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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↗
NASA NTRS2021

Micromechanics-based Modeling of Laminated SiC/SiC Ceramic Matrix Composites

The behavior and response of ceramic matrix composites (CMCs), in particular silicon carbide fiber reinforced silicon carbide matrix (SiC/SiC), is affected by many factors such as variation of fiber volume fraction, residual stresses resulting from processing of the composites at high temperature, random microstructures, and the presence of matrix flaws (e.g., voids, pores, cracks etc.) as well as general material nonlinearity and heterogeneity that occurs randomly in a composite. Residual stresses arising from the phase change of constituents are evaluated in this paper and it is shown that they do influence composite strength and need to be properly accounted for. Additionally, the microstructures (location of fiber centers, coating thickness etc.) of advanced CMCs are usually disordered (or random) and fiber diameter and strength typically have a distribution. They rarely resemble the ordered fiber packing (square, rectangular, or hexagonal) that is generally assumed in micromechanics-based models with periodic boundary conditions for computational expediency. These issues raise the question of how should one model such systems effectively? Can an ordered hexagonal packed repeating unit cell (RUC) accurately represent the random microstructure behavior? How many fibers need to be included to enable accurate representation? Clearly, the number of fibers within an RUC must be limited to insure a balance between accuracy and efficiency. NASA’s in-house micromechanics-based code MAC/GMC provides a framework to analyze such RUCs for the overall composite behavior and the FEAMAC computer code provides linkage of MAC/GMC to the commercial FEA code, ABAQUS. The appropriate level of discretization of the RUC as well as the analysis method employed, i.e., Generalized Method of Cells (GMC) or High Fidelity Generalized Method of Cells (HFGMC), is investigated in this paper in the context of a unidirectional as well as a cross-ply laminated CMC. Results including effective composite properties, proportional limit stress (an important design parameter) and fatigue are shown utilizing both GMC as well as HFGMC. Finally, a few multiscale analyses are performed on smooth bar test coupons as well as test coupons with features such as open-hole and double notches using FEAMAC. Best practices and guidance are provided to take these phenomena into account and keep a proper balance between fidelity (accuracy) and efficiency. Following these guidelines can account for important physics of the problem and provide significant advantages when performing large multiscale composite structural analyses.

Ceramic Matrix Composites↗
DOE OSTI2014

Towards ultra-stiff materials: Surface effects on nanoporous materials

The significant rise in the strength and stiffness of porous materials at nanoscale cannot be described by conventional scaling laws. This letter investigates the effective Young's modulus of such materials by taking into account surface effect in a microcellular architecture designed for an ultralight material whose stiffness is an order of magnitude higher than most porous materials. We find that by considering the surface effects the predicted stiffness using Euler-Bernoulli beam theory compares well to experimental data for spongelike nanoporous gold with random microstructures. Analytical results show that, of the two factors influencing the effective Young's modulus, the residual stress is more important than the surface stiffness.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2017

Micromechanics of Composite Materials Governed by Vector Constitutive Laws

The high-fidelity generalized method of cells micromechanics theory has been extended for the prediction of the effective property tensor and the corresponding local field distributions for composites whose constituents are governed by vector constitutive laws. As shown, the shear analogy, which can predict effective transverse properties, is not valid in the general three-dimensional case. Consequently, a general derivation is presented that is applicable to both continuously and discontinuously reinforced composites with arbitrary vector constitutive laws and periodic microstructures. Results are given for thermal and electric problems, effective properties and local field distributions, ordered and random microstructures, as well as complex geometries including woven composites. Comparisons of the theory's predictions are made to test data, numerical analysis, and classical expressions from the literature. Further, classical methods cannot provide the local field distributions in the composite, and it is demonstrated that, as the percolation threshold is approached, their predictions are increasingly unreliable. XXXX It has been observed that the bonding between the fibers and matrix in composite materials can be imperfect. In the context of thermal conductivity, such imperfect interfaces have been investigated in micromechanical models by Dunn and Taya (1993), Duan and Karihaloo (2007), Nan et al. (1997) and Hashin (2001). The present HFGMC micromechanical method, derived for perfectly bonded composite materials governed by vector constitutive laws, can be easily generalized to include the effects of weak bonding between the constituents. Such generalizations, in the context of the mechanical micromechanics problem, involve introduction of a traction-separation law at the fiber/matrix interface and have been presented by Aboudi (1987), Bednarcyk and Arnold (2002), Bednarcyk et al. (2004) and Aboudi et al. (2013) and will be addressed in the future.

micromechanics↗
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 OSTI2016

Microstructural characterization of random packings of cubic particles

Understanding the properties of random packings of solid objects is of critical importance to a wide variety of fundamental scientific and practical problems. The great majority of the previous works focused, however, on packings of spherical and sphere-like particles. We report the first detailed simulation and characterization of packings of non-overlapping cubic particles. Such packings arise in a variety of problems, ranging from biological materials, to colloids and fabrication of porous scaffolds using salt powders. In addition, packing of cubic salt crystals arise in various problems involving preservation of pavements, paintings, and historical monuments, mineral-fluid interactions, CO 2 sequestration in rock, and intrusion of groundwater aquifers by saline water. Not much is known, however, about the structure and statistical descriptors of such packings. We have developed a version of the random sequential addition algorithm to generate such packings, and have computed a variety of microstructural descriptors, including the radial distribution function, two-point probability function, orientational correlation function, specific surface, and mean chord length, and have studied the effect of finite system size and porosity on such characteristics. Here, the results indicate the existence of both spatial and orientational long-range order in the packing, which is more distinctive for higher packing densities.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Microstructure Quantification and Random Forest Regression Models for Li4Ti5O12–Ni Property Prediction

All-solid-state structural lithium-ion batteries are sought to enable all-electric propulsion in next generation aerospace concepts through improved safety and systems level weight savings. In this work, the influence of processing conditions on microstructural evolution was evaluated for anode composites of strain-free Li4Ti5O12 and metallic nickel current collector. Beyond size distributions, this study explored methods of quantifying microstructural features that describe changes in the spatial distribution and coalescence of nickel particles as a function of sample composition and sintering conditions. Processing-microstructure-property relationships were described by microstructure quantifiers including nickel particle count per area, nearest neighbor distance distribution, and edge-to-edge distance distribution. Machine learning methods were applied to compare the relative influence of processing conditions and microstructural features on electrical conductivity and mechanical strength to optimize for simultaneous energy storage and load bearing performance. Insights gained from this work inform future evaluation of alternative energy storage materials and microstructures for multifunctional performance, and generation of microstructural descriptors strengthens modeling across length scales.

anode↗
DOE OSTI2016

A microstructure-guided constitutive modeling approach for random heterogeneous materials: Application to structural binders

This paper presents a microstructure-guided modeling approach to predict the effective elastic response of heterogeneous materials, and demonstrates its application toward two highly heterogeneous, uncon- ventional structural binders, i.e., iron carbonate and fly ash geopolymer. Microstructural information from synchrotron X-ray tomography (XRT) and intrinsic elastic properties of component solid phases from statistical nanoindentation are used as the primary inputs. The virtual periodic 3D microstructure reconstructed using XRT, along with periodic boundary conditions is used as a basis for strain- controlled numerical simulation scheme in the linear elastic range to predict the elastic modulus as well as the stresses in the microstructural phases. The elastic modulus of the composite material predicted from the microstructure-based constitutive modeling approach correlates very well with experimental measurements for both the materials considered. This technique efficiently links the microstructure to mechanical properties of interest and helps develop material design guidelines for novel heterogeneous composites

36 MATERIALS SCIENCE↗
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 OSTI2016

Fabrication and characterization of powder metallurgy tantalum components prepared by high compaction pressure technique

The present study has investigated the consolidation behaviors of tantalum powders during compaction and sintering, and the characteristics of sintered components. For die compaction, the densification behaviors of the powders are simulated by finite element analyses based on the yield function proposed by Shima and Oyane. Accordingly, the green density distribution for coarser particles is predicted to be more uniform because they exhibits higher initial relative tap density owing to lower interparticle friction. It is also found that cold isostatic pressing is capable of producing higher dense compacts compared to the die pressing. However, unlike the compaction behavior, the sintered density of smaller particles is found to be higher than those of coarser ones owing to their higher specific surface area. The maximum sintered density was found to be 0.96 of theoretical density where smaller particles were pressed isostatically at 400 MPa followed by sintering at 2000 °C. Moreover, the effects of processing conditions on grain size and texture were also investigated. The average grain size of the sintered specimen is 30.29 μm and its texture is less than 2 times random intensity. Consequently, it is concluded that the higher pressure compaction technique is beneficial to produce high dense and texture-free tantalum components compared to hot pressing and spark plasma sintering. - Highlights: • Higher Ta density is obtained from higher pressure and sintering temperature. • High compaction method enables P/M Ta to achieve the density of 16.00 g·cm{sup −3}. • A P/M Ta component with fine microstructure and random orientation is developed.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Numerical models for the prediction of failure for multilayer fusion Al-alloy sheets

Initiation and propagation of cracks in monolithic and multi-layer aluminum alloys, called “Fusion”, is investigated. 2D plane strain finite element simulations are performed to model deformation due to bending and to predict failure. For this purpose, fracture strains are measured based on microscopic pictures of Nakajima specimens. In addition to, micro-structure of materials is taken into account by introducing a random grain distribution over the sheet thickness as well as a random distribution of the measured yield curve. It is shown that the performed experiments and the introduced FE-Model are appropriate methods to highlight the advantages of the Fusion material, especially for bending processes.

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↗