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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Chrysler Upset Protrusion Joining Techniques for Joining Dissimilar Metals

The project goal was to develop and demonstrate a robust, cost effective, and versatile joining technique, known as Upset Protrusion Joining (UPJ), for joining challenging dissimilar metal com-binations, especially those where one of the metals is a die cast magnesium (Mg) component. Since two of the key obstacles preventing more widespread use of light metals (especially in high volume automotive applications) are 1) a lack of robust joining techniques and 2) susceptibility to galvanic corrosion, and since the majority of the joint combinations evaluated in this project include die cast Mg (the lightest structural metal) as one of the two materials being joined, and since die casting is the most common and cost effective process for producing Mg components, then successful project completion provides a key enabler to high volume application of lightweight materials, thus potentially leading to reduced costs, and encouraging implementation of lightweight multi-material vehicles for significant reductions in energy consumption and reduced greenhouse gas emissions. Eco-nomic benefits to end-use consumers are achieved primarily via the reduction in fuel consumption. Unlike currently available commercial processes, the UPJ process relies on a very robust mechanical joint rather than intermetallic bonding, so the more cathodic material can be coated prior to joining, thus creating a robust isolation against galvanic attack on the more anodic material. Additionally, since the UPJ protrusion is going through a hole that can be pre-drilled or pre-punched prior to coating, the UPJ process is less likely to damage the coating when the joint is being made. Further-more, since there is no additional cathodic material (such as a steel fastener) used to create the joint, there is no joining induced galvanic activity beyond that of the two parent materials. In accordance with its originally proposed plan, this project has successfully developed process variants of UPJ to enable joining of Mg die castings to aluminum (Al) and steel sheet components of various thicknesses, strengths and coating configurations. While most development focused on the simpler round boss version of the process, an additional phase of the work focused on devel-opment of an oval boss version to support applications with narrow flanges, while yet another vari-ant of the process, known as Upset Cast Riveting (UCR), was developed and evaluated for joining mixed metals that may not necessarily include Mg or Al die cast components. Although each varia-tion posed unique challenges described later in the report, all variations were successfully produced and evaluated, and each could be further developed for specific types of commercial applications. In this project, UPJ performed favorably against the benchmark self-pierce riveting (SPR) process in Mg AM60B to Al 6013 combinations although significant corrosion challenges were observed in both processes, especially for the bare Mg to bare Al configurations. Additional challenges were observed in joining Mg to steel with the UPJ process (SPR was not evaluated for this combination as it was not considered viable). To pass FCA’s specified corrosion tests with Mg/steel combina-tions, new steel treatments were evaluated, as well as adhesives and sealed edges. These showed significant improvement. In general, UPJ performed very well in Mg to Al 6016 combinations, even in corrosion evaluation of the bare Mg to bare Al configuration (again, SPR was not evaluated for this material combination as the 1.1 mm thick Al6016 sheet thickness was considered too thin for the SPR process). The improvement in corrosion performance of the Mg to Al 6016 combina-tion over the Mg to Al 6013 combination was thought to be a result of the lower copper content in the Al 6016 alloy. Oval boss joints showed substantial improvement in all joint strength criteria compared to 8.0-mm diameter round boss joints but were not evaluated for corrosion performance. The improved joint strength is likely a result of larger shear area. Cosmetic corrosion performance of all test assemblies (UPJ, UCR and SPR) was a challenge due to exposed edges and crevices al-lowing undercutting of the coatings. In real world component applications, the exposed edges, so prevalent on the joining test coupons, would be less prevalent and easier to protect.

36 MATERIALS SCIENCE↗

Radiation‐Resistant Aluminum Alloy for Space Missions in the Extreme Environment of the Solar System

Future human exploration of the solar system demands advanced materials capable of withstanding extreme environments, particularly exposure to solar energetic particle radiation. Current material selection criteria for space applications prioritize a high strength-to-weight ratio, high corrosion resistance and manufacturability, favoring age-hardenable Al-based alloys. However, conventional precipitation-hardened Al alloys suffer from irradiation-assisted dissolution of strengthening phases at doses as low as 0.2 displacements-per-atom (dpa), undermining their performance. Furthermore, these alloys develop radiation-induced defects, such as dislocation loops and voids, even at low doses. This study presents a novel ultrafine-grained (UFG) Al-based alloy, designed using the crossover alloying concept and strengthened by T-phase precipitates, featuring a chemically-complex structure with 162 atoms in its unit cell composed of Mg 32 (Zn,Al) 49 . It is showed that T-phase precipitates have exceptional radiation tolerance up to 24 dpa. Owing to the nanoscale UFG structure, dislocation loops are suppressed, and voids are only observed beyond 75 dpa. Microtensile tests up to 20 dpa confirm the preservation of mechanical performance under irradiation. The results underline the potential of this alloy as a radiation-resistant, lightweight material for future space applications. Three key strategies enable this performance: (i) stabilization of a UFG microstructure, (ii) T-phase precipitation featuring a highly negative Gibbs free energy and chemically-complex giant unit cell, and (iii) precise process control to prevent grain growth during heat treatment and irradiation.

36 MATERIALS SCIENCE↗

A Novel CAE Method for Compression Molding Simulation of Carbon Fiber-Reinforced Thermoplastic Composite Sheet Materials

Its high-specific strength and stiffness with lower cost make discontinuous fiber-reinforced thermoplastic (FRT) materials an ideal choice for lightweight applications in the automotive industry. Compression molding is one of the preferred manufacturing processes for such materials as it offers the opportunity to maintain a longer fiber length and higher volume production. In the past, we have demonstrated that compression molding of FRT in bulk form can be simulated by treating melt flow as a continuum using the conservation of mass and momentum equations. However, the compression molding of such materials in sheet form using a similar approach does not work well. The assumption of melt flow as a continuum does not hold for such deformation processes. To address this challenge, we have developed a novel simulation approach. First, the draping of the sheet was simulated as a structural deformation using the explicit finite element approach. Next, the draped shape was compressed using fluid mechanics equations. The proposed method was verified by building a physical part and comparing the predicted fiber orientation and warpage measurements performed on the physical parts. The developed method and tools are expected to help in expediting the development of FRT parts, which will help achieve lightweight targets in the automotive industry.

36 MATERIALS SCIENCE↗

Charge‐Programmable Photopolymers for 3D Electronics via Additive Manufacturing

Charge‐programmed 3D printing enables the fabrication of 3D electronics with lightweight and high precision via selective patterning of metals. This selective metal deposition is catalyzed by Pd nanoparticles that are specifically immobilized onto the charged surface and promises to fabricate a myriad of complex electronic devices with self‐sensing, actuation, and structural elements assembled in a designed 3D layout. However, the achievable property space and the material‐performance correlation of the charge‐programmed printing remain unexplored. Herein, a series of photo‐curable resins are designed for unveiling how the charge and crosslink densities synergistically impact the nanocatalyst‐guided selective deposition in catalytic efficiency and properties of the 3D printed charge‐programmed architectures, leading to high‐quality 3D patterning of solid and liquid metals. The findings offer a wide tunability of the structural properties of the printed electronics, ranging from stiff to extreme flexibility. Capitalizing on these results, the printing and successful application of an ultralight‐weight and deployable 3D multi‐layer antenna system operating at an ultrahigh‐frequency of 19 GHz are demonstrated.

36 MATERIALS SCIENCE↗

Microporous and Flexible Framework Acoustic Metamaterials for Sound Attenuation and Contrast Agent Applications

The low-frequency (100-1250 Hz) acoustic properties of metal-organic framework (MOF) materials were examined in impedance tube experiments. The anomalously-high sound transmission loss of HKUST-1, FeBTC, and MIL-53(Al) quantitatively demonstrated that these prototypical MOFs are absorptive acoustic metamaterials. To the best of our knowledge this is the first example of MOFs that have been demonstrated to be acoustic metamaterials. The low-frequency acoustic dampening by subwavelength MOF metamate-rials is likely due to sound dissipation and absorption facilitated by multiple internal reflections within the microporous framework structure. Modification of MIL-53(Al) with flexible organic linkers clarified that acoustic signatures of the metal-organic frameworks may be tailored to add or alter certain diagnostic acoustic signatures. These results may be applied to the rational design of lightweight sound-insulating construction materials and acoustic contrast agents for subsurface mapping and monitoring applications at low frequency (100-1250 Hz).

Miller, Quin R. S. (ORCID:0000000330099702)↗

3D printable polymeric lightning strike protection system for fiber reinforced composites

The current embodiments include all-polymeric protective material for mitigating lightning strike damage. The protective material includes a hybrid matrix comprising PANI and MXene dispersed within a thermosetting epoxy resin. This hybrid matrix can be painted, printed, or applied as a conductive polymeric layer to a FRCP structure, for example an aircraft fuselage, wing, empennage, control surface (aileron, flap, slats, rudder, elevator) or a wind turbine blade. The protective material not only withstands lightning strikes, but also functions as shielding against electromagnetic interference and is corrosion-resistant and lightweight.

Kumar, Vipin↗

Fabrication of Conductive Paths on a Fused Deposition Modeling Substrate using Inkjet Deposition

Inkjet deposition is one of the most attractive fabrication techniques for producing cost efficient and lightweight electronic devices on various substrates with low environmental impact. Fused Deposition Modeling (FDM) is one of the most used and reliable additive manufacturing processes by extrusion of wire-shaped thermoplastic materials, which provides an opportunity for embedding printed electronics into mechanical structures during the building process and enables the design of compact smart structures that can sense and adapt to their own state and the environment. This paper represents one of the first explorations of integrating inkjet deposition of silver nanoparticle inks with the FDM process for making compact electro-mechanical structures. Three challenges have been identified and investigated, including the discontinuity of the printed lines resulting from the irregular surface of the FDM substrate, the non-conductivity of the printed lines due to the particle segregation during the droplet drying process, and the slow drying process caused by the skinning effect . Two different techniques are developed in this paper to address the issue of continuity of the printed lines, including surface ironing and a novel thermal plow technique that plows a channel in the FDM substrate to seal off the pores in the substrate and contain the deposited inks. Two solutions are also found for obtaining conductivity from the continuous printed lines, including porous surface coating and using a more viscous ink with larger nanoparticle size. Then the effects of the printing and post-processing parameters on the conductivity are examined. It is found that post-processing is a dominant factor in determining the conductivity of the printed lines.

42 ENGINEERING↗

Friction Stir Scribe Joining of Carbon Fiber Reinforced Polymer (CFRP) to Aluminum

The purpose of this project was to develop the critical process technology, models, and tools necessary to advance the Friction Stir Scribe, FSS, joining method through experimentation, validation at the laboratory scale, and integration into a production-like robotic environment. Implementation of FSS technology for joining polymer composites to metals will enable greater use of lightweight materials by providing technology capable of joining linear configurations without the use of adhesives or other third-body fasteners by creating an in-situ joint from the parent materials. As FSS technology provides the capability to join multi-material structures on robotic platforms using linear configurations, the development of this technology for use on the BIW will impact a great diversity of CFRP joints within the vehicle; thus, allowing a greater reduction in vehicle mass through more specifically designed structures. The FSS process has been developed to include integration of the FSS tool with a stationary shoulder, which has been shown to be required to achieve the desired surface quality (i.e., crown flash level). However, the targeted joint strength has not been achieved because the resulting stirred CFRP microstructure does not provide similar performance as the as-molded composite leading to low fracture strengths despite our efforts investigating various unique alternative approaches. In support of the experimental work, a process-structure model was developed and validated for the FSS joining (FSSJ) process using surrogate materials (steel and Al). The cyclic corrosion testing of the FSS joints and self-piercing riveted (SPR) joints revealed different modes of galvanic corrosion in the two types of joints. The SPR samples exhibited a greater amount of corrosion on the external surfaces. The presence of steel rivets in these joints exacerbated the situation, with the rivets getting preferentially corroded. The FSSJ samples despite exhibiting less surface corrosion, exhibited severe corrosion under the joint overlap area.

36 MATERIALS SCIENCE↗

LightMAT: Continous Fiber Malleable Thermoset Composites with sub-1-minute dwell times; validation of impact performance and evaluation of the efficacy of the compression forming process

Recent major advances in polymer chemistry are enabling a paradigm shift in the area of processing and re-processing/recycling of advanced composite materials. Inexpensive compression molding with short cycle times, traditionally available for thermoplastic composites only, are now possible for the thermoset resins based on polyimine chemistry. Participant will collaborate with the LightMAT consortium Labs ORNL, SNL, and PNNL to non-destructively characterize microscopic structural defects (such as voids and resin-rich areas), and perform high speed impact characterization of its malleable thermoset CFRP's. This work is critical to the validation and adoption of these materials for the automotive market and towards DOE-VTO lightweighting mission objectives.

36 MATERIALS SCIENCE↗

Synthesis and Processing by Design of High-Nickel Cathode Materials

The high demand of lightweight, high energy density batteries for energy storage promotes new materials discovery and development. Despite the large number of battery materials being discovered, very few of them have been commercially deployed, mostly bottlenecked by synthesis and processing – namely, making certain phases with the desired structure and properties to meet the multifaceted performance requirements. Alternative to the traditional trial and error, we present here an in situ study aided synthesis- and processing-by-design approach. With specific examples, we illustrate how to use the approach to identify reaction pathways in synthesis and processing of high-Nickel (Ni) cathode materials for next-generation lithium-ion batteries, thereby ensuring precise control of their structure, morphology, and surface properties. Furthermore, perspectives are provided on the wide applicability of the approach to solving critical issues inherent to high-Ni cathodes and the new directions and opportunities in the area.

36 MATERIALS SCIENCE↗

Elucidating microstructural evolution and hardness variation across friction self-piercing riveted Al-7055 using synchrotron X-ray scattering and advanced microscopy techniques

Friction self-piercing riveting (FSPR) is a unique hybrid joining technique that combines the advantages of mechanical interlocking, frictional heat, and solid-state joining (if metallurgically compatible) to produce crack free joints in high strength and/or low-ductility alloys at room temperature. Here, in the current study, Al-7055 sheets were joined using FSPR for lightweight automotive applications and significant microhardness variations were observed across the joint cross-section. A detailed microstructural characterization at multiple length scales was carried out using advanced electron microscopy and X-ray scattering techniques to provide a fundamental understanding of the process-structure-property relationships. The relative contributions of microstructural characteristics at various length scales (i.e., grain size, dislocation density, solute concentration, precipitate nature) to strengthening were estimated using existent formulations (i.e., Hall-Petch, Taylor, precipitate bypass/shear equations) and correlated to the observed microhardness values across different regions. Small-angle X-ray scattering and scanning transmission electron microscopy revealed significant changes in the size and volume fraction of precipitate species, i.e., GP-I Zones, η′, and Mg/Zn solute co-clusters, depending on the process region. It was observed that the dissolution of the small η′/GP-I zones (T ∼ 150–200 °C) in the heat-affected zone were the key reason for the hardness drop. Further, it was shown that solid-solution, dislocation, grain size and solute co-cluster strengthening played a key role in the thermo-mechanically affected zone and grain-refined zone (GRZ). Finally, these observations were leveraged along with the Zener-Holloman relationship and grain size in the GRZ to estimate the peak joining temperature of the GRZ (∼ 350 °C) near the steel rivet.

aluminum 7xxx alloy↗

Integrated Computational Materials Engineering Development of Carbon Fiber Composites for Lightweight Vehicles

This project, Integrated Computational Materials Engineering Development of Carbon Fiber Composites for Lightweight Vehicles, develops Integrated Computational Materials Engineering (ICME) techniques for Carbon Fiber Reinforced Polymer (CFRP) composites and uses these ICME tools within a multi-disciplinary optimization scheme to design a carbon-fiber intensive front subframe for a passenger sedan. The subframe is a structural automotive component with stringent requirements for vibration, strength, durability and safety performance. CFRP composites, with a density of 1.55 g/cm3 and a tensile strength of up to 2,000 MPa in the fiber direction, have a high strength-to-weight ratio, making them one of the most promising candidates to replace the metals currently used for automotive structural components. By increasing the accessibility of CFRP component designs, reducing development-to-deployment lead time of CFRP components, and improving the robustness of initial designs, this project supports weight reduction in light-duty vehicles. These efforts can help mitigate greenhouse gas emissions from passenger vehicles and have the potential to improve national energy independence.

36 MATERIALS SCIENCE↗

Integrated Computational Materials Engineering Development of Carbon Fiber Composites for Lightweight Vehicles

This project, Integrated Computational Materials Engineering Development of Carbon Fiber Composites for Lightweight Vehicles, develops Integrated Computational Materials Engineering (ICME) techniques for Carbon Fiber Reinforced Polymer (CFRP) composites and uses these ICME tools within a multi-disciplinary optimization scheme to design a carbon-fiber intensive front subframe for a passenger sedan. The subframe is a structural automotive component with stringent requirements for vibration, strength, durability and safety performance. CFRP composites, with a density of 1.55 g/cm 3 and a tensile strength of up to 2,000 MPa in the fiber direction, have a high strength-to-weight ratio, making them one of the most promising candidates to replace the metals currently used for automotive structural components. By increasing the accessibility of CFRP component designs, reducing development-to-deployment lead time of CFRP components, and improving the robustness of initial designs, this project supports weight reduction in light-duty vehicles. These efforts can help mitigate greenhouse gas emissions from passenger vehicles and have the potential to improve national energy independence.

36 MATERIALS SCIENCE↗

Scalable generalized screening for high-order terms in the many-body expansion: Algorithm, open-source implementation, and demonstration

The many-body expansion lies at the heart of numerous fragment-based methods that are intended to sidestep the nonlinear scaling of ab initio quantum chemistry, making electronic structure calculations feasible in large systems. In principle, inclusion of higher-order n-body terms ought to improve the accuracy in a controllable way, but unfavorable combinatorics often defeats this in practice and applications with n ≥ 4 are rare. Here, we outline an algorithm to overcome this combinatorial bottleneck, based on a bottom-up approach to energy-based screening. This is implemented within a new open-source software application (“Fragme∩t”), which is integrated with a lightweight semi-empirical method that is used to cull subsystems, attenuating the combinatorial growth of higher-order terms in the graph that is used to manage the calculations. This facilitates applications of unprecedented size, and we report four-body calculations in (H2O)64 clusters that afford relative energies within 0.1 kcal/mol/monomer of the supersystem result using less than 10% of the unique subsystems. We also report n-body calculations in (H2O)20 clusters up to n = 8, at which point the expansion terminates naturally due to screening. These are the largest n-body calculations reported to date using ab initio electronic structure theory, and they confirm that high-order n-body terms are mostly artifacts of basis-set superposition error.

Chemistry↗

MOSIQS: Persistent Memory Object Storage With Metadata Indexing and Querying for Scientific Computing

Scientific applications often require high-bandwidth shared storage to perform joint simulations and collaborative data analytics. Shared memory pools provide a chance to satisfy such needs. Recently, a high-speed network such as Gen-Z utilizing persistent memory (PM) offers an opportunity to create a shared memory pool connected to compute nodes. However, there are several challenges to use scientific applications on the shared memory pool directly such as scalability, failure-atomicity, and lack of scientific metadata-based search and query. In this paper, we propose MOSIQS, a persistent memory object storage framework with metadata indexing and querying for scientific computing. We design MOSIQS based on the key idea that memory objects on PM pool can live beyond the application lifetime and can become the sharing currency for applications and scientists. MOSIQS provides an aggregate memory pool atop an array of persistent memory devices to store and access memory objects to accelerate scientific computing. MOSIQS uses a lightweight persistent memory key-value store to manage the metadata of memory objects, which enables memory object sharing. To facilitate metadata search and query over millions of memory objects resident on memory pool, we introduce Group Split and Merge (GSM), a novel persistent index data structure designed primarily for scientific datasets. GSM splits and merges dynamically to minimize the query search space and maintains low query processing time while overcoming the index storage overhead. MOSIQS is implemented on top of PMDK. We evaluate the proposed approach on many-core server with an array of real PM devices. Experimental results show that MOSIQS gains a 100% write performance improvement and executes multi-attribute queries efficiently with 2.7× less index storage overhead offering significant potential to speed up scientific computing applications.

97 MATHEMATICS AND COMPUTING↗

Nested Workflows for Loosely Coupled HPC Simulations

The increasing complexity of modern scientific simulations has given rise to the notion of re-usability as a means to reduce development time and effort. One form of re-usability involves hierarchical modelling, where the code and artifacts that model a physical phenomenon are used as the building blocks for more complex coupled physical systems. This reusability mode allows for improvements in constituents sub-models to impact the overall fidelity of the entire system with minimal effort. This benefit, however, hinges upon the ability to provide a fairly loose coupling across model boundaries, where changes in any sub-model do not result in wholesale changes to other sub-models, or in the structure and details of the code for the entire physical system. In this paper, we present the design, implementation, and case studies for incorporating sub-workflows as building blocks in a framework for loosely coupled high performance simulations. We outline the issues involved in providing lightweight customization points for full workflows that allows their use unchanged in a nested-workflow setting, while providing each sub-workflow with a separate execution context that ensures non-interference with other parts of the simulation. We present several use cases that demonstrate the successful use of the proposed design and its flexibility in accommodating different customization and scaling requirements.

Elwasif, Wael↗

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗