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At least 1,405 records · Page 78

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Domain knowledge-informed, process-mapping AI graph for designing Fe-based alloys

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Continuous improvement in efficiency of a power plant relies on designing materials for use at increasingly higher temperature and/or pressure, for 100,000s hours of operation. Due to complexity, non-linearity and high-dimensionality of the problem, traditional Machine Learning (ML) approaches require unreasonably large datasets for the data-driven model development. Science-based material and process engineering complements hard data with, sometimes soft and intuitive, empirical domain knowledge. Artificial Intelligence (AI) was used in this study to incorporate such knowledge into computational graph architecture (process-mimicking artificial neuron design, causal layer and graph structures, ensemble modeling of latent states) and learning procedures (variable transformation, fuzzy physics pre-training and freezing of deep layers, virtual microstructure representation, and adversarial multi-objective optimization). The first alloys design pathways suggested by the AI tool (pyroMind) passed a preliminary engineering review on soundness and transparency.</span>

Romanov, Vyacheslav↗

DOE OSTI2025

Interface morphology and dislocation-mediated processes during rapid solidification of thin films

Rapid solidification experiments have, in recent years, revealed a wealth of new microstructural phenomena that suggest a strong connection between the kinetics of solidification and the crystalline structures that emerge as a result. In this work, we investigate the interplay between interface morphology and defect-mediated processes during rapid solidification conditions using a Phase Field Crystal (PFC) model, enabling us to simultaneously and efficiently explore the physics of solidification and elasto-plasticity in the formalism of a single-field theory. We predict that there are two mechanisms by which dislocations emitted directly from the solid–liquid interface induce orientation gradients as well as the formation of subgrain boundaries within a single solidifying cell. We relate these mechanisms to the morphology of the moving solid–liquid interface and identify a suitable control parameter in the PFC model with which we can go between said morphologies by effectively changing the relative strength of the capillary length and kinetic coefficients of the solid–liquid interface. Thus, we are able to provide mechanistic explanations for several microstructural features (with an emphasis on orientation gradients and subgrain boundaries) observed during the rapid solidification of pure materials. We also provide a simple explanation for the formation of “jagged” subgrain boundaries, which is consistent with our experimental observations in rapidly solidified samples of Aluminum, whose mechanisms have thus far been unknown.

Interface morphology↗

DOE OSTI2022

Characterization and Accelerated Life Testing of a New Solid Oxide Electrolysis Cell

The project aims to develop mechanistic degradation models that realistically predict long-term Solid Oxide Electrolysis Cell (SOEC) durability, using input data from accelerated electrochemical life testing combined with quantitative microstructural and microchemical evaluation. A promising SOEC type will be further developed. The understanding achieved by combining experimental results and theory will be used to guide improvements in long-term SOEC durability, and validate that this technology can reach DOE H 2 production cost and durability targets. Planned outcomes include: (1) new experimental accelerated testing data on SOEC degradation at the oxygen electrode, fuel electrode, and electrolyte; (2) predictive theory of degradation developed based on the accelerated test data; (3) new electrode materials and processing methods that minimize degradation rate; (4) determination of the impact of SOEC electrolyte thickness and electrode composition/microstructure on performance and degradation; (5) determination of the operating conditions where degradation is minimized; and (6) validation of degradation models for extrapolating accelerated test data to predict long-term durability.

08 HYDROGEN↗

DOE OSTI2024

Bayesian Conavigation: Dynamic Designing of the Material Digital Twins via Active Learning

Scientific advancement is universally based on the dynamic interplay between theoretical insights, modeling, and experimental discoveries. However, this feedback loop is often slow, including delayed community interactions and the gradual integration of experimental data into theoretical frameworks. This challenge is particularly exacerbated in domains dealing with high-dimensional object spaces, such as molecules and complex microstructures. Hence, the integration of theory within automated and autonomous experimental setups, or theory in the loop-automated experiment, is emerging as a crucial objective for accelerating scientific research. The critical aspect is to use not only theory but also on-the-fly theory updates during the experiment. Furthermore, we introduce a method for integrating theory into the loop through Bayesian conavigation of theoretical model space and experimentation. Our approach leverages the concurrent development of surrogate models for both simulation and experimental domains at the rates determined by latencies and costs of experiments and computation, alongside the adjustment of control parameters within theoretical models to minimize epistemic uncertainty over the experimental object spaces. This methodology facilitates the creation of digital twins of material structures, encompassing both the surrogate model of behavior that includes the correlative part and the theoretical model itself. While being demonstrated here within the context of functional responses in ferroelectric materials, our approach holds promise for broader applications, such as the exploration of optical properties in nanoclusters, microstructure-dependent properties in complex materials, and properties of molecular systems.

Microscopy↗

DOE OSTI2026

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗

DOE OSTI2021

Fracture Mechanics—Theory, Modeling and Applications

The field of fracture mechanics was developed during the throes of World War II, and since then, it has been a very active area of research. This is a very energetic and vibrant field because fracture processes are relevant for a vast range of engineering applications spanning different temporal and length scales. Depending on the application, material fracture and fragmentation may be either a desirable feature (for example, for the purpose of hydraulic fracturing operations), or something that is to be avoided at all costs (for example, in key components of mechanical systems). In some other instances, fractures are already present and must be accommodated through novel design (for example, in the case of earthquake ruptures occurring in the Earth’s crust). Because of this wide spectra of motivation, there is a continuous need for the fracture mechanics research community to gain more insight on how fractures are created, evolve, and interact with themselves and with material microstructures. In addition, there are still many remaining questions about how fracture propagation, growth, and interaction impact overall material behavior, and how to develop accurate models to predict this behavior.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Simulation of Oxidative Etch Pit Formation and Growth on FiberForm

Erosion of carbon surfaces due to oxidation does not occur uniformly but through the formation of localized etch pits because of active surface sites. These active sites are formed due to the presence of atomic defects on the carbon surface and have much higher reactivity compared to average non-defective sites. Thus, these active sites are the first to react during ablation, resulting in their removal. This causes all the neighboring atoms to be defective, and increasing their reactivity, thus leading to localized carbon removal around these “active” sites. In this manner, these highly reactive defects serve as nucleation sites for the formation and growth of etch pits, with detrimental effects on the structural integrity. In order to understand the influence of these etch pits on the material properties of carbon fiber microstructures, we have developed a new capability within direct simulation Monte Carlo (DSMC) to capture the etch pit formation process. This capability is developed within the DSMC code SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) and can model the material removal in the presence of active sites leading to the formation of etch pits. The focus of the current work will be to study the effect of etch pits on the material properties of FiberForm, the precursor substrate of the PICA Thermal Protection System (TPS) material. The microstructure of virgin FiberForm obtained directly from X-ray microtomography scans is used within SPARTA to obtain the ablated geometries with etch pits. These pitted microstructures are then imported into the Porous Microstructure Analysis (PuMA) software and various material properties such as thermal conductivity, elasticity, and permeability are computed. The variation of these properties because of the complex evolution of the surface topology due to the formation of etch pits is studied and analyzed. Furthermore, the effect of pitting is compared to the case of uniform radial shrinking of fibers, which has been the standard for modelling ablation of carbon structures, and significant differences are observed. Thus, a physically realistic model of material removal through the formation of etch pits will be helpful in predicting the degradation of carbon-based TPS more accurately during oxidation; as well as other mechanisms such as spallation, which involves the removal of chunks of material into the flow due to the growth of etch pits. This will ultimately improve our understanding of the failure modes in these materials due to ablation.

DSMC↗

NASA NTRSDate not supplied

Simulation of Oxidative Etch Pit Formation and Growth on FiberForm

DSMC↗

DOE OSTI2022

Stochastic Modeling in a Multimaterial Continuum Mixture Shock Physics Code

Stochastic modelling approaches are presented to capture random effects at multiple time and length scales. Random processes that occur at the microscale produce nondeterministic effects at the macroscale. Here we present three stochastic modeling approaches that describe random processes at microscopic length scales and map these processes to the macroscopic length scale. The first stochastic modeling approach is based upon a particle based numerical technique to solve a Stochastic Differential Equation (SDE) using an arbitrary diffusion process to capture random processes at the microstructural level. The second approach prescribes a Probability Density Function (PDF) for the drift and diffusion of the random variable derived using the forward and backward Kolmogorov equations. This method requires mean and drift evolution PDF transport equations. The third approach is the coupling of multiple random variables which are dependent on each other. The relationship of the PDFs and a coupling function, known as a copula, produces a Joint Probability Density Function (JPDF). These stochastic modeling approaches are implemented into a Multiple Component (MC) shock physics computational code and used to model statistical fracture and reactive flow applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Three-dimensional phase field sintering simulations accounting for the rigid-body motion of individual grains

Sintering is a widely used powder processing technique in industrial applications. During sintering, atoms migrate to decrease the energy of the system via two main mechanisms: coarsening and densification, both of which lead to significant morphological variation of the sintered microstructure. When simulating sintering dynamics, the phase-field method has been broadly utilized because of its convenience in tracking morphology evolution. When a large number of grains is involved, it is common to use the same order parameter to describe multiple grains that are not in direct contact with one another (in order to reduce the computational memory demands). However, with this treatment it is difficult to handle the rigid-body motion of individual grains during densification. In this work, an implementation scheme is introduced to overcome the challenge of calculating individual particle motion based on existing equations. It uses a grouping algorithm and sets a cutoff radius on each grain for calculating the particle velocity during densification. This method allows for the incorporation of the densification mechanism, which has been commonly ignored in previous work, into phase-field sintering models in three-dimensional simulations with a large number of particles/grains. Moreover, through combination with the smoothed boundary method, material properties of sintered microstructures, such as the effective diffusivity and Young’s modulus, can be calculated during the sintering processes.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Atomistic simulations of nanoindentation on nanoglasses: Effects of grain size and gradient microstructure on the mechanical properties

The use of nanoglass (NG) microstructures has been shown as an effective strategy to improve the ductility of rather brittle metallic glass alloys. To evaluate the effects of grain size and gradient design on the mechanical properties of NGs, we perform molecular dynamics simulations of nanoindentation on Cu 64 Zr 36 NGs. We consider samples with uniform 3 and 7 nm grain sizes as well as gradient microstructures with gradient grain sizes varying from 3 to 7 nm. Here, the results show that the deformation mechanism in NGs with small grain sizes is dominated by the activation and evolution of multiple shear transformation zones. Increasing grain sizes enhances the elastic modulus and hardness at the cost of reduced abrasion resistance. Though the average grain size at the indentation surface plays a crucial role in the deformation behavior of gradient NG models, their strain localization and plastic deformation states are affected by the grain sizes far from the indenter. Desired combinations of mechanical properties can be realized by different NG microstructure designs.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A physically based mechanical model for Mullins effect in thermoplastic polyurethanes

Despite decades of research, connecting the chemical and physical structure of thermoplastic polyurethanes to their mechanical properties remains highly challenging. Of particular note are their large-deformation and rate-dependent behaviors, which vary greatly with molecular chemistry, including the type and relative content of soft and hard segments. In this work, we develop a physically motivated mechanical theory for predicting the behavior of thermoplastic polyurethanes. The theory incorporates a representation of microstructural evolution during mechanical deformation, which captures the signatures of stress softening over cyclic loading (commonly referred to as the Mullins effect). There are only eight physically motivated fitting parameters, including a direct dependence on the hard segment fraction. The model predicts that increasing the hard segment fraction leads to higher stiffness and greater energy dissipation, in quantitative agreement with published experimental data. Furthermore, we provide a comprehensive analysis of the model and validate its predictions across several independent datasets focused on mechanical characterization. Direct comparisons to experimental data demonstrate its predictive capability on the effect of loading rate, cyclic deformations, and applied tension or compression. Altogether, this work establishes a predictive framework that connects polymer chemistry and microstructure to emergent mechanical behaviors.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Microstructural design of fiber composites

The optimum performance design of composite microstructures is discussed. The forces driving progress in fiber composites are examined, and recent developments in the mechanics of laminated composites are surveyed, emphasizing thick laminates, hygrothermal effects, and thermal transient effects. The strength of continuous-fiber composites is discussed, presenting analyses of local load redistribution due to fiber breakages and treatments of statistical tensile strength theories. Modes of failure of laminated composites are examined. Elastic, physical, and viscoelastic properties as well as the strength and fracture behavior of short-fiber composites are studied, and it is shown how the performance of composites can be controlled by selecting material systems and their geometric distributions. 2D textile structural composites based on woven, knitted, and braided preforms are considered, and techniques for analyzing and modeling the thermomechanical behavior of 2D textile composites are presented. Recent developments in the processing of 3D textile preforms are introduced and the processing-microstructure relationship is demonstrated. Finite elastic deformation of flexible composites is addressed.

Chou, Tsu-Wei↗

DOE OSTI2024

A Multiphysics Multiscale Simulation Platform for Damage, Environmental Degradation, and Life Prediction of CMCs in Extreme Environments

This project successfully developed a multiphysics, multiscale computational framework to enhance the design and development of CMCs, with a focus on modeling highly nonlinear, time-dependent damage mechanisms and material degradation under extreme conditions, such as those experienced in turbine service environments. The project made significant advances in improving our understanding of progressive damage, oxidative degradation, and time-dependent inelastic deformation in CMCs, with particular attention to the role of uncertainties in predictions. Key outcomes include the integration of advanced material characterization, uncertainty quantification, and multiphysics constitutive models to predict the behavior of CMCs over their service life. A novel multiscale methodology was employed, which integrated microscale constituent behaviors with structural-scale responses, enabling the manufacturing defects in the microstructure that are prone to damage nucleation. Through the development of DL algorithms, the project advanced the prediction of damage initiation and crack propagation, taking into account the defect morphology and statistical variations across multiple scales. The framework was rigorously validated using thermomechanical experiments, which tested CMCs under various mechanical loadings at elevated temperatures, further enhancing the model's predictive capability. Overall, the research outcomes have provided a more accurate, reliable method for predicting CMC component life, significantly advancing material design, and improving component reliability in extreme environments. This work has strong implications for the optimization of turbine components and other high-performance applications where CMCs are used.

03 NATURAL GAS↗

NASA NTRS2002

Effects of Thermomechanical History on the Tensile Behavior of Nitinol Ribbon

Shape memory alloys (SMAs) have enormous potential for a wide variety of applications. A large body of work exists on the characterization of the microstructure and stress-strain behavior of these alloys, Nitinol (NiTi) in particular. However, many attributes of these materials are yet to be fully understood. Previous work at NASA Langley Research Center (LaRC) has included fabrication of hybrid composite specimens with embedded Nitinol actuators and modeling of their thermomechanical behavior. An intensive characterization effort has been undertaken to facilitate fundamental understanding of this alloy and to promote implementation of Nitinol in aerospace applications. Previous work revealed attributes of the Nitinol ribbon that were not easily rationalized with existing data in the literature. In particular, tensile behavior at ambient temperature showed significant dependence on the thermomechanical history prior to testing. The present work is focused on characterizing differences in the microstructure of Nitinol ribbons exposed to four different thermomechanical histories and correlation of the microstructure with tensile properties. Differential scanning calorimetry (DSC) and x-ray diffraction (XRD) analysis were employed to rationalize the microstructures present after exposure to various thermomechanical histories. Three of the Nitinol ribbon conditions were reversible upon heating (in the DSC) through the reverse transformation temperature (A(sub f) to transform the microstructure to austenite. However, the prior thermomechanical conditioning for the Nitinol ribbon that reflected the entire fabrication procedure (4% thermal cycle condition) was found to have an irreversible effect on the microstructure, as it remained unchanged after repeated complete thermal cycles. Tensile tests were conducted to determine the effect of prior thermomechancal conditioning on both the tensile behavior of the Nitinol ribbons and the stress state of the microstructure. The stress-strain behavior of the Nitinol actuators appears to be governed by the interplay between two major variables: namely, microstructural constituents such as the R-phase and the martensite; and the stress state of these constituents (whether twinned with low residual stresses, or detwinned with high residual stresses). The most significant difference in the stress-strain behavior of the four conditions, the critical stress required to achieve an initial stress plateau, was found to depend on both the amount and stress state (twinned or detwinned) of R-phase present in the initial microstructure. Thus, the effect of prior thermomechanical processing is critical to the resulting tensile behavior of the Nitinol actuator. For numerical modeling inputs one must take into account the entire fabrication process on the Nitinol actuator.

Lach, Cynthia L.↗

DOE OSTI2021

A Review: Microstructural and Phase Evolution in Alloys during Extended Plastic Deformation

Materials in service and during processing are often subjected to plastic deformation. For multi-phase metallic alloys, simple geometric models and atomistic simulations suggest that two distinctive regimes in these materials’ evolution during deformation exist. At low strains, evolutions are often dominated by the kinetic roughening of interfaces, which results from the superdiffusive transport of matter in sheared crystals. Furthermore, at high strains and temperatures where thermal diffusion is sluggish, on the other hand, shearing- induced forced atomic mixing dominates these evolutions, resulting in significantly enhanced solubility. Distinguishing these two regimes is shown to provide a convenient framework for rationalizing and analyzing recent experiments and simulations on wear of layered structures in the low strain-regime and nonequilibrium phase co-existence and self-organization in highly immiscible or reactive alloy systems in the high-strain regime.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Microstructural characterization and assessment of mechanical properties of concrete based on combined elemental analysis techniques and Fast-Fourier transform-based simulations

This paper presents a pixel-based modeling approach of concrete which combines an experimental characterization of concrete and the Fast-Fourier transform simulations. High-resolution phase maps created from experimental characterization by micro X-ray fluorescence, energy dispersive X-ray analysis, and X-ray diffraction contain 9 different phases, including 22.17 vol.% of hydrated cement paste, 54.21 vol.% of minerals, and 23.62 vol.% of interfaces. These phases provide the input for determining the effective elastic properties, coupled with Fast-Fourier transform-based simulation. The simulation results show that the effective range of Young’s modulus of concrete is comparable with the range of experimental values ~ 37 ± 4 GPa with the assumption of realistic properties of interfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Impact of titanium content on the thermo-mechanical and oxidation response of TiAlTa

This study aimed to analyze how the addition of titanium (Ti) to TiAlTa alloys affects their mechanical properties (Young’s modulus and hardness) and oxidation behavior. Alloys with three different Ti additions and equi-atomic Al and Ta were fabricated with nominal compositions of 33Ti-33Al-33Ta at%, 50Ti-25Al-25Ta at%, and 70Ti-15Al-15Ta at%. Phase identification of as-processed and compositionally homogenized alloys was conducted by coupling various electron microscopy, diffraction, and chemical analysis techniques. Composition and structures were modeled using CALPHAD-based phase predictions and compared with experimental results. Each of the alloys exhibited a unique set of microstructures with distinctly different ordered precipitates, dependent on cooling rate and chemical composition. Subsequently, nanoindentation tests were performed at temperatures of 25°C, 250°C, 500°C, and 750°C. Oxidation studies were conducted under static air at 750°C for up to 200 h. 33Ti-33Al-33Ta at% and 70Ti-15Al-15Ta at% alloys showed higher hardness and modulus than 50Ti-25Al-25Ta at% at room temperature. The 50Ti-25Al-25Ta at% alloy exhibited higher hardness and modulus values but lower oxidation resistance at 750°C when compared with the other specimens. The X-ray photoelectron spectroscopy experiments were conducted to further analyze the oxides present in the samples. Despite each sample displaying combinations of mixed oxide layers, TiO 2 was the preferred oxide forming in the 50Ti-25Al-25Ta composition, while the other samples preferred to form Al 2 O 3 . In conclusion, the findings from this systematic exploration of phase evolution in the TiAlTa alloy space provide insights for optimized material chemistries, processing, and properties.

36 MATERIALS SCIENCE↗