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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comparative Analysis of Radial and Random Microstructures of Mesophase Pitch Carbon Fibers

Carbon fibers (CF) with radial and random microstructures are produced. Here, these fibers are subjected to identical treatment before being mechanically tested and analyzed with Weibull analysis, with the results revealing a statistically significant difference in tensile strengths of 2.23 GPa for random CF and 1.69 GPa for radial CF. Raman mapping probed the crystalline structure perpendicular to the fiber axis and found a uniform structure, while wide‐angle X‐ray diffraction showed a significant difference of 7.5 Å in the crystallites’ basal lengths parallel to the fiber. Small‐angle X‐ray scattering is completed parallel to the fiber for the first time. A cross‐section Guinier plot of the 1D azimuthal integration is generated assuming symmetric scattering, and the parallel scatterers are found to have a similar length scale to the crystallite's length, validating the testing method. Finally, transmission electron microscopy is completed on the longitudinal cross‐section of each fiber. The radial carbon fiber is found to have a core–shell structure, as evidenced further by fast Fourier transform images. Through all studies, it is shown that the structure developed during mesophase pitch spinning altered the microstructure, thus impacting the mechanical properties, confirming a direct relationship between processing, structure, and properties.

Scherschel, Alexander [Univ. of Virginia, Charlott↗
DOE OSTI2021

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Peridynamic Models for Random Media Found by Coarse Graining

Using coarse graining, the upscaled mechanical properties of a solid with small scale heterogeneities are derived. The method maps internal forces at the small scale onto peridynamic bond forces in the coarse grained mesh. These upscaled bond forces are used to calibrate a peridynamic material model with position-dependent parameters. These parameters incorporate mesoscale variations in the statistics of the small scale system. The upscaled peridynamic model can have a much coarser discretization than the original small scale model, allowing larger scale simulations to be performed efficiently. The convergence properties of the method are investigated for representative random microstructures. In conclusion, a bond breakage criterion for the upscaled peridynamic material model is also demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A predictive discrete-continuum multiscale model of plasticity with quantified uncertainty

Multiscale models of materials, consisting of upscaling discrete simulations to continuum models, are unique in their capability to simulate complex materials behavior. The fundamental limitation in multiscale models is the presence of uncertainty in the computational predictions delivered by them. In this work, a sequential multiscale model has been developed, incorporating discrete dislocation dynamics (DDD) simulations and a strain gradient plasticity (SGP) model to predict the size effect in plastic deformations of metallic micro-pillars. The DDD simulations include uniaxial compression of micro-pillars with different sizes and over a wide range of initial dislocation densities and spatial distributions of dislocations. An SGP model is employed at the continuum level that accounts for the size-dependency of flow stress and hardening rate. Sequences of uncertainty analyses have been performed to assess the predictive capability of the multiscale model. The variance-based global sensitivity analysis determines the effect of parameter uncertainty on the SGP model prediction. The multiscale model is then constructed by calibrating the continuum model using the data furnished by the DDD simulations. A Bayesian calibration method is implemented to quantify the uncertainty due to microstructural randomness in discrete dislocation simulations (density and spatial distribution of dislocations) on the macroscopic continuum model prediction (size effect in plastic deformation). Here, the outcomes of this study indicate that the discrete-continuum multiscale model can accurately simulate the plastic deformation of micro-pillars, despite the significant uncertainty in the DDD results. Additionally, depending on the macroscopic features represented by the DDD simulations, the SGP model can reliably predict the size effect in plasticity responses of the micropillars with below 10% of error.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermo-Mechanical Phase-Field Modeling of Fracture in High-Burnup UO2 Fuels Under Transient Conditions

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO2) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits.

Chemistry↗
DOE OSTI2024

Spherulite-enhanced macroscopic polarization in molecular ferroelectric films from vacuum deposition

Proton-transfer type molecular ferroelectrics hold significant promise for practical application due to their large spontaneous polarizations, high Curie temperatures, and small switching fields. However, it remains puzzling that preparation of quasi-2D films exhibiting macroscopic ferroelectric behaviors has been reported in only few molecular ferroelectrics. To address this puzzle, we studied the impact of microstructures on the macroscopic ferroelectric properties of 5,6-dichloro-2-methylbenzimidazole (DC-MBI) films grown using the low-temperature deposition followed by the restrained crystallization (LDRC) method. Our findings revealed a competition between dense spherulites and porous microstructures containing randomly oriented nanograins in the as-grown films. Post-growth annealing at moderate temperature promotes the formation of spherulites, leading to macroscopic ferroelectric polarization switching. These results underscore the critical role of microstructure density in determining macroscopic ferroelectric properties, potentially resolving the puzzle for the absence of such behavior in many molecular ferroelectric films. Here, we anticipate that the approach proposed in this study to enhance microstructure density will significantly advance the fabrication of quasi-2D molecular ferroelectric films and unlock their potential in device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Grain boundary inter-connections in polycrystalline aluminum with random orientation

Highlights: • The GBICs in a pure aluminum are not random, showing remarkable preference on the planes of low Miller index. • {1 1 1}/{1 1 1} is the most frequent GBIC in pure aluminum. • {1 1 1}/{1 1 1} GBIC is mainly coming from the GBs formed by rotations around , and axes. • {1 1 1}/{1 1 1} GBIC possesses higher PCSD and definite dislocation structures compared to the general GBs. • To pursue {1 1 1}/{1 1 1} GBIC is a pint-cut for the GBE research in high stacking fault energy FCC materials. - Abstract: Grain boundary inter-connection (GBIC) is the matching of two crystallographic planes from two abutting grains ending on the grain boundary (GB) position in polycrystalline materials, which can be expressed as {h_1k_1l_1}/{h_2k_2l_2}. GBIC is the critical parameter that intrinsically defines the character and properties of a GB. In current work, a zone-melted polycrystalline aluminum bar with a purity higher than 99.99% (mass fraction) was subjected to a multi-directional forging (MDF) with a true strain of 4 followed by a recrystallization annealing at 360 °C. Such process repeated at least 4 times until an equiaxed-grain microstructure with random orientation and averaged grain size approximate 30 μm was achieved. Then the GBICs were determined by electron backscatter diffraction (EBSD) measurement and stereology-based five-parameter analysis (FPA) coupled with crystallographic analysis after the grain boundaries (GBs) were filtered according to their misorientations (e.g. angle/axis pair). The results revealed that the GBICs for any group of GBs with a given misorientation are not random, showing remarkable preference on the planes of low Miller index forming mixed and twist GBs. The work also demonstrated that among the high angle boundaries (HABs), {1 1 1}/{1 1 1}, including coherent ∑3 boundaries, is the most frequent GBIC, mainly due to the GBs formed by rotations around <1 1 1>, <1 2 2> and <1 1 2> axes. Near coincidence site (NCS) and O-lattice theory analyses indicate that the {1 1 1}/{1 1 1} GBICs usually possess higher planar coincidence site density (PCSD) and definite dislocation structures compared to the general GBs, implying their more structural stability when only crystallography is taken into account. This result agrees very well with the recent results obtained by molecular dynamic simulations. It is significant to the grain boundary engineering (GBE) in the high stacking fault energy (SFE) face-centered cubic (FCC) materials such as aluminum and its alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multifunctional Utilization of Pitch-Coated Carbon Fibers in Lithium-Based Rechargeable Batteries

This work reports carbon fibers as an electrode material and current collector for dual-carbon and lithium-ion batteries. Here, fully graphitic and semigraphitic carbon fibers undergo anion intercalation beyond 4.5 V versus Li/Li + . Symmetric dual-carbon full cells using a pitch-coated fully graphitic carbon fiber mat as both cathode and anode delivers an energy-density of 276 and 322 Wh kg -1 at 342 W kg -1 power density in the voltage range of 3.0–5.0 and 3.0–5.2 V, respectively. On the other hand, nongraphitic carbon fibers do not exhibit anion intercalation up to 5.2 V and can be used as a current collector. They also possess a larger number of Li + storage sites in their randomly oriented microstructure when used as an anode. A lithium-ion full cell with double carbon-coated C-LiFePO 4 loaded on nongraphitic carbon fiber as a cathode and pitch-coated nongraphitic carbon fiber as an anode exhibits 202.6 and 75.2 Wh kg -1 energy density at power densities of 46.75 W kg -1 and 11.7 kW kg -1 , respectively in 2.0–3.5 V range. This pitch-coated carbon fiber-based battery configuration eliminates the need for metal foils and costly fluorinated binders, lowers overall weight of the cell, and is capable of sustaining mechanical stress and thermal shock.

PF6− intercalation↗
DOE OSTI2020

A description of structured waves in shock compressed particulate composites

Dynamic compression of composite materials is of scientific interest because the mechanical mismatch between internal phases challenges continuum theories. Typical assumptions about steady wave propagation and quasi-instantaneous state changes require reexamination along with the need for time-dependent models. To that end, data and models are presented here for the shock compression of an idealized particulate composite. To serve as a generic representative of this material class, a polymer matrix was filled with tungsten particles, ranging from 1 to 50 vol. %. This creates a simple microstructure containing randomly scattered particles with an extreme impedance mismatch to the binding matrix. These materials were parallel plate impact loaded by Al flyers traveling at 1.8–5.0 km/s. Velocimetry provided records of the equilibrium state and the compression wave structure for each case with trends quantified by an empirical fit. The same quantities were also studied as a function of the wave's propagation distance. A homogenized viscoelastic model then made it possible to progress from cataloging trends to making predictions. Starting from a Mie–Gruneisen equation of state, additional time varying terms were added to capture the transient response. After calibration, accurate predictions of the steady wave structure were possible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Light Extraction System for OLED (LESO)

The DOE Office of Energy Efficiency and Renewable Energy is funding development of Solid-State Lighting (SSL) to replace incandescent and fluorescent technologies. A more aggressive innovation schedule could achieve site electricity consumption reductions from current projections of 40% to 60% by the year 2030 when compared to the no-LED scenario in the United States. These increased reductions would total an increase in savings of 395 TWh of energy. Based on preliminary data showing improvements of 2x in extraction efficiency with diffuser films, we will optimize surface relief structures to maximize the light extraction efficiency of OLED devices and test the optimized structures in prototype samples. To address the DOE desire for rapid SSL acceptance, Luminit, LLC, proposes to develop a new Light Extraction System for OLED (LESO) implemented in an ultraviolet (UV)-curable HRI polymer. The LESO uses optimized surface relief structures in high-index and low-index interfaces, which will significantly increase light extraction from the OLEDs. The LESO will significantly reduce environmental pollution compared to incandescent, compact fluorescent (CFL), and LED lamps. It will do so at a low price compared to other technologies, and with extremely high quality lighting (nearly perfect color matching, for example). Through LESO adoption, both CO 2 and other pollutants will be reduced by hundreds of megatons annually.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Multi-fidelity Uncertainty Quantification for Homogenization Problems in Structure-Property Relationships from Crystal Plasticity Finite Elements

Crystal plasticity finite element method (CPFEM) has been an integrated computational materials engineering (ICME) workhorse to study materials behaviors and structure-property relationships for the last few decades. These relations are mappings from the microstructure space to the materials properties space. Due to the stochastic and random nature of microstructures, there is always some uncertainty associated with materials properties, for example, in homogenized stress-strain curves. For critical applications with strong reliability needs, it is often desirable to quantify the microstructure-induced uncertainty in the context of structure-property relationships. However, this uncertainty quantification (UQ) problem often incurs a large computational cost because many statistically equivalent representative volume elements (SERVEs) are needed. In this article, we apply a multi-level Monte Carlo (MLMC) method to CPFEM to study the uncertainty in stress-strain curves, given an ensemble of SERVEs at multiple mesh resolutions. By using the information at coarse meshes, we show that it is possible to approximate the response at fine meshes with a much reduced computational cost. We focus on problems where the model output is multi-dimensional, which requires us to track multiple quantities of interest (QoIs) at the same time. In conclusion, our numerical results show that MLMC can accelerate UQ tasks around 2.23x, compared to the classical Monte Carlo (MC) method, which is widely known as ensemble average in the CPFEM literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Unraveling the implications of finite specimen size on the interpretation of dynamic experiments for polycrystalline aluminum through direct numerical simulations

Normal and Pressure-shear plate impact (NPI and PSPI) experiments are popular experimental techniques for studying the mean-field macroscopic behavior of polycrystalline metals under high-rate dynamic loading. However, since both configurations rely upon geometry for subjecting the specimen to high strain rates, these experiments often involve a limited specimen size. Moreover, because of the inherent heterogeneities present within polycrystalline metals, it is difficult to ascertain if the size of the specimen and/or regions where measurements are made are sufficiently large for making representative inferences about the mean-field macroscopic properties from single-point velocity measurements. In the present study, we quantify the expected measurement variability on observable point measurements in NPI and PSPI experiments by carrying out direct numerical simulations (DNS) of statistically representative polycrystalline microstructures subjected to dynamic compression and compression-shear loading. In particular, we consider the role of specific material heterogeneities (e.g. the grain-to-grain difference in size, crystallographic orientation) on dispersion in the normal and transverse particle velocity records and on local fluctuations in key state variables (e.g. velocity, accumulated plastic strain) by incorporating these effects directly into a representative synthetic microstructure geometry and crystalline description of pure polycrystalline aluminum. The form of the present study is a large parametric investigation, consisting of ten ensembles of one hundred simulations. Each of the thousand simulations reflects a randomly realized synthetic microstructure in one of five cases of decreasing average grain size for the two loading configurations. Our analysis of the DNS results demonstrates that for both of these experimental configurations, the grain size directly correlates with the coefficient of variation (CV) in simulated point measurements, showing a convergent decrease in CV to zero (i.e. particle velocity record approaches the mean-field value) with decreasing grain size. Remarkably, the magnitude of variations in the particle velocity record is shown to be largest where the deviatoric stresses are most significant. In the case of NPI, this occurs at the elastic and plastic wavefront, whereas, in the case of PSPI, the magnitude of fluctuations are approximately constant throughout the experimental window time. The reasoning for the scatter in particle velocity due to the heterogeneous microstructure is demonstrated to be dependent on the mechanisms for accommodating deformation and on the interaction of reflection waves generated at sites of heterogeneities occurring at the scale of grains. Lastly, we develop a power-law description for the magnitude of scattering versus characteristic length, which provides a statistical framework for assessing the required number of grains per characteristic specimen dimension for minimizing scatter within these two experimental configurations (NPI, PSPI).

36 MATERIALS SCIENCE↗
DOE OSTI2026

In-situ observations of cyclic deformation in an extruded Mg-2Nd-1Y-0.1Zr-0.1Ca alloy

In this study, the evolution of deformation mechanisms during cyclic loading in an extruded, solution-treated Mg–2Nd–1Y–0.1Zr–0.1Ca alloy was investigated using a combination of in-situ loading, scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and focused ion beam (FIB) nanofabrication. The initial microstructure exhibited a random crystallographic texture with no preferred grain orientation. Flat, rectangular dog-bone specimens were subjected to load-controlled, fully reversed fatigue for 50 cycles, during which the same region was sequentially mapped to track microstructural changes. After 10 cycles of loading deformation twins were observed. During tensile reloading detwinning or narrowing of those twinned regions occurred. After 20 cycles, detwinning ceased and residual twins remained in the material. SEM imaging revealed numerous surface slip traces after cyclic loading. EBSD-assisted slip trace analysis identified the activation of prismatic and pyramidal < c+a> slip systems during low-cycle fatigue. Site-specific scanning transmission electron microscopy (STEM) further revealed that deformation was also accommodated by basal < a> slip and the dissociation of < c+a> dislocations. Center-of-symmetry (COS) analysis confirmed that the dissociation of < c+a> dislocations resulted in the formation of I₁ intrinsic stacking faults after cyclic loading. These findings provide new insights into the complex interplay of dislocation mechanisms governing fatigue deformation in rare-earth-containing Mg alloys.

Cyclic deformation↗