis–McMeeking type hydrogen transport model with a microstructure-informed finite-element model, TDS data can be deconvoluted to reveal the underlying adsorption–diffusion–desorption processes, hydrogen diffusivity, and trap-binding energies. In conclusion, the austenitic steel SS316L in solution-annealed condition is used as a demonstration material, and we focused on investigating the interaction of deuterium (hydrogen isotope) with grain boundaries, which is difficult to investigate from experiments alone but critical for design of alloys for hydrogen infrastructure.

Finite element simulation, Polycrystalline Microst↗

DOE OSTI2019

Creation of nanoscale magnetic fields using nano-magnet arrays

In this paper, we present the fabrication of nano-magnet arrays, comprised of two sets of interleaving SmCo 5 and Co nano-magnets, and the subsequent development and implementation of a protocol to program the array to create a one-dimensional rotating magnetic field. We designed the array based on the microstructural and magnetic properties of SmCo 5 films annealed under different conditions, also presented here. Leveraging the extremely high contrast in coercivity between SmCo 5 and Co, we applied a sequence of external magnetic fields to program the nano-magnet arrays into a configuration with alternating polarization, which based on simulations creates a rotating magnetic field in the vicinity of nano-magnets. Our proof-of-concept demonstration shows that complex, nanoscale magnetic fields can be synthesized through coercivity contrast of constituent magnetic materials and carefully designed sequences of programming magnetic fields.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Report on Properties and Microstructure of 3D Printed Inc-718

The report presents the microstructure and mechanical properties of 3D printed Inconel 718 to assess its potential use as a structural material for the Transformation Challenge Reactor (TCR). The structural components near the outlet of the core will experience significant neutron fluxes and outlet coolant temperatures from the hot standby temperature of 300°C to nearly 550°C at the center of the part. These components must support the core in appropriate loading conditions and require structural analysis at relevant temperatures. Strong spatial and chemical heterogeneity was found in as-built (ASB) Inconel 718. Three heat treatments were designed and conducted to simplify the microstructure and determine how each precipitating phase contributed to the overall strength. Baseline mechanical properties were measured from uniaxial tensile tests on subsize SS-J2 specimens at room temperature and at elevated temperatures of 300, 450, and 600°C. Microstructure electron microscopy was performed on ASB Inconel 718 and heat treated to correlate the observed mechanical properties with nanoscale features. Homogenization of the microstructure led to a highly ductile Inconel with lower strength compared with wrought Inconel 718. The tensile properties of additively manufactured 718 using a standard ASTMrecommended heat treatment were consistent with literature and with the ASTM for the properties of this alloy. A higher fraction of the δ phase led to shorter uniform elongation without altering other engineering properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Report on Evolution of Inconel 718 Following HFIR Irradiation

The report presents the microstructure and mechanical properties of 3D printed Inconel 718 after irradiation in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) to assess its potential use as a structural material. The structural components near the outlets of several proposed reactor cores will experience significant neutron fluxes and outlet coolant temperatures ranging from the hot standby temperature of 300 °C to nearly 550 °C at the center of the part. These components must support the core in appropriate loading conditions and require structural analysis at relevant temperatures. In FY21, three heat treatments were designed and conducted to simplify the microstructure and to determine how each precipitating phase contributed to the overall strength. In FY21, baseline mechanical properties were measured from uniaxial tensile tests on subsize SS-J2 specimens at room temperature and at elevated temperatures of 300, 450, and 600 °C to serve a comparison to the irradiated properties. Four capsules containing 3D printed Inconel 718 were inserted into HFIR in FY21 for a matrix of two temperatures and two doses. The lower of the two doses was available for characterization in FY22. Multiple heat treatments of Inconel 718 irradiated to nominal conditions of 2 displacements per atom (dpa) at either 300 or 600 °C were strained with uniaxial tensile tests at the Irradiated Material Examination and Testing (IMET) Facility to discern the mechanical properties. Transmission electron microscopy was performed to correlate the observed mechanical properties with nanoscale features. The initially homogenous AM718-HM increased in strength at both irradiation temperatures based on a high density of nanometer-scale radiation-induced cavities at lower temperature and nucleation and growth of γ" precipitates at higher temperatures. The precipitate-hardened AM718-HT2 showed very small differences in strength before and after irradiation: the contribution to strength from γ" precipitates was replaced with dislocation loops. Because the radioactivity of the nickel superalloys from neutron activation limited the scope of the analysis, a feasibility study examined the possibility of an ultra-miniature specimen geometry, colloquially SS-Tiny (SS-T), for mechanical property determination using the nonirradiated Inconel 718. This study found an overestimation of ductility from the SS-T geometry with yield strength and ultimate tensile strength slightly above the SS-J2 geometry: this could be contributed to a reduction in specimen thickness.

36 MATERIALS SCIENCE↗

NASA NTRS1994

Integrated design of structures, controls, and materials

In this talk we shall discuss algorithms and CAD tools for the design and analysis of structures for high performance applications using advanced composite materials. An extensive mathematical theory for optimal structural (e.g., shape) design was developed over the past thirty years. Aspects of this theory have been used in the design of components for hypersonic vehicles and thermal diffusion systems based on homogeneous materials. Enhancement of the design methods to include optimization of the microstructure of the component is a significant innovation which can lead to major enhancements in component performance. Our work is focused on the adaptation of existing theories of optimal structural design (e.g., optimal shape design) to treat the design of structures using advanced composite materials (e.g., fiber reinforced, resin matrix materials). In this talk we shall discuss models and algorithms for the design of simple structures from composite materials, focussing on a problem in thermal management. We shall also discuss methods for the integration of active structural controls into the design process.

Blankenship, G. L.↗

NASA NTRS2010

A New Approach of Designing Superalloys for Low Density

New low-density single-crystal (LDS) alloy, have bee. developed for turbine blade applications, which have the potential for significant improvements in the thrust-to-weight ratio over current production superalloys. An innovative alloying strategy was wed to achieve alloy density reductions, high-temperature creep resistance, microstructural stability, and cyclic oxidation resistance. The alloy design relies on molybdenum as a potent. lower-density solid-solution strengthener in the nickel-based superalloy. Low alloy density was also achieved with modest rhenium levels tmd the absence of tungsten. Microstructural, physical mechanical, and environmental testing demonstrated the feasibility of this new LDS superalloy design.

MacKay, Rebecca A.↗

NASA NTRS2008

Microstructure Modeling of 3rd Generation Disk Alloy

The objective of this initiative, funded by NASA's Aviation Safety Program, is to model, validate, and predict, with high fidelity, the microstructural evolution of third-generation high-refractory Ni-based disc superalloys during heat treating and service conditions. This initiative is a natural extension of the DARPA-AIM (Accelerated Insertion of Materials) initiative with GE/Pratt-Whitney and with other process simulation tools. Strong collaboration with the NASA Glenn Research Center (GRC) is a key component of this initiative and the focus of this program is on industrially relevant disk alloys and heat treatment processes identified by GRC. Employing QuesTek s Computational Materials Dynamics technology and PrecipiCalc precipitation simulator, physics-based models are being used to achieve high predictive accuracy and precision. Combining these models with experimental data and probabilistic analysis, "virtual alloy design" can be performed. The predicted microstructures can be optimized to promote desirable features and concurrently eliminate nondesirable phases that can limit the reliability and durability of the alloys. The well-calibrated and well-integrated software tools that are being applied under the proposed program will help gas turbine disk alloy manufacturers, processing facilities, and NASA, to efficiently and effectively improve the performance of current and future disk materials.

Jou, Herng-Jeng↗

DOE OSTI2025

Metal additive manufacturing simulation across length, time, and computing scales

Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. Here, these problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges.

additive manufacturing↗

DOE OSTI2016

Microstructure and mechanical properties of a novel rapidly solidified, high-temperature Al-alloy

Rapid solidification (RS) processing, as a production method, offers a variety of unique properties based on far-from-equilibrium microstructures obtained through rapid cooling rates. In this study, we seek to investigate the microstructures and properties of a novel Al-alloy specifically designed for high temperature mechanical stability. Synthesis of, AlFe{sub 11.4}Si{sub 1.8}V{sub 1.6}Mn{sub 0.9} (wt.%), was performed by two approaches: rotating cup atomization (“shot”) and melt spinning (“flake”). These methods were chosen because of their ability to produce alloys with tailored microstructures due to their inherent differences in cooling rate. The as-solidified precursor materials were microstructurally characterized with electron microscopy. The results show that the higher cooling rate flake material exhibited the formation of nanocrystalline regions as well additional phase morphologies not seen in the shot material. Secondary dendritic branching in the flake material was on the order of 0.1–0.25 μm whereas branching in the shot material was 0.5–1.0 μm. Consolidated and extruded material from both precursor materials was mechanically evaluated at both ambient and high (300 °C) temperature. The consolidated RS flake material is shown to exhibit higher strengths than the shot material. The ultimate tensile strength of the melt spun flake was reported as 544.2 MPa at room temperature and 298.0 MPa at 300 °C. These results forecast the ability to design alloys and processing approaches with unique non-equilibrium microstructures with robust mechanical properties at elevated temperatures. - Highlights: • A novel alloy, AlFe{sub 11.4}Si{sub 1.8}V{sub 1.6}Mn{sub 0.9} was fabricated by rapid solidification. • Room temperature yield strength exceeded 500 MPa. • Elevated temperature (300 °C) yield strength exceeded 275 MPa. • Forging, after extrusion of the alloy resulted in microstructural coarsening. • Decreased strength and ductility was identified as a result of forging.

36 MATERIALS SCIENCE↗

DOE OSTI2021

The role of Si in determining the stability of the θ; precipitate in Al-Cu-Mn-Zr alloys

Precipitate-strengthened Al-Cu-Mn-Zr (ACMZ) alloys demonstrate improved microstructural stability compared to conventional Al-Cu alloys. Si is typically considered an impurity in these alloys, but a systematic analysis of ACMZ alloys with a range of Si levels revealed that there is a Si content range (~0.05 wt. % < Si < ~0.10 wt. %) for achieving optimal high temperature microstructural stability. A combination of hardness testing, scanning electron microscopy, and atom probe tomography has been used to understand the relationship between Si content, aging response, and thermal stability in ACMZ alloys. It is shown that the optimum Si content range corresponds to a reduced as-aged hardness, but a greater hardness value retained by the alloy after thermal exposure to 350 °C for 200 hours. A mechanism is proposed in which optimum Si levels reduce the number density of nucleation sites for θ' precipitates, resulting in larger precipitates that, on average, provide a reduced as-aged strength but are more coarsening resistant. This inherent θ' coarsening resistance allows more time for slow-diffusing Mn and Zr to reach the θ' interface and further stabilize the precipitates. Designing the optimal as-aged microstructure for improved thermal stability of the alloy by controlling impurity levels is a concept that has implications beyond the investigated Al-Cu alloy system.

36 MATERIALS SCIENCE↗

DOE OSTI2024

De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity

Relating the macroscopic properties of protein-based materials to their underlying component microstructure is an outstanding challenge. Here, we exploit computational design to specify the size, flexibility, and valency of de novo protein building blocks, as well as the interaction dynamics between them, to investigate how molecular parameters govern the macroscopic viscoelasticity of the resultant protein hydrogels. We construct gel systems from pairs of symmetric protein homo-oligomers, each comprising 2, 5, 24, or 120 individual protein components, that are crosslinked either physically or covalently into idealized step-growth biopolymer networks. Through rheological assessment, we find that the covalent linkage of multifunctional precursors yields hydrogels whose viscoelasticity depends on the crosslink length between the constituent building blocks. In contrast, reversibly crosslinking the homo-oligomeric components with a computationally designed heterodimer results in viscoelastic biomaterials exhibiting fluid-like properties under rest and low shear, but solid-like behavior at higher frequencies. Exploiting the unique genetic encodability of these materials, we demonstrate the assembly of protein networks within living mammalian cells and show via fluorescence recovery after photobleaching (FRAP) that mechanical properties can be tuned intracellularly in a manner similar to formulations formed extracellularly. We anticipate that the ability to modularly construct and systematically program the viscoelastic properties of designer protein-based materials could have broad utility in biomedicine, with applications in tissue engineering, therapeutic delivery, and synthetic biology.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Microstructure-Based Estimation of Strength and Ductility Distributions for \(\alpha +\beta \) Titanium Alloys

Titanium alloys are processed to develop a wide range of microstructure configurations and therefore material properties. While these properties are typically measured experimentally, a framework for property prediction could greatly enhance alloy design and manufacturing. In this work, a microstructure-sensitive framework is presented for the prediction of strength and ductility as well as estimates of the bounds in variability for these properties. The framework explicitly considers distributions of microstructure via new approaches for instantiation of structure in synthetic samples. The parametric evaluation strategy, including the finite element simulation package FEpX, is used to create and test virtual polycrystalline samples to evaluate the variability bounds of mechanical properties in Ti-6Al-4V. Critical parameters for the property evaluation framework are provided by measurements of single crystal properties and advanced characterization of microstructure and slip system strengths in 2D and 3D. Property distributions for yield strength and ductility are presented, along with the validation and verification steps undertaken. Comparisons between strain localization and slip activity in virtual samples and in experimental grain-scale strain measurements are also discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2020

3D Characterization of the Columnar-to-Equiaxed Transition in Additively Manufactured Inconel 718

Additive manufacturing (AM) provides enormous processing flexibility, enabling novel part geometries and optimized designs. Access to a local heat source further permits the potential for local microstructure control on the scale of individual melt pools, which can enable local control of part properties. In order to design tailored processing strategies for target microstructures, models predicting the columnar-to-equiaxed transition must be extended to the high solidification velocities and complex thermal histories present in AM. Here, we combine 3D characterization with advanced modeling techniques to develop a more complete understanding of the solidification process and evolution of microstructure during electron beam melting (EBM) of Inconel 718. Full calibration of existing microstructure prediction models demonstrates the differences between AM processes and more conventional welding techniques, underlying the need for accurate determination of key parameters that can only be measured directly in 3D. The ability to combine multisensor data in a consistent 3D framework via data fusion algorithms is essential to fully leverage these advanced characterization approaches. Thermal modeling provides insight on microstructure development within isolated solidification events and demonstrates the role of Marangoni effects on controlling solidification behavior.

Polonsky, Andrew↗

NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗

NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators Using Micro and Macro-Scale Modeling

Thermal Protection Systems↗

DOE OSTI2025

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗