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Investigations are conducted into the optical properties of the glass and Kapton substrate materials, and three variables were chosen: deposition rate, sputter gas pressure, and film contamination time. Substrate tests have shown that fabrication of an dielectric broadband reflector would require an extremely complex and expensive filter design.
As composites are introduced into more complex structures with out-of-plane loadings, a better understanding is needed of the out-of-plane, matrix-dominated failure mechanisms. This work investigates the transverse tension fatigue characteristics of IM6/3501 composite materials. To test the 90 degree laminae, a three-point bend test was chosen, potentially minimizing handling and gripping issues associated with tension tests. A finite element analysis was performed of a particular specimen configuration to investigate the influence of specimen size on the stress distribution for a three-point bend test. Static testing of 50 specimens of 9 different sized configurations produced a mean transverse tensile strength of 61.3 Mpa (8.0 ksi). The smallest configuration (10.2 mm wide, Span-to-thickness ratio of 3) consistently exhibited transverse tensile failures. A volume scale effect was difficult to discern due to the large scatter of the data. Static testing of 10 different specimens taken from a second panel produced a mean transverse tensile strength of 82.7 Mpa (12.0 ksi). Weibull parameterization of the data was possible, but due to variability in raw material and/or manufacturing, more replicates are needed for greater confidence. Three-point flex fatigue testing of the smallest configuration was performed on 59 specimens at various levels of the mean static transverse tensile strength using an R ratio of 0.1 and a frequency of 20 Hz. A great deal of scatter was seen in the data. The majority of specimens failed near the center loading roller. To determine whether the scatter in the fatigue data is due to variability in raw material and/or the manufacturing process, additional testing should be performed on panels manufactured from different sources.
The LBV characteristics of the new LBV candidate WRA 751 suggested by Hu et al. (1990) are studied in greater detail. A comparison is made with observational characteristics of the well-known LBVs Ag Car and HR Car using photometric and spectroscopic data of Hu et al. supplemented with an IUE spectrum and direct CCD images in H-alpha, blue, and red. It is found that the spectra of WRA 751 and HR Car discussed in this paper are similar to the minimum-phase spectrum of AG Car and therefore resemble the Of/WN 9 spectral type. The characteristics of the optical, near- and far-UV (IUE) spectra of the Fe II spectrum in these wavelength regions is due to continuum fluorescence. The H, He I, Fe II and forbidden Fe II emission lines are formed in different parts of the stars' envelopes, corresponding to their expanding velocities. It is concluded that WRA 751 has properties which fit well the LBV properties at minimum-brightness phase, and possesses circumstellar material with observational properties similar to those of the known LBVs AG Car and HR Car.
Austenitic stainless steels are used extensively in harsh environments, including for high-pressure gaseous hydrogen service. However, the tensile ductility of this class of materials is very sensitive to materials and environmental variables. While tensile ductility is generally insufficient to qualify a material for hydrogen service, ductility is an effective tool to explore microstructural and environmental variables and their effects on hydrogen susceptibility, to inform understanding of the mechanisms of hydrogen effects in metals, and to provide insight to microstructural variables that may improve relative performance. In this study, hydrogen precharging was used to simulate high-pressure hydrogen environments to evaluate hydrogen effects on tensile properties. Several austenitic stainless steels were considered, including both metastable and stable alloys. Room temperature and subambient temperature tensile properties were evaluated with three different internal hydrogen contents for type 304L and 316L austenitic stainless steels and one hydrogen content for XM-11. Significant ductility loss was observed for both metastable and stable alloys, suggesting the stability of the austenitic phase is not sufficient to characterize the effects of hydrogen. Internal hydrogen does influence the character of deformation, which drives local damage accumulation and ultimately fracture for both metastable and stable alloys. While a quantitative description of hydrogen-assisted fracture in austenitic stainless steels remains elusive, these observations underscore the importance of the hydrogen-defect interactions and the accumulation of damage at deformation length scales.
A limited number of foams and fabrics was evaluated in the course of developing test procedures for determining the relative toxicity of materials. The principal variable studied, heating rate, did not affect the relative ranking of the materials tested. Two pyrolysis test procedures using the same basic approach but employing different sample weights, chamber volumes, laboratory animals, heating rates, and upper temperature limits, resulted in identical rankings of relative toxicity. The data obtained show that modification of conventional flexible polyurethane foams with flame retardants to comply with California upholstered furniture flammability regulations seems to consistently reduce toxicity under pyrolysis conditions.
A thermodynamically consistent damage model is proposed for the simulation of progressive delamination in composite materials under variable-mode ratio. The model is formulated in the context of Damage Mechanics. A novel constitutive equation is developed to model the initiation and propagation of delamination. A delamination initiation criterion is proposed to assure that the formulation can account for changes in the loading mode in a thermodynamically consistent way. The formulation accounts for crack closure effects to avoid interfacial penetration of two adjacent layers after complete decohesion. The model is implemented in a finite element formulation, and the numerical predictions are compared with experimental results obtained in both composite test specimens and structural components.
The limitations on sheet growth material in terms of the defect structure and minority carrier lifetime are discussed. The effect of various defects on performance are estimated. Given these limitations designs for a sheet growth cell that will make the best of the material characteristics are proposed. Achievement of optimum synergy between base material quality and device processing variables is proposed. A strong coupling exists between material quality and the variables during crystal growth, and device processing variables. Two objectives are outlined: (1) optimization of the coupling for maximum performance at minimal cost; and (2) decoupling of materials from processing by improvement in base material quality to make it less sensitive to processing variables.
This paper presents an uncertainty quantification (UQ) framework for the physics-based model prediction of material response with a large number of parameters. The application problem presented in this work is that of predicting creep in Grade 91 steel at 600°C. The material response is defined with a physically based microstructural model with constitutive equations emulating several observed phenomena in Grade 91 and embodied into an explicit geometry mesoscale finite element model for prior austenite grains and grain boundaries. Creep within the grains and in grain boundaries are represented by crystal plasticity for dislocation motion and a physics-based model for cavity growth and nucleation, respectively. The creep behavior of this material is influenced by several parameters, some of which have a wide range of variation based on experimental data. UQ combined with microstructural modeling can discover the core microstructural causes of experimental variability, leading to improved materials with lower variability in critical long-term material properties. In this study, we investigate the model's uncertainty to identify material properties that may be modified during production to increase creep life and analyze different components of the crystal plasticity model for improvements. For this purpose, a quantity of interest is defined as time to minimum creep rate, which correlates well to the creep failure of the material. A deep neural network model was trained and validated to be used as a surrogate for the finite element model. Then, a variance-based sensitivity analysis is performed on the surrogate model to find the Sobol indices of the input parameters in respect to the output quantity of interest. The Sobol indices are used to reduce the dimensionality of the model. Generalized polynomial chaos expansion is used on the reduced basis models to propagate the uncertainty from the input parameters to the quantity of interest using the deep neural network surrogate model. These results are benchmarked against uncertainty propagation using Monte Carlo simulations. In conclusion, the UQ performed through the reduced basis model captures almost all the uncertainty in the model with significantly fewer simulations, making it possible to perform the UQ directly via simulations with the finite element model rather than surrogate machine-learned models.
A methodology for structural synthesis is presented in which the optimal material selection for the structural members is treated in terms of (0,1) variables. Structural member sizes and material selection variables are treated simultaneously as design variables. Optimization is carried out by generating and solving a sequence of explicit approximate problems using a branch and bound strategy. Intermediate design variables and intermediate response quantities are used to enhance the quality of the approximate design problems. Numerical results for example problems are presented to illustrate the efficiency of the design procedure set forth.
Nuclear material packaging involves many complex variables derived from the stored material's properties, the storage environment, and the synergistic interaction of said material and its environment on the containment boundary. In the Plutonium Facility (PF-4) at Los Alamos National Laboratory (LANL) the typical containment boundary found, starting from the stored material itself to the outermost containment layer, consists of the material contained within a stainless steel (typically 304) slip-lid (or other equivalent stainless steel packaging layer) wrapped in an sPVC bag-out bag contained within a facility approved outer container stored within the boundaries of an approved facility (i.e., a building designed and approved to store nuclear material). This packaging configuration, though occasionally deviated from in the past, represents the current procedurally enforced, expected containment structure for all interim nuclear material containment outside of an engineered control barrier (e.g., a glovebox). Over the life of containerization research at LANL, packaging engineers have become increasingly concerned with the degradation of the sPVC bag-out bag, which can cause corrosion to the outermost packaging layer as well as possible exposure to alpha contamination if the bag-out bag layer is degraded to the point of containment failure. A bag-out bag degradation predictive tool (BDT) is therefore needed to assess the current and future nuclear material inventory for possible bag degradation in order to continue to ensure safe operations for the facility and its workers to deliver on the vital national security mission of 30 PPY.
Review of the thermophysical properties of granular materials or silicates believed to simulate the lunar surface layer. Emphasis is placed on thermal conductivity data and the effects of material and environmental variables on the thermal conductivity. There are three basic mechanisms of heat transfer in particulate materials: conduction by the gas contained in the void spaces between the particles; conduction within the solid particles and across the interparticle contacts; and thermal radiation within the particles, across the void spaces between particle surfaces, and between void spaces themselves. Gas and solid conduction, thermal radiation, and the interaction between conduction and radiation are considered.
Program uses multistation structural-synthesis to size and design box-beam structures for transport aircraft. Program optimizes static strength and scales up to satisfy fatigue and fracture criteria. It has multimaterial capability and library of materials properties, including advanced composites. Program can be used to evaluate impact on weight of variables such as materials, types of construction, structural configurations, minimum gage limits, applied loads, fatigue lives, crack-growth lives, initial crack sizes, and residual strengths.
Advanced materials and manufacturing technologies are poised to improve the safety and design characteristics of nuclear technologies and meet US energy, environmental, and economic needs. In particular, metal additive manufacturing (AM) provides an opportunity to produce novel materials and component geometries, but their use is not without hurdles arising from the inherent microstructure variability that can result from the layer-by-layer build approach. Given the greater possible microstructure variability in AM materials—and the dearth of materials test reactors—it is impractical to rely solely on neutron irradiation studies to produce data for materials qualification for every possibility. This work within the Advanced Materials and Manufacturing Technologies (AMMT) Environmental Effects technical area contributes to the rapid qualification framework by developing a science-driven framework for the accelerated qualification of materials for nuclear environments. A key product of the Environmental Effects technical area of the AMMT program is the Licensing Approach with Ions and Neutrons (LAIN). This approach recognizes that whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. In FY 2023, the AMMT program presented a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame informed by the state of the art in materials science and a review of the current regulatory landscape. The objective of this section of the Environmental Effects technical area is to critically evaluate and refine the proposed qualification framework presented under AMMT by integrating the research results of the neutron irradiations, the ion irradiations, and modeling efforts. These ongoing efforts span across Argonne National Laboratory (ANL), Idaho National Laboratory (INL), and Oak Ridge National Laboratory (ORNL) and are closely coordinated.
Fracture toughness and static Young's modulus were measured for the low-density silic fiber materials used as tiles in the thermal protection system of the Space Shuttle. The fracture behavior was found to be in excellent agreement with a previously formulated micromechanical model and allowed both (density) classes of tile material to be correlated to a single function. A similar correlation was also found between strength and Young's modulus, which is the basis of a nondestructive evaluation test for these materials. It was shown that the value of Young's modulus determined from a dynamic test can be substantially greater than that determined in a static mechanical test. This effect must be taken into account in the correlation. Finally, it was also determined that these materials have significant variations in Kc, both within and between production units, so that the strength variability in these materials is dependent on both fracture toughness and flaw-size variations.
Semiconductor/electrolyte interfaces are of great interest to numerous scientific fields including renewable energy, (photo)electrochemistry, and energy storage. The semiconductor flatband potential is a key parameter in locating the conduction band minimum or valence band maximum of the semiconductor material in electrolyte. Despite its importance for quantifying the energetic location of the semiconductor bands, literature reports for the same material demonstrate significant variability in the flatband potential. In this compendium and meta-analysis, reported flatband potentials of the common semiconductor materials TiO2, SnO2, and ZnO in aqueous electrolyte were compiled and assessed to quantify the spread in literature flatband potentials as well as determine the factors that lead to the significant spread. For TiO2, SnO2, and ZnO, literature flatband potentials referenced to the reversible hydrogen electrode span a range of nearly 2 V each. Flatband potential tabulations were separated by variables such as the solution pH, the crystalline polymorph, the crystal facet, the morphology, and the dimensions or combinations of these variables to assess the factors that contribute to the observed spread. Important and surprising findings from these categorizations are summarized: (1) Even for the narrowest categorizations, the spread in flatband potential is still large. (2) Flatband potentials of TiO2 and SnO2 follow the expected Nernstian dependence with solution pH. ZnO materials deviate from this Nernstian dependence. (3) In the aggregate, there is no statistically significant difference in the reported flatband potentials of anatase and rutile TiO2. Single crystal tabulations were the only distributions to have statistically significant differences in the flatband potential between anatase and rutile TiO2. (4) Anatase TiO2 materials with a nanotube morphology appear to have a +400 mV difference in mean flatband potential compared to all other morphologies, but we argue that this is likely due to widespread misuse of the Mott–Schottky analysis. Other interesting findings are revealed within the spread of literature flatband potentials, and possible explanations are provided to generate discussion. We also briefly review and discuss common techniques that were used to determine the flatband potential and the pitfalls/criticisms of these techniques. Last, we discuss some ways in which future research on the determination of the flatband potential can be performed to improve the reliability of reported values and the quality of the work. In total, the results from this meta-analysis suggest multiple factors can affect the measured flatband potential and that an abundance of caution should be applied when attempting to quantify the flatband potential of complex or nanostructured systems.
Synthesis prediction is a key accelerator for the rapid design of advanced materials. However, determining synthesis variables such as the choice of precursor materials is challenging for inorganic materials because the sequence of reactions during heating is not well understood. In this work, we use a knowledge base of 29,900 solid-state synthesis recipes, text-mined from the scientific literature, to automatically learn which precursors to recommend for the synthesis of a novel target material. The data-driven approach learns chemical similarity of materials and refers the synthesis of a new target to precedent synthesis procedures of similar materials, mimicking human synthesis design. When proposing five precursor sets for each of 2654 unseen test target materials, the recommendation strategy achieves a success rate of at least 82%. Our approach captures decades of heuristic synthesis data in a mathematical form, making it accessible for use in recommendation engines and autonomous laboratories.
This study presents a novel physics-informed neural network (PINN) framework for modeling poroelasticity in heterogeneous media with material interfaces. The approach introduces a composite neural network (CoNN) where separate neural networks predict displacement and pressure variables for each material. While sharing identical activation functions, these networks are independently trained for all other parameters. To address challenges posed by heterogeneous material interfaces, the CoNN is integrated with the Interface-PINNs (I-PINNs) framework (Sarma et al., Comput. Methods Appl. Mech. Eng. 429: 117135, 2024), allowing different activation functions across material interfaces. Further, this ensures accurate approximation of discontinuous solution fields and gradients. Performance and accuracy of this combined architecture were evaluated against the conventional PINNs approach, a single neural network (SNN) architecture, and the eXtended PINNs (XPINNs) framework through two one-dimensional benchmark examples with discontinuous material properties. The results show that the proposed CoNN with I-PINNs architecture achieves an RMSE that is two orders of magnitude better than the conventional PINNs approach and is at least 40 times faster than the SNN framework. Compared to XPINNs, the proposed method achieves an RMSE at least one order of magnitude better and is 40% faster.
This research involved construction of a conditioned test hut in a cold climate (Climate Zone 5A) with multiple side-by-side instrumented roof rafter bays. This work examined seven experimental unvented roofs and one code-compliant control hybrid ccSPF-cellulose roof over three winters and following summers. Examined variables included insulation material (fiberglass and cellulose), the presence or absence of a ridge diffusion vent (vapor-open material at the roof ridge to promote drying), the effect of various interior vapor control membranes (fixed and variable permeance), the effect of interior relative humidity, and the effect of interstitial airflow (from the interior into the cavity). This experiment was run over three winters, changing variables of interior conditions, roof configurations/materials, and the addition of intentional air leakage.