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Results for “microstructure property relationships”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Microstructure-Property Relationships in Epitaxial Cu(In, Ga)Se2 Solar-Cell Absorbers

Epitaxially grown Cu(In,Ga)Se 2 (CIGS) absorber layers were analyzed by various techniques in scanning electron microscopy in order to reveal microstructure-property relationships in these thin films. Owing to their epitaxial nature, these CIGS absorber layers do not contain any grain boundaries, but only anti-phase domains (APDs) and dislocations. By combining electron channeling-contrast imaging, electron backscatter diffraction, and cathodoluminescence (CL), in some cases on identical specimen positions of polished cross-sections of CIGS/Mo/glass stacks, it was possible to correlate the presence and orientations of APDs and dislocations with the lateral distributions of the CL intensity and emission-peak energy. We studied CIGS layers with three different [Ga]/([Ga]+[In]) ratios as well as with and without NaF/KF treatments. Considerable differences between the CIGS layer properties in the microstructure-property relationships were found, depending on the growth parameters. Dislocations in the epitaxial CIGS layers do not tend to exhibit strong CL intensity decreases, which contrasts with the situation in numerous other semiconductor materials.

anti-phase domains↗
DOE OSTI2024

High-throughput, Ultra-fast Laser Sintering of Ceramics and AI Based Prediction on Processing-Microstructure-Property Relationships

We report high-throughput, ultra-fast laser sintering of alumina sample array and characterization of sample units’ microstructure and hardness, as a fast exploration of laser processing parameters, microstructure, and property. These experimental data were used to train machine-learning (ML) models. Accurate ML predictions were demonstrated for the processing-microstructure-property relationship, specifically in (1) prediction of the microstructure of alumina under arbitrary laser power and (2) prediction of the expected microstructure from the desired hardness. An independent neural network was developed and showed that ML-predicted microstructure had less than 10% error from real ones, in terms of projected hardness. To monitor the microstructure during laser sintering, we demonstrated an ML model that can instantaneously predict ceramic’s microstructure at the laser spot, based on the laser spot brightness. The ML model can generate more than 10 predictions per second, and the error in average grain size was less than 5% from the experimental observations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding process-microstructure-property relationships in laser powder bed fusion of non-spherical Ti-6Al-4V powder

Powder feedstock is a major cost driver in metal additive manufacturing (AM). Replacing the spherical powder with the cost-efficient non-spherical one can reduce the feedstock cost up to 50% and attract more interest to adopt AM in production and new alloy development. Here, for this paper, a comprehensive study was conducted to understand process-microstructure-property relationships in laser powder bed fusion of hydride-dehydride Ti-6Al-4V powder. We demonstrated that variation of laser scan speed had a significant impact on the grain structure, pore evolution and properties compared to laser power. Dynamic X-ray radiography showed that with decreasing scan speed at a constant laser power, a transition from conduction to keyhole mode laser processing occurred, in which a deeper melt pool at lower scan speed intensified texture. In other words, an increase in laser scan speed resulted in formation of the refined prior β grains with shape factor of ~5, lowering the anisotropy. Furthermore, the degree of variant selection was evaluated based on the analyzed texture as a function of laser power and scan speed. With increasing laser scan speed, the dominant α/α boundary type was altered from type 2 to 4 and the degree of variant selection was noticeably decreased. On the other hand, increasing laser power left the morphology of prior β grains, their size, and the dominant α/α boundary (type 4) unchanged, while the texture and anisotropy were intensified, and the degree of variant selection was slightly decreased. Finally, dependency of surface roughness and microhardness were discussed as a function of laser processing parameters.

variant selection↗
NASA NTRS1986

Microstructure-property relationships in directionally solidified single crystal nickel-base superalloys

Some of the microstructural features which influence the creep properties of directionally solidified and single crystal nickel-base superalloys are discussed. Gamma precipitate size and morphology, gamma-gamma lattice mismatch, phase instability, alloy composition, and processing variations are among the factors considered. Recent experimental results are reviewed and related to the operative deformation mechanisms and to the corresponding mechanical properties. Special emphasis is placed on the creep behavior of single crystal superalloys at high temperatures, where directional gamma coarsening is prominent, and at lower temperatures, where gamma coarsening rates are significantly reduced. It can be seen that very subtle changes in microstructural features can have profound effects on the subsequent properties of these materials.

Mackay, R. A.↗
NASA NTRS1991

Microstructure-property relationships in Al-Cu-Li-Ag-Mg Weldalite (tm) alloys, part 2

The microstructure and mechanical properties of the ultrahigh strength Al-Cu-Li-Ag-Mg alloy, Weldalite (tm) 049, were studied. Specifically, the microstructural features along with tensile strength, weldability, Young's modulus and fracture toughness were studied for Weldalite (tm) 049 type alloys with Li contents ranging from 1.3 to 1.9 wt. pct. The tensile properties of Weldalite 049 and Weldalite 049 reinforced with TiB2 particles fabricated using the XD (tm) process were also evaluated at cryogenic, room, and elevated temperatures. In addition, an experimental alloy, similar in composition to Weldalite 049 but without the Ag+Mg, was fabricated. The microstructure of this alloy was compared with that of Weldalite 049 in the T6 condition to assess the effect of Ag+Mg on nucleation of strengthening phases in the absence of cold work.

Langan, T. J.↗
DOE OSTI2025

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗
NASA NTRS1988

Microstructure-property relationships in directionally solidified single-crystal nickel-base superalloys

This paper discusses some of the microstructural features which influence the creep properties of directionally solidified and single-crystal nickel-base superalloys. Gamma prime precipitate size and morphology, gamma-gamma (prime) lattice mismatch, phase instability, alloy composition, and processing variations are among the factors considered. Recent experimental results are reviewed and related to the operative deformation mechanisms and to the corresponding mechanical properties. Special emphasis is placed on the creep behavior of single-crystal superalloys at high temperatures, where directional gamma (prime) coarsening is prominent, and at lower temperatures, where gamma (prime) coarsening rates are significantly reduced. It can be seen that very subtle changes in microstructural features can have profound effects on the subsequent properties of these materials.

Mackay, Rebecca A.↗
DOE OSTI2022

Exploring the Microstructure-Property Relationship of Mg-Al-Mn alloys enhanced via Friction Stir Processing

Friction Stir Processing (FSP) is a solid-state thermomechanical processing technique that enables local grain refinement, densification, and homogenization of microstructure in metallic components. Here, FSP is applied to thin sheets of high-pressure die cast AM60 to address the porosity and heterogeneities inherent to the casting process. In this work, microstructure characterization is correlated to improvements in the static mechanical properties of the Mg-Al-Mn alloy system at various FSP processing conditions. Notably, there is a significant increase in the ductility and ultimate tensile stress of system following FSP. The dominant deformation mechanisms for the as-cast material and the FSP material are investigated. Finally, the fatigue life improvement is correlated to microstructure modifications that may lead to distinct behavior in crack initiation and crack propagation for the as-cast and FSP material.

Garcia, David↗
DOE OSTI2021

Quantitative Characterization of the Microstructure-Property Relationships in Ni and MIEC Nanocatalyst-Infiltrated Ni/YSZ Anodes

The performance of solid oxide fuel cell (SOFC) anodes can be improved by infiltration of nanoscale electrocatalysts, which increases triple phase boundary (TPB) density, but only when the added TPBs are active. Quantitative characterization of the microstructure of infiltrated nanocatalysts remains a critical challenge in understanding their role in improved performance. This paper explores the relationship between electrochemical performance and microstructure for Ni/YSZ anodes infiltrated with Ni, gadolinium-doped-ceria (GDC), and Ni/GDC nanocatalysts using a combination of electrochemical impedance spectroscopy (EIS), distribution of relaxation times (DRT) analysis, scanning electron microscopy (SEM) microstructural characterization, and three-dimensional (3-D) anode reconstruction. Estimated polarization resistance improvements as a result of nickel nanoparticle infiltration are discussed.

Rix, Jillian↗
DOE OSTI2025

Process-Microstructure-Property Relationships in Low Heat Input Wire-Arc Additive Manufacturing (WAAM) of Ni-Based Superalloy Haynes 282

Conference presentation on WAAM process optimization on Ni-based superalloy Haynes® 282®. This alloy is targeted for advanced power generation systems for its superior high temperature mechanical properties. Wire-arc additive manufacturing (WAAM) offers attractive cost and materials savings with high deposition rates. Based on initial build process optimization, WAAM blocks were made, and screened for defects using high-throughput CT scanning. The microstructural evolution in arc energy range of 250-700 J/mm was characterized in the as-built and aged conditions, using electron microscopy. Results showed self-consistent microstructure across conditions, with grain size dependence on arc energy, MC and M6C carbides in as-built, and blocky grain boundary M23C6 in as-heat-treated condition. Further reductions in as-built porosity were explored through 20+ combinations of H2 and CO2 additions to shielding gas. Initial results show improved wetting behavior, and bead overlap with up to 1% H2 and up to 0.25% CO2. Combination of experimentally determined datasets provided comprehensive understanding of process-structure-property relationships in WAAM Haynes 282.

Haynes 282↗
NASA NTRS2016

Joining and Integration of Silicon Carbide-Based Materials for High Temperature Applications

Advanced joining and integration technologies of silicon carbide-based ceramics and ceramic matrix composites are enabling for their implementation into wide scale aerospace and ground-based applications. The robust joining and integration technologies allow for large and complex shapes to be fabricated and integrated with the larger system. Potential aerospace applications include lean-direct fuel injectors, thermal actuators, turbine vanes, blades, shrouds, combustor liners and other hot section components. Ground based applications include components for energy and environmental systems. Performance requirements and processing challenges are identified for the successful implementation different joining technologies. An overview will be provided of several joining approaches which have been developed for high temperature applications. In addition, various characterization approaches were pursued to provide an understanding of the processing-microstructure-property relationships. Microstructural analysis of the joint interfaces was conducted using optical, scanning electron, and transmission electron microscopy to identify phases and evaluate the bond quality. Mechanical testing results will be presented along with the need for new standardized test methods. The critical need for tailoring interlayer compositions for optimum joint properties will also be highlighted.

Ceramic Matrix Composites↗
DOE OSTI2026

Machine learning insights into microstructural origins of transport and mechanical properties in porous microstructures

Multifunctional porous materials are increasingly needed across various fields, but their complex microstructures create significant challenges due to the intricate microstructure-property relationships. This complexity, combined with limitations of traditional analysis methods, hinders efforts to understand and optimize microstructure–property relationships. Here, to address this, we integrate physics-based mesoscale modeling with interpretable machine learning (ML) to uncover how microstructural features govern effective diffusivity and elastic modulus. At constant porosity, we show diffusivity varies by over 150 × and modulus by ∼50 ×, highlighting the power of microstructure engineering. Statistical analysis reveals bimodal behavior in diffusivity and unimodal in modulus. ML identifies connectivity as the dominant factor, while modulus is also sensitive to domain size and feature interactions. Controlled simulations further highlight domain shape as a critical feature for modulus. This framework enables efficient exploration of microstructure-property correlations, offering new insights to guide the design of advanced porous materials.

Bicontinuous microstructure↗