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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 OSTI2024

Simulating the effect of grain structure and porosity on creep for powder bed fusion 316H

This report details results from modeling studies focused on identifying the potential factors influencing creep performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF), with a focus on experimentally-observed and predicted differences between the response of the AM material and conventionally manufactured wrought 316H. The studies presented here systematically look at the role of grain structure, porosity and texture in the anisotropic creep behavior of the material under conditions expected in high temperature advanced nuclear reactors. A physics-based Crystal Plasticity Finite Element modeling approach has allowed us to look at these factors in isolation and study their role in the material's long-term deformation behavior. An update to the precipitation model used in the constitutive framework for 316H is also presented here, with the aim of improving the accuracy of our results from this modeling effort. This work is a step in the direction of gaining mechanistic understanding of the long-term deformation behavior of LPBF 316H, helping us model its long term performance and reducing the qualification time for the material.

36 MATERIALS SCIENCE↗
DOE OSTI2024

DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing

Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of a concurrent coupled Atomistic - Continuum model to predict the defect and grain structure for Additive Manufacturing process [Slides]

Development of a coupled atomistic-continuum model for metal AM process. Two-way coupling between atomistic (heat flux) and continuum (temperature) domain. Identification of grain and dislocation structure at the atomistic domain. Conversion of dislocation data from discrete atomistic to density form at the continuum. Obtain the spatial distribution of grain structure and dislocation density in additively manufactured metal polycrystal material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Prediction of grain structure after thermomechanical processing of U-10Mo alloy using sensitivity analysis and machine learning surrogate model

Abstract Hot rolling and annealing are critical intermediate steps for controlling microstructures and thickness variations when fabricating uranium alloyed with 10% molybdenum (U-10Mo), which is highly relevant to worldwide nuclear non-proliferation efforts. This work proposes a machine-learning surrogate model combined with sensitivity analysis to identify and predict U-10Mo microstructure development during thermomechanical processing. Over 200 simulations were collected using physics-based microstructure models covering a wide range of thermomechanical processing routes and initial alloy grain features. Based on the sensitivity analysis, we determined that an increase in rolling reduction percentage at each processing pass has the strongest effect in reducing the grain size. Multi-pass rolling and annealing can significantly improve recrystallization regardless of the reduction percentage. With a volume fraction below 2%, uranium carbide particles were found to have marginal effects on the average grain size and distribution. The proposed stratified stacking ensemble surrogate predicts the U-10Mo grain size with a mean square error four times smaller than a standard single deep neural network. At the same time, with a significant speedup (1000×) compared to the physics-based model, the machine learning surrogate shows good potential for U-10Mo fabrication process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High radiation tolerance of an ultrastrong nanostructured NiCoCr alloy with stable dispersed nanooxides and fine grain structure

The present paper reports the irradiation behavior of nanostructured NiCoCr medium entropy alloy enhanced by Y-Hf-O nanooxides and fine grains produced by powder metallurgy. Ion beam irradiation to a peak dose of 130 dpa at 580°C produced neither detectable void swelling nor irradiation-induced hardening, in contrast to significant void swelling and property degradation of single phase NiCoCr concentrated solid-solution alloy under the similar irradiation condition. The dispersed nanooxides and high density of grain boundaries act as defect sinks that effectively annihilate irradiation-induced interstitials and vacancies. Furthermore, high-density nanooxides maintain their crystalline structures and stabilize the grain boundaries during irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Solid Electrolyte Bimodal Grain Structures for Improved Cycling Performance

Here, the application of solid-state electrolytes in Li batteries is hampered by the occurrence of Li-dendrite-caused short circuits. To avoid cell failure, the electrolytes can only be stressed with rather low current densities, severely restricting their performance. As grain size and pore distributions significantly affect dendrite growth in ceramic electrolytes such as Li 7 La 3 Zr 2 O 12 and its variants; here, a “detour and buffer” strategy to bring the superiority of both coarse and fine grains into play, is proposed. To validate the mechanism, a coarse/fine bimodal grain microstructure is obtained by seeding unpulverized large particles in the green body. The rearrangement of coarse grains and fine pores is fine-tuned by changing the ratio of pulverized and unpulverized powders. The optimized bimodal microstructure, obtained when the two powders are equally mixed, allows, without extra interface decoration, cycling for over 2000 h as the current density is increased from 1.0 mA·cm -2 , and gradually, up to 2.0 mA·cm -2 . The “detour and buffer” effects are confirmed from postmortem analysis. The complex grain boundaries formed by fine grains discourage the direct infiltration of Li. Simultaneously, the coarse grains further increase the tortuosity of the Li path. This study sheds light on the microstructure optimization for the polycrystalline solid-state electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2025

Investigating Grain Structure and Microcracking in SiCf-SiCm Composites Using 4D-STEM

Silicon carbide (SiC) fiber-reinforced SiC matrix composites (SiCf-SiCm) are promising materials for accident-tolerant fuel (ATF) cladding in light water reactors. This paper, using four-dimensional scanning transmission electron microscopy (4D-STEM), studied the microstructure of SiCf-SiCm at nanoscale and provided grain statistics at the CVI/fiber region. Here, the results reveal that CVI region mainly contain irregular sub-micron grains (115 nm to 1800 nm) with a preferred orientation, while the fiber region has nano equiaxed grains (21 nm to 78 nm) with random orientations. Centered dark field imaging over the fiber regions verified the grain size measurement by 4D-STEM. Through 4D-STEM virtual dark field imaging and orientation mapping, intragranular propagation was identified as the fracture mechanism for a microcrack observed within the CVI region. The amorphous pyrolytic carbon layer was also shown to effectively arrest the microcrack.

4D-STEM↗
DOE OSTI2022

Effect of manganese substitution of ferrite nanoparticles on particle grain structure

To investigate the influence of manganese substitution on the saturation magnetization of manganese ferrite nanoparticles, samples with various compositions (Mn x Fe 3–x O 4 , x = 0, 0.25, 0.5, 0.75, and 1) were synthesized and characterized. The saturation magnetization of such materials was both calculated using density functional theory and measured via vibrating sample magnetometry. A discrepancy was found; the computational data demonstrated a positive correlation between manganese content and saturation magnetization, while the experimental data exhibited an inverse correlation. X-ray diffraction (XRD) and magnetometry results indicated that the crystallite diameter and the magnetic diameter decrease when adding more manganese, which could explain the loss of magnetization of the particles. For 20 nm nanoparticles, with increasing manganese substitution level, the crystallite size decreases from 10.9 nm to 6.3 nm and the magnetic diameter decreases from 15.1 nm to 3.5 nm. Further high resolution transmission electron microscopy (HRTEM) analysis confirmed the manganese substitution induced defects in the crystal lattice, which encourages us to find ways of eliminating crystalline defects to make more reliable ferrite nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bulk nanocrystalline Al alloys with hierarchical reinforcement structures via grain boundary segregation and complexion formation

Grain size engineering, particularly reducing grain size into the nanocrystalline regime, offers a promising pathway to further improve the strength-to-weight ratio of Al alloys. Unfortunately, the fabrication of nanocrystalline metals often requires non-equilibrium processing routes, which typically limit the specimen size and require large energy budgets. In this study, multiple dopant elements in ternary Al alloys are deliberately selected to enable segregation to the grain boundary region and promote the formation of amorphous complexions. Three different fully dense bulk nanocrystalline Al alloys (Al-Mg-Y, Al-Fe-Y, and Al-Ni-Y) with small grain sizes were successfully fabricated using a simple powder metallurgy approach, with full densification connected directly to the onset of amorphous complexion formation. All the compositions demonstrate densities above 99% with grain sizes <60 nm following consolidation via hot pressing at 585 °C. The very fine grain structure results in excellent mechanical properties, as evidenced by nanoindentation hardness values in the range of 2.2-2.8 GPa. Detailed microstructural characterization verifies the segregation of all dopant species to grain boundaries as well as the formation of amorphous complexions, which suggests their influential role in aiding effective consolidation and endowing thermal stability in the alloys. Moreover, nanorods with a core-shell structure are also observed at the grain boundaries, which likely contribute to the stabilization of the grain structure while also strengthening the materials. Lastly, intermetallic particles with sizes of hundreds of nanometers form in all systems. As a whole, the results presented here demonstrate a general alloy design strategy of segregation and boundary evolution pathway that enables the fabrication of multiple nanocrystalline Al alloys with hierarchical microstructures and improved performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimizing Grain Boundary Structures with LAMMPS Using Evolutionary Algorithms

Grain boundary structure optimization is an important part of materials modeling. Current methods for grain boundary structure optimization involve inefficient, time-consuming processes that do not fully explore the interface parameter space. Evolutionary algorithms have recently been demonstrated to be effective at determining both stable and metastable grain boundary interface structures. In this work, we demonstrate the use of GBOpt, a grain boundary structure optimization software designed to use the Large-scale Atomic/Molecular Massively Parallel Simulation (LAMMPS) software to efficiently determine grain boundary structures. We demonstrate that a only a few manipulations, namely atom insertion, atom removal, and relative grain displacement, are sufficient to explore much of the grain boundary structure parameter space. The efficacy of this approach is demonstrated on an FCC Ni system, and a BCC Fe system. The computational cost is compared against the gamma-surface sampling approach to demonstrate performance improvement.

Evolutionary algorithms↗
DOE OSTI2024

A computational study of the effects of graphene additions on electrical properties of polycrystalline copper

The addition of graphene has recently shown promise as a route for the significant improvement of the bulk electrical properties of metallic materials. Here, we explore the effects these additions have on the net electrical conductivity of fabricated copper-graphene (Cu-Gr) nanocomposites as a function of grain structure and grain boundary properties. Synthetic 3D microstructures were generated to represent polycrystalline copper with different average grain diameters and twinned grain boundary fractions. Then, the Poisson equation of electrical transport was solved using a finite difference method in order to predict the net electrical conductivity of each microstructure. In this context, the potential effect of graphene on the conductivity of the composite was evaluated as a function of the number of affected grain boundaries. The results of these calculations indicate that 1.) as supported by literature, net electrical conductivity decreases with decreasing grain size, 2.) the presence of twinned grain boundaries results in smaller loss of conductivity than would otherwise be expected, and 3.) the presence of graphene on the grain boundaries can be expected to lead to improvements in net electrical conductivity. However, we also find that 4.) when the Cu grain structure becomes sufficiently refined, the addition of graphene could conceivably result in significant improvements in electrical conductivity over and above coarse-grained Cu. It is estimated from our calculations that, assuming microstructures with average grain sizes between 100 nm and 100 μm and graphene conductivity 1000 to 10,000 that of a typical Cu grain boundary, an improvement in electrical conductivity of approximately 17% over that of bulk Cu may be attainable. Therefore, by performing this study we suggest a possible route for the improvement of Cu electrical properties through the addition of graphene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An Integrated Simulation of Multiple-Pass U-10Mo Alloy Hot Rolling and Static Recrystallization

To achieve a desired microstructure and minimize the thickness variation in rolled foils, researchers must understand the effects of foil fabrication process variables on microstructure evolution. We developed an integrated simulation of deformation and recrystallization that employs the finite element method (FEM) and the kinetic Monte Carlo (KMC) Potts model, respectively, to investigate microstructure evolution during multiple-pass hot rolling and heat treatment in polycrystalline U-10Mo fuel. Scanning electron microscopy and electron backscatter diffraction images of microstructures were directly used as input in FEM calculation of deformation, and the calculated strains were used to determine the driving force of nucleation and growth of recrystallized grains in the Potts model. Grain structures predicted by the Potts model were used to update the grain structure and material properties for FEM. Simulation alternated between FEM and the Potts model to simulate grain structure evolution during multiple rolling and heat treatments. The initial model parameters were determined by benchmarking the recrystallization kinetics against experimental data. Then, the model was applied to predict the grain structure evolution. Results showed that our model can capture the coupling between deformation and recrystallization and can quantitatively reproduce the observed U-10Mo recrystallization and grain growth kinetics. The simulation results demonstrated that the developed model can predict U-10Mo grain structures as a function of initial microstructure and foil fabrication parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermal Stability and Mechanical Properties of Cold-Sprayed Nickel-Yttria Coating

The microstructural evolution under the extreme environments imposed during cold spray deposition of cermet coatings and the microstructural recovery during post-processing annealing treatments is rather complex and not well understood. Here, Ni-Yttria cermet coatings on an SS304 substrate were produced using cold spray technique, resulting in a bimodal grain structure. The grain growth, phase stability, hardness, and wear properties are observed in as-deposited and annealed (at 400 °C) Ni-Yttria and pure Ni coatings. A multimodal microstructural characterization using electron microscopy, and atom probe tomography shows the structural and compositional stability of yttria particles and Ni grains. A fragmentation of Y-rich particles and dispersion in Ni was observed, however, no forced mixing/dissolution of Y in Ni is detected. Nano-yttria dispersed within the Ni grains slowed the grain growth during annealing. After annealing, Yttria reinforced coating was 1.5 times harder and showed better thermal and mechanical stability compared to the Ni coating.

Gwalani, Bharat↗