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At least 73 records · Page 4

On the Cu-Nb Phase Diagram and Solidified Microstructures

Container and containerless processing was employed to determine liquidus temperatures and to examine microstructural development in the Cu-Nb system. The Cu-Nb phase diagram of an S-shaped, near-horizontal liquidus, has been confirmed by both the temperature-time profiles and resultant microstructures with only Nb dendrites in a Cu matrix, which were obtained from crucible experiments under clean conditions. However, the microstructural pathways of Cu-Nb alloys are particularly sensitive to processing variables. By the addition of oxygen impurities or rapid solidification, droplet-shaped morphology was observed for some compositions, implying occurrence of a liquid-phase separation. The effects of impurities and cooling rates are analyzed in connection with a stable and metastable liquid miscibility gap, respectively.

Li, D.↗

Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) with many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.

42 ENGINEERING↗

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗

Time–connectivity superposition and the gel/glass duality of weak colloidal gels

Colloidal gels result from the aggregation of Brownian particles suspended in a solvent. Gelation is induced by attractive interactions between individual particles that drive the formation of clusters, which in turn aggregate to form a space-spanning structure. We study this process in aluminosilicate colloidal gels through time-resolved structural and mechanical spectroscopy. Using the time–connectivity superposition principle a series of rapidly acquired linear viscoelastic spectra, measured throughout the gelation process by applying an exponential chirp protocol, are rescaled onto a universal master curve that spans over eight orders of magnitude in reduced frequency. This analysis reveals that the underlying relaxation time spectrum of the colloidal gel is symmetric in time with power-law tails characterized by a single exponent that is set at the gel point. The microstructural mechanical network has a dual character; at short length scales and fast times it appears glassy, whereas at longer times and larger scales it is gel-like. These results can be captured by a simple three-parameter constitutive model and demonstrate that the microstructure of a mature colloidal gel bears the residual skeleton of the original sample-spanning network that is created at the gel point. Our conclusions are confirmed by applying the same technique to another well-known colloidal gel system composed of attractive silica nanoparticles. The results illustrate the power of the time–connectivity superposition principle for this class of soft glassy materials and provide a compact description for the dichotomous viscoelastic nature of weak colloidal gels.

36 MATERIALS SCIENCE↗

Critical Current Distributions of Recent Bi-2212 Round Wires

Bi 2 Sr 2 CaCu 2 O 8+x (Bi-2212) is the only high-field, high-temperature superconductor (HTS) capable of reaching a critical current density J c (16 T, 4.2 K) of 6500 A·mm –2 in the highly desirable round wire (RW) form. However, state-of-the-art Bi-2212 conductors still have a critical current density (J c ) to depairing current density (J d ) ratio around 20 to 30 times lower than that of state-of-the-art Nb–Ti or REBCO. Previously, we have shown that recent improvements in Bi-2212 RW J c are due to improved connectivity associated with optimization of the heat treatment process, and most recently due to a transition to a finer and more uniform powder manufactured by Engi-Mat. One quantitative measure of connectivity may be the critical current (I c ) distribution, since the local I c in a wire can vary along the length due to variable vortex-microstructure interactions and to factors such as filament shape variations, grain-to-grain connectivity variations and blocking secondary phase distributions. Modeling the experimental V-I transition measured on a low resistance shunt as a complex sum of voltage contributions of individual filament and wire sub-sections allows a numerical extraction of the I c distribution from the d 2 V/dI 2 treatment of the V-I curves. Here we compare ~0.1 m length I c distributions of Bi-2212 RWs with recent state-of-the-art very high-J c Engi-Mat powder and lower J c and older Nexans granulate powder. We do find that the I c spread for Bi-2212 wires is about twice the relative standard of high-J c Nb–Ti well below H irr . We do not yet see any obvious contribution of the Bi-2212 anisotropy to the I c distribution and are rather encouraged that these Bi-2212 round wires show relative I c distributions not too far from high-J c Nb–Ti wires.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

Polymer composites based on gypsum matrix

The role of polymers as retarder additives is to prolong the workability connected with setting time of gypsum. Various cellulose derivatives, soluble in water in concentration up to 1,5% by weight were applied taking different water/binder ratio. The hydration process of calcium sulfate hemihydrate (gypsum binder) into dihydrate (gypsum plaster) was observed by setting and calorimetric techniques. Scanning electron microscopy confirmed that the gypsum microstructure was varied when polymers are used. The mechanical properties of gypsum plasters were studied by bending strength test and they are correlated with sample microstructure.

36 MATERIALS SCIENCE↗

An Insidious Mode of Oxidative Degradation in a SiC-SiC Composite

The oxidative durability of a SiC-SiC composite with Hi-Nicalon fiber and BN interphase was investigated at 800 C (where pesting is known to occur in SiC-SiC composites) for exposure durations of up to 500 hours and in a variety of oxidant mixes and flow rates, ranging from quasi-stagnant room air, through slow flowing O2 containing 30-90% H2O, to the high-velocity flame of a burner rig. Degradation of the composite was determined from residual strength and fracture strain in post-exposure mechanical tests and correlated with microstructural evidence of damage to fiber and interphase. The severest degradation of composite behavior was found to occur in the bumer rig, and is shown to be connected with the high oxidant velocity and substantial moisture content, as well as a thin sublayer of carbon indicated to form between fiber and interphase during composite processing.

Ogbuji, Linus U. J. T.↗

High-energy x-ray scattering studies of battery materials

High-energy x-ray (HEX) scattering is a sensitive and powerful tool to nondestructively probe the atomic and mesoscale structures of battery materials under synthesis and operational conditions. The penetration power of HEXs enables the use of large, practical samples and realistic environments, allowing researchers to explore the inner workings of batteries in both laboratory and commercial formats. This article highlights the capability and versatility of HEX techniques, particularly from synchrotron sources, to elucidate materials synthesis processes and thermal instability mechanisms in situ, to understand (dis)charging mechanisms in operando under a variety of cycling conditions, and to spatially resolve electrode/electrolyte responses to highlight connections between inhomogeneity and performance. Such studies have increased our understanding of the fundamental mechanisms underlying battery performance. Here, by deepening our understanding of the linkages between microstructure and overall performance, HEXs represent a powerful tool for validating existing batteries and shortening battery-development timelines.

25 ENERGY STORAGE↗

Micro- and nano-porosity of the active Alpine Fault zone, New Zealand

Porosity reduction in rocks from a fault core can cause elevated pore fluid pressures and consequently influence the recurrence time of earthquakes. We investigated the porosity distribution in the New Zealand's Alpine Fault core in samples recovered during the first phase of the Deep Fault Drilling Project (DFDP-1B) by using two-dimensional nanoscale and three-dimensional microscale imaging. Synchrotron X-ray microtomography-derived analyses of open pore spaces show total microscale porosities in the range of 0.1 %–0.24 %. These pores have mainly non-spherical, elongated, flat shapes and show subtle bipolar orientation. Scanning and transmission electron microscopy reveal the samples' microstructural organization, where nanoscale pores ornament grain boundaries of the gouge material, especially clay minerals. Our data imply that (i) the porosity of the fault core is very small and not connected; (ii) the distribution of clay minerals controls the shape and orientation of the associated pores; (iii) porosity was reduced due to pressure solution processes; and (iv) mineral precipitation in fluid-filled pores can affect the mechanical behavior of the Alpine Fault by decreasing the already critically low total porosity of the fault core, causing elevated pore fluid pressures and/or introducing weak mineral phases, and thus lowering the overall fault frictional strength. We conclude that the current state of very low porosity in the Alpine Fault core is likely to play a key role in the initiation of the next fault rupture.

58 GEOSCIENCES↗

Pore2Chip: All-in-one python tool for soil microstructure analysis and micromodel design

The Pore2Chip Python package is designed to create 2D micromodels using extracted data from 3D X-ray computed tomography (XCT) images. This package helps analyze soil structure and function, allowing for the investigation of hydro-biogeochemical processes that impact mineral extraction and reactivity, oxygen concentrations, and nutrient availability in disturbed or managed soils. Key metrics encompass pore size distributions, pore throat size distributions, and connectivity (pore coordination numbers). The final output is a 2D scalable SVG design representing a core or aggregate. Designs can be fabricated with methods such as laser etching, 3D printing, and photolithography.

lab-on-chip↗

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗

Effect of a Zinc Interlayer on a Cu/Al Lap Joint in Ultrasound-Assisted Friction Stir Welding

This study proposes a welding process, ultrasound-assisted friction stir welding of dissimilar Al/Cu metals. Zinc foil is melted using the heat generated by a pinless stirring tool, and the molten intermediate layer is stirred by ultrasonic cavitation to achieve an effective connection. The metallurgical reaction behavior of the joint under the action of the sound field was studied, and the effects of different microstructures on the joint performance were analyzed. Specifically, the following observations were reported in this study: (1) When ultrasound assistance was used, the cavitation effect changed the brittle intermetallic compounds of Al{sub 2}Cu from a continuous distribution to a block distribution, and the mechanical properties of the joint were greatly improved; (2) the effects of the thickness of the zinc were also determined. The results showed that the highest shear tensile force was obtained when the thickness of the zinc foil was 0.2 mm. When the thickness was 0.3 mm, the ultrasound effect was weakened. The copper-side interface generated a zigzag-shaped Al{sub 4.2}Cu{sub 3.2}Zn{sub 0.7} layer with a thickness of 3.4 μm and had a continuous distribution. Increasing the thickness of the zinc to 0.5 mm, however, drastically decreased the mechanical properties of the joint due to incomplete melting of the zinc layer.

36 MATERIALS SCIENCE↗

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗

A strong fracture-resistant high-entropy alloy with nano-bridged honeycomb microstructure intrinsically toughened by 3D-printing

Strengthening materials via conventional “top-down” processes generally involves restricting dislocation movement by precipitation or grain refinement, which invariably restricts the movement of dislocations away from, or towards, a crack tip, thereby severely compromising their fracture resistance. In the present study, a high-entropy alloy Al0.5CrCoFeNi is produced by the laser powder-bed fusion process, a “bottom-up” additive manufacturing process similar to how nature builds structures, with the microstructure resembling a nano-bridged honeycomb structure consisting of a face-centered cubic (fcc) matrix and an interwoven hexagonal net of an ordered body-centered cubic B2 phase. While the B2 phase, combined with high-dislocation density and solid-solution strengthening, provides strength to the material, the nano-bridges of dislocations connecting the fcc cells, i.e., the channels between the B2 phase on the cell boundaries, provide highways for dislocation movement away from the crack tip. Consequently, the nature-inspired microstructure imparts the material with an excellent combination of strength and toughness.

36 MATERIALS SCIENCE↗

Digital Rock Physics and 3D Printing for Fractured Porous Media

Imaging techniques for the analysis of porous structures have revolutionized our ability to quantitatively characterize geomaterials. Digital representations of rock from CT images and physics modeling based on these pore structures provide the opportunity to further advance our quantitative understanding of fluid flow, geomechanics, and geochemistry, and the emergence of coupled behaviors. Additive manufacturing, commonly known as 3D printing, has revolutionized production of custom parts with complex internal geometries. For the geosciences, recent advances in 3D printing technology may be co-opted to print reproducible porous structures derived from CT-imaging of actual rocks for experimental testing. The use of 3D printed microstructure allows us to surmount typical problems associated with sample-to-sample heterogeneity that plague rock physics testing and to test material response independent from pore-structure variability. Together, imaging, digital rocks and 3D printing potentially enables a new workflow for understanding coupled geophysical processes in a real, but well-defined setting circumventing typical issues associated with reproducibility, enabling full characterization and thus connection of physical phenomena to structure. Here we report on our research exploring the possibilities that these technologies can bring to geosciences for coupled multiscale experimental and numerical analysis using 3D printed fractured rock specimens.

42 ENGINEERING↗

Degradation processes in high-temperature creep of cast cobalt-based superalloys

Highlights: • Creep degradation processes in Nb or Ta strengthened cobalt-based superalloys were investigated. • CoNb superalloy exhibits longer creep life compared to CoTa superalloy. • Creep fracture ductility of CoTa superalloy is higher than CoNb superalloy. • Low fracture ductility of CoNb superalloy resulted from a premature fracture. • Ductile creep fracture in CoTa superalloy is caused by instability of dislocation microstructure. - Abstract: Degradation processes in high-temperature creep of two cast high-chromium cobalt-based superalloys strengthened by niobium and tantalum for use in the glass industry were analysed via various experimental techniques. Constant load creep tests were conducted at 900, 950 and 1000 °C in a tensile stress range from 40 to 80 MPa. It was found that the CoNb superalloy possesses considerably longer creep life compared to the CoTa superalloy under the same loading conditions. Conversely, the creep ductility of the fractured specimens shows the opposite order of the creep life. The creep behaviour of both superalloys obeys the Monkman-Grant formula indicating that the creep deformation mechanism and fracture processes are mutually interlinked. The homogeneously distributed creep damage of the CoNb superalloy is closely connected with primary carbides and is predominantly initiated either as interface decohesion between the carbide/matrix and carbide eutectics/matrix or by breakage of bulk M{sub 23}C{sub 6} carbides. The dominant type of creep damage in the CoTa superalloy is localized breakage of M{sub 23}C{sub 6} carbides in close proximity of the fracture path. The final brittle fracture in the CoNb superalloy occurs via relatively fast propagation of the longest cracks after the ultimate state of damage is reached. Due to premature fracture, the inherent creep ductility of the CoNb matrix is not exhausted. The final ductile transgranular creep fracture of the CoTa superalloy is caused by a local strain-induced instability of the dislocation microstructure leading to a loss of an external section of specimen (necking).

36 MATERIALS SCIENCE↗

Final Project Report CFA-14-6357: A New Paradigm for Understanding Multiphase Ceramic Waste Form Performance

This project fabricated model multiphase ceramic waste forms with processing-controlled microstructures followed by advanced characterization with synchrotron and electron microscopy-based 3D tomography to provide elemental and chemical state-specific information resulting in compositional phase maps of ceramic composites. Details of 3D microstructural features were incorporated into computer-based simulations using durability data for individual constituent phases as inputs in order to predict the performance of multiphase waste forms with varying microstructure and phase connectivity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗