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At least 937 records · Page 52

Material Modeling of Space Shuttle Leading Edge and External Tank Materials For Use in the Columbia Accident Investigation

Upon the commencement of the analytical effort to characterize the impact dynamics and damage of the Space Shuttle Columbia leading edge due to External Tank insulating foam, the necessity of creating analytical descriptions of these materials became evident. To that end, material models were developed of the leading edge thermal protection system, Reinforced Carbon Carbon (RCC), and a low density polyurethane foam, BX-250. Challenges in modeling the RCC include its extreme brittleness, the differing behavior in compression and tension, and the anisotropic fabric layup. These effects were successfully included in LS-DYNA Material Model 58, *MAT_LAMINATED_ COMPOSITE_ FABRIC. The differing compression and tension behavior was modeled using the available damage parameters. Each fabric layer was given an integration point in the shell element, and was allowed to fail independently. Comparisons were made to static test data and coupon ballistic impact tests before being utilized in the full scale analysis. The foam's properties were typical of elastic automotive foams; and LS-DYNA Material Model 83, *MAT_FU_CHANG_FOAM, was successfully used to model its behavior. Material parameters defined included strain rate dependent stress-strain curves for both loading and un-loading, and for both compression and tension. This model was formulated with static test data and strain rate dependent test data, and was compared to ballistic impact tests on load-cell instrumented aluminum plates. These models were subsequently utilized in analysis of the Shuttle leading edge full scale ballistic impact tests, and are currently being used in the Return to Flight Space Shuttle re-certification effort.

Carney, Kelly↗

Wake up and retention in zinc magnesium oxide ferroelectric films

Zn 0.64 Mg 0.36 O (ZMO) is a newly discovered ferroelectric oxide with the wurtzite structure. Epitaxial Zn 0.64 Mg 0.36 O films from 0.036 to 0.5 μm in thickness are grown on Pt/sapphire with the crystallographic c-axis out of plane. At room temperature, the remanent polarization is ~80 μC/cm 2 and the coercive field is ~3 MV/cm. The coercive field is strongly temperature dependent up to 240 °C with a pseudo-activation energy of 23 ± 0.3 meV, suggesting that polarization reversal occurs through an extrinsic process such as domain wall motion. ZMO films can be woken up in 20 electric field cycles on driving near the coercive field; they wake up in a single loop at fields in excess of 4 MV/cm. A thermally activated fluid imprint process, with a pseudo-activation energy of 67 ± 8 meV, enlarges the coercive field by several hundred kV cm –1 after switching the polarization. Additionally, ZMO films exhibit excellent retention characteristics; no reduction in the polarization is observed up to 1000 h from room temperature to 200 °C bakes. Here, this current early generation of ZMO films can survive several thousand switching cycles before dielectric breakdown occurs.

36 MATERIALS SCIENCE↗

Simulation Studies of Electromagnetic Energy Absorption by Hydride Materials

This paper investigates the key parameters that contribute to electromagnetic (EM) energy absorption and heating of hydride materials which could be used to release hydrogen for use as a fuel. Our simulation study using COMSOL focuses on EM energy absorption and resulting temperature rise in a thin circular slab of hydride material using resonant dipole and loop antennas. Presented results delineate the effects of conductivity, relative permeability, antenna type and slab size on temperature rise when the distance and amount of RF power are kept fixed.

Brown, Michael A.↗

Machine learning the Hubbard U parameter in DFT+U using Bayesian optimization

Abstract Within density functional theory (DFT), adding a Hubbard U correction can mitigate some of the deficiencies of local and semi-local exchange-correlation functionals, while maintaining computational efficiency. However, the accuracy of DFT+U largely depends on the chosen Hubbard U values. We propose an approach to determining the optimal U parameters for a given material by machine learning. The Bayesian optimization (BO) algorithm is used with an objective function formulated to reproduce the band structures produced by more accurate hybrid functionals. This approach is demonstrated for transition metal oxides, europium chalcogenides, and narrow-gap semiconductors. The band structures obtained using the BO U values are in agreement with hybrid functional results. Additionally, comparison to the linear response (LR) approach to determining U demonstrates that the BO method is superior.

Chemistry↗

Meshfree simulation and prediction of recrystallized grain size in friction stir processed 316L stainless steel

Friction stir processing (FSP) is a promising solid-phase microstructural modification technique that can repair and enhance damaged stainless steel surfaces exposed to harsh environments. The quality of the repaired material is closely correlated to the recrystallized grain size in the stir zone (SZ), which is influenced by the thermomechanical conditions dictated by FSP process parameters. Thus, establishing a reliable relationship between these parameters and recrystallized grain size in the SZ is crucial for optimizing repair quality. However, existing experimental approaches often rely on indirect temperatures measured far from the SZ, along with rough strain rate estimations, which are imprecise and time-consuming. Meanwhile, existing mesh-based modeling methods usually face numerical challenges when dealing with the large material deformations inherent in FSP. Here, to address these issues, this study introduces a meshfree process model for FSP based on the smoothed particle hydrodynamics (SPH) method, aimed at predicting process conditions under different parameters. The model is validated using experimental data from 11 combinations of tool traverse and rotation speeds on 316 L stainless steel. Correlations between process parameters, material flow, temperature, strain, strain rate, and recrystallized grain size are revealed through SPH simulations and electron backscatter diffraction (EBSD) imaging. The results show that in situ SZ temperatures range from 1071 to 1322°C, which exceed the tool temperature by over 300°C. Furthermore, SZ temperature, strain rate, and grain size increase monotonically with higher tool temperature and faster traverse speed. A relationship is then established between the model-predicted Zener-Hollomon parameter and the recrystallized grain size based on EBSD data, expressed as ln(d) = -0.364 ln(Z) + 14.673. Finally, this relationship exhibits satisfactory accuracy with errors of less than 26.9% in predicting grain sizes at various SZ locations, which offers valuable insights for optimizing FSP repair processes for 316 L stainless steel.

316L stainless steel↗

Characterization of multi-material 316L-Hastelloy X fabricated via laser powder-bed fusion

The aim of this work is to provide firsthand knowledge of 316 L stainless steel (316 L) and Hastelloy X (HX) multi-material processing via laser powder bed fusion (PBF). Specifically, microstructure of the interface is studied using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). Surface metrology is performed to characterize the resulting surface roughness at the interface followed by tensile and flexural testing of multi-material samples to characterize the mechanical properties of the interfaces. Results showed that use of proper process parameters for each individual material led to formation of a compositional gradient at the interface that stretched for 240 μm (10–12 layers) with no evidence of cracking or porosity. The interface exhibited higher surface roughness compared to 316 L or HX as measured by arithmetic mean height, Sa, and maximum valley depth, Sv, parameters. During tensile testing, samples failed in the 316 L region away from the interface, with comparable yield strength, ultimate strength, and ductility. Finally, it was concluded that the “naturally” formed interface created a compositional gradient which was defect free due to similar values of coefficient of thermal expansion, input energy density, and different Marangoni numbers of the materials.

316L stainless Steel↗

Summary of process research analysis efforts

A summary of solar-cell process research analysis efforts was presented. Process design and cell design are interactive efforts where technology from integrated circuit processes and other processes are blended. The primary factors that control cell efficiency are: (1) the bulk parameters of the available sheet material, (2) the retention and enhancement of these bulk parameters, and (3) the cell design and the cost to produce versus the finished cells performance. The process sequences need to be tailored to be compatible with the sheet form, the cell shape form, and the processing equipment. New process options that require further evaluation and utilization are lasers, robotics, thermal pulse techniques, and new materials. There are numerous process control techniques that can be adapted and used that will improve product uniformity and reduced costs. Two factors that can lead to longer life modules are the use of solar cell diffusion barriers and improved encapsulation.

Burger, D. R.↗

Using Response Surface Methods to Correlate the Modal Test of an Inflatable Test Article

This paper presents a practical application of response surface methods (RSM) to correlate a finite element model of a structural modal test. The test article is a quasi‐cylindrical inflatable structure which primarily consists of a fabric weave, with an internal bladder and metallic bulkheads on either end. To mitigate model size, the fabric weave was simplified by representing it with shell elements. The task at hand is to represent the material behavior of the weave. The success of the model correlation is measured by comparing the four major modal frequencies of the analysis model to the four major modal frequencies of the test article. Given that only individual strap material properties were provided and material properties of the overall weave were not available, defining the material properties of the finite element model became very complex. First it was necessary to determine which material properties (modulus of elasticity in the hoop and longitudinal directions, shear modulus, Poisson's ratio, etc.) affected the modal frequencies. Then a Latin Hypercube of the parameter space was created to form an efficiently distributed finite case set. Each case was then analyzed with the results input into RSM. In the resulting response surface it was possible to see how each material parameter affected the modal frequencies of the analysis model. If the modal frequencies of the analysis model and its corresponding parameters match the test with acceptable accuracy, it can be said that the model correlation is successful.

Gupta, Anju↗

Fracture mechanics concepts in reliability analysis of monolithic ceramics

Basic design concepts for high-performance, monolithic ceramic structural components are addressed. The design of brittle ceramics differs from that of ductile metals because of the inability of ceramic materials to redistribute high local stresses caused by inherent flaws. Random flaw size and orientation requires that a probabilistic analysis be performed in order to determine component reliability. The current trend in probabilistic analysis is to combine linear elastic fracture mechanics concepts with the two parameter Weibull distribution function to predict component reliability under multiaxial stress states. Nondestructive evaluation supports this analytical effort by supplying data during verification testing. It can also help to determine statistical parameters which describe the material strength variation, in particular the material threshold strength (the third Weibull parameter), which in the past was often taken as zero for simplicity.

Manderscheid, Jane M.↗

Probabilistic modeling and prediction of out-of-plane unidirectional composite lamina properties

Computational simulation provides an efficient means to predict the behavior of customized hybrid material configurations using validated, physics-based models. One limitation to this approach is the quality and quantity of available data to characterize the many constituent input properties. Therefore, a systematic approach to identify the most influential parameters on the hybrid behavior and quantify the corresponding uncertainty in predictive capabilities is required. Here, an approach using Bayesian multimodel inference and imprecise global sensitivity analysis is presented to investigate the effects of sparse constituent data on the prediction of composite material properties. The methodology allows the identification, using quantified uncertainties, of the most influential constituent material parameters for specified homogenized properties. This sensitivity analysis further enables a dimension reduction when assessing the influence of uncertainties on material properties and can be used to inform testing programs of the constituent properties that require additional testing/data collection in order to minimize uncertainty in macro-scale composite properties. The methodology is specifically demonstrated on the prediction and sensitivity analysis of out-of-plane mechanical properties of a unidirectional lamina.

36 MATERIALS SCIENCE↗

Memristor design rules for dynamic learning and edge processing applications

The ability to dynamically learn and adapt to changes in the environment is one of the hallmarks of biological systems. In this work, we identify the subset of the design space of memristive materials that is optimal for dynamic learning applications. Using an architecture inspired on the learning center of the insect brain, we implement a model system consisting of a discrete implementation of spiking neurons where dynamic learning takes place on a set of plastic synapses formed by memristor pairs in a crossbar array. Using two separate benchmarks, one comprising the dynamic learning of the Modified National Institute of Standards and Technology dataset and another one targeting one shot learning, we have identified the key properties that memristive materials should have to be optimal dynamic learners. The results obtained show that a fine degree of control of the memristor internal state is key to achieve high classification accuracy during dynamic learning but that within this optimal region learning is extremely robust both to device variability and to errors in the writing of the internal state, in all cases allowing for 2 sigma variations greater than 40% without significant loss of accuracy, hence overcoming two of the perceived limitations of memristors. By additionally requiring that learning takes place concurrently to information processing, we are able to derive a set constraints to the memristor dynamics.

36 MATERIALS SCIENCE↗

Contact-free reversible switching of improper ferroelectric domains by electron and ion irradiation

Focused ion beam (FIB) and scanning electron microscopy (SEM) are used to reversibly switch improper ferroelectric domains in the hexagonal manganite ErMnO 3 . Surface charging is achieved by local ion (positive charging) and electron (positive and negative charging) irradiation, which allows controlled polarization switching without the need for electrical contacts. Polarization cycling reveals that the domain walls tend to return to the equilibrium configuration obtained in the as-grown state. The response of sub-surface domains is studied by FIB cross-sectioning, enabling imaging in the direction perpendicular to the applied electric field. The results clarify how the polarization reversal in hexagonal manganites progresses at the level of domains, resolving both domain wall movements and the nucleation and growth of new domains. Our FIB-SEM based switching approach is applicable to all ferroelectrics where a sufficiently large electric field can be built up via surface charging, facilitating contact-free high-resolution studies of the domain and domain wall response to electric fields in 3D.

36 MATERIALS SCIENCE↗

Applied in-plane strain effects on the polarization response of ferroelectric hafnium zirconium oxide thin films

The influence of biaxial stress on the maximum and remanent polarizations of 10 nm thick hafnium zirconium oxide thin films in metal–ferroelectric–metal capacitor structures has been quantified. In the as-prepared state with a nominal biaxial tensile strain of 0.20% and no applied extrinsic stress, remanent and maximum polarizations of 7.6 and 13.1 μC/cm 2 , respectively, were measured using a 2 MV/cm applied electric field. Reducing the intrinsic strain by 0.111% through the application of a compressive uniaxial stress results in a decrease in the remanent and maximum polarizations to 6.8 and 12.2 μC/cm 2 , respectively. Here, the polarization dependence on strain is nearly linear between these values. The observed variation in polarization with strain is consistent with strain impacting ferroelastic switching whereby in-plane tension increases the fraction of the short polar axis orienting out-of-plane, hence increasing out-of-plane polarization. In contrast, reducing the in-plane strain through compression results in an increase in the fraction of the long non-polar axis orienting out-of-plane, thereby decreasing out-of-plane polarization.

36 MATERIALS SCIENCE↗

Comparison of Weibull strength parameters from flexure and spin tests of brittle materials

Fracture data from five series of four point bend tests of beam and spin tests of flat annular disks were reanalyzed. Silicon nitride and graphite were the test materials. The experimental fracture strengths of the disks were compared with the predicted strengths based on both volume flaw and surface flaw analyses of four point bend data. Volume flaw analysis resulted in a better correlation between disks and beams in three of the five test series than did surface flaw analysis. The Weibull (moduli) and characteristic gage strengths for the disks and beams were also compared. Differences in the experimental Weibull slopes were not statistically significant. It was shown that results from the beam tests can predict the fracture strength of rotating disks.

Holland, Frederic A., Jr.↗

Probabilistic Modeling Of Ocular Biomechanics In VIIP: Risk Stratification

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a major health concern for long-duration space missions. Currently, it is thought that a cephalad fluid shift in microgravity causes elevated intracranial pressure (ICP) that is transmitted along the optic nerve sheath (ONS). We hypothesize that this in turn leads to alteration and remodeling of connective tissue in the posterior eye which impacts vision. Finite element (FE) analysis is a powerful tool for examining the effects of mechanical loads in complex geometries. Our goal is to build a FE analysis framework to understand the response of the lamina cribrosa and optic nerve head to elevations in ICP in VIIP. To simulate the effects of different pressures on tissues in the posterior eye, we developed a geometric model of the posterior eye and optic nerve sheath and used a Latin hypercubepartial rank correlation coef-ficient (LHSPRCC) approach to assess the influence of uncertainty in our input parameters (i.e. pressures and material properties) on the peak strains within the retina, lamina cribrosa and optic nerve. The LHSPRCC approach was repeated for three relevant ICP ranges, corresponding to upright and supine posture on earth, and microgravity [1]. At each ICP condition we used intraocular pressure (IOP) and mean arterial pressure (MAP) measurements of in-flight astronauts provided by Lifetime Surveillance of Astronaut Health Program, NASA Johnson Space Center. The lamina cribrosa, optic nerve, retinal vessel and retina were modeled as linear-elastic materials, while other tissues were modeled as a Mooney-Rivlin solid (representing ground substance, stiffness parameter c1) with embedded collagen fibers (stiffness parameters c3, c4 and c5). Geometry creationmesh generation was done in Gmsh [2], while FEBio was used for all FE simulations [3]. The LHSPRCC approach resulted in correlation coefficients in the range of 1. To assess the relative influence of the uncertainty in an input parameter on the peak strains, we ranked and then normalized these coefficients, considering that normalized values 0.5 implied a substantial influence on the range of the peak strains in the optic nerve head (ONH). IOP and ICP were found to have a major influence on the peak strains in the ONH, as did optic nerve and LC stiffness. Interestingly, the stiffness of the sclera far from the scleral canal did not have a large influence on peak strains in ONH tissues; however, the collagen fiber stiffness in the peripapillary sclera and annular ring both influenced the peak strains within the ONH. We have created a physiologically relevant model that incorporated collagen fibers to study the effects of elevated ICP. Elevated ICP resulted in strains in the optic nerve that are not predicted to occur on earth: the upright or supine conditions. We found that IOP, ICP, lamina cribrosa stiffness and optic nerve stiffness had the highest association with these extreme strains in the ONH. These extreme strains may activate mechanosensitive cells that induce tissue remodeling and are a risk factor for the development of VIIP.

biomechanics↗

Excitonic Shockley-Read-Hall recombination in organic semiconductors

Trap-mediated recombination influences the performance of a wide range of electronic devices. The well-known Shockley-Read-Hall (SRH) expression for inorganic semiconductors is often invoked to describe the recombination rate in organic materials, although without a clear understanding of how its parameters relate to the underlying material properties or how it should be modified to account for the finite lifetime of exciton intermediates in, for example, the doped emissive layer of an organic light-emitting diode (OLED). Here, we formalize SRH recombination for organic semiconductors based on diffusive trapping and Langevin recombination. We show that including the exciton state suppresses the recombination rate in host-guest systems with type II energy level alignment whenever the interfacial gap between the host and guest molecular orbitals is comparable to the exciton energy. Furthermore, these results quantify the balance between bimolecular and trap-mediated recombination in doped OLED emissive layers, and indicate that devices with type II host-guest pairings can, in principle, beat the thermodynamic limit of their neat guest counterparts.

36 MATERIALS SCIENCE↗

Hierarchical morphologies in co-sputter deposited thin films

Co-depositions of immiscible alloy films at specific processing conditions have yielded hierarchical microstructures which consist of distinct features at multiple length scales, often agglomerates and concentration modulations on the sub-micrometer-scale and fine nanoprecipitates in a matrix on the nanoscale. The present work examined a series of immiscible alloy systems: Cu-Mo, Cu-Ag, Cu-Fe, Cu-Ta, Mo-Ag, Cu-Mo-Ag, to determine the kinetic conditions favorable for hierarchical organization and the formation mechanism of such structures. Thin films of six immiscible systems were sputter co-deposited over a range of deposition rates from 0.12 to 2 nm/s and various temperatures from 400 to 800°C. The resulting microstructures indicate that hierarchical structures form with sufficient disparity in kinetic energy between the constituent atoms, one species being highly mobile (A) and the other relatively immobile (B). This condition arises typically at elevated deposition temperatures and reduced deposition rates but is also alloy dependent. The hierarchical structures form during deposition via phase separation and self-organization processes across the multiple length scales. The adatoms diffuse on the film surface with the highly mobile species swiftly agglomerating into A-rich domains within which B-rich nanoprecipitates form, often self-organizing into periodic arrays. The smallest B-rich nanoprecipitates in the A-rich domains are found to be coherent and in a metastable crystal structure (B taking the structure of A), but coarser precipitates that exhibit the equilibrium structure of B element. The A-rich domains are surrounded by a B-rich matrix that phase-separates into a concentration modulated structure. In conclusion, the observations are interpreted via a model incorporating material properties and process parameters.

36 MATERIALS SCIENCE↗

Sensitivity analysis of the add-on price estimate for the silicon web growth process

The web growth process, a silicon-sheet technology option, developed for the flat plate solar array (FSA) project, was examined. Base case data for the technical and cost parameters for the technical and commercial readiness phase of the FSA project are projected. The process add on price, using the base case data for cost parameters such as equipment, space, direct labor, materials and utilities, and the production parameters such as growth rate and run length, using a computer program developed specifically to do the sensitivity analysis with improved price estimation are analyzed. Silicon price, sheet thickness and cell efficiency are also discussed.

Mokashi, A. R.↗