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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

“Flower-like” LI 4 TI 5 O 12 -multiwalled carbon nanotube composite structures with performance as highrate anode-materials for Li-ion battery applications and methods of synthesis thereof

A method of fabricating nanocomposite anode material embodying a lithium titanate (LTO)-multi-walled carbon nanotube (MWNT) composite intended for use in a lithium-ion battery includes providing multi-walled carbon nanotube (MWNTs), including nanotube surfaces, onto which functional oxygenated carboxylic acid moieties are arranged, generating 3D flower-like, lithium titanate (LTO) microspheres, including thin nanosheets and anchoring the acid-functionalized MWNTs onto surfaces of the 3D LTO microspheres by π-π interaction strategy to realize the nanocomposite anode material.

Wong, Stanislaus S.↗
DOE OSTI2025

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗
DOE OSTI2023

Spatial Effect on the Performance of Carboxylate Anode Materials in Na-Ion Batteries

Developing low-voltage carboxylate anode materials is critical for achieving low-cost, high-performance, and sustainable Na-ion batteries (NIBs). However, the structure design rationale and structure-performance correlation for organic carboxylates in NIBs remains elusive. Herein, the spatial effect on the performance of carboxylate anode materials is studied by introducing heteroatoms in the conjugation structure and manipulating the positions of carboxylate groups in the aromatic rings. Planar and twisted organic carboxylates are designed and synthesized to gain insight into the impact of geometric structures to the electrochemical performance of carboxylate anodes in NIBs. Among the carboxylates, disodium 2,2’-bipyridine-5,5’-dicarboxylate (2255-Na) with a planar structure outperforms the others in terms of highest specific capacity (210 mAh g -1 ), longest cycle life (2000 cycles), and best rate capability (up to 5 A g -1 ). Further, the cyclic stability and redox mechanism of 2255-Na in NIBs are exploited by various characterization techniques. Moreover, high-temperature (up to 100 °C) and all-organic batteries based on a 2255-Na anode, a polyaniline (PANI) cathode, and an ether-based electrolyte are achieved and exhibited exceptional electrochemical performance. Therefore, this work demonstrates that designing organic carboxylates with extended planar conjugation structures is an effective strategy to achieve high-performance and sustainable NIBs.

25 ENERGY STORAGE↗
DOE OSTI2023

Probing the Morphology and Mobility of Amines in Porous Silica CO 2 Sorbents by 1 H T 1 – T 2 Relaxation Correlation NMR

Molecular and oligomeric amines supported in porous oxide supports are a promising class of CO 2 sorbent materials studied for CO 2 removal from diverse streams such as flue gas and ambient air. Among the various amines investigated, low molecular weight, hyperbranched poly(ethyleneimine) (PEI), and tetraethylenepentamine (TEPA) are among the most extensively studied. While macroscopic structure–performance relationships relating the support structure, amine loading, and other factors affecting CO 2 sorption capacities and kinetics have been developed, structural and dynamic information about the organic amine phase in the porous support is less plentiful. The structure and mobility of amines impregnated in the pores of porous supports directly impact gas sorption, as the accessibility of amine sites in the pores directly relates to amine distribution in the pores and overall pore filling as well as the dynamics of the amine chains. Here, we prepare a family of mesoporous silica SBA-15 materials containing varying loadings of oligomeric (PEI) and molecular (TEPA) amines. 1 H T 1 –T 2 relaxation correlation solid-state NMR experiments are used to characterize the structural and dynamic properties of the confined amines. Both TEPA and PEI are shown to form multiple different domains in the pores, each with distinguishable dynamic properties. TEPA and PEI form more rigid layers around the silica support walls at lower organic loading fractions, characterized by lower mobilities, followed by the formation of more mobile domains less engaged in pore wall interactions at higher loadings. TEPA shows faster mobilities than PEI because of its lower molecular weight. TEPA also appears to more easily transfer between domains within the pores, leading to generally faster CO 2 uptake rates with higher sorption capacities, while PEI located closer to the pore walls remained much less mobile and is thus less engaged in CO 2 capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evidence for Field-Dependent Charge Separation Caused by Mixed Phases in Polymer–Fullerene Organic Solar Cells

As organic photovoltaic performance approaches 20% efficiencies, causal structure–performance relationships must be established for devices to realize theoretical limits and become commercially competitive. Here, we reveal evidence of a causal relationship between mixed donor–acceptor interfaces and charge generation in polymer–fullerene solar cells. To do this, we combine a holistic loss analysis of device performance with quantitative synchrotron X-ray nanocharacterization to identify a >98% anticorrelation between field-dependent geminate recombination and nanodomain purity. Importantly, our analysis eliminates other possible explanations of the performance trends, a requirement to establish causality. The unprecedented granular level of our analysis also separates field-dependent and field-independent recombination at the interface, where we find for the first time that this system is free of field-independent recombination, a loss channel that plagues high-performance systems, including those with non-fullerene acceptors. Furthermore, this result broadens the case that minimizing mixed phases to promote sharp interfaces between pure aggregated domains is the ideal nanostructure for realizing theoretical efficiency limits of organic photovoltaics.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Foldable semi-ladder polymers: novel aggregation behavior and high-performance solution-processed organic light-emitting transistors

A critical issue in developing high-performance organic light-emitting transistors (OLETs) is to balance the trade-off between charge transport and light emission in a semiconducting material. Although traditional materials for organic light-emitting diodes (OLEDs) or organic field-effect transistors (OFETs) have shown modest performance in OLET devices, design strategies towards high-performance OLET materials and the crucial structure–performance relationship remain unclear. Our research effort in developing cross-conjugated weak acceptor-weak donor copolymers for luminescent properties lead us to an unintentional discovery that these copolymers form coiled foldamers with intramolecular H-aggregation, leading to their exceptional OLET properties. An impressive external quantum efficiency (EQE) of 6.9% in solution-processed multi-layer OLET devices was achieved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Performance Prediction of High‐Entropy Perovskites La 0.8 Sr 0.2 Mn x Co y Fe z O 3 with Automated High‐Throughput Characterization of Combinatorial Libraries and Machine Learning

Perovskite oxides form a large family of materials with applications across various fields, owing to their structural and chemical flexibility. Efficient exploration of this extensive compositional space is now achievable through automated high-throughput experimentation combined with machine learning. In this study, we investigate the composition–structure–performance relationships of high-entropy La 0.8 Sr 0.2 Mn x Co y Fe z O 3±𝞭 perovskite oxides (0 < x, y, z <1; x+y+z≈1) for application as oxygen electrodes in Solid Oxide Cells. Following the deposition of a continuous compositional map using thin-film combinatorial pulsed laser deposition, compositional, structural, and performance properties are characterized using six different techniques with mapping capabilities. Random forests effectively model electrochemical performance, consistently identifying Fe-rich oxides as optimal compounds with the lowest area-specific resistance values for oxygen electrodes at 700 °C. Additionally, the models identify a statistical correlation between oxygen sublattice distortion—derived from spectral analysis of Raman-active modes—and enhanced performance.

high entropy oxides↗
DOE OSTI2023

Structured light scanning artifact-based performance study

Structured light scanning is used to create a digital twin of a manufactured part, where features are extracted to determine if the part meets the designer’s intent and required tolerances. This paper describes repeatability and reproducibility analyses for a commercially-available structured light scanning system and measurement artifact. The repeatability study used five repeated scans at 15 measurement positions. Repeatability was assessed by randomly selecting one of the five scans at each of the 15 positions and creating a part mesh. This process was performed 50 times and the statistics for the dimension variations were calculated to isolate the scanning effects only. The same sequence was then performed for 10 of the 15 positions and five of the 15 positions to evaluate the repeatability sensitivity to the number of measurement positions. Reproducibility was assessed by selecting 15 positions to create a mesh and repeating the 15-position measurement sequence 10 times using different positions for each mesh construction. The statistics for the dimension variations were then calculated. This incorporated the effects of both scanning and the position and orientation of the part relative to the scanner. This sequence was repeated for 10-position and five-position scans to evaluate the corresponding sensitivity. Finally, the artifact dimensions from structured light scanning were compared to coordinate measuring machine measurements of the same features.

42 ENGINEERING↗
DOE OSTI2024

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗
DOE OSTI2024

Characteristics of Vertical Ground Motions and Their Effect on the Seismic Response of Bridges in the Near-Field: A State-of-the-Art Review

Despite the evidence from past earthquakes and several numerical investigations demonstrating the detrimental impact of vertical ground motions (VGMs) on the integrity of bridge structures, incorporating their effects into seismic assessment and design procedures has traditionally been given limited consideration. Current codes utilize rather simplistic approaches to account for the concurrent effects of vertical and horizontal motions in structural performance evaluations, potentially leading to unconservative estimates of structural demands. This paper reviews the main features of VGMs and their effect on the seismic response of bridges. The methods and empirical models available to estimate vertical motions for design purposes are discussed, and research gaps and related research needs are identified. Finally, the emerging role of physics-based ground-motion simulations, as well as their limitations, in supporting future research and informing the development of simplified design procedures is examined. The main areas of interest for future research are identified in the need to carry out systematic sensitivity studies to gain insight into the main earthquake parameters that influence key VGMs features, understand the influence of soil nonlinearities on VGMs amplitude and frequency content, inform the development of empirical models that cover a range of site conditions and source-to-site distances where current models are poorly constrained, generate arrays of motions to update coherency models to properly inform the analysis of distributed infrastructure, investigate the impulsive character of VGMs, and assess the approximations made in estimating VGMs with 1D site response analyses. Furthermore, specific focus is laid on large-magnitude earthquakes in the near-field.

Asynchronous ground motion↗
DOE OSTI2025

Embedded 3D printing of isotropically enhanced lattice structure with programmable elasticity via three-dimensional fiber alignment

Engineered composites with fiber orientation in a complete three-dimensional (3D) context are highly desired for maximizing structural performance as they mimic the well-organized fiber arrangement in natural composites. However, most fabrication techniques lack the capability for through-plane (z-axis) alignment, limiting the possibility for structural design and performance optimization. In this study, we present an embedded 3D printing approach that enables complete 3D fiber alignment, including region-specific alignment control along the through-plane direction. Our method utilizes the extrusion and suspension of composite inks within a supporting matrix. By regionally adjusting the ink extrusion rate and nozzle translation rate, we locally manipulated the fiber arrangement within the composite 3D architecture. Here, we demonstrate that the 3D alignment of carbon fibers in a structural composite significantly enhances both mechanical properties and thermal conductivity in the in-plane and through-plane directions. Furthermore, by strategically arranging regional fiber orientations within micro-architected materials, we fabricated metamaterial engineered composites with programmable anisotropy ratio and directional moduli.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structure prediction of epitaxial inorganic interfaces by lattice and surface matching with Ogre

We present a new version of the Ogre open source Python package with the capability to perform structure prediction of epitaxial inorganic interfaces by lattice and surface matching. In the lattice matching step, a scan over combinations of substrate and film Miller indices is performed to identify the domain-matched interfaces with the lowest mismatch. Subsequently, surface matching is conducted by Bayesian optimization to find the optimal interfacial distance and in-plane registry between the substrate and the film. For the objective function, a geometric score function is proposed based on the overlap and empty space between atomic spheres at the interface. The score function reproduces the results of density functional theory (DFT) at a fraction of the computational cost. The optimized interfaces are pre-ranked using a score function based on the similarity of the atomic environment at the interface to the bulk environment. Final ranking of the top candidate structures is performed with DFT. Ogre streamlines DFT calculations of interface energies and electronic properties by automating the construction of interface models. The application of Ogre is demonstrated for two interfaces of interest for quantum computing and spintronics, Al/InAs and Fe/InSb.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
DOE OSTI2023

Develop a Fast Analysis Solver for Welding Sequence Optimization

During the shipbuilding manufacturing process, materials are exposed to significant stresses, as induced both thermally and mechanically, that alter the intended design and significantly affect the production schedule, labor hours (fitting, welding, rework, etc.), and material structural performance. The type and magnitude of deformation of a given structure depends on many factors such as the material, thickness and quality of components, the process heat input, preheat and inter-pass temperatures, type and size of welds, welding sequence and direction, location, sequence, and degree of fixturing. Numerical simulations using finite element analysis (FEA) have long been used to analyze welding-induced structural distortion. For large assemblies, transient thermal elastic-plastic analysis (TEPA) can take days or weeks to run, and optimization of welding sequence is not feasible. Simplified analysis methods were developed to reduce computational time. However, it is challenging to use these techniques to fully optimize welding sequencing because of their applied simplifications in modeling weld details. A fast analysis solver that could be used by the shipbuilding industry is being developed for optimizing welding sequences by taking full advantage of modern GPU-based HPC hardware and incorporating patented acceleration schemes. The accelerated processing factors are up to 2200 times greater for large, multi-pass welded structures.

Yang, Yu-Ping↗
DOE OSTI2025

Electromagnetic Modeling of Lattice Structures in Additively Manufactured Electric Machines

Recent advancements in metal additive manufacturing (AM) show great potential to revolutionize the design and manufacturing of electromagnetic components used in the field of electrical engineering. Lattice structures directly printed by AM processes typically offer better structural performance with reduced weight, such as high stiffness, surface area, elongation, energy absorption, and porosity, than the solid counterpart. This paper aims to study the electromagnetic modeling of lattice structures used in additively manufactured magnetic cores or windings for electric machines. Three dimensional (3D) electromagnetic finite element (FE) analysis with high performance computing (HPC) shows the highest fidelity in predicting the electromagnetic performance of designs with lattice structures by preserving complex geometry details. FE-based homogenization methods have also been explored to potentially speed up concept design. A case study based on an additively manufactured axial-flux permanent magnet machine with a Hilbert pattern stator validates the discussed electromagnetic modeling approaches.

Chung, Shi-Uk [ANSYS, Inc.]↗
DOE OSTI2023

Structure optimization with stochastic density functional theory

Linear-scaling techniques for Kohn–Sham density functional theory are essential to describe the ground state properties of extended systems. Still, these techniques often rely on the localization of the density matrix or accurate embedding approaches, limiting their applicability. In contrast, stochastic density functional theory (sDFT) achieves linear- and sub-linear scaling by statistically sampling the ground state density without relying on embedding or imposing localization. In return, ground state observables, such as the forces on the nuclei, fluctuate in sDFT, making optimizing the nuclear structure a highly non-trivial problem. In this work, we combine the most recent noise-reduction schemes for sDFT with stochastic optimization algorithms to perform structure optimization within sDFT. We compare the performance of the stochastic gradient descent approach and its variations (stochastic gradient descent with momentum) with stochastic optimization techniques that rely on the Hessian, such as the stochastic Broyden–Fletcher–Goldfarb–Shanno algorithm. In conclusion, we further provide a detailed assessment of the computational efficiency and its dependence on the optimization parameters of each method for determining the ground state structure of bulk silicon with varying supercell dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural mapping and tuning of mixed halide ions in amorphous sulfides for fast Li-ion conduction and high deformability

Amorphous sulfides are among the most promising candidates for solid electrolytes (SEs) owing to their excellent deformability and acceptable Li-ion conductivity (σion) at room temperature. However, the complex atomic structure of these amorphous materials without long-range ordering results in a lack of structural understanding and difficulties in tuning material properties. Here, in this study, we performed structural mapping of glassy sulfide SEs composed of various anion clusters using a combinatorial atomic level analysis of synchrotron X-ray-based pair distribution function (PDF) and reverse Monte-Carlo (RMC) methods, demonstrating the potential to tune σ ion in glass SEs. First, we prepared a new glassy sulfide with a mixed anion framework of two halogens (Br and I) as atomic anions, with PS 4 3- molecular anions in a Li 2 S–P 2 S 5 -based glass SE. At a specific Br content, [(Li 2 S) 0.658 (LiI 0.9 LiBr 0.1 ) 0.342 ] 0.825 [P 2 S 5 ] 0.175 recorded a σ ion of 2.27 mS cm -1 , the highest value for any glass sulfides reported to date; however, its elastic modulus was still suppressed to 14.48 GPa. PDF and RMC calculations successfully provided structural mapping of anion clusters, including two halogens. Molecular dynamics simulations of each composition confirmed that flexible coordination caused by the rattling of small polarizable Br ions in the mixed halogens of glassy SEs contributed to the superior σ ion . Our results may provide new insights into the design of superior glassy SEs that play key roles in all-solid-state batteries requiring fast Li-ion conduction and high deformability.

36 MATERIALS SCIENCE↗