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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Structural Optimization (Final Technical Report V.2.0)

The overall Project (Project) objective is to materially decrease the leveled cost of energy (LCOE) of the Columbia Power (CPwr) StingRAY utility-scale wave energy converter (WEC). This will be achieved by reducing structural material and manufacturing costs and increasing energy output. In this Project, improving the overall Power-to-Weight ratio (PWR) is accomplished through lowering design margins - allowing for weight reduction and more efficient, cost-effective WEC manufacturing and assembly - and by optimizing mass-related WEC performance parameters, such as center of gravity and system inertia. A mixed materials approach to further structural optimization was developed under this Project and validated with extensive laboratory structural testing. This approach substitutes fiber-reinforced plastic (FRP) for steel where appropriate. The benefits of steel are maintained where most useful, for instance at structural joints where the stiffness of steel is required, and the complex geometry is more readily fabricated with steel. However, there are structural spans whose simple shapes are readily fabricated with mandrel-wound FRP and where significant cost and weight savings can be found. An adhesive, double lap shear joint is used to join the FRP and steel subcomponents.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Effect of PCEs with different structures on hydration and properties of cementitious materials with low water-to-binder ratio

Polycarboxylate ethers (PCEs) with different structures and densities of anchor groups in the backbone were synthesized and characterized. The surface tension of their solutions, their adsorption on cementitious particles and zeta potential of cement-silica fume pastes with PCEs were measured. Their effects on hydration and properties of cement-silica fume paste with low water-to-binder ratio were examined. Results indicated that the adsorption kinetics of theses PCEs on cementitious particles are fitted the pseudo-second-order model. The introduction of long silane chain on PCE decreased its electrostatic adsorption, while PCE was adsorbed onto the surface of particles via both chemical and electrostatic adsorption, when silicon hydroxyl is directly connected to its backbone. In the presence of PCE with higher adsorbed amount, pastes exhibited lower yield stress and higher flowability, and higher strength at 7 d and 28 d. The low plastic viscosity, autogenous and drying shrinkage were related to the low surface tension of PCE solution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Polyanionic insertion hosts for aqueous rechargeable batteries

Safety concerns and costs of present-day lithium-ion batteries (LIBs) are prompting the development of alternate battery technologies with different types of electrolyte ( e.g. , solid-state, gel-polymer, aqueous, etc. ); notably, systems based on aqueous electrolytes have emerged as a promising alternative, especially for grid storage applications. The last decade has witnessed a considerable spike in the research carried out on aqueous batteries. However, the narrow operating voltage window of aqueous electrolytes and the structural instability of materials in aqueous media demand proper selection of cathode materials to achieve desirable energy density. Polyanionic materials can be an ideal choice as they are structurally more stable and exhibit tunable redox potentials. This class of materials is considered as a storehouse in which many materials can be realized by substituting different polyanionic subunits. Here, this review highlights some of the recent advances made in the polyanionic class of cathode materials for rechargeable aqueous batteries (Li-, Na- and Zn-ion batteries). The challenges facing the field, possible remedies to overcome them and future perspectives are also presented.

25 ENERGY STORAGE↗
DOE OSTI2023

Porous ceramics for additive manufacturing, filtration, and membrane applications

In accordance with one aspect of the presently disclosed inventive concepts, a porous ceramic structure includes a three-dimensional printed structure having predefined features, where the three-dimensional structure has a geometric shape. The average length of the features may be at least 10 microns. The three-dimensional structure includes a ceramic material having an open cell structure with a plurality of pores, where the pores form continuous channels through the ceramic material from one side of the ceramic material to an opposite side of the ceramic material.

Campbell, Patrick↗
DOE OSTI2021

Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations

Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.

Du, Jincheng↗
DOE OSTI2022

Development of Large Scale Extrusion Deposition for Structural Applications

Large Scale Extrusion Deposition (LSED) is an evolving additive manufacturing (AM) technology that research, such as that taking place at Oak Ridge National Laboratory (ORNL) and companies like Local Motors, are continuing to utilize and develop new applications. A major LSED application of interest has been molds and tooling as it allows for much shorter production time and lower cost. However, interest has been expanding into using LSED for more structural applications due to more frequent use of high performing polymer composites as feedstock. The use of LSED for structural applications is of particular interest to Local Motors as it is currently being used to create commercially viable, energy efficient electric vehicles. LSED offers a unique opportunity when compared to traditional manufacturing methods as it can significantly reduce the number of components necessary, while decreasing embodied energy and carbon emissions. Even with these benefits however, it is important that LSED is properly understood from a structural aspect as this field has not been as heavily researched as tooling. To ensure a high level of safety and repeatability is an essential responsibility of a manufacturer whose products are structural in nature. As such it is important to understand the materials and LSED process to make structural objects that the manufacturer can be confident in. The main goals of this project were to: develop and investigate materials that are of interest for structural LSED applications, further develop and understand the current machines used in LSED and develop simulations tools of LSED and the mechanical properties of the created structure. Material development focused on composite materials that have high mechanical properties and are stable in a variety of environments. The materials were tested to determine their as printed mechanical and thermal properties as these are necessary for simulations. Once the materials were investigated thoroughly, it allowed for simulations to be performed to compare to experimental data with simulations. Materials were also vetted to determine candidates for multi-material printing. The machine development focused around the areas of process monitoring, non-destructive evaluation, and quality control. Finally, the goal of the simulations was to develop a realistic model of printed structures, including in-process simulation and dynamic simulation. The routes to get to some of these goals and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. This project resulted in many valuable results such as the development of an nondestructive evaluation (NDE) technique for interlayer defects, proof of simulation for warpage in simple parts, the development and utilization of a profilometer to monitor a print for defects or inconsistencies, thorough investigation of a material used commercially for structural LSED applications and valuable experimental data on the applicability and advantages of multi-material crush structures versus their neat counterparts by creation and testing of samples.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomic structure and phase assemblages in novel M-(N)-A-S-H materials

This paper investigates the atomic structure and phase assemblages in new sodium-stabilized magnesium aluminosilicate hydrate (M-(N)-A-S-H) cementitious binders. Results indicate that in the absence of Ca{sup 2+}, Mg{sup 2+} promotes a binder atomic structure of Si-Al tetrahedral sheets and octahedral Mg sheets with hydrated Na{sup +} cations likely in the interlayer sites similar to trioctahedral micas (phyllosilicates). NMR studies verify the incorporation of Al in tetrahedral silicate sheets. XRD demonstrates the ability of these regions to nucleate and form zeolites (i.e., sodalite) as well as the formation of Mg-Al layered double hydroxide (LDH) phases (i.e., meixnerite), which is expected due to high concentrations of Mg and Al. TGA results indicate that M-(N)-A-S-H possesses chemically bound water and hydroxyl units similar to other Mg binders. These results evince the critical role of Mg to form unique atomic structures and durability-linked phases in low-calcium alkali-activated materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Determining Compression Characteristics of Honeycomb Material - 19674

The objective is to determine compression test characteristics of stainless steel honeycomb material to be able to represent honeycomb structures accurately in analytical models used to simulate hypothetical accident scenarios of shipping packages. Honeycomb is a material used primary in the aerospace industry due to its high strength-to-weight ratio. Because it doesn't have a shelf life and can withstand high heats, it is an excellent candidate for a structural material in package designs. Honeycomb has orthotropic material properties. The honeycomb currently being evaluated is made of metal ribbons spot welded together to form hexagon pattern between metal plates. The hexagon ribbons are brazed to the metal plates. The complexity of the honeycomb significantly lengthens the simulation time, which is further complicated when the brazing, welding, and imperfections of the material is considered. This means to affectively represent the honeycomb in simulation programs, such as Abaqus, the material needs to be approximated as a uniform orthotropic material. This requires material properties in each of the three directions, T, W, and L. The T direction is defined as the 'strong' direction, perpendicular to the honeycomb sheet. The L direction is parallel the ribbon and the W direction is perpendicular to the ribbon. Honeycomb has 3 different compression stages. Stage 1 is the initial compression where the honeycomb maintains its structural integrity and does not permanently deform from loads from normal operations. Stage 2 is when the initial buckling causes irreversible damage to the honeycomb. Stage 2 is the one we are most interested in because it absorbs the most energy from a hypothetical accident scenario. During Stage 2, the honeycomb fails layer-by-layer, indicating that the more layers, the longer material crushing is sustained, and thus the more energy that is absorbed. Stage 3 is final compression, similar to compressing solid metal. During stage 3 the stress increases with a diminishing rate of elongation and the honeycomb is completely failed where the plates between the honeycomb core sandwich the crushed honeycomb ribbon. The stress-strain graph bellow shows compression test of 3 different samples in the T direction. The red lines divide the three stages. The far left is Stage 1, the middle stage 2, and the right stage 3. The data collected is displayed in the table below. The expressions in the table represent the regression formula that represents each stage of the compression on a stress-strain graph. Stage 1 is assumed to intersect with the origin; data for stage 3 for the crush in W and L directions where unable to be gathered due to the nature of failure for those directions. Stage 1 and 2 are linear regressions while stage 3 is a degree 2, to best match the curve. Linear regression is used on stage 2 because ultimately that represents the energy absorbed. With more data, a degree n x 2 regression would be a more appropriate regression for stage 2, where n is the number of layers. The table below is the approximation of each scenario and stage. Each stage starts and ends at the intersection of the next stage. There where two main objectives for these tests: firstly to understand how honeycomb performs under extreme compression, and secondly to be able to numerically represent the honeycomb structure. Both of these where completed to varying degrees. It is important understood how the honeycomb fails. If it is crushed in the T direction it retains its integrity even after being crushed, however when crushed in the L and W crush direction, if it fails, it disintegrates, and loses all integrity. Also, the more layers the more time the material spends in stage 2. Failure is started by buckling, thus if there is any imperfection, the stress will not spike but transition straight into stage 2. The data collected and aggregated can be used for initial simulation of honeycomb used in packages. The initial testing has set the ground work for more data to be collected in order to verify results and to allow more confidence in the simulation results. This is only the initial data collected. The next steps is to continue to collect more data to verify results and to test more variants of honeycomb, with different brazing, layers, and shape.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping

Application of artificial intelligence (AI), and more specifically machine learning, to the physical sciences has expanded significantly over the past decades. In particular, science-informed AI, also known as scientific AI or inductive bias AI, has grown from a focus on data analysis to now controlling experiment design, simulation, execution and analysis in closed-loop autonomous systems. The CAMEO (closed-loop autonomous materials exploration and optimization) algorithm employs scientific AI to address two tasks: learning a material system’s composition-structure relationship and identifying materials compositions with optimal functional properties. By integrating these, accelerated materials screening across compositional phase diagrams was demonstrated, resulting in the discovery of a best-in-class phase change memory material. Key to this success is the ability to guide subsequent measurements to maximize knowledge of the composition-structure relationship, or phase map. In this work we investigate the benefits of incorporating varying levels of prior physical knowledge into CAMEO’s autonomous phase-mapping. This includes the use of ab-initio phase boundary data from the AFLOW repositories, which has been shown to optimize CAMEO’s search when used as a prior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Investigating property-porosity relationships for micro-architected lattice structures

Micro-architected structures are increasingly valued for their light weight and tunable mechanical properties; this class of material includes sheet structures like the Schöen gyroid and beam lattices like the octet. For design purposes, it is critical to understand how to tune the relative density (RD) to obtain desired mechanical properties. This study investigates the mechanical response of Ti-6Al-4V gyroid structures, spanning a broad range of RDs (0.03–0.90), unit cell sizes (1–4 cm), and sheet thicknesses (0.2–7.8 mm). Results demonstrate that the classical Gibson-Ashby power law scaling between RD and modulus and yield stress does not adequately capture the response over a wide range of RDs, nor does it extrapolate correctly to the fully dense solid. Analytical models, in concert with experimental results and high-fidelity finite element calculations, show that the deviation from Gibson-Ashby reflects a transition from structure-dominated to material-dominated behavior. Distinctions are drawn between scaling relationships and property-porosity models, and an analytical model is proposed to better capture the evolution of mechanical properties with RD. These observations are mirrored in other architected topologies, like the octet, and highlight the importance of understanding the relationship between mechanical properties and geometry for design purposes.

Materials science↗
DOE OSTI2023

High-Entropy Oxides in the Mullite-Type Structure

High-entropy materials (HEMs) represent a new class of solid solutions containing at least five different elements. Their compositional diversity makes them promising as platforms for the development of functional materials. We synthesized new HEMs in a mullite-type structure and present five compounds, i.e., Bi 2 (Al 0.25 Ga 0.25 Fe 0.25 Mn 0.25 ) 4 O 9 and A 2 Mn 4 O 10 with variations of A = Nd, Sm, Y, Er, Eu, Ce, and Bi, demonstrating the vast accessible composition space. By combining scattering, microscopy, and spectroscopy techniques, we show that our materials are mixed solid solutions. Remarkably, when following their crystallization in situ using X-ray diffraction and X-ray absorption spectroscopy, we find that the HEMs form through a metastable amorphous phase without the formation of any crystalline intermediates. We expect that our synthesis is excellently suited to synthesizing diverse HEMs and therefore will have a significant impact on their future exploration.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Assessment of Machine Learning for Ultrasonic Nondestructive Evaluation of Alkali–Silica Reaction in Concrete

Alkali–silica reaction (ASR) is a type of material degradation in concrete structures that leads to concrete cracking and rebar corrosion, thereby reducing the material’s structural integrity and the overall structure’s lifetime and raising safety concerns. Ultrasonic nondestructive evaluation (NDE) has been proven to be a valuable technique for assessing concrete properties and monitoring ASR progression in concrete. However, the deployment and analysis of ultrasonic NDE and its data requires specialized expertise, often relying on the engineer’s subjective interpretation. With the surge in computational power, artificial intelligence (AI) and machine learning (ML) algorithms have become popular in automating NDE data analysis. Various industrial sectors are increasingly adopting ML algorithms for NDE data analysis with a growing emphasis on AI–assisted automation. Regulatory agencies are also preparing for this technological shift, anticipating corresponding revisions in standards. Thus, there is an urgent need to identify the capabilities and limitations of current ML technologies for the evaluation of concrete material properties and damage status. Furthermore, the effects of various factors on ML model performance must be thoroughly investigated. The study summarized herein evaluated the effectiveness of two ML models (i.e., support vector regression (SVR) and deep neural network (DNN)) in predicting concrete material damage induced by ASR based on the long-term ultrasonic monitoring data. Four distinct concrete specimens were cast with artificially induced ASR, and over a period exceeding 500 days, ultrasonic signals and expansion data were continuously collected. For the SVR model, wave velocity and 12 other wave features were extracted from the ultrasonic signals, with 6 out of 13 features selected as input for the model. Different combinations of training and testing datasets were designed to explore factors influencing prediction performance, including the range of data within training and testing sets, in addition to various signal preprocessing methodologies. These findings suggest the importance of using a training dataset with a broader data range compared with testing datasets for improved model performance alongside consistent signal preprocessing across datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Small-Angle X-ray Scattering Analysis of Colloidal Crystals and Replica Materials Made from L-Arginine-Stabilized Silica Nanoparticles

Colloidal crystals made from sub-100 nm silica nanoparticles have provided a versatile platform for the template-assisted synthesis of three-dimensionally interconnected semiconducting, metallic, and magnetic replicas. However, the detailed structure of these materials has not yet been characterized. Here, we investigated the structures of colloidal crystalline films and germanium replicas by scanning electron microscopy and small angle X-ray scattering. The structures of colloidal crystals made by evaporative assembly depends on the size of L-arginine-capped silica nanoparticles. Particles smaller than ~31 nm diameter assemble into non-close-packed arrangements (bcc) whereas particles larger than 31 nm assemble into random close-packed structures with disordered hexagonal phase. Polycrystalline films of these materials retain their structures and long-range order upon infiltration at high temperature and pressure, and the structure is preserved in Ge replicas. The shear force during deposition and dispersity of silica nanoparticles contributes to the size-based variation in the structure and to the size of crystal domains in the colloidal crystal films.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mixed-Flux Techniques for Rational Synthesis and Structural Control in Silver Chalcogenides

The functionality of materials is intrinsically linked to their structures, an axiom encapsulated in the principle of structure-property relationships. The pinnacle of materials design is the tailoring of its structure for a specific function, which requires the ability of rational synthesis and the development of synthesis science. This idea, however, remains elusive for the synthesis of complex extended solids. A major obstacle is the difficulty in using established chemical principles selectively to control reaction paths and favor certain structural patterns over numerous other possible results. In this context, we are developing a synthesis science approach that facilitates the control of the structure and bonding to create new structures. This is achieved by employing a two-component flux consisting of mixed hydroxides and halides as the reaction medium. This enables reaction conditions that allow better control of the structure dimensionality and composition by manipulating the temperature and solvent basicity (via the flux component ratio). Here, we demonstrate the efficacy of this method in controlling their structural motifs to arrive at 23 unreported compositions and 6 unique structure types. These materials are expected to exhibit a broad range of properties, from metallic to semiconducting, with calculations suggesting the potential for emergent phenomena such as Dirac semimetals. The reaction paths afforded by these mixed fluxes establish a direct correlation between the synthetic variables and properties, providing significant insight into a broadly applicable approach for new materials.

Zhou, Xiuquan [Argonne National Laboratory (ANL), ↗
DOE OSTI2020

Machine Learning Chemical Guidelines for Engineering Electronic Structures in Half-Heusler Thermoelectric Materials

Half-Heusler materials are strong candidates for thermoelectric applications due to their high weighted mobilities and power factors, which is known to be correlated to valley degeneracy in the electronic band structure. However, there are over 50 known semiconducting half-Heusler phases, and it is not clear how the chemical composition affects the electronic structure. While all the n-type electronic structures have their conduction band minimum at either the Γ - or X -point, there is more diversity in the p-type electronic structures, and the valence band maximum can be at either the Γ -, L -, or W -point. Here, we use high throughput computation and machine learning to compare the valence bands of known half-Heusler compounds and discover new chemical guidelines for promoting the highly degenerate W -point to the valence band maximum. We do this by constructing an “orbital phase diagram” to cluster the variety of electronic structures expressed by these phases into groups, based on the atomic orbitals that contribute most to their valence bands. Then, with the aid of machine learning, we develop new chemical rules that predict the location of the valence band maximum in each of the phases. These rules can be used to engineer band structures with band convergence and high valley degeneracy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2023

Synthesis and Characterization of Carbon Microbeads

We report a microfluidic-based droplet generation platform for synthesizing micron-sized porous carbon microspheres. The setup employs carbon materials such as graphite, carbon nanotubes, graphene, fullerenes, and carbon black as starting materials. Custom composition, structure, and function are achieved through combinations of carbon materials, cross-linkers, and additives along with variations in process parameters. Carbon materials can be assembled into spheres with a mean diameter of units to hundreds of μm with relatively tight size distribution (<25% RSD). Pore structure and size (tens to hundreds of angstrom) can be modulated by incorporating porogen/coporogen dilutants during synthesis. The microbeads have excellent mechanical stability with an elastic modulus of hundreds of MPa. They can sustain high dynamic fluid flow pressures of up to 9000 psi. This work lays the foundation for synthesizing novel tailorable and customizable carbon microbeads. It opens avenues for applying these novel materials for composite and additive manufacturing, energy, life science, and biomedical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Materials Data on Pd(S3N)2 by Materials Project

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

36 MATERIALS SCIENCE↗