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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design of novel refractory equiatomic multi-principal elemental alloys based on Mo-Nb-Ti system for Gen IV reactor applications

Excellent irradiation damage resistance demonstrated by multi-principal elemental alloys (MPEAs) has sparked significant interest among researchers, prompting exploration into their vast compositional space, to validate their suitability for nuclear applications. A combined approach of thermodynamic and empirical parameters calculations alongside CALPHAD (CALculation of PHAse Diagrams) for phase formation predictions enable high-throughput material selection for sophisticated applications like nuclear, overcoming laborious and time-consuming experiments. Key thermodynamic and empirical parameters for eight novel equiatomic MPEAs, based on seven low thermal neutron cross section refractory elements, for predicting phase formation were calculated, and equilibrium and non-equilibrium simulations in CALPHAD were employed to comprehensively model the systems. Pseudo binary phase diagram simulations showed that Zr, V or equiatomic CrV additions to the base MoNbTi alloy (MoNbTi-Zr, MoNbTi-V and MoNbTi-CrV alloys) favor the formation of isomorphous body-centered cubic (BCC) phase at high temperatures, while Cr, Al, equiatomic ZrV, or equiatomic CrAl additions (MoNbTi-Cr, MoNbTi-Al, MoNbTi-ZrV or MoNbTi-CrAl alloys) limit the solubility of them. Equilibrium CALPHAD simulations at 750 oC were consistent with XRD results on MoNbTi, MoNbTiZr and MoNbTiCr alloys, and partially for others. Notably, elemental segregation observed in the backscattered electron (BSE) scanning electron microscopy (SEM) images of the alloys was accurately simulated through non-equilibrium Scheil solidification calculations in CALPHAD, further verified by experiments. The precipitation of TiCr2 Laves phase in Cr containing MoNbTiCr and MoNbTiCrAl was accurately predicted while discrepancies were noted in MoNbTiCrV. The equilibrium simulations also provided insights into phase compositions at specific temperatures offering a pathway for tailoring the desired microstructure and properties of these systems. Empirical parameters calculations successfully predicted random solid solution in the base MoNbTi alloy, and with an exception in MoNbTiV and MoNbTiAl, predicted intermetallic precipitation in the rest, especially, Laves phase precipitation in Cr containing alloys.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Three-dimensional morphology of an ultrafine Al-Si eutectic produced via laser rapid solidification

Al-Si alloys processed by laser rapid solidification yield eutectic microstructures with ultrafine and interconnected fibers. Such fibrous structures have long been thought to bear resemblance to those formed in impurity-doped alloys upon conventional casting. Here, we show that any similarity is purely superficial. By harnessing high-throughput characterization and computer vision techniques, we perform a three-dimensional analysis of the branching behavior of the ultrafine eutectic and compare it against an impurity-modified eutectic as well as a random fractal (as a benchmark). Differences in the branching statistics point to different microstructural origins of the impurity- and quench-modified eutectic. Finally, our quantitative approach is not limited to the data presented here but can be used to extract abstract information from other volumetric datasets, without customization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Blocky Selective Postpolymerization C–H Functionalization of Polyolefins

C–H functionalization of commodity polyolefins affords functional materials derived from a high-volume, low-cost resource. However, current postpolymerization modification strategies result in randomly distributed functionalization along the length of the polymer backbone, which has a negative impact on the crystallinity of the resultant polymers, and thus the thermomechanical properties. Here, we demonstrate an amidyl radical mediated C–H functionalization of polyolefins to access blocky microstructures, which exhibit a higher crystalline fraction, larger crystallite size, and improved mechanical properties compared to their randomly functionalized analogues. Taking inspiration from the site-selective C–H functionalization of small molecules, we leverage the steric protection provided by crystallites and target polymer functionalization to amorphous domains in a semicrystalline polyolefin gel. The beneficial outcomes of blocky functionalization are independent of the identity of the pendant functional group that is installed through functionalization. Here, the decoupling of functional group incorporation and crystallinity highlights the promise in accessing nonrandom microstructures through selective functionalization to circumvent traditional tradeoffs in postpolymerization modification, with potential impact in advanced materials and upcycling plastic waste.

Neidhart, Eliza K. [The University of North Caroli↗
NASA NTRS1980

Propagation in a shearing plasma. II - Turbulence and the frequency range of pulsar microstructure

Numerical calculations are presented which explore the propagation of radio waves and pulses through a turbulent shearing plasma. A stochastic model is used to describe the turbulent velocity field, in which random fluctuations are superposed on a mean profile. Both Gaussian wave packets and shot-noise pulses polarized in the plane of shearing acquire quasi-periodic intensity modulations above the rest-frame plasma frequency. The frequency range over which these modulations appear is shown to depend on the spatial correlation length of the turbulent fluctuations and on their standard deviation from the mean velocity. The period of the modulations is variable from one realization of the random process to the next, and the average period is frequency dependent. The results of these calculations lend further support to a model for pulsar microstructure in which periodic micropulses are pure temporal modulations of the emitted radiation due to propagation effects in magnetospheric shearing regions. It is shown that turbulence on a scale of approximately 10 cm can produce these quasi-periodic modulations over a frequency range comparable to that of observed microstructure.

Harding, A. K.↗
NASA NTRS1993

Mullite Whiskers and Mullite-whisker Felt

The Naval Surface Warfare Center has developed processes for the preparation of mullite (3(Al2O3)(dot)2(SiO2)) whiskers and mullite-whisker felt. Three patents on the technology were issued in 1990. The processes are based on chemical reactions between AlF3, Al2O3, and SiO2. The felt is formed in-situ during the processing of shaped powdered precursors. It consists of randomly oriented whiskers which are mutually intergrown forming a rigid structure. The microstructure and properties of the felt and size of the whiskers can be modified by varying the amount of Al2O3 in the starting mixture. Loose mullite whiskers can be used as a reinforcement for polymer-, metal-, and ceramic-matrix composites. The felt can be used as preforms for fabricating composite materials as well as for thermal insulation and high temperature, chemically stable filters for liquids (melts) and gases.

Talmy, Inna G.↗
DOE OSTI2023

Predictive machine learning approaches for the microstructural behavior of multiphase zirconium alloys

Abstract Zirconium alloys are widely used in harsh environments characterized by high temperatures, corrosivity, and radiation exposure. These alloys, which have a hexagonal closed packed (h.c.p.) structure thermo-mechanically degrade, when exposed to severe operating environments due to hydride formation. These hydrides have a different crystalline structure, than the matrix, which results in a multiphase alloy. To accurately model these materials at the relevant physical scale, it is necessary to fully characterize them based on a microstructural fingerprint, which is defined here as a combination of features that include hydride geometry, parent and hydride texture and crystalline structure of these multiphase alloys. Hence, this investigation will develop a reduced order modeling approach, where this microstructural fingerprint is used to predict critical fracture stress levels that are physically consistent with microstructural deformation and fracture modes. Machine Learning (ML) methodologies based on Gaussian Process Regression, random forests, and multilayer perceptrons (MLP) were used to predict material fracture critical stress states. MLPs, or neural networks, had the highest accuracy on held-out test sets across three predetermined strain levels of interest. Hydride orientation, grain orientation or texture, and hydride volume fraction had the greatest effect on critical fracture stress levels and had partial dependencies that were highly significant, and in comparison hydride length and hydride spacing have less effects on fracture stresses. Furthermore, these models were also used accurately predicted material response to nominal applied strains as a function of the microstructural fingerprint.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images

Dental enamel, the outermost tissue of mammalian teeth, must withstand a lifetime of wear and cyclic contact. To meet this demand, enamel possesses a combination of high hardness and resistance to fracture, properties that are typically mutually exclusive. The impressive damage tolerance has been attributed largely to decussation of the enamel rods, the principal unit of its microstructure. As such, enamel is inspiring the design of next‐generation structural materials. However, quantitative descriptions of the decussated enamel rod microstructure remain limited due to challenges encountered in applying computed tomography and in acquiring quality images appropriate for traditional digital processing methods. Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set ( n = 3 images). A validation of this segmentation method is presented, in addition to its application to calculate relevant microstructural parameters for images of tooth enamel from selected mammalian species. The methodology applied here is equally applicable to other hard tissues.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Effects of TiB{sub 2} Particle and Short Fiber Sizes on the Microstructure and Properties of TiB{sub 2}-Reinforced Composite Coatings

In this study, particle and short fiber-reinforced titanium matrix composite coatings are prepared via laser in situ technique using (0.5 and 50 μm) TiB{sub 2} and Ti powder as cladding materials. The microstructure and properties of the composite coatings are studied, and the changing mechanism of the microstructure is discussed. The results reveal that particle agglomeration is prone to appear with using fine TiB{sub 2} particles. Decomposition of the particles preferentially occurs with using coarse TiB{sub 2} particles. The cracks and pores on the surface of the coating are formed at a lower laser energy density. With the increase in the laser energy density, cracking on the surface of the coating diminishes, but the coating exhibits depression behavior. The depression extent of the coating using fine TiB{sub 2} particle as the reinforcement is much less than that of the coating using coarse TiB{sub 2} particle. Moreover, the size of the aggregate and the tendency of cracking can be reduced with the increase in Ti addition. Meanwhile, short TiB fiber bundles are formed by the diffusion mechanism of rod aggregate, and randomly oriented TiB short fibers are formed mainly by the dissolution–precipitation mechanism of fine TiB{sub 2} particles. Moreover, the growth of short TiB fibers can be in an alternating manner between B27 and Bf structures. The micro-hardness and wear resistance of the coatings are evidently higher than that of the titanium alloy substrate. The wear resistance of the large size TiB{sub 2} coating is higher than that of the small size TiB{sub 2} coating under the condition of low load.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network

The relationships between porous microstructures and transport properties are of fundamental importance in various scientific and engineering applications. Due to the intricacy, stochasticity and heterogeneity of porous media, reliable characterization and modeling of transport properties often require a complete dataset of internal microstructure samples. However, it is often an unbearable cost to acquire sufficient 3D digital microstructures by purely using microscopic imaging systems. Herein this paper presents a machine learning-based technique to hierarchically reconstruct 3D well-connected porous microstructures from one isotropic or several anisotropic low-cost 2D exemplar(s). To compactly characterize the large-scale microstructural features, a Gaussian image pyramid is built for each 2D exemplar. Local morphology patterns are collected from the Gaussian image pyramids, and then they serve as the training data to embed the 2D morphological statistics into feed-forward neural networks at multiple length levels. By using a specially-developed morphology integration scheme, the 3D morphological statistics at different levels can be inferred from the statistics-informed neural networks. Gibbs sampling is adopted to hierarchically reconstruct 3D microstructures by using multi-level 3D morphological statistics, where the large-scale, regional and local morphological patterns are statistically generated and successively added to the same 3D random field. The proposed method is tested on a series of porous media with distinct morphologies, and the statistical equivalence between the reconstructed and the real microstructures is systematically evaluated by comparing morphological descriptors and transport properties. The results demonstrate that the proposed 2D-to-3D microstructure reconstruction method is a universal and efficient approach to generating morphologically and physically realistic samples of porous media.

42 ENGINEERING↗
NASA NTRS1985

The effect of material heterogeneity and random loading on the mechanics of fatigue crack growth

This paper reviews experimental work on the influence of variable amplitude or random loads on the mechanics and micromechanisms of fatigue crack growth. Implications are discussed in terms of the crack driving force, local plasticity, crack closure, crack blunting, and microstructure. Due to heterogeneity in the material's microstructure, the crack growth rate varies with crack tip position. Using the weakest link theory, an expression for crack growth rate is obtained as the expectation of a random variable. This expression is used to predict the crack growth rates for aluminum alloys, a titanium alloy, and a nickel steel in the mid-range region. It is observed, using the present theory, that the crack growth rate obeys the power law for small stress intensity factor range, and that the power is a function of a material constant.

Srivatsan, T. S.↗
NASA NTRS1989

Stochastic modeling of crack initiation and short-crack growth under creep and creep-fatigue conditions

A simplified stochastic model is proposed for crack initiation and short-crack growth under creep and creep-fatigue conditions. Material inhomogeneity provides the random nature of crack initiation and early growth. In the model, the influence of microstructure is introduced by the variability of: (1) damage accumulation along grain boundaries, (2) critical damage required for crack initiation or growth, and (3) the grain-boundary length. The probabilities of crack initiation and growth are derived by using convolution integrals. The model is calibrated and used to predict the crack density and crack-growth rate of short cracks of 304 stainless steel under creep and creep-fatigue conditions. The mean-crack initiation lives are predicted to be within an average deviation of about 10 percent from the experimental results. The predicted cumulative distributions of crack-growth rate follow the experimental data closely. The applicability of the simplified stochastic model is discussed and the future research direction is outlined.

Kitamura, Takayuki↗
NASA NTRS1992

Stochastic modeling of crack initiation and short-crack growth under creep and creep-fatigue conditions

A simplified stochastic model is proposed for crack initiation and short-crack growth under creep and creep-fatigue conditions. Material inhomogeneity provides the random nature of crack initiation and early growth. In the model, the influence of microstructure is introduced by the variability of: (1) damage accumulation along grain boundaries, (2) critical damage required for crack initiation or growth, and (3) the grain-boundary length. The probabilities of crack initiation and growth are derived by using convolution integrals. The model is calibrated and used to predict the crack density and crack-growth rate of short cracks of 304 stainless steel under creep and creep-fatigue conditions. The mean-crack initiation lives are predicted to be within an average deviation of about 10 percent from the experimental results. The predicted comulative distributions of crack-growth rate follow the experimental data closely. The applicability of the simplified stochastic model is discussed and the future research direction is outlined.

Kitamura, Takayuki↗
DOE OSTI2018

Annealing-induced microstructural evolution and mechanical anisotropy improvement of the Mg-Gd-Y-Zr alloy processed by hot ring rolling

Highlights: • Growth of SRX grains in GBR is random, while that of TBR is anisotropic. • The new texture component in annealed MR weakens the anisotropy obviously. • T6 treatment leads to an excellent comprehensive mechanical property. - Abstract: Hot ring rolling (HRR) is widely used to fabricate large-size seamless ring-shape components. However, this process produces a severe mechanical anisotropy, which is not acceptable in practical industrial application and should be avoided. This paper reports the annealing-induced microstructural evolution and mechanical anisotropy improvement of HRRed Mg-8.12Gd-1.82Y-0.35Zr alloy ring. Results show that annealing treatment could improve the microstructural homogeneity of the ring owing to the occurrence of static recrystallization (SRX). SRX grains are preferentially formed at twin boundaries and initial grain boundaries due to high dislocation density, high level of stored energy, and stress concentration. Twin boundaries, to some extent, can suppress the migration of SRX grain boundaries. In addition, occurrence of SRX weakens the texture intensity and basal pole inclination, leading to a decrease in the mechanical anisotropy of the ring. Considering the weakened anisotropy, comparable strength, and improved ductility, annealing + aging (T6), compared with direct aging (T5), is a more suitable heat treatment schedule for the HRRed Mg-8.12Gd-1.82Y-0.35Zr alloy ring.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Installing Controlled Stereo-Defects Yields Semicrystalline and Biodegradable Poly(3-Hydroxybutyrate) with High Toughness and Optical Clarity

Stereo-defects present in stereo-regular polymers often diminish thermal and mechanical properties, and hence suppressing or eliminating them is a major aspirational goal for achieving polymers with optimal or enhanced properties. Here, we accomplish the opposite by introducing controlled stereo-defects to semicrystalline biodegradable poly(3-hydroxybutyrate) (P3HB), which offers an attractive biodegradable alternative to semicrystalline isotactic polypropylene but is brittle and opaque. We enhance the specific properties and mechanical performance of P3HB by drastically toughening it and also rendering it with the desired optical clarity while maintaining its biodegradability and crystallinity. This toughening strategy of stereo-microstructural engineering without changing the chemical compositions also departs from the conventional approach of toughening P3HB through copolymerization that increases chemical complexity, suppresses crystal-lization in the resulting copolymers, and is thus undesirable in the context of polymer recycling and performance. More specifically, syndio-rich P3HB (sr-P3HB), readily synthesized from the eight-membered meso-dimethyl diolide, has a unique set of stereo-microstructures comprising enriched syndiotactic [rr] and no isotactic [mm] triads but abundant stereo-defects randomly distributed along the chain. This sr-P3HB material is characterized by high toughness (UT = 96 MJ/m 3 ) as a result of its high elongation at break (>400%) and tensile strength (34 MPa), crystallinity (T m = 114 degrees C), optical clarity (due to its submicron spherulites), and good barrier properties, while it still biodegrades in freshwater and soil.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Model Parameter Development for Complex Materials: Species-Specific Diffusion Barriers in 316 Stainless Steel from Systematic DFT Calculations

Vacancy-mediated diffusion barriers in 316 stainless steel have been systematically calculated using density functional theory to provide essential parameters for mesoscale microstructure evolution models. A statistical sampling approach employing 210 nudged elastic band calculations across multiple special quasi-random structures captures the effects of local chemical environments in this concentrated alloy. The computational methodology addresses challenges specific to chemically disordered systems, including proper magnetic treatment throughout multi-step calculations and validation against experimental structural properties. The calculated activation barriers reveal clear species-dependent diffusion behavior with the hierarchy Ni >> Fe ˜ Cr >> Mo. Nickel exhibits the highest barriers (0.74–1.31 eV, mean 1.045 eV), confirming its role as the slowest-diffusing major component. Iron and chromium show similar moderate barriers averaging 0.587 eV and 0.522 eV, respectively. Remarkably, molybdenum demonstrates exceptionally low barriers (0.12–0.28 eV, mean 0.194 eV), suggesting much higher mobility than previously recognized and potentially significant implications for precipitation kinetics and microstructure evolution. The barrier ranges remain consistent across different 316 SS compositions, supporting parameter transferability for modeling applications. The overall mean barrier of 0.64 eV provides a practical approximation for phase field simulations, while species-specific values enable detailed treatments of diffusion-controlled processes. This systematic approach establishes a validated framework for generating diffusion parameters in other concentrated alloys where experimental data are limited, while providing the first systematic set of species-specific barriers for predictive modeling of 316 stainless steel microstructure evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Directional solidification and annealing of Mn55Al45 alloys

The use of directional solidification to produce aligned or magnetic microstructures for the MnAl alloy and the effect of annealing on the bulk magnetic properties of the alloy are investigated. The phase composition, cylindrically shaped magnetization, and room-temperature magnetization of the samples are analyzed. The microstructure of a directionally solidified Al-Mn alloy is characterized by a two-phase structure consisting of randomly-oriented Al-rich fibers of about 40 at. pct Al dispersed in a textureless matrix of about 50 at. pct Al; the matrix phase contains at least 50 wt pct of the metastable and ferrimagnetic tau-phase, and the Al-rich fibers as a precipitated Cr5Al8-type Al-Mn phase. Significant macrosegregation for the thermally stable growth-up orientation is detected. The data reveal that the annealing enhances the cell-like microstructure observed transverse of the solidification direction and increases remanent magnetization and intrinsic coercivity.

Pirich, Ronald G.↗
DOE OSTI2018

Effect of build geometry on the microstructural development of 316L parts produced by additive manufacturing

Highlights: • Stainless steel ribs were created via direct metal laser sintering to investigate microstructural effect of part design. • EBSD confirmed the presence of large elongated grains in the center of the part, with preferred orientation. • Small grains at the rib surface were found to grow towards the center of the rib with random orientation. • By changing rib thickness and build angle varying texture was observed in the final products. • Large intragranular misorientations were observed in all samples. - Abstract: Additive manufacturing (AM) technology has shown great potential in manufacturing complex products, such as lattice structures without extensive tooling. The focus of this study was to understand the effect of the part geometry on the resulting microstructure. Direct metal laser sintering was used for fabrication of ribs with thicknesses varying between 0.2 and 3.0 mm as well as inclined ribs the with build angles of 30° and 45°. The investigation showed that grains were growing in an epitaxial manner parallel to the building direction. The large elongated grains had a preferential orientation, resulting from the temperature gradient. Additionally, it was found that small grains had formed close to the part surface which were inclined towards the center of the rib. In contrast to the elongated grains, they had a random orientations. The results also indicated that at build angles below 45°, the formed microstructure consisted of the large grains elongated in the building direction. For the used process parameters, the critical part thickness to avoid large elongated grains was found to be about 0.4 mm. These findings allowed us to establish the basics for design rules when it comes to thin wall structures.

36 MATERIALS SCIENCE↗