Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Structural Properties”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Orientation-dependent structural properties during growth and growth mechanism of CoO films

The orientation-dependent local structural properties of CoO films on sapphire substrates during growth were investigated through linearly-polarized extended X-ray absorption fine structure (EXAFS) measurements. Specifically, CoO(1 1 1) and (100) crystals with a rock-salt structure (Fm3m) were epitaxially grown on alpha-Al2O3(0001) and (1012) substrates, respectively, at 700 degrees C using a radio-frequency sputtering system. The local structural properties of CoO films in the in-plane and out-of-plane orientations were quantitatively determined using linearly-polarized EXAFS at the Co K-edge during growth. The EXAFS analysis revealed that during the initial stages of growth, the local structural properties exhibit significant differences compared to thick films, with short atomic distances and large (small) Debye-Waller factors observed in the out-of-plane (in-plane) orientations. The local structural strain mostly diminished when approximately 20 CoO layers accumulated on the substrate. Density functional theory (DFT) calculations further supported these findings by confirming that cobalt atoms initially form stable bonds with the sapphire surface, leading to the simultaneous growth of oxygen and cobalt layers in a coordinated manner through layer-by-layer growth.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Determination of HART I Blade Structural Properties by Laboratory Testing

The structural properties of higher harmonic Aeroacoustic Rotor Test (HART I) blades were measured using the original set of blades tested in the German-dutch wind tunnel (DNW) in 1994. the measurements include bending and torsion stiffness, geometric offsets, and mass and inertia properties of the blade. the measured properties were compared to the estimated values obtained initially from the blade manufacturer. The previously estimated blade properties showed consistently higher stiffness, up to 30 percent for the flap bending in the blade inboard root section.

Jung, Sung N.↗
DOE OSTI2020

Physically Based Modeling of PEMFC Cathode Catalyst Layers: Effective Microstructure and Ionomer Structure–Property Relationship Impacts

Abstract This work presents a pseudo-two-dimensional proton exchange membrane fuel cell (PEMFC) model incorporating Nafion ionomer structure–property relationships in the cathode catalyst layer (CL) to capture and explain losses at low Pt loading. Structural data from neutron reflectometry and thin film Nafion conductivity measurements predict variations in the oxygen diffusion coefficient and ionic conductivity with changing CL ionomer thickness and Pt loading. By including these structure–property relationships, predicted polarization curves agree closely with previously published experimental data from cells with Pt loadings between 0.025 and 0.2 mg/cm2. Results demonstrate that structure–property relationships based on physically measurable ionomer and CL properties provide a feasible interpretation of PEMFC CL phenomena for a range of Pt loadings and help explain previously unaccounted-for losses at low Pt. Results also show that simulations must account for surface species coverage variations in order to properly capture the kinetic losses. Finally, results suggest that an increase in ionomer thickness surrounding the C/Pt surfaces may lead to improved cell performance due to improved ionic conductivity.

Electrochemistry↗
NASA NTRSDate not supplied

Integrated Process-Structure-Property Simulations for Additive Manufacturing Using the Open-Source Materialite Package

The microstructure and properties of additively manufactured (AM) metals are strongly dependent on process conditions. Therefore, process-structure-property (PSP) simulations are a useful tool for exploring process parameter space, studying process variations, and quantifying uncertainty in material properties. However, integrating process-structure and structure-property simulations often involves connecting multiple software packages. Each package may use unique data structures and require substantial domain knowledge. This presentation demonstrates PSP simulation capabilities of Materialite, an open-source package developed at NASA Langley Research Center. Materialite simplifies model linkages by using a common data structure and model interface, enabling straightforward simulation across a PSP model chain. Physics-based models, including kinetic Monte Carlo and crystal plasticity, are implemented within the package. The model interface is also intended to simplify implementation of new models and enable integration with external simulation tools. Example use cases include uncertainty quantification with PSP models and GPU-accelerated powder bed fusion AM process models.

additive manufacturing↗
DOE OSTI2026

Attention-based explainability for structure–property relationships

Machine learning methods are emerging as a universal paradigm for constructing correlative structure–property relationships in materials science based on multimodal characterization. However, this necessitates the development of methods for the physical interpretability of the resulting correlative models. Here, we demonstrate the potential of attention-based neural networks for revealing structure–property relationships and the underlying physical mechanisms, using the ferroelectric properties of PbTiO3 thin films as a case study. Through the analysis of attention scores, we disentangle the influence of distinct domain patterns on the polarization switching process. The attention-based Transformer model is explored both as a direct interpretability tool and as a surrogate for explaining representations learned via unsupervised machine learning, enabling the identification of physically grounded correlations. We compare attention-derived interpretability scores with classical SHapley Additive exPlanations analysis and show that, in contrast to applications in natural language processing, attention mechanisms in materials science exhibit high efficiency in highlighting meaningful structural features.

Slautin, Boris [Independent Researcher]↗
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 OSTI2023

Energy–structure–property relationships in uranium metal–organic frameworks

Energy–structure–property relationships in uranium metal–organic frameworks offer a deeper understanding of their behaviors, explaining why structure produces function. This understanding becomes crucial for the rational design of such materials with enhanced properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2015

Finite Element Estimation of Meteorite Structural Properties

The goal of the project titled Asteroid Threat Assessment at NASA Ames Research Center is to develop risk assessment tools. The expertise in atmospheric entry in the Entry Systems and Technology Division is being used to describe the complex physics of meteor breakup in the atmosphere. The breakup of a meteor is dependent on its structural properties, including homogeneity of the material. The present work describes an 11-week effort in which a literature survey was carried for structural properties of meteoritic material. In addition, the effect of scale on homogeneity isotropy was studied using a Monte Carlo approach in Nastran. The properties were then in a static structural response simulation of an irregularly-shape meteor (138-scale version of Asteroid Itokawa). Finally, an early plan was developed for doctoral research work at Georgia Tech. in the structural failure fragmentation of meteors.

Structural Properties↗
DOE OSTI2022

Building Structure-Property Relationships of Cycloalkanes in Support of Their Use in Sustainable Aviation Fuels

In 2018 13.7 EJ of fuel were consumed by the global commercial aviation industry. Worldwide, demand will increase into the foreseeable future. Developing Sustainable Aviation Fuels (SAFs), with decreased CO 2 and soot emissions, will be pivotal to the on-going mitigation efforts against global warming. Minimizing aromatics in aviation fuel is desirable because of the high propensity of aromatics to produce soot during combustion. Because aromatics cause o-rings to swell, they are important for maintaining engine seals, and must be present in at least 8 vol% under ASTM-D7566. Recently, cycloalkanes have been shown to exhibit some o-ring swelling behavior, possibly making them an attractive substitute to decrease the aromatic content of aviation fuel. Cycloalkanes must meet specifications for a number of other physical properties to be compatible with jet fuel, and these properties can vary greatly with the cycloalkane chemical structure, making their selection difficult. Building a database of structure-property relationships (SPR) for cycloalkanes greatly facilitates their furthered inclusion into aviation fuels. The work presented in this paper develops SPRs by building a data set that includes physical properties important to the aviation industry. The physical properties considered are energy density, specific energy, melting point, density, flashpoint, the Hansen solubility parameter, and the yield sooting index (YSI). Further, our data set includes cycloalkanes drawn from the following structural groups: fused cycloalkanes, n-alkylcycloalkanes, branched cycloalkanes, multiple substituted cycloalkanes, and cycloalkanes with different ring sizes. In addition, a select number of cycloalkanes are blended into Jet-A fuel (POSF-10325) at 10 and 30 wt%. Comparison of neat and blended physical properties are presented. One major finding is that ring expanded systems, those with more than six carbons, have excellent potential for inclusion in SAFs. Our data also indicate that polysubstituted cycloalkanes have higher YSI values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

Structural properties of bismuth-bearing semiconductor alloys

The structural properties of bismuth-bearing III-V semiconductor alloys are addressed. Because the Bi compounds are not known to form zincblende structures, only the anion-substituted alloys InPBi, InAsBi, and InSbBi are considered candidates as narrow-gap semiconductors. Miscibility calculations indicate that InSbBi will be the most miscible, and InPBi, with the large lattice mismatch of the constituents, will be the most difficult to mix. Calculations of the hardness of the Bi compounds indicate that, once formed, the InPBi alloy will be harder than the other Bi alloys, and substantially harder than the currently favored narrow-gap semiconductor HgCdTe. Thus, although InSbBi may be an easier material to prepare, InPBi promises to be a harder material. Growth of the Bi compounds will require high effective growth temperatures, probably attainable only through the use of nonequilibrium energy-assisted epitaxial growth techniques.

Berding, M. A.↗
NASA NTRS1988

Structural properties of bismuth-bearing semiconductor alloys

The structural properties of bismuth-bearing III-V semiconductor alloys InPBi, InAsBi, and InSbBi were studied theoretically. Bond energies, bond lengths, and strain coefficients were calculated for pure AlBi, GaBi, and InBi compounds and their alloys, and predictions were made for the mixing enthalpies, miscibility gaps, and critical metastable-to-stable material transition temperatures. Miscibility calculations indicate that InSbBi will be the most miscible, and the InPBi will be the the most difficult to mix. However, calculations of the hardness of the Bi compounds indicate that, once formed, the InPBi alloy will be harder than the other Bi alloys and substantially harder than the currently favored narrow-gap semiconductor HgCdTe.

Berding, M. A.↗
NASA NTRS1992

Energetics and structural properties of twist grain boundaries in Cu

Structural and energetics properties of atoms near a grain boundary are of great importance from theoretical and experimental standpoints. From various experimental work it is concluded that diffusion at low temperatures at polycrystalline materials take place near grain boundary. Experimental and theoretical results also indicate changes of up to 70 percent in physical properties near a grain boundary. The Embedded Atom Method (EAM) calculations on structural properties of Au twist grain boundaries are in quite good agreement with their experimental counterparts. The EAM is believed to predict reliable values for the single vacancy formation energy as well as migration energy. However, it is not clear whether the EAM functions which are fitted to the bulk properties of a perfect crystalline solid can produce reliable results on grain boundaries. One of the objectives of this work is to construct the EAM functions for Cu and use them in conjunction with the molecular static simulation to study structures and energetics of atoms near twist grain boundaries in Cu. This provides tests of the EAM functions near a grain boundary. In particular, we determine structure, single vacancy formation energy, migration energy, single vacancy activation energy, and interlayer spacing as a function of distance from grain boundary. Our results are compared with the available experimental and theoretical results from grain boundaries and bulk.

Karimi, Majid↗
DOE OSTI2025

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗
DOE OSTI2021

Epitaxial nanotwinned metals and alloys: synthesis-twin structure–property relations

Extensive studies have been performed to understand the structure–property relationship in nanotwinned (NT) metals, where the average twin thickness or twin spacing is less than 100 nm. NT metals may have high strength, ductility, good electrical conductivity and corrosion resistance and have promising applications in microelectronics, structural materials and coatings for gas and oil industry. Most prior studies focus on the computational and experimental investigations of NT metals with low stacking fault energy (SFE) and often in polycrystalline forms. In this highlight, we review recent findings on epitaxial growth of NT metals and alloys with low and high SFEs deposited on single crystal substrates, and focus primarily on advancing our comprehension towards tailoring the microstructures and properties of NT metals via extrinsic factors, including the synthesis technique, parametric control and growth template, and intrinsic factors, such as SFE and thermodynamic, kinetic alloying effects. The review intends to illuminate how to synthesize and design epitaxial NT structures to achieve desirable properties.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Dynamically hot galaxies. I - Structural properties

Results are reported from an analysis of the structural properties of dynamically hot galaxies which combines central velocity dispersion, effective surface brightness, and effective radius into a new 3-space (k), in which the axes are parameters that are physically meaningful. Hot galaxies are found to divide into groups in k-space that closely parallel conventional morphological classifications, namely, luminous ellipticals, compacts, bulges, bright dwarfs, and dwarf spheroidals. A major sequence is defined by luminous ellipticals, bulges, and most compacts, which together constitute a smooth continuum in k-space. Several properties vary smoothly with mass along this continuum, including bulge-to-disk ratio, radio properties, rotation, degree of velocity anisotropy, and 'unrelaxed'. A second major sequence is comprised of dwarf ellipticals and dwarf spheroidals. It is suggested that mass loss is a major factor in hot dwarf galaxies, but the dwarf sequence cannot be simply a mass-loss sequence, as it has the wrong direction in k-space.

Bender, Ralf↗
DOE OSTI2023

Lignin with controlled structural properties by N-heterocycle-based deep eutectic solvent extraction

The complex and heterogeneous nature of the lignin macromolecule has presented a lasting barrier to its utilization. To achieve high lignin yield, the technical lignin extraction process usually severely modifies and condenses the native structure of lignin, which is a critical drawback for its utilization in conversion processes. In addition, there is no method capable of separating lignin from plant biomass with controlled structural properties. Here, we developed an N-heterocycle-based deep eutectic solvent formed between lactic acid and pyrazole (La–Py DES) with a binary hydrogen bonding functionality resulting in a high affinity toward lignin. In this study, up to 93.7% of lignin was extracted from wheat straw biomass at varying conditions from 90 °C to 145 °C. Through careful selection of treatment conditions as well as lactic acid to pyrazole ratios, lignin with controlled levels of ether linkage content, hydroxyl group content, and average molecular weight can be generated. Under mild extraction conditions (90 °C to 120 °C), light-colored native-like lignin can be produced with up to 80% yield, whereas ether linkage–free lignin with low polydispersity can be obtained at 145 °C. Overall, this study offers a new strategy for native lignin extraction and generating lignin with controlled structural properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structure-property correlations and scaling in the magnetic and magnetocaloric properties of GdCrO 3 particles

The structure, magnetic, and magnetocaloric (MC) properties of orthorhombic nanocrystalline GdCrO 3 with six particle sizes: < d > = 87, 103, 145, 224, 318, and 352 nm are reported. The particle size was tailored by annealing under different temperatures and estimated by scanning electron microscopy. With increase in < d >, Goldschmidt tolerance factor t, orthorhombic strain s, and out-of-plane Cr–O 1 –Cr bond angle first decrease, reaching minimum values for < d > = 224 nm, and then increase for sample with < d > = 318 nm and 352 nm, thus showing a V-shaped variation. Temperature dependence of the magnetization (M) reveals an antiferromagnetic transition at ${T}_{\text{N}}^{\text{Cr}}\sim 168$ K for < d > ≥ 224 nm and ${T}_{\text{N}}^{\text{Cr}}\sim 167$ K for < d > < 224 nm and an essentially d-independent spin-reorientation at T SR = 9 K. M measured at 5 K and 7 T first increases with increase in < d >, reaching maximum value for sample with < d > = 224 nm, and then decreases for samples with < d > = 318 nm and 352 nm, showing an inverted-V variation with < d >. Similar < d >-dependence is observed for the magnetic entropy change (MEC) and relative cooling power (RCP) showing a close relationship between the structural and magnetic properties of GdCrO 3 nanoparticles investigated here. The 224 nm sample with the minimum values of t, s, and Cr–O 1 –Cr bond angle exhibits the maximum value of MEC (–ΔS) = 37.8 J kg –1 K –1 at 5 K under a field variation (ΔH) of 7 T and its large estimated RCP of 623.6 J Kg –1 is comparable with those of typical MC materials. Both (–ΔS) and RCP are shown to scale with the saturation magnetization MS, suggesting that MS is the crucial factor controlling their magnitudes. Assuming (–ΔS) ~ (ΔH) n , the temperature dependence of n for the six samples are determined, n varying between 1.3 at 5 K to n = 2.2 at 130 K in line with its expected magnitudes based on mean-field theory. Furthermore, these results on structure-property correlations and scaling in GdCrO 3 suggest that its MC properties are tunable for potential low-temperature magnetic refrigeration applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗