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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cooling dynamics of two titanium alloys during laser powder bed fusion probed with in situ X-ray imaging and diffraction

Metal parts produced by laser powder bed fusion (LPBF) additive manufacturing exhibit characteristic microstructures comparable to those observed in laser welding. The primary cause of this characteristic microstructure is rapid, localized heating and cooling cycles, which result in extreme thermal gradients where material solidification is followed by fast cooling in the solid state. The final microstructure and mechanical performance are also influenced by pore formation caused by melt pool fluid dynamics. Here, we use high speed, in situ X-ray diffraction to probe the kinetics of cooling and solid-solid phase transitions after laser melting in two aerospace titanium alloys: Ti-6Al-4V, an α + β alloy; and Ti-5Al-5V-5Mo-3Cr, a near-β alloy. We complement these diffraction studies with in situ X-ray imaging to probe melt pool dynamics and pore formation. From these two complementary probes, we quantify pore formation during melting and the subsequent microstructural evolution as the material rapidly cools after solidification. These results are critical for understanding defect formation and residual stress development in different titanium alloys under LPBF conditions and can help inform process models to predict final part performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Conjugated Polymer Controlled Morphology and Charge Transport of Small-Molecule Organic Semiconductors

In this study, we report an efective approach to tune the crystallization, microstructure and charge transport of solution-processed organic semiconductors by blending with a conjugated polymer additive poly(3-hexylthiophene) (P3HT). When 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS pentacene) was used as a model semiconductor material to mix with diferent amount of P3HT, their intermolecular interactions led to distinctive TIPS pentacene flm morphologies, including randomly-oriented crystal ribbons, elongated needles with enhanced long-range order, and grasslike curved microwires with interlinkages. Each type of morphology was found to further correlate to considerably diferent charge transport and device performance. As compared to pristine TIPS pentacene devices, bottom-gate, top-contact OTFTs with 2% in weight P3HT additive showed a 2-fold and 5-fold improvement of average feld-efect mobility and performance consistency (defned as the ratio of average mobility to the standard deviation), respectively. The improvement in transistor electrical performance can be attributed to the combined efect of enhanced crystal orientation and uniformity, as well as increased areal coverage. This work can be applied beyond the particular example demonstrated in this study and to tune the charge transport of other small-molecule organic semiconductors in general.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

The mechanical response of micron-sized molecular crystals

Abstract Microstructures and corresponding properties of compacted powders ultimately depend on the mechanical response of individual particles. In principle, computational simulations can predict the results of powder compaction processes, but the selection of appropriate models for both particle–particle interactions and particle deformations across all relevant length scales remain nontrivial tasks, especially in material systems lacking detailed mechanical property information. The work presented here addresses these issues by conducting uniaxial compressions in situ inside of a scanning electron microscope to characterize the mechanical response of individual micron-sized particles of a molecular crystal, hexanitrohexaazaisowurtzitane (CL-20). This experimental approach enabled the collection of quantitative force and displacement data alongside simultaneous imaging to capture morphology changes. The results reveal information about elastic deformation, yield, plastic deformation, creep, and fracture phenomena. Accordingly, this work demonstrates a generalizable approach for assessing the mechanical response of individual micron-sized molecular crystal particles and utilizing those responses in particle-level models. Graphic abstract

36 MATERIALS SCIENCE↗
NASA NTRS1986

Carbon-rich ceramic composites from ethynyl aromatic precrusors

A number of polyfunctional aromatic acetylenes thermally polymerize at low temperatures (180 C) and pyrolyze with greater than 90 char yield. In nonoxidizing environments, they are thermally stable to 1450 C. These monomers were chosen as the basis of a model system to study the fabrication and mechanical properties of continuous filament ceramic matrix composite. Composites were fabricated from aryl poly(acetylenes), SiC particulate filler and graphite, Avco SiC, Nicalon and Nextel fibers. Microstructure, physical and mechanical properties are reported.

Hurwitz, F. I.↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRS2003

Nanolayered Features of Collagen-like Peptides

We have been investigating collagen-like model oligopeptides as molecular bases for complex ordered biomimetic materials. The collagen-like molecules incorporate aspects of native collagen sequence and secondary structure. Designed modifications to native primary and secondary structure have been incorporated to control the nanostructure and microstructure of the collagen-like materials produced. We find that the collagen-like molecules form a number of lyotropic rod liquid crystalline phases, which because of their strong temperature dependence in the liquid state can also be viewed as solvent intercalated thermotropic liquid crystals. The liquid crystalline phases formed by the molecules can be captured in the solid state by drying off solvent, resulting in solid nanopatterned (chemically and physically) thermally stable (to greater than 100 C) materials. Designed sequences which stabilize smectic phases have allowed a variety of nanoscale multilayered biopolymeric materials to be developed. Preliminary investigations suggest that chemical patterns running perpendicular to the smectic layer plane can be functionalized and used to localize a variety of organic, inorganic, and organometallic moieties in very simple multilayered nanocomposites. The phase behavior of collagen-like oligopeptide materials is described, emphasizing the correlation between mesophase, molecular orientation, and chemical patterning at the microscale and nanoscale. In many cases, the textures observed for smectic and hexatic phase collagens are remarkably similar to the complex (and not fully understood) helicoids observed in biological collagen-based tissues. Comparisons between biological morphologies and collagen model liquid crystalline (and solidified materials) textures may help us understand the molecular features which impart order and function to the extracellular matrix and to collagen-based mineralized tissues. Initial studies have utilized synthetic collagen-like peptides while future work will also focus on similar sequences generated via genetic engineering methods.

Valluzzi, Regina↗
DOE OSTI2023

Oxygen-Vacancy Abundant Nanoporous Ni/NiMnO 3 /MnO 2 @NiMn Electrodes with Ultrahigh Capacitance and Energy Density for Supercapacitors

High-performance energy storage devices (HPEDs) play a critical role in the realization of clean energy and thus enable the overarching pursuit of nonpolluting, green technologies. Supercapacitors are one class of such lucrative HPEDs; however, a serious limiting factor of supercapacitor technology is its sub-par energy density. Here, this report presents hitherto unchartered pathway of physical deformation, chemical dealloying, and microstructure engineering to produce ultrahigh-capacitance, energy-dense NiMn alloy electrodes. The activated electrode delivered an ultrahigh specific-capacitance of 2700 F/cm 3 at 0.5 A/cm 3 . The symmetric device showcased an excellent energy density of 96.94 Wh/L and a remarkable cycle life of 95% retention after 10,000 cycles. Transmission electron microscopy and atom probe tomography studies revealed the evolution of a unique hierarchical microstructure comprising fine Ni/NiMnO 3 nanoligaments within MnO 2 -rich nanoflakes. Theoretical analysis using density functional theory showed semimetallic nature of the nanoscaled oxygen-vacancy-rich NiMnO 3 structure, highlighting enhanced carrier concentration and electronic conductivity of the active region. Furthermore, the geometrical model of NiMnO 3 crystals revealed relatively large voids, likely providing channels for the ion intercalation/de-intercalation. The current processing approach is highly adaptable and can be applied to a wide range of material systems for designing highly efficient electrodes for energy-storage devices.

25 ENERGY STORAGE↗
DOE OSTI2024

Dual X-ray computed tomography-aided classification of melt pool boundaries and flaws in crept additively manufactured parts

In metal additive manufacturing (AM), understanding the process-structure-performance relationships requires a combination of multi-scale characterization techniques that allows for the measurement of the melt pool shape and boundary and classifying various defects and flaws in the AM parts. Such approaches can be destructive, only 2D in nature, or have a small field of view and can be complex to co-register and analyze. Here, in this work, we present a non-destructive 3D inspection technique that employs dual-energy X-ray computed tomography (XCT) along with a model-based iterative reconstruction (MBIR) and a new segmentation algorithm. The proposed approach and algorithm are not only capable of classifying and quantifying flaws such as pores, cracks, and inclusions, but they also allow for the extraction of microstructural features such as melt pool boundaries (MPB) and melt pool regions (MPR), that can help understand process-structure-performance relationships for alloys under study. As an exemplar application, we employed the method for characterization of an additively manufactured aluminum alloy crept under tensile stress at 300 °C for 1064 h. Our results demonstrate high quality segmentation and classification of various flaws and MPB and MPR, for the first time, using 3D X-ray CT inspection. The delineated MPB and MPR in the crept samples reveal the preferential growth paths of cracks that formed during creep deformation. The technique was used for successfully quantifying the characteristics (number of defects, their density, volume fraction, etc.) of the manufacturing-induced pores and creep-induced cracks, which is necessary to better understand the creep failure mechanisms of the material.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Utilizing Controlled Vibrations in a Microgravity Environment to Understand and Promote Microstructural Homogeneity During Floating-Zone Crystal Growth

It has been demonstrated in floating-zone configurations utilizing silicone oil and nitrate salts that mechanically induced vibration effectively minimizes detrimental, gravity independent, thermocapillary flow. The processing parameters leading to crystal improvement and aspects of the on-going modeling effort are discussed. Plans for applying the crystal growth technique to commercially relevant materials, e.g., silicon, as well as the value of processing in a microgravity environment are presented.

Grugel, Richard N.↗
DOE OSTI2022

Predicted Impacts of Pt and Ionomer Distributions on Low-Pt-Loaded PEMFC Performance

Low-cost, high performance proton exchange membrane fuel cells (PEMFCs) have been difficult to develop due to limited understanding of coupled processes in the cathode catalyst layer (CCL). Low-Pt-loaded PEMFCs suffer losses beyond those predicted solely due to reduced catalyst area. Although consensus links these losses to thin ionomer films in the CCL, a precise mechanistic explanation remains elusive. In this publication, we present a physically based PEMFC model with novel structure-property relationships for thin-film Nafion, validated against PEMFC data with low Pt loading. Results suggest that flooding exacerbates kinetic limitations in low-loaded PEMFCs, shifting the Faradaic current distribution. As current density increases, protons travel further into the CCL, resulting in higher Ohmic overpotentials. We also present a parametric study of CCL design parameters. We find that graded Pt and ionomer loadings reduce Ohmic losses and flooding, but individually do not provide significant improvements. However, a dual-graded CCL (i.e., graded Pt and ionomer) is predicted to significantly improve the maximum power density and limiting current compared to uniformly loaded CCLs. This work highlights the importance of accurate transport parameters for thin-film Nafion and provides a pathway to low-cost PEMFCs via precise control of CCL microstructures.

08 HYDROGEN↗
NASA NTRS1990

Influence of convection on microstructure

In eutectic growth, as the solid phases grow they reject atoms to the liquid. This results in a variation of melt composition along the solid/liquid interface. In the past, mass transfer in eutectic solidification, in the absence of convection, was considered to be governed only by the diffusion induced by compositional gradients. However, mass transfer can also be generated by a temperature gradient. This is called thermotransport, thermomigration, thermal diffusion or the Soret effect. A theoretical model of the influence of the Soret effect on the growth of eutectic alloys is presented. A differential equation describing the compositional field near the interface during unidirectional solidification of a binary eutectic alloy was formulated by including the contributions of both compositional and thermal gradients in the liquid. A steady-state solution of the differential equation was obtained by applying appropriate boundary conditions and accounting for heat flow in the melt. Following that, the average interfacial composition was converted to a variation of undercooling at the interface, and consequently to microstructural parameters. The results obtained show that thermotransport can, under certain circumstances, be a parameter of paramount importance.

Wilcox, William R.↗
DOE OSTI2025

Investigation of Corrosion Behavior of Carbide Phase Strengthened Nickel‐Based Alloy in Molten Fluoride Salt

The corrosion behavior of a high creep strength carbide-phase strengthened Ni-based alloy in molten FLiNaK (LiF-NaF-KF: 46.5-11.5-42 mol%) salt in the temperature range of 700°C–750°C has been investigated as a part of the development of structural alloys for fluoride salt-based molten salt reactors (MSRs). The alloy composition was designed based on Hastelloy-N, but with the goal of improving creep strength. Cr depletion depth, a measure of corrosion, was observed to be single micrometers after several hundred hours of corrosion testing. Sequential corrosion testing involving testing of pre-tested samples in fresh salt coupled with SEM-EDS, scanning transmission electron microscopy (STEM) examinations and thermodynamic and kinetic modeling, suggest that the corrosion rate at the alloy-salt interface is governed by diffusion of elements from the alloy bulk to the surface. The carbide phases in the corrosion-tested sample microstructure were identified to be largely M 6 C-type Mo-rich carbides and MC-type mixed carbides. Atom probe tomography (APT) showed some partitioning of Cr and Ti to the carbide phase and showed the carbide phases to be stable at the salt-facing surface.

Gordon, Ryan [Univ. of Wisconsin, Madison, WI (Uni↗
DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Bayesian inferencing framework for ultrasound wave speed measurements in metal additive manufacturing

Process-related changes during metal additive manufacturing introduce microstructural variability in the material properties of printed parts, directly affecting component reliability. Accurate estimation of these property variations with part performance are essential for quality assurance. Ultrasound testing offers a non-destructive means to estimate mechanical properties and detect defects; however, conventional analysis methods often neglect the influence of microstructural variability, limiting their effectiveness. Here, this research presents a Bayesian inference technique for quantifying wave speed uncertainty from ultrasound measurements of metal additive manufactured parts. By integrating prior ultrasound data with a Bayesian model, the proposed approach generates posterior density estimates of wave speed that systematically account for manufacturing-induced variability and uncertainty. The novelty of this research lies in applying a Bayesian framework to analyze experimental ultrasound measurements within the context of metal additive manufacturing variability. The method enhances the accuracy of wave speed estimation by 64%, defect position by 50% and increases confidence associated with wave speed variance by 30% across different porosity levels, thereby providing a robust foundation for improved decision-making and increased reliability in additively manufactured components.

Additive manufacturing↗
DOE OSTI2024

Mechanisms of Three-Dimensional Solid-Phase Epitaxial Crystallization of Strontium Titanate

Strontium titanate (SrTiO 3 , STO) is a complex metal oxide with a cubic perovskite crystal structure. Due to its easily described and understood crystal structure in the cubic phase, STO is an ideal model system for exploring the mechanistic details of solid-phase epitaxy (SPE) in complex oxides. SPE is a crystallization approach that aims to guide crystal growth at low homologous temperatures to achieve targeted microstructures. Beyond planar thin films, SPE can also exploit the addition of a chemically inert, noncrystallizing, amorphous obstacle in the path of crystallization to generate complex three-dimensional structures. The introduction of this mask fundamentally alters the SPE process, inducing a transition from two- to three-dimensional geometries and from vertical to lateral crystal growth under the influence of the crystal/mask/amorphous boundary. Using a combination of molecular dynamics simulations and experiments, we identify several unique phenomena in the nanoscale growth behaviors in both conventional (unmasked) and masked SPE. Examining conventional SPE of STO, we find that crystallization at the interface is strongly correlated to, and potentially driven by, density fluctuations in the region of the amorphous STO near the crystalline/amorphous interface with a strong facet dependence. In the masked case, we find that the crystalline growth front becomes nonplanar near contact with the mask. We also observe a minimum vertical growth requirement prior to lateral crystallization. Both phenomena depend on the relative bulk and interfacial free energies of the three-phase (crystal/mask/amorphous) system.

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

Phase evolution and structural modulation during in situ lithiation of MoS 2 , WS 2 and graphite in TEM

Li-ion batteries function by Li intercalating into and through the layered electrode materials. Intercalation is a solid-state interaction resulting in the formation of new phases. The new observations presented here reveal that at the nanoscale the intercalation mechanism is fundamentally different from the existing models and is actually driven by nonuniform phase distributions rather than the localized Li concentration: the lithiation process is a ‘distribution-dependent’ phenomena. Direct structure imaging of 2H and 1T dual-phase microstructures in lithiated MoS 2 and WS 2 along with the localized chemical segregation has been demonstrated in the current study. Li, a perennial challenge for the TEM, is detected and imaged using a low-dose, direct-electron detection camera on an aberration-corrected TEM and confirmed by image simulation. This study shows the presence of fully lithiated nanoscale domains of 2D host matrix in the vicinity of Li-lean regions. This confirms the nanoscale phase formation followed by Oswald ripening, where the less-stable smaller domains dissolves at the expense of the larger and more stable phases.

25 ENERGY STORAGE↗