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At least 289 records · Page 16

Bio-inspired Surface Structures to Mitigate Interfacial Particle Adhesion and Erosion - A Review

Lunar dust known as regolith is a huge challenge for lunar exploration missions. Formed over millennia by a complex process involving impacts of meteoroids and micrometeoroids on the lunar surface, lunar dust is porous, highly abrasive with sharp jagged edges, chemically reactive, electrostatically charged and sometimes magnetic. The chemical composition and thickness of the dust layer also varies in different regions of the lunar surface. From samples obtained by previous lunar missions, the average particle size is below 100 microns. This dust has the tendency to strongly adhere to any exposed surfaces, and often degrades the material functionality to eventually cause failure. Any material on the lunar surface is also subject to harsh temperature cycles ranging from -178 ̊C to + 123 ̊C and extreme ultraviolet radiation. While on the lunar surface, different classes of materials would be required for different applications. Advanced materials have been and will be used throughout the lunar lander, habitat, and mission equipment. Examples include: polymeric materials for astronaut protective clothing; metals and ceramics for the lunar lander legs and habitats, and excavating equipment; and semiconductors for solar panels and on-board electronics. In all these applications, the surfaces of the materials are expected or understood to be exposed to the extreme lunar environment condition that includes the regolith dust. During the Apollo missions, the dust clung to and abraded the astronaut’s suits, degraded seals, optics, clogged sensors and reduced performance of thermal radiators. The lunar dust adheres to the surface by various mechanisms, which include electrostatic and Coulombic interactions, Van-der-Waals forces, magnetic forces, mechanical interlocking, chemical bonding and donor-acceptor interactions. There are three primary strategies for developing technologies to minimize the lunar dust adhesion: active, passive and a combination of active and passive. In the active approach, an external energy is needed to prevent or remove particles from collecting on the surface. Mechanically powered brushes and electrodynamic dust screens are two examples. In the passive approach, no external power is needed, and the material surface properties are able to mitigate dust adhesion. A well-known example of this strategy is the low work function coatings for non-stick surfaces. In most cases a combination of active and passive methods might be needed to optimally manage the lunar regolith. The passive method is significantly more attractive as it does not require any external power or an additional control subsystem. These approaches optimize the mission payload and reduce risk. Surface modification to minimize the dust adhesion is thus very important to lunar missions. Here, naturally evolved surface structures might provide guidance for solutions. There are several factors that have to be considered for minimizing particle adhesion to a surface. These include the substrate material properties, surface topography, chemistry, and the characteristics of the adhering particles. When engineering a surface, the substrate material chosen would be dependent on the needs of the application. Tailoring the surface microstructure or chemistry opens up more possibilities for its optimal utilization

Lunar Dust↗

A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the deficiencies that currently exist in materials informatics, particularly a lack of standardized experimental data management. The challenges associated with experimental data management are especially true for combinatorial materials science, where advancements in automation of experimental workflows have produced datasets that are often too large and too complex for human reasoning. The data management challenge is further compounded by the multimodal and multi-institutional nature of these datasets, as they tend to be distributed across multiple institutions and can vary substantially in format, size, and content. Furthermore, modern materials engineering requires the tuning of not only composition but also of phase and microstructure to elucidate processing–structure–property–performance relationships. To adequately map a materials design space from such datasets, an ideal materials data infrastructure would contain data and metadata describing (i) synthesis and processing conditions, (ii) characterization results, and (iii) property and performance measurements. In this work, we present a case study for the low-barrier development of such a dashboard that enables standardized organization, analysis, and visualization of a large data lake consisting of combinatorial datasets of synthesis and processing conditions, X-ray diffraction patterns, and materials property measurements generated at several different institutions. While this dashboard was developed specifically for data-driven thermoelectric materials discovery, we envision the adaptation of this prototype to other materials applications, and, more ambitiously, future integration into an all-encompassing materials data management infrastructure.

36 MATERIALS SCIENCE↗

Predicting extreme anisotropy and shape variations in impact testing of tantalum single crystals

We report recent Taylor cylinder impact tests carried out for Ta single crystals showed strong variations in dimensional changes for different crystallographic directions aligned with the cylindrical axis. In order to capture the effect of crystallography on the deformation characteristics and final shapes of the impacted cylinders, a single crystal material subroutine is adapted and embedded in the solid mechanics/dynamics Finite Element solver Abaqus to simulate the aforementioned single crystal Ta Taylor impact experiments. Details of the coupled model implementation, and insights on the role played by single crystal anisotropic flow on the deformation behavior across a broad range of strain rates and temperatures for different single crystal orientations are presented and discussed. We demonstrate the predictive capability of the adopted crystal plasticity model to capture the significant role played by crystal orientation-induced anisotropy, as well as strain hardening and adiabatic heating, on the dynamic deformation response of crystalline materials. This re-emphasizes the need of microstructure-aware models to improve the accuracy of simulations for high-consequence engineering design.

36 MATERIALS SCIENCE↗

Real-space visualization of a defect-mediated charge density wave transition

Here, we study the coupled charge density wave (CDW) and insulator-to-metal transitions in the 2D quantum material 1T-TaS 2 . By applying in situ cryogenic 4D scanning transmission electron microscopy with in situ electrical resistance measurements, we directly visualize the CDW transition and establish that the transition is mediated by basal dislocations (stacking solitons). We find that dislocations can both nucleate and pin the transition and locally alter the transition temperature T c by nearly ~75 K. This finding was enabled by the application of unsupervised machine learning to cluster five-dimensional, terabyte scale datasets, which demonstrate a one-to-one correlation between resistance—a global property—and local CDW domain-dislocation dynamics, thereby linking the material microstructure to device properties. This work represents a major step toward defect-engineering of quantum materials, which will become increasingly important as we aim to utilize such materials in real devices.

4D-STEM↗

Performance Evaluation of LPBF Manufactured 316H Components

This work represents the continuation of a benchmark study that includes modeling, fabrication and characterization as demonstration to support industry’s adoption of advanced manufacturing processes in a variety of structures. This comprehensive study investigated the feasibility of using additive manufacturing (AM) technologies, specifically Laser Powder Direct Energy Deposition (LP-DED) and Laser Powder Bed Fusion (LPBF), to produce complex nuclear microreactor components using 316H stainless steel. The research focused on manufacturing an expanded elbow pipe component with transitioning sections, which are traditionally difficult and costly to produce through conventional manufacturing methods. The overall study’s primary objectives are therefore demonstrating AM viability for nuclear applications, optimizing process parameters, developing comprehensive material characterization protocols, validating computational modeling approaches, and establishing manufacturing guidelines for complex geometries. Although the initial work included the phased approach of cubical, upscaled cylindrical components, it is to enable to obtain more knowledge for the printing of the expanded elbow structure. The project achieved significant progress in process development by successfully optimizing LP-DED parameters to achieve 99.16-99.97% relative density in 316H stainless steel components. Through systematic evaluation of sixteen cube samples with varied laser powers (400-700W) and scan speeds (600-900 mm/min), optimal processing windows were identified at 500-550W with 600-700 mm/min or 650-700W with 650-900 mm/min scan speeds. The DED manufactured 316H demonstrated mechanical properties comparable or superior to wrought materials, with Young's modulus ranging from 153-208 GPa and controlled microstructural characteristics including greater than 95% face-centered cubic (FCC) phases and engineered cellular structures with sizes between 3.23-6.17 µm.

36 MATERIALS SCIENCE↗

Characterizing the microstructures of mammalian enamel by synchrotron phase contrast microCT

The enamel of mammalian teeth is a highly mineralized tissue that must endure a lifetime of cyclic contact and is inspiring the development of next-generation engineering materials. Attempts to implement enamel-inspired structures in synthetic materials have had limited success, largely due to the absence of a detailed understanding of its microstructure. Here, the present work used synchrotron phase-contrast microCT imaging to evaluate the three-dimensional microstructure of enamel from four mammals including Lion, Gray Wolf, Snow Leopard, and Black Bear. Quantitative results of image analysis revealed that the decussation pattern of enamel consists of discrete diazone (D) and parazone (P) bands of rods organized with stacking arrangement of D+/P/D-/P in all mammals evaluated; the D+ and D- refer to distinct diazone bands with juxtaposed rod orientations from the reference plane. Furthermore, the rod orientations in the bands can be described in terms of two principal angles, defined here as the pitch and yaw. While the pitch angle increases from the outer enamel to a maximum (up to ≈ 40°) near the dentin enamel junction, minimal spatial variations are observed in yaw across the enamel thickness. There are clear differences in the decussation parameters of enamel across species that are interpreted here with respect to the structural demands placed on their teeth. The rod pitch and band width of enamel are identified as important design parameters and appear to be correlated with the bite force quotient of the four mammals evaluated.

36 MATERIALS SCIENCE↗

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗

Characterization of paste microstructure for durability properties of concrete

In this study, paste samples from different cementitious systems were characterized by using X-Ray Micro Computed Tomography (µ-CT) and Fluorescence Microscopy techniques. Quantitative and qualitative aspects of defects from paste samples were investigated to develop indicators of durability related properties of corresponding concrete samples. In the first phase of this study, hour glass shaped 3D printed molds were used to investigate five cementitious combinations consisting of three cement types (Coarse Ground portland cement, Type IL Portland Limestone Cement and Type I/II ordinary portland cement) and fly ash as a supplementary cementitious material. In the second phase, metal molds were used to compare the results of Coarse Ground portland cement with Type I ordinary portland cement, 5% of which was replaced with colloidal nanosilica. Potential correlations between paste and concrete have been presented. This work was supported by US Department of Energy and North Dakota Department of Commerce.

36 MATERIALS SCIENCE↗

Refining Microstructures in Additively Manufactured Al/Cu Gradients Through TiB 2 Inclusions

Here, the additive manufacture of compositionally graded Al/Cu parts by laser engineered net shaping (LENS) is demonstrated. The use of a blue light build laser enabled deposition on a Cu substrate. The thermal gradient and rapid solidification inherent to selective laser melting enabled mass transport of Cu up to 4 mm from a Cu substrate through a pure Al deposition, providing a means of producing gradients with finer step sizes than the printed layer thicknesses. Divorcing gradient continuity from layer or particle size makes LENS a potentially enabling technology for the manufacture of graded density impactors for ramp compression experiments. Printing graded structures with pure Al, however, was prevented by the growth of Al 2 Cu 3 dendrites and acicular grains amid a matrix of Al 2 Cu. A combination of adding TiB 2 grain refining powder and actively varying print layer composition suppressed the dendritic growth mode and produced an equiaxed microstructure in a compositionally graded part. Material phase was characterized for crystal structure and nanoindentation hardness to enable a discussion of phase evolution in the rapidly solidifying melt pool of a LENS print.

36 MATERIALS SCIENCE↗

Thermochemical and microstructural contributions of high temperature particle erosion durability in CMAS exposed EBCs

Particulate/debris damage caused by ingestion of calcium magnesium aluminosilicates (CMAS) hinders the use of environmental barrier coatings (EBCs) to protect SiC-based ceramic matrix composite components in next generation gas turbine engines. Similarly, ingestion of any debris in the engine can lead to mechanical damage and recession of coatings due to particulate erosion. Investigating particulate interactions at relevant engine conditions is crucial in determining limiting mechanisms in the operating lifetime of EBCs. This study assesses the effects of extrinsic phase formation and microstructural changes due to CMAS interactions on the erosion durability of Yb 2 Si 2 O 7 -based EBCs in NASA Glenn’s Erosion Burner Rig Facility. CMAS exposures and erosion testing were carried out at 1316°C. Using 60 µm Al 2 O 3 particles as the erodent material, the effects of CMAS loading on erosion durability at various impingement angles were evaluated.

Jamesa L. Stokes↗

Bioinspired nonwetting surfaces for corrosion inhibition over a range of temperature and corrosivity

Applications of superhydrophobic (SHS) and lubricant infused surfaces (LIS) involve exposure to corrosive environments from the acidic to the basic, at a range of temperatures, that are not fully characterized. Here, we present for the first time a multifactorial study of the effects of surface fabrication method, surface modification, surface functionalization time, temperature and pH of the immersion medium on the corrosion performance of nonwetting copper surfaces. Bioinspired SHS and LIS fabricated using facile methods of etching and electrodeposition are systematically assessed using potentiodynamic polarization measurements for their corrosion resistance in saline solution (pH ≈7) over a temperature range 23–85°C. SHS and LIS are shown to exhibit diminished corrosion rate, by up to two orders of magnitude, compared to bare copper surface. An Arrhenius model is developed for the first time, describing the temperature- dependent corrosion rate of SHS and LIS. Electrochemical impedance spectroscopy is used to show that corrosion resistance of LIS is larger by three orders of magnitude in extremely acidic (pH = 1) and by an order magnitude in extremely alkaline (pH = 14) media compared to bare copper surface. Etched LIS are generally more resistant to corrosion compared to SHS at all temperatures with excellent microstructural durability.

42 ENGINEERING↗

Los Alamos Summer Project 2020 [PowerPoint]

The summer project dealt with Additively Manufactured Energetic Material (AMEM) . The intent is to bridge the gap between macroscale print level structure, and explicitly resolved PBX microstructures.

36 MATERIALS SCIENCE↗

Model-informed, Adaptive Physical Vapor Deposition to Fabricate Hierarchical Binary-alloy Thin-films

Designing next generation thin films, tailor-made for specific applications, relies on the availability of robust processing-structure-property relationships. Traditional structure zone diagrams are limited to low-dimensional mappings, with machine-learning methods only recently attempting to relate multiple processing parameters to the final microstructure. Despite this progress, structure-processing relationships are unknown for processing conditions that vary during thin-film deposition, limiting the range of microstructures and properties achievable. In this project, we employed a phase-field computational model combined with a genetic algorithm (GA) to identify and design time-dependent processing protocols that achieve tailor-made microstructures. We simulate the physical vapor deposition of a binary-alloy thin film by employing a phase-field model, where deposition rates and diffusivities are controlled via the genetic algorithm. Our GA-guided protocols achieve targeted microstructures with lateral and vertical concentration modulations, as well as more complex, hierarchical microstructures previously not described in simple structure zone diagrams. Our algorithm provides insight to experimentalists looking for additional avenues to design novel thin-film microstructures.

36 MATERIALS SCIENCE↗

Failure analysis of a tool steel torque shaft

A low design load drive shaft used to deliver power from an experimental exhaust heat recovery system to the crankshaft of an experimental diesel truck engine failed during highway testing. An independent testing laboratory analyzed the failure by routine metallography and attributed the failure to fatigue induced by a banded microstructure. Visual examination by NASA of the failed shaft plus the knowledge of the torsional load that it carried pointed to a 100 percent ductile failure with no evidence of fatigue. Scanning electron microscopy confirmed this. Torsional test specimens were produced from pieces of the failed shaft and torsional overload testing produced identical failures to that which had occurred in the truck engine. This pointed to a failure caused by a high overload and although the microstructure was defective it was not the cause of the failure.

Reagan, J. R.↗

Advances in imaging, scattering, spectroscopy, and machine learning-aided approaches for multiscale characterization of cementitious systems

Recent progress in methods used in the multiscale characterization of cementitious systems is reviewed, focusing on advances in imaging, scattering, and spectroscopy. The review includes relevant applications and developments in machine learning and other data analytics approaches to enhance characterization. Developments in imaging using light and electron microscopy as well as x-ray (i.e., from synchrotron) methods are summarized. Updates include scanning electron microscopy (SEM), transmission electron microscopy (TEM), tomography, and holography. A critical overview of spectroscopy (e.g., MAS NMR, Raman) and scattering (e.g., neutron, x-ray, synchrotron x-ray) methods is provided, and the intersection of these with imaging is developed (e.g., Raman imaging). Additionally, the paper summarizes recent developments in and implementations of state-of-the-art machine-learning algorithms and data analytics methods for automated, systematic, and/or quantitative analyses of image data sets. The review considers but is not limited to the application of these methods for investigating the hydration and microstructure development of cement phases, low-carbon-footprint cements (e.g., limestone calcined clay cements, LC3), environmental interactions (e.g., ASR) and model systems. Finally, the present work provides a critical presentation of advances in characterization methods that link together the composition and multiscale structure of cementitious materials.

42 ENGINEERING↗

Interfacial-Strain-Controlled Ferroelectricity in Self-Assembled BiFeO 3 Nanostructures

Self-assembled BiFeO 3 -CoFe 2 O 4 (BFO-CFO) vertically aligned nanocomposites are promising for logic, memory, and multiferroic applications, primarily due to the tunability enabled by strain engineering at the prodigious epitaxial vertical interfaces. However, local investigations directly revealing functional properties in the vicinity of such critical interfaces are often hampered by the size, geometry, microstructure, and concomitant experimental artifacts. Ferroelectric switching in the presence of lateral distributions of vertical strain thus remains relatively unexplored, with broader implications for all strain-engineered functional devices. Additionally, by implementing tomographic atomic force microscopy, 3D domain orientation mapping, and spatially-resolved ferroelectric switching movies, local tensile strain significantly impacts the ferroelectric switching, principally by retarding domain nucleation in the BFO nearest to the vertically epitaxial tensile-strained interfaces. The relaxed centers of the BFO pillars become preferred domain nucleation and growth sites for low biases, with up to an order of magnitude change in the edge:center switching ratio for high biases. The new, multi-dimensional imaging approach—and its corresponding insights especially for directly strained interface effects on local properties—thereby advances the fundamental understanding of polarization switching and provides design principles for optimizing functional response in confined nanoferroic systems.

36 MATERIALS SCIENCE↗

A 2000-hour cyclic endurance test of a laboratory model multipropellant resistojet

The technological readiness of a long-life multipropellant resistojet for space station auxiliary propulsion is demonstrated. A laboratory model resistojet made from grain-stabilized platinum served as a test bed to evaluate the design characteristics, fabrication methods, and operating strategies for an engineering model multipropellant resistojet developed under contract by the Rocketdyne Division of Rockwell International and Technion Incorporated. The laboratory model thruster was subjected to a 2000-hr, 2400-thermal-cycle endurance test using carbon dioxide propellant. Maximum thruster temperatures were approximately 1400 C. The post-test analyses of the laboratory model thruster included an investigation of component microstructures. Significant observations from the laboratory model thruster are discussed as they relate to the design of the engineering model thruster.

Morren, W. Earl↗