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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

TAOI B- Computational Microstructural Optimization Design Tool for High Temperature Structural Materials

The objectives of this research were two-fold: (a) develop a methodology for microstructural optimization of alloys - genetic algorithm approach for alloy microstructural optimization using theoretical models based on fundamental micro-mechanisms, and (b) develop a new computationally designed Ni-Cr alloy for coal-fired power plant applications. The broader outcome of these objectives is expected to be creation of an integrated approach for ‘structural materials by microstructural design’. Three alloy systems were considered for computational optimization and validation, (i) Ni-20Cr (wt.%) base alloy using only solid solution strengthening, (ii) nano-Y 2 O 3 containing Ni-20Cr-1.2Y 2 O 3 (wt.%) alloy for dispersion strengthening and (iii) a sub-micron Al 2 O 3 for composite strengthening, Ni-20Cr-1.2Y 2 O 3 -5.0Al 2 O 3 (wt.%). The specimens were synthesized by mechanical alloying and consolidated using spark plasma sintering. Detailed microstructural characterization was done along with initial mechanical properties to validate the computational prediction. A key target property is to have creep rate of 1x10 -9 s -1 at 100 MPa and 800°C. The initial results were quite promising and require additional quantification of strengthening contributions from dislocation-particle attractive interaction and load transfer. The observed creep rate was in order of 10 -9 s -1 for longer time creep test of Ni-20Cr -1.2Y 2 O 3 -5Al 2 O 3 , lending support to the overall approach pursued in this project.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Li-ion battery design through microstructural optimization using generative AI

Lithium-ion batteries are used across various applications, necessitating tailored cell designs to enhance performance. Optimizing electrode manufacturing parameters is a key route to achieving this, as these parameters directly influence the microstructure and performance of the cells. However, linking process parameters to performance is complex, and experimental or modeling campaigns are often slow and expensive. This study introduces a fast computational optimization framework for electrode manufacturing parameters. A generative model, trained on a small dataset of microstructural images associated with different manufacturing parameters, efficiently generates representative microstructures for new parameters. This model is integrated into a Bayesian optimization loop that includes microstructure generation, characterization, and simulation, aiming to find optimal manufacturing parameters for a particular application. Significant improvement in the energy density of a 4680 cell is achieved through bespoke cell design, highlighting the importance of cell-scale normalization. The framework’s modularity allows its application to various advanced materials manufacturing scenarios.

batteries↗
NASA NTRS1976

Creep resistance

High-temperature structural applications usually require creep resistance because some average stress is maintained for prolonged periods. Alloy and microstructural design guidelines for creep resistance are presented through established knowledge on creep behavior and its functional dependences on alloy microstructure. Important considerations related to creep resistance of alloys as well as those that are harmful to high-temperature properties are examined. Although most of the creep models do not predict observed creep behavior quantitatively, they are sophisticated enough to provide alloy or microstructural design guidelines. It is shown that creep-resistant microstructures are usually in conflict with microstructures that improve such other properties as stress rupture ductility. Greater understanding of the effects of environments on creep and stress rupture behavior of materials is necessary before one can optimally design alloys for applications in different environments.

Tien, J. K.↗
DOE OSTI2023

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗
DOE OSTI2014

Concepts for the development of nanoscale stable precipitation-strengthened steels manufactured by conventional methods

In this study, the development of oxide dispersion strengthened ferrous alloys has shown that microstructures designed for excellent irradiation resistance and thermal stability ideally contain stable nanoscale precipitates and dislocation sinks. Based upon this understanding, the microstructures of conventionally manufactured ferritic and ferritic-martensitic steels can be designed to include controlled volume fractions of fine, stable precipitates and dislocation sinks via specific alloying and processing paths. The concepts proposed here are categorized as advanced high-Cr ferritic-martensitic (AHCr-FM) and novel tailored precipitate ferritic (TPF) steels, which have the potential to improve the in-reactor performance of conventionally manufactured alloys. AHCr-FM steels have modified alloy content relative to current reactor materials (such as alloy NF616/P92) to maximize desirable precipitates and control phase stability. TPF steels are designed to incorporate nickel aluminides, in addition to microalloy carbides, in a ferritic matrix to produce fine precipitate arrays with good thermal stability. Both alloying concepts may also benefit from thermomechanical processing to establish dislocation sinks and modify phase transformation behaviors. Alloying and processing paths toward designed microstructures are discussed for both AHCr-FM and TPF material classes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effect of microstructure on fatigue crack propagation in additive manufactured nickel-based superalloy Haynes 282: an experiment and crystal plasticity study

Haynes 282 is a γ' precipitation-strengthened nickel-based superalloy known for its exceptional high-temperature creep resistance and excellent fabricability. Recent advancements in powder-bed fusion-based additive manufacturing (PBF-AM) have enabled the fabrication of Haynes 282 with accurate, site-specific control of the grain orientation and morphology at the microscale. This ability opens up new avenues for microstructure design, to improve the material’s fatigue crack resistance and service life. This paper investigates the fatigue crack growth behavior of hybrid microstructure Haynes 282 fabricated via PBF-AM. Previous experiments revealed a higher crack propagation rate in the coarse columnar-grained microstructural regions when compared against fine-grained areas. Here, a strain gradient crystal plasticity model was adapted to study the fracture-related mechanical fields at the crack tip in the two microstructures. The simulation results showed a consistent influence of grain structure and texture on crack propagation, as was seen in the experiment. The model analysis revealed higher crack propagation driving force along crack direction in the coarse-grained sharply textured microstructure and higher driving force for crack kinking in fine-grained more diffusely textured microstructure, which is ascribed to the combined effect of yield stress, hardening rate, texture and grain morphology. The presented modeling approach will facilitate the development of the AM-based accurate microstructure design by deepening the fundamental study in AM-specific microstructure-properties relations.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Toughening of Boron Carbide Composites by Hierarchical Microstructuring

Due to a unique combination of properties including high hardness, low density, chemical and thermal stability, semi-conductivity, and high neutron absorption, boron carbide (B4C) is a potential candidate for various applications involving extreme environment. However, B4C’s current application is limited because of its low fracture toughness. In this study, a hierarchical microstructure design with features including TiB2 grains and graphite platelets was used to toughen B4C by simultaneously utilizing multiple toughening mechanisms including crack deflection, bridging, and micro-crack toughening. Using field-assisted sintering technology (FAST), B4C composites with dense and hierarchical microstructure were fabricated. Previously, the fracture toughness of fabricated B4C composites was measured at micro-scale using micro-indentation to have up to 56% improvement. In this work, the B4C composites’ fracture toughness was characterized at macro-scale using four-point bending methods and compared with previous results obtained at micro-scale. Micromechanics modeling of fracture behaviors for B4C-TiB2 composites was also performed to evaluate the contributions from experimentally observed toughening mechanisms. From four-point bending tests, B4C composites reinforced with both TiB2 grains (~15 vol%) and graphite platelets (~8.7 vol%) exhibited the highest fracture toughness enhancement from 2.38 to 3.65 MPa∙m^(1/2). The measured values were lower than those obtained using micro-indentation but maintained the general trends. The discrepancy between the indentation and four-point bending test results originated from the complex deformation behaviors triggered by the high contact load during indentation tests. Through micromechanics modeling, introduced thermal residual stress due to thermal expansion mismatch between B4C and TiB2, and weak interphases at B4C-TiB2 boundaries were identified as the main causes for experimentally observed toughness enhancement. These results proved the effectiveness of hierarchical microstructure designs for B4C toughening and can provide reference for the future design of B4C composites with optimized microstructures for further fracture toughness enhancement.

composites↗
DOE OSTI2015

Crystal plasticity analysis of stress partitioning mechanisms and their microstructural dependence in advanced steels

Two-phase advanced steels contain an optimized combination of high yield strength and large elongation strain at failure, as a result of stress partitioning between a hard phase (martensite) and a ductile phase (ferrite or austenite). Provided with strong interfaces between the constituent phases, the failure in the brittle martensite phase will be delayed by the surrounding geometric constraints, while the rule of mixture will dictate a large strength of the composite. To this end, the microstructural design of these composites is imperative especially in terms of the stress partitioning mechanisms among the constituent phases. Based on the characteristic microstructures of dual phase and multilayered steels, two polycrystalline aggregate models are constructed to simulate the microscopic lattice strain evolution of these materials during uniaxial tensile tests. By comparing the lattice strain evolution from crystal plasticity finite element simulations with advanced in situ diffraction measurements in literature, this study investigates the correlations between the material microstructure and the micromechanical interactions on the intergranular and interphase levels. Finally, it is found that although the applied stress will be ultimately accommodated by the hard phase and hard grain families, the sequence of the stress partitioning on grain and phase levels can be altered by microstructural designs. Implications of these findings on delaying localized failure are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Microstructural Engineering and Accelerated Test Method Development to Achieve Low Cost, High Performance Solutions for Hydrogen Storage and Delivery

This project made advancements in developing lower cost steel alloys with novel microstructural design for use in hydrogen refueling infrastructure such as storage, compressors, and dispensing components, and utilizing accelerated test methods to efficiently evaluate variations in alloy and microstructure design. The project specifically sought to design alloys with lower nickel contents to reduce alloy cost, which was accomplished through substituting manganese for nickel along with other alloy additions to control deformation characteristics known to be important for hydrogen embrittlement resistance. Through Mn substitutions for nickel, austenitic and duplex austenite-ferrite steels were successfully developed with lower cost than currently available commercial stainless steel products that are employed for hydrogen refueling infrastructure. The steels were processed to achieve comparable strength and toughness in hydrogen environments as the commercially available steels containing high Ni contents. To evaluate mechanical performance in hydrogen, a testing methodology was employed to compare ubiquitous laboratory testing using electrochemical hydrogen charging in a liquid electrolyte to less accessible high pressure gaseous testing. While the application of these steels is in high pressure gaseous environments, the electrochemical hydrogen charging tests produced comparable results. Additionally, the Los Alamos Neutron Scatting Center enabled characterization of deformation mechanisms of the steel alloys in the presence of hydrogen, which has been associated with steel alloy characteristics associated with hydrogen embrittlement. Finally, a fracture mechanics based test bed model was developed to predict the influence of hydrogen gas pressure and fatigue conditions on fatigue lifetimes of pressure vessel steels. Together, these developments can be employed to enable lower cost hydrogen fueling infrastructure and more reliable prediction of steel alloy components in hydrogen service conditions. In particular, the newly alloys have the potential to replace stainless steels, having demonstrated comparable performance at substantially reduced cost.

08 HYDROGEN↗
DOE OSTI2014

A Composite Modeling Analysis of the Deformation Behavior of Medium Manganese Steels

The deformation behavior of medium manganese steels was evaluated with uniaxial tensile testing and the results were correlated with predictions of a composite model shown previously to provide design insight into the development of multi-phase steels with third-generation advanced high strength steel (3GAHSS) properties. An equilibrium thermodynamic-based methodology to design microstructures containing systematic amounts of metastable austenite with controlled stability against transformation is presented. The analysis is based on Mn enrichment of austenite during intercritical annealing of medium Mn (7 and 10 wt pct.) low carbon (0.1 and 0.15 wt pct) steels. The steels were produced as laboratory heats that were hot and cold rolled prior to annealing. After annealing the microstructures consisted primarily of either a matrix of fine grained ferrite with austenite contents between 32.6 and 45.2 wt pct (7Mn, 0.1C steels) or a matrix of martensite with various amounts of austenite in the higher Mn steel. The different intercritical annealing conditions produced steels with wide variations in austenite contents and austenite compositions (Mn and C contents) resulting in steels with significant variations in austenite stability. Predictions based on the composite analysis with different assumed flow behaviors for the individual constituents and stability functions for the meta-stable austenite are presented and shown to accurately predict strength-ductility combinations over a range of austenite volume fractions for the 7Mn steel. Applicability of the composite analysis is extended to consider the deformation behavior of the 10Mn steel and evaluate other possible microstructural combinations leading to 3GAHSS properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effect of die design on microstructure and mechanical joint strength in friction self-piercing riveted AA7055-T76 and AA7055-T76

In the present study, a unique friction self-piercing riveting (F-SPR) was applied to join high-strength, low-ductility aluminum alloy (AA) 7055-T76 and AA7055-T76 to mitigate a cracking issue. Also, the effect of die design on both joint formation and the mechanical joint performance were investigated. A crack-free joint was achieved when joining AA7055-T76 and AA7055-T76 by F-SPR. As the bottom diameter of the die increased, the mechanical interlocking distance initially increased then became almost saturated. At the same time, the solid-state bonding gradually disappeared, and the lap-shear fracture changed from bottom aluminum fracture to rivet pull-out with partial bottom aluminum fracture. The average maximum lap-shear joint strength of 11.57 kN and cross tension of 5.65 kN were achieved from the D2 die design owing to the combined contributions from high mechanical interlocking distance and good solid-state bonding at the joint interface. Ultrafine grain refinement was observed at the region next to the rivet shank outer surface and along the materials flow line between the top and bottom aluminum sheet in the rivet cavity. Further, because of the same joint-process parameters, the hardness profile at the joints made by different dies did not show obvious differences. As the distance from the base metal to the rivet outer surface decreased, frictional heat caused the hardness to initially decrease from 190 to 150 HV in the heat-affected zone. Hardness increased up to 175 HV in the thermomechanical affected zone (TMAZ-I) owing to large plastic deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design

Abstract There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed. Inverse problems are used extensively in various scientific fields, such as geophysics, health care and materials science. Exploring the relationships from properties to microstructures is one of the inverse problems in material science. It is challenging to solve the microstructure discovery inverse problem, because it usually needs to learn a one-to-many nonlinear mapping. Given a target property, there are multiple different microstructures that exhibit the target property, and their discovery also requires significant computing time. Further, microstructure discovery becomes even more difficult because the dimension of properties (input) is much lower than that of microstructures (output). In this work, we propose a framework consisting of generative adversarial networks and mixture density networks for inverse modeling of structure–property linkages in materials, i.e., microstructure discovery for a given property. The results demonstrate that compared to baseline methods, the proposed framework can overcome the above-mentioned challenges and discover multiple promising solutions in an efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The interpenetration polymer network in a cement paste–waterborne epoxy system

The formation of the interpenetrating polymer network (IPN) structure within the cement-polymer system has been revealed by experiments from 2 dimensional to 3-dimensional scales. However, the microstructure design and performance prediction of IPN as a function of specific C-S-H/polymer components or ingredients' parameters e.g. water to cement ratios (w/c), polymer to cement ratios (p/c), monomer components, degree of polymerization (DP), etc. is by far not available. Here we developed a mesoscale model for IPN visualization based on the Flory-Huggins interaction theory which was applied to cement science for the first time. All the ingredients in the micro-structure were considered as soluble beads with rational sizes based on their properties obtained by molecular dynamic methods. The interaction parameters of each bead were then determined based on their element ratios and chemical backbones. The model was validated with the waterborne epoxy-cement material (WECM) in which a novel waterborne epoxy resin (WEP) was prepared and impregnated. The verification results on the 2D-3D scale show that the developed model predicts the WECM's IPN structures by rule and line concerning DP, w/c, and p/c in the mixture. The C-S-H beads were progressively scaled in size which alters the C-S-H texture to have completely different dissolution characteristics. Beads of diameter ~6 Å are more unstable and soluble which enable them to form a continuous phase in water or a composite structure with WEP. In contrast, beads with diameters larger than 10 Å have different properties with stronger nucleation effects. The results also suggest the impregnation content of WEP in cement-based material should be limited to 10% vol. to prevent the polymer IPN from decomposing into discrete clusters. The application of Flory-Huggins theory in cement-based composites demonstrates great potential in performance prediction and microstructure design.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Deformation mechanisms in a precipitation-strengthened ferritic super alloy revealed by in situ neutron dffraction studies at elevated temperatures

The ferritic superalloy Fe–10Ni–6.5Al–10Cr–3.4Mo strengthened by ordered (Ni,Fe)AlB2-type precipitates is a candidate material for ultra-supercritical steam turbine applications above 923 K. Despite earlier success in improving its room-temperature ductility, the creep resistance of this material at high temperatures needs to be further improved, which requires a fundamental understanding of the high-temperature deformation mechanisms at the scales of individual phases and grains. In situ neutron diffraction has been utilized to investigate the lattice strain evolution and the microscopic load-sharing mechanisms during tensile deformation of this ferritic superalloy at elevated temperatures. Finite-element simulations based on the crystal plasticity theory are employed and compared with the experimental results, both qualitatively and quantitatively. Based on these interphase and intergranular load-partitioning studies, it is found that the deformation mechanisms change from dislocation slip to those related to dislocation climb, diffusional flow and possibly grain boundary sliding, below and above 873 K, respectively. Insights into microstructural design for enhancing creep resistance are also discussed.

nuclear (including radiation effects), defects, me↗
DOE OSTI2018

Li-rich Li[Li1/6Fe1/6Ni1/6Mn1/2]O2 (LFNMO) Cathodes: Atomic Scale Insight on the Mechanisms of Cycling Decay and of the Improvement due to Cobalt Phosphate Surface Modification

Lithium-rich Li[Li1/6Fe1/6Ni1/6Mn1/2]O2(0.4Li2MnO3-0.6LiFe1/3Ni1/3Mn1/3O2, LFNMO) is a new member of the xLi2MnO3·(1-x)LiMO2 family of high capacity - high voltage LIB cathodes. Unfortunately, it suffers from the severe degradation during cycling both in terms of reversible capacity and operating voltage. We are the first to document the corresponding degradation occurring in LFNMO at an atomic scale using aberration- corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) , as well as tracing the elemental crossover to the Li metal anode using XPS. We also demonstrate that a phosphate coating significantly boosts LFNMO cycling stability and rate capability. Due to cycling, the unmodified LFNMO undergoes extensive elemental dissolution (especially Mn) and O loss, forming Kirkendall-type voids. The associated structural degradation is from the as-synthesized R-3m layered structure to a disordered rock-salt phase. Prior to cycling, the phosphate coating shares the crystallography of the parent material. During cycling, a 2-3 nm thick disordered Co-based rock-salt structure is formed on the Mod-LFNMO surface, while the bulk material retains R-3m crystallography. Electrochemical impedance spectroscopy (EIS) analysis highlights how the phosphide treatment stabilizes the charge transfer resistance (RCT), the CEI resistance (RCEI), and the lithium ion diffusion coefficient (DLi). XPS analysis demonstrates that the coating also reduces the amount of cross-over Mn, Fe and especially Ni deposited on the Li metal anode, which is expected to lead to a more stable SEI layer during cycling. These combined cathode - anode findings significantly advance the microstructural design principles for next generation Li-rich cathode materials and coatings.

: high voltage cathode, Li - and Mn - rich cathode↗