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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Biopolymer-supramolecular polymer hybrids for photocatalytic hydrogen production

Solar generation of H 2 is a promising strategy for dense energy storage. Supramolecular polymers composed of chromophore amphiphile monomers containing perylene monoimide (PMI) have been reported as crystalline light-harvesting assemblies for aqueous H 2 -evolving catalysts. Gelation of these supramolecular polymers with multivalent ions creates hydrogels with high diffusivity but insufficient mechanical stability and catalyst retention for reusability. We report here on using sodium alginate (SA) biopolymer to both induce supramolecular polymerization of PMI and co-immobilize them with catalysts in a robust hydrogel with high diffusivity that can also be 3D-printed. Faster mass transfer was achieved by controlling the material macrostructure by reducing gel diameter and microstructure by reducing biopolymer loading. Optimized gels produce H 2 at rates rivaling solution-based PMI and generate H 2 for up to 6 days. The PMI assemblies in the SA matrix create a percolation network capable of bulk-electron transfer under illumination. These PMI–SA materials were then 3D-printed on conductive substrates to create 3D hydrogel photoelectrodes with optimized porosity. The design of these versatile hybrid materials was bioinspired by the soft matter environment of natural photosynthetic systems and opens the opportunity to carry out light-to-fuel conversion within soft matter with arbitrary shapes and particular local environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Additively-manufactured monocrystalline YBCO superconductor

Abstract Single-crystal microstructures enable high-performance YBa 2 Cu 3 O 7-x superconductors which are however limited to simple shapes due to their brittleness. Additive manufacturing can fabricate YBa 2 Cu 3 O 7-x superconductor with complex shapes, albeit with a polycrystalline microstructure. Here, we demonstrate a route to grow single-crystals from 3D-ink-printed, polycrystalline, sintered superconducting YBa 2 Cu 3 O 7-x (YBCO or Y123) + Y 2 BaCuO 5 (Y211), manufacturing objects with complex architectures displaying both high critical current density (J c =2.1 × 10 4 A . cm –2 , 77 K) and high critical temperature (T c = 88-89.5 K). An ink containing precursor powders (Y 2 O 3 , BaCO 3 , and CuO) is 3D-extruded into complex geometries and then reaction-sintered to obtain polycrystalline Y123 + Y211. A seed is then utilized to transform these 3D-printed parts from polycrystal to monocrystal via the melt growth method. The geometric details of 3D-printed parts survive the process without slumping, sagging or collapse, despite the long-term presence of liquid above the peritectic temperature. Origami structures can be created by sheet folding after 3D-printing. This additive approach enables the facile fabrication of superconducting devices with complex shapes and architectures, such as advanced undulator magnets to generate synchrotron radiation and microwave cavities for dark-matter axion search. This work highlights the potential of additive manufacturing for producing monocrystalline cuprate superconductors and opens the door to additive manufacturing of other monocrystalline functional ceramic or semiconductor materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Fused Deposition Modeling Additive Manufacturing of Carbonized Structures via Waste-Enhanced Filaments

This report details the development, characterization, and use of coal-enhanced composite materials in additive manufacturing applications. High coal loading formulations—containing up to 70 wt.% coal—were successfully extruded and processed using commercially available 3D printers. Extensive experimental testing was conducted to assess the mechanical, thermal, and microstructural properties of the composites. In parallel, multi-scale computational modeling was employed to elucidate atomistic interactions and evaluate the effects of printing-induced defects on structural performance. Large-scale printability trials demonstrated the feasibility of fabricating complex components for tooling and construction applications, including wind turbine blade molds and modular wall sections. Techno-economic analyses demonstrated the cost-effectiveness and scalability of coal-enhanced composites for large-scale additive manufacturing applications such as wind turbine blade tooling.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2012

Development of Matrix Microstructures in UHTC Composites

One of the major issues hindering the use of ultra high temperature ceramics for aerospace applications is low fracture toughness. There is considerable interest in developing fiber-reinforced composites to improve fracture toughness. Considerable knowledge has been gained in controlling and improving the microstructure of monolithic UHTCs, and this paper addresses the question of transferring that knowledge to composites. Some model composites have been made and the microstructures of the matrix developed has been explored and compared to the microstructure of monolithic materials in the hafnium diboride/silicon carbide family. Both 2D and 3D weaves have been impregnated and processed.

Johnson, Sylvia↗
NASA NTRS2024

Direct Ink Write 3D Printing of Fully Dense and Functionally Graded Liquid Metal Elastomer Foams

Liquid metal (LM) elastomer composites offer promising potential in soft robotics, wearable electronics, and human-machine interfaces. Direct ink write (DIW) 3D printing offers a versatile manufacturing technique capable of precise control over LM microstructures, yet challenges such as interfilament void formation in multilayer structures impact material performance. Here, a DIW strategy is introduced to control both LM microstructure and material architecture. Investigating three key process parameters–nozzle height, extrusion rate, and nondimensionalized nozzle velocity–it is found that nozzle height and velocity predominantly influence filament geometry. The nozzle height primarily dictates the aspect ratio of the filament and the formation of voids. A threshold print height based on filament geometry is identified; below the height, significant surface roughness occurs, and above the ink fractures, which facilitates the creation of porous structures with tunable stiffness and programmable LM microstructure. These porous architectures exhibit reduced density and enhanced thermal conductivity compared to cast samples. When used as a dielectric in a soft capacitive sensor, they display high sensitivity (gauge factor = 9.0), as permittivity increases with compressive strain. These results demonstrate the capability to simultaneously manipulate LM microstructure and geometric architecture in LM elastomer composites through precise control of print parameters, while maintaining geometric fidelity in the printed design.

Spencer Pak↗
DOE OSTI2025

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↗
DOE OSTI2025

Demonstration of and future perspective on scaling ultrafast-laser-ablation microstructuring of Li-ion battery electrodes to roll-to-roll production and large-format cells

This work demonstrates integration of an ultrafast laser onto a roll-to-roll machine, the laser structuring of a double-sided, 700 m long roll of graphite battery anode and its subsequent manufacture into 27 Ah prismatic cells. The electrode was ablated with a novel hybrid-microstructure composed of both hexagonally arranged pores for enhanced rate performance and channels for fast electrolyte wetting. Subsequently, this anode and a non-ablated baseline anode are paired with an NMC111 cathode for cell building and electrochemical characterization. Compared to the baseline, laser ablated cells demonstrated a reduction in soaking time of at least 60%, an improvement in fast charge capability with >30% more capacity accepted during 6C charging, and an extension of cycle life of >40% during 0.5C cycling. Further, a perspective is provided on scaling ultrafast laser ablation of battery electrodes to industrial throughputs. Additionally, lessons learned from this pilot-scale demonstration are provided in regards to optical architecture, debris removal, and system control. A techno-economic analysis is used to demonstrate that laser ablation can be integrated into existing electrode manufacturing facilities with only ≈$\$$1.3 per kWh increase (≈2%) in manufacturing cost. Preemptive electrode design for laser ablation is discussed as a further method for enhancing performance. Finally, an analysis of available laser systems and beam-scanning architectures is used to determine design requirements to scale process throughput to a state-of-the-art speed of 50 m min −1 . This analysis demonstrates that laser ablating Li-ion battery electrodes has multiple benefits to manufacturing and battery performance, that the technology already exists to achieve high laser-ablation throughputs, and that integrating ultrafast laser ablation to electrode manufacturing will not create a cost or processing bottleneck.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Porous Microstructure Analysis (PuMA) software

The Porous Microstructure Analysis (PuMA) software was developed to provide a robust and efficient framework for computing material properties based on their microstructures. The development was motivated by advancements in X-ray microtomography, an imaging technology that can resolve the structure of a material at a sub-micron scale, in 3D and even in 4D (over time). PuMA provides the capability of computing a comprehensive spectrum of properties, from the most fundamental geometric features of a microstructure, to advanced anisotropic thermo-elastic properties. In addition, the software can generate artificial microstructures, ranging from simple analytical shapes to complex fibrous woven and non- woven geometries, which can be used in performance optimization studies. This presentation will highlight many of the capabilities of the recent open-source release.

microtomography↗
NASA NTRSDate not supplied

Exploration of Particle Size Engineering and Microencapsulation Technologies for Multifunctional Applications

There is a critical need for high performance materials for functional and space-based applications, including tires for exploratory rovers and external structures for landing vehicles. Novel ternary borides, such as iron aluminum boride (Fe2AlB2) and molybdenum aluminum boride (MoAlB), have emerged as potential materials for such application owing to their hardness, mechanical behavior and oxidation resistance. In this poster presentation, we will present different methods of fabricating these particles and engineering them for additive manufacturing and other related manufacturing practices. As an integral component of this study, we will demonstrate technologies to (a) synthesize these particles and (b) microencapsulate these particles with bioplastics like polylactic acid (PLA). The resulting particles will be evaluated for their processability as coatings on hydroxyapatite and Inconel particles using microstructural and flowability studies. It is expected that these particles can be used for 3D printing.

ceramics↗
NASA NTRS1994

Micromechanics of fatigue in woven and stitched composites

The goals of this research program were to: (1) determine how microstructural factors, especially the architecture of reinforcing fibers, control stiffness, strength, and fatigue life in 3D woven composites; (2) identify mechanisms of failure; (3) model composite stiffness; (4) model notched and unnotched strength; and (5) model fatigue life. We have examined a total of eleven different angle and orthogonal interlock woven composites. Extensive testing has revealed that these 3D woven composites possess an extraordinary combination of strength, damage tolerance, and notch insensitivity in compression and tension and in monotonic and cyclic loading. In many important regards, 3D woven composites far outstrip conventional 2D laminates or stitched laminates. Detailed microscopic analysis of damage has led to a comprehensive picture of the essential mechanisms of failure and how they are related to the reinforcement geometry. The critical characteristics of the weave architecture that promote favorable properties have been identified. Key parameters are tow size and the distributions in space and strength of geometrical flaws. The geometrical flaws should be regarded as controllable characteristics of the weave in design and manufacture. In addressing our goals, the simplest possible models of properties were always sought, in a blend of old and new modeling concepts. Nevertheless, certain properties, especially regarding damage tolerance, ultimate failure, and the detailed effects of weave architecture, require computationally intensive stochastic modeling. We have developed a new model, the 'binary model,' to carry out such tasks in the most efficient manner and with faithful representation of crucial mechanisms. This is the final report for contract NAS1-18840. It covers all work from April 1989 up to the conclusion of the program in January 1993.

Cox, B. N.↗
NASA NTRSDate not supplied

Modeling the Effective Elasticity of Anisotropic Porous Materials

The development and optimization of composite materials designed for thermal protection of NASA’s spacecraft require understanding their physical response to high-enthalpy environments. To predict their macro-scale properties and behavior, high-fidelity 3D simulations are performed at the microscale on realistic representations of these composites. The digital microstructures are generated either synthetically or through X-ray micro-computed tomography reconstructions. One of the main challenges in the prediction of the structural response of heatshield materials is the computation of the effective elasticity of the fibrous composite, as well as the understanding of the deformation and stresses generated at the microscale. These are driven by the fiber layout within the microstructure and the distribution of the infused matrix. In this effort, the micro-mechanical linear elastic behavior of fibrous ablators is modeled using a numerical method based on the Multi-Point Stress Approximation (MPSA) finite volume scheme, a generalization of the more commonly used Multi-Point Flux Approximation (MPFA) that was presented at the 10th Ablation Workshop. To predict the behavior of fibrous and woven architectures, algorithms that compute the local fiber orientation are used. The implementation of the MPSA was verified using analytical solutions, engineering test cases, and compared against legacy Finite Element Analysis (FEA) software. The stress analysis models were then applied to real geometries used by NASA in thermal protection systems such as fibrous preforms and woven materials and the results were compared to experimental data.

Elasticity↗
DOE OSTI2024

Microstructural evolution in doped high entropy alloys NiCoFeCr-3X (X=Pd/Al/Cu) under irradiation

Commonly studied equatomic single-phase FCC high entropy alloys based on 3d transition metals like NiCoFeCr do not provide adequate strength and radiation resistance at high doses for nuclear structural applications. In the current study, the major alloying effects like lattice distortion, ordering and clustering tendencies were investigated by adding low concentration of Pd, Al, or Cu respectively to study the doping effects on the ion irradiation response of NiCoFeCr alloy. The alloys were irradiated with 3 MeV Ni 2+ ions at 500 °C to a fluence of 1 × 10 17 /cm 2 at a beam flux of approximately 2.8 × 10 12 ions/cm 2 /s. The microstructural evolution upon irradiation i.e., formation of dislocation networks, radiation induced segregation and precipitation, and void formation were studied in detail. Further, post-irradiation characterization results showed that a Pd addition leads to a high void nucleation rate but controlled void growth, which may be attributed to increased lattice distortion. In Al added HEA, our microstructural analysis indicates that radiation induced ordered L1 2 precipitates do not affect void swelling significantly. Cu addition led to Cu precipitation that drastically suppressed dislocation density and void swelling of the alloy. Additionally, a model was developed to qualitatively describe the trend in void swelling of typical FCC alloys under ion irradiation. This model was able to qualitatively explain the suppression and reappearance of void swelling in ion irradiated alloys that generally occurs near the region with peak implanted ion concentration.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Vacuum-assisted extrusion to reduce internal porosity in large-format additive manufacturing

Large-scale 3D printing of polymer composite structures has gained popularity and seen extensive use over the last decade. Much of the research related to improving the mechanical properties of 3D-printed parts has focused on exploring new materials and optimizing print parameters to improve geometric control and minimize voids between printed beads. However, porosity at the microstructural level (within the printed bead) has been much less studied although it is almost universally observed at levels of 4 %-10 % when using fiber reinforced materials. This study introduces a vacuum-assist approach that minimizes internal porosity by removing ambient air from the interstitial space between pellets in the hopper and acts as a negative pressure vent for gases that evolve during the initial stages of single-screw extrusion. Vacuum-assisted extrusion was able to reduce porosity below 2 % across a wide range of processing parameters, moisture content, fiber reinforcements, and printing platforms. Specifically, when printing on a large-format extruder (Strangpresse Model-30), the vacuum-assisted extrusion reduced internal porosity by 35–75 % compared to conventional non-vacuum extrusion, and only pores with length scale > 2 microns are affected. The success of this approach prompted the design of a patent-pending continuous vacuum hopper relevant for large-scale 3D printing on commercial systems.

36 MATERIALS SCIENCE↗
NASA NTRS2001

C-Coupon Studies of CMCS: Fracture Behavior and Microstructural Characterization

A curved beam 'C-coupon' was used to assess fracture behavior in a Sylramic(tm)/melt infiltration (MI) SiC matrix composite. Failure stresses and fracture mechanisms, as determined by optical and scanning electron microstructural analysis, are compared with finite element stress calculations to analyze failure modes. Material microstructure was found to have a strong influence on mechanical behavior. Fracture occurs in interlaminar tension (ILT), provided that the ratio of ILT to tensile strength for the material is less than the ratio of radial to hoop stresses for the C-coupon geometry. Utilization of 3D architectures to improve interlaminar strength requires significant development efforts to incorporate through thickness fibers in regions with high curvatures while maintaining uniform thickness, radius, and microstructure.

Hurwitz, Frances I.↗
DOE OSTI2025

Shining light on nanoscale ‘vine-on-stick’ eutectic structures in the Al-Ce-Ni system

Multiphase eutectics often comprise entangled solid phases with nanoscale periodicity, making it difficult to unravel their 3D connectivity using conventional 2D techniques. Among such systems, the three-phase eutectic Al-Al 11 Ce 3 -Al 3 Ni stands out for its ultrafine (∼100 nm) interphase spacing and promising creep resistance, yet its microstructure remains relatively unexplored despite its potential for high-temperature applications. Here, we use scanning hard X-ray microscopy with an unprecedented ∼10 nm pixel size to resolve its 3D morphology. Reconstructions reveal a novel “vine-on-stick” motif, wherein Al 11 Ce 3 wraps around Al 3 Ni pillars. Analysis of phase tortuosities confirms that Al 11 Ce 3 exhibits more convoluted morphologies than Al 3 Ni. No orientation relationship was observed between the two intermetallics, suggesting that growth is controlled by local solute gradients rather than epitaxy. Fragmentation of intermetallics along their longitudinal axis suggests a Rayleigh-type breakup mechanism in solid state. The “vine-on-stick” pattern may generalize to other alloy systems with variable interfacial anisotropies and low mutual solubilities.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Super-resolution model for overlapping peak detection and improved spatial resolution in high-energy diffraction microscopy

Reconstruction quality in Far-field High-Energy Diffraction Microscopy (FF-HEDM) is limited by the spatial resolution of area detectors and the frequent occurrence of overlapping diffraction spots. To address these challenges, we developed a super-resolution (SR) framework using convolutional neural networks (CNNs) to recreate 2D diffraction peaks at up to ×8 resolution from raw detector data. A specialized simulation tool was created to generate synthetic training datasets with varying degrees of peak overlap. Integrated into the Microstructural Imaging using Diffraction Analysis Software (MIDAS), the SR model improves the spatial accuracy and precision of 3D grain reconstruction by an order of magnitude. This approach provides a robust solution for investigation of complex micromechanical states and material classes where the analysis is limited by the presence of overlapping peaks. Furthermore, the methodology developed here can potentially be extended to other techniques that require sub-pixel accuracy for high-fidelity data analysis.

High-energy diffraction microscopy↗
NASA NTRSDate not supplied

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗
DOE OSTI2024

The use of digital thread for reconstruction of local fiber orientation in a compression molded pin bracket via deep learning

A deep convolutional neural network (DCNN) was used for microstructure reconstruction using artificial intelligence (MR-AI) by predicting local average fiber orientation distributions (FOD) in a 3D prepreg platelet molded composite (PPMC) pin bracket. To train the MR-AI model, surface strain fields from residual stresses simulated in PPMC plates were used as the input to the DCNN. A training dataset included PPMC plates with various degrees of global fiber alignment, based on the information obtained from high-fidelity flow simulation of a pin bracket. Further, the MR-AI model was then deployed to analyze FOD in the 3D pin bracket by conducting thermo-elastic residual stress analysis. Initially, the MR-AI model was established entirely on the synthetic simulation data. Then, a μCT scan of a physically molded pin bracket was used to create a finite element model that provided data for additional validation of the DCNN model. For the μCT scan finite element pin bracket the MR-AI model predicted the distribution of fiber orientation tensor components with MAE of 0.10 indicating a global prediction error of 10%. For the flow simulated pin bracket, the MR-AI model predicted the distribution of fiber orientation tensor components with a global prediction error of 11%. The MR-AI model showed the ability to predict regions of varying alignment in the base and flange of the pin bracket. The proposed MR-AI methodology allows for rapid prediction of FOD in geometrically complex parts and offers a promising path to detecting unique fiber orientation states in molded components.

42 ENGINEERING↗