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At least 1,117 records · Page 62

The metallurgy of high temperature alloys

Nickel-base, cobalt-base, and high nickel and chromium iron-base alloys are dissected, and their microstructural and chemical components are assessed with respect to the various functions expected of high temperature structural materials. These functions include the maintenance of mechanical integrity over the strain-rate spectrum from creep resistance through fatigue crack growth resistance, and such alloy stability expectations as microstructural coarsening resistance, phase instability resistance and oxidation and corrosion resistance. Special attention will be given to the perennial conflict and trade-off between strength, ductility and corrosion and oxidation resistance. The newest developments in the constitution of high temperature alloys will also be discussed, including aspects relating to materials conservation.

Tien, J. K.↗

Successful Coupling of a Bis-Amidoxime Uranophile with a Hydrophilic Backbone for Selective Uranium Sequestration

The amidoxime group (-RNH2NOH) has long been used to extract uranium from seawater on account of its high affinity toward uranium. The development of tunable sorbent materials for uranium sequestration remains a research priority as well as a significant challenge. Herein, we report the design, synthesis, and uranium sorption properties of bis-amidoxime-functionalized polymeric materials (BAP 1–3). Bifunctional amidoxime monomers were copolymerized with an acrylamide cross-linker to obtain bis-amidoxime incorporation as high as 2 mmol g–1 after five synthetic steps. The resulting sorbents were able to uptake nearly 600 mg of uranium per gram of polymer after 37 days of contact with a seawater simulant containing 8 ppm uranium. Moreover, the polymeric materials exhibited low vanadium uptake with a maximum capacity of 128 mg of vanadium per gram of polymer. This computationally predicted and experimentally realized selectivity of uranium over vanadium, nearly 5 to 1 w/w, is one of the highest reported to date and represents an advancement in the rational design of sorbent materials with high uptake capacity and selectivity.

36 MATERIALS SCIENCE↗

Direct Visualization of Localized Vibrations at Complex Grain Boundaries

Abstract Grain boundaries (GBs) are a prolific microstructural feature that dominates the functionality of a wide class of materials. The functionality at a GB results from the unique atomic arrangements, different from those in the grain, that have driven extensive experimental and theoretical studies correlating atomic‐scale GB structures to macroscopic electronic, infrared optical, and thermal properties. In this work, a SrTiO 3 GB is examined using atomic‐resolution aberration‐corrected scanning transmission electron microscopy and ultrahigh‐energy‐resolution monochromated electron energy‐loss spectroscopy, in conjunction with density functional theory. This combination enables the correlation of the GB structure, nonstoichiometry, and chemical bonding with a redistribution of vibrational states within the GB dislocation cores. The new experimental access to localized GB vibrations provides a direct route to quantifying the impact of individual boundaries on macroscopic properties.

36 MATERIALS SCIENCE↗

A Subspace-Inclusive Sampling Method for the Computational Design of Compositionally Graded Alloys

Abstract Compositionally graded alloys, a subclass of functionally graded materials (FGMs), utilize localized variations in composition with a single metal part to achieve higher performance than traditional single material parts. In previous work [Kirk, T., Galvan, E., Malak, R., and Arroyave, R., 2018, “Computational Design of Gradient Paths in Additively Manufactured Functionally Graded Materials,” J. Mech. Des., 140, p. 111410. 10.1115/1.4040816], the authors presented a computational design methodology that avoids common issues which limit a gradient alloy’s feasibility, such as deleterious phases, and optimizes for performance objectives. However, the previous methodology only samples the interior of a composition space, meaning designed gradients must include all elements in the space throughout the gradient. Because even small amounts of additional alloying elements can introduce new deleterious phases, this characteristic often neglects potentially simpler solutions to otherwise unsolvable problems and, consequently, discourages the addition of new elements to the state space. The present work improves upon the previous methodology by introducing a sampling method that includes subspaces with fewer elements in the design search. The new method samples within an artificially expanded form of the state space and projects samples outside the true region to the nearest true subspace. This method is evaluated first by observing the sample distribution in each subspace of a 3D, 4D, and 5D state space. Next, a parametric study in a synthetic 3D problem compares the performance of the new sampling scheme to the previous methodology. Lastly, the updated methodology is applied to design a gradient from stainless steel to equiatomic NiTi that has practical uses such as embedded shape memory actuation and for which the previous methodology fails to find a feasible path.

Engineering↗

Dynamic self-assembly of compartmentalized DNA nanotubes

Abstract Bottom-up synthetic biology aims to engineer artificial cells capable of responsive behaviors by using a minimal set of molecular components. An important challenge toward this goal is the development of programmable biomaterials that can provide active spatial organization in cell-sized compartments. Here, we demonstrate the dynamic self-assembly of nucleic acid (NA) nanotubes inside water-in-oil droplets. We develop methods to encapsulate and assemble different types of DNA nanotubes from programmable DNA monomers, and demonstrate temporal control of assembly via designed pathways of RNA production and degradation. We examine the dynamic response of encapsulated nanotube assembly and disassembly with the support of statistical analysis of droplet images. Our study provides a toolkit of methods and components to build increasingly complex and functional NA materials to mimic life-like functions in synthetic cells.

59 BASIC BIOLOGICAL SCIENCES↗

First principles materials design of novel functional oxides

We review our efforts to develop and implement robust computational approaches for exploring phase stability to facilitate the prediction-to-synthesis process of novel functional oxides. These efforts focus on a synergy between (i) electronic structure calculations for properties predictions, (ii) phenomenological/empirical methods for examining phase stability as related to both phase segregation and temperature-dependent transitions and (iii) experimental validation through synthesis and characterization. We illustrate this philosophy by examining an inaugural study that seeks to discover novel functional oxides with high piezoelectric responses. Lastly, our results show progress towards developing a framework through which solid solutions can be studied to predict materials with enhanced properties that can be synthesized and remain active under device relevant conditions.

36 MATERIALS SCIENCE↗

SNL-NJOY-2016

This is a wrapper around the LANL NJOY-2016 code that interfaces with extended code capabilities and minor modification of the LANL NJOY-2016 code that supports modeling radiation damage to materials. The NJOY Nuclear Data Processing System is a modular computer code designed to read evaluated data in ENDF format, transform the data in various ways, and output the results as libraries designed to be used in various applications. The wrapper provided here permits Sandia-specific control parameters to be used in the input data file. The modifications incorporated here enhance the ability of NJOY to address material damage response functions for many materials, e.g. to include the NRT and arc-dpa forms of the damage energy in addition to the default NJOY-2016 implementation of the sharp-threshold Kinchin-Pease threshold energy treatment. All of the modifications provided here are being made available to the GitHub-based NJOY-2016 code. As useful enhancements found here are incorporated into the baseline NJOY-2016 code, they will be eliminated from this version so as to maintain our compatibility with the baseline NJOY-2016 code. SAND2020-13060 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA00035

Griffin, Patrick↗

Reducing Uncertainty in High-Resolution Sea Ice Models

Arctic sea ice is an important component of the global climate system, reflecting a significant amount of solar radiation, insulating the ocean from the atmosphere and influencing ocean circulation by modifying the salinity of the upper ocean. The thickness and extent of Arctic sea ice have shown a significant decline in recent decades with implications for global climate as well as regional geopolitics. Increasing interest in exploration as well as climate feedback effects make predictive mathematical modeling of sea ice a task of tremendous practical import. Satellite data obtained over the last few decades have provided a wealth of information on sea ice motion and deformation. The data clearly show that ice deformation is focused along narrow linear features and this type of deformation is not well-represented in existing models. To improve sea ice dynamics we have incorporated an anisotropic rheology into the Los Alamos National Laboratory global sea ice model, CICE. Sensitivity analyses were performed using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) to determine the impact of material parameters on sea ice response functions. Two material strength parameters that exhibited the most significant impact on responses were further analyzed to evaluate their influence on quantitative comparisons between model output and data. The sensitivity analysis along with ten year model runs indicate that while the anisotropic rheology provides some benefit in velocity predictions, additional improvements are required to make this material model a viable alternative for global sea ice simulations.

Peterson, Kara J.↗

Organosilicon-Based Electrolytes for Long-Life Lithium Primary Batteries

This report describes advances in electrolytes for lithium primary battery systems. Electrolytes were synthesized that utilize organosilane materials that include anion binding agent functionality. Numerous materials were synthesized and tested in lithium carbon monofluoride battery systems for conductivity, impedance, and capacity. Resulting electrolytes were shown to be completely non-flammable and showed promise as co-solvents for electrolyte systems, due to low dielectric strength.

25 ENERGY STORAGE↗

Hybrid particles and associated methods

Hybrid particles that comprise a coating surrounding a chalcopyrite material, the coating comprising a metal, a semiconductive material, or a polymer; a core comprising a chalcopyrite material and a shell comprising a functionalized chalcopyrite material, the shell enveloping the core; or a reaction product of a chalcopyrite material and at least one of a reagent, heat, and radiation. Methods of forming the hybrid particles are also disclosed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Three-dimensional Reconstruction and Homogenization of Heterogeneous Materials Using Statistical Correlation Functions and FEM

In this study, a previously developed reconstruction methodology is extended to three-dimensional reconstruction of a three-phase microstructure, based on two-point correlation functions and two-point cluster functions. The reconstruction process has been implemented based on hybrid stochastic methodology for simulating the virtual microstructure. While different phases of the heterogeneous medium are represented by different cells, growth of these cells is controlled by optimizing parameters such as rotation, shrinkage, translation, distribution and growth rates of the cells. Based on the reconstructed microstructure, finite element method (FEM) was used to compute the effective elastic modulus and effective thermal conductivity. A statistical approach, based on two-point correlation functions, was also used to directly estimate the effective properties of the developed microstructures. Good agreement between the predicted results from FEM analysis and statistical methods was found confirming the efficiency of the statistical methods for prediction of thermo-mechanical properties of three-phase composites.

36 MATERIALS SCIENCE↗

Understanding the bond-energy, hardness, and adhesive force from the phase diagram via the electron work function

Properties of metallic materials are intrinsically determined by their electron behavior. However, relevant theoretical treatment involving quantum mechanics is complicated and difficult to be applied in materials design. Electron work function (EWF) has been demonstrated to be a simple but fundamental parameter which well correlates properties of materials with their electron behavior and could thus be used to predict material properties from the aspect of electron activities in a relatively easy manner. In this article, we propose a method to extract the electron work functions of binary solid solutions or alloys from their phase diagrams and use this simple approach to predict their mechanical strength and surface properties, such as adhesion. Two alloys, Fe-Ni and Cu-Zn, are used as samples for the study. EWFs extracted from phase diagrams show same trends as experimentally observed ones, based on which hardness and surface adhesive force of the alloys are predicted. This new methodology provides an alternative approach to predict material properties based on the work function, which is extractable from the phase diagram. This work may also help maximize the power of phase diagram for materials design and development.

36 MATERIALS SCIENCE↗

Photoinduced electric effects in various plasmonic materials

Photoinduced voltages associated with surface plasmon polariton excitations are studied both theoretically and experimentally in various plasmonic systems as the function of material, wavelength, and type of structure. Experimental photovoltage normalized to the absorbed power shows a general decrease upon an increase in the wavelength, enhancement in the nanostructured samples, and a strong variation in the magnitude as a function of the material, which are not in line with the theoretical predictions of the simple plasmonic pressure approach. Furthermore, the results can be used for clarification of the mechanisms and further development of an adequate theoretcial approach to the plasmon drag effect.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Structural constraint integration in a generative model for the discovery of quantum materials

Billions of organic molecules have been computationally generated, yet functional inorganic materials remain scarce due to limited data and structural complexity. Here, in this work, we introduce Structural Constraint Integration in a GENerative model (SCIGEN), a framework that enforces geometric constraints, such as honeycomb and kagome lattices, within diffusion-based generative models to discover stable quantum materials candidates. SCIGEN enables conditional sampling from the original distribution, preserving output validity while guiding structural motifs. This approach generates ten million inorganic compounds with Archimedean and Lieb lattices, over 10% of which pass multistage stability screening. High-throughput density functional theory calculations on 26,000 candidates shows over 95% convergence and 53% structural stability. A graph neural network classifier detects magnetic ordering in 41% of relaxed structures. Furthermore, we synthesize and characterize two predicted materials, TiPd 0.22 Bi 0.88 and Ti 0.5 Pd 1.5 Sb, which display paramagnetic and diamagnetic behaviour, respectively. Our results indicate that SCIGEN provides a scalable path for generating quantum materials guided by lattice geometry.

36 MATERIALS SCIENCE↗

Evaluating Opportunities to Improve Material and Energy Impacts in Commodity Supply Chains.

When evaluated at the process level, next-generation technologies may be more energy and emissions intensive than current technology. However, many advanced technologies have the potential to reduce material and energy consumption in upstream or downstream processing stages. In order to fully understand the benefits and consequences of technology deployment, next-generation technologies should be evaluated in context, as part of a supply chain. This work presents the Material Flows through Industry (MFI) scenario modeling tool. The MFI tool is a cradle-to-gate linear network model of the U.S. industrial sector that can model a wide range of manufacturing scenarios, including changes in production technology, increases in industrial energy efficiency, and substitution between functionally equivalent materials. The MFI tool was developed to perform supply chain scale analyses in order to quantify the impacts and benefits of next-generation technologies and materials at that scale. For the analysis presented in this paper, the MFI tool is utilized to explore a case study comparing a steel supply chain to the supply chains of several functionally equivalent materials. Several of the alternatives to the baseline steel supply chain include next-generation production technologies and materials. Results of the case study show that aluminum production scenarios can out-perform the steel supply chain by using either an advanced smelting technology or an increased aluminum recycling rate. The next-generation material supply chains do not perform as well as either aluminum or steel, but may offer additional use phase reductions in energy and emissions that are outside the scope of the MFI tool. Future work will combine results from the MFI tool with a use phase analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Design and Function of α-Helix-Rich, Heme-Binding Peptide Materials

Peptide materials often employ short peptides that self-assemble into unique nanoscale architectures and have been employed across many fields relevant to medicine and energy. A majority of peptide materials are high in beta-sheet, secondary structure content, including heme-binding peptide materials. To broaden the structural diversity of heme-binding peptide materials, a small series of peptides were synthesized to explore the design criteria required for (1) folding into an alpha-helix structure, (2) assembling into a nanoscale material, (3) binding heme, and (4) demonstrating functions similar to that of heme proteins. One peptide was identified to meet all four criteria, including the heme protein function of CO binding and its microsecond-to-millisecond recombination rates, as measured by transient absorption spectroscopy. In conclusion, implications of new design criteria and peptide material function through heme incorporation are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Bulk Grain-Boundary Materials from Nanocrystals

Grain-boundary engineering is pivotal to fully utilize the mechanical, electrical, and thermal-transport properties of various materials. However, current methods in metallurgy rely almost exclusively on top-down approaches, making precise grain-boundary engineering, especially at nanoscale, difficult to achieve. Herein, we report a method to produce tailored grain-boundary conditions with nanoscale precision from colloidal metal nanocrystals through surface treatment followed by a pressure-sintering process. The resulting bulk grain-boundary materials (which we call “nanocrystal coins”) possess a metal-like appearance and conductivity while inheriting the original domain features of the nanocrystal building blocks. In this work, nanoindentation measurements confirmed the superior mechanical hardness of the obtained materials. Further, we use this method to fabricate, for the first time, a single-component bulk metallic glass from amorphous palladium nanoparticles. Our discovery may spur the development of new materials whose functionality crucially depends on the domain configuration at nanoscale, such as superhard materials, thermoelectric generators, and functional electrodes.

36 MATERIALS SCIENCE↗

Coupled Thermomechanical Micromechanics Modeling of the Influence of Thermally Grown Oxide Layer in an Environmental Barrier Coating System

Environmental Barrier Coatings (EBCs) have emerged as a promising means of protecting critical components for high temperature applications (e.g., aircraft engines). EBCs are often used to protect an underlying material (substrate) from extreme thermal/chemical environments. However, systems that utilize EBCs are susceptible to a number of failure modes including oxidation/delamination. Environmental Barrier Coatings (EBCs) have emerged as a promising means of protecting silicon based ceramic matrix composite (CMC) components for high temperature applications (e.g., aircraft engines). EBCs are often used to protect an underlying material (substrate) such as silicon carbide from extreme thermal/chemical environments. In a typical CMC/EBC system, an EBC may or may not be adhered to an underlying substrate with a bond coat (e.g., silicon). Irrespective, systems that utilize EBCs are susceptible to a number of failure modes including oxidation/delamination, recession, chemical attack and dissolution, thermo-mechanical degradation, erosion, and foreign object damage. Current work at NASA Glenn Research Center is aimed at addressing these failure modes in EBC systems and developing robust analysis tools to aid in the design process. The Higher-Order Theory for Functionally Graded Materials (HOTFGM), a precursor to the High-Fidelity Generalized Method of Cells micromechanics approach, was developed to investigate the coupled thermo-mechanical behavior of functionally graded composites and will be used herein to assess the development and growth of a low-stiffness thermally grown oxide (TGO) layer in EBC/CMC systems without a silicon bond coat. To accomplish this a sensitivity study is conducted to examine the influence of uniformly and non-uniformly grown oxide layer on the associated driving forces leading to mechanical failure (spallation) of EBC layer when subjected to isothermal loading, recession, chemical attack and dissolution, thermomechanical degradation, erosion, and foreign object damage. Current work at NASA Glenn Research Center is aimed at addressing these failure modes in EBC systems and developing robust analysis tools to aid in the design process. The Higher-Order Theory for Functionally Graded Materials (HOTFGM), a precursor to the High-Fidelity Generalized Method of Cells micromechanics approach, was developed to investigate the coupled thermo-mechanical behavior of functionally graded composites (Aboudi et al., 1999, Composites B). For example, HOTFGM was previously used (Arnold et al, 1995, NASA CP 10178, paper 34), to assess interlaminar stresses (including free edge effects) in a substrate with a thermal barrier coating (TBC). In this study, HOTFGM micromechanics analyses will be used to assess the development and growth of a low-stiffness thermally grown oxide (TGO) layer between a silicon carbide substrate and a ytterbium disilicate EBC. In order to realistically simulate TGO growth, an evolution law will be incorporated into HOTFGM. In addition, the effect of TGO roughness will be explored consistent with previous TBC work (Pindera et al., 2000. Material Science and Engineering, A284, pp. 158-175). This model represents a first step in developing a robust analysis tool that can ultimately be used to design durable EBC systems. Additional failure modes will be considered as part of a future work.

environmental barrier coating↗