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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Microstructure Analysis of Bismuth Absorbers for Transition-Edge Sensor X-ray Microcalorimeters

Given its large X-ray stopping power and low specific heat capacity, bismuth (Bi) is a promising absorber material for X-ray microcalorimeters and has been used with transition-edge sensors (TESs) in the past. However, distinct X-ray spectral features have been observed in TESs with Bi absorbers deposited with different techniques. Evaporated Bi absorbers are widely reported to have non-Gaussian low-energy tails, while electroplated ones do not show this feature. In this study, we fabricated Bi absorbers with these two methods and performed microstructure analysis using scanning electron microscopy and X-ray diffraction microscopy. The two types of material showed the same crystallographic structure, but the grain size of the electroplated Bi was about 40 times larger than that of the evaporated Bi. This distinction in grain size is likely to be the cause of their different spectral responses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Microstructural analysis of recycled concrete using X-ray microtomography

This paper reports an investigation of the recycled concrete (RC) microstructure using synchrotron microtomography (μCT) at the Advanced Light Source combined with Scanning Electron Microscopy analysis. The study evaluated the influence of 50% of recycled concrete aggregate (RCA) and its water absorption compensation on the RC microstructure. The following variables were studied: a) the compressive strength of the original concrete used to obtain the RCA (40 and 80 MPa) and b) the initial moisture condition of the RCA (Saturated Surface Dry and Oven Dry). The microtomographic images showed the mixtures cast with RCA in the dry condition developed an evident macropore network surrounding the RCA particle that was not observed in the mixtures using RCA in the SSD condition. SEM images confirmed the initial findings from μCT and showed that the thickness of the interfacial transition zone in RC is in the same order of magnitude as the reference concrete.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is a suite of tools for the analysis of porous materials and generation of material microstructures. From microstructural data, often obtained through X-ray microtomography, PuMA can determine a number of effective material properties and perform material response simulations. Version 2.2 includes capabilities for computing volume fractions, porosity, specific surface area, effective thermal and electrical conductivities, and continuum and rarefied diffusive tortuosity. PuMA can also simulate competitive diffusion/reaction processes at the micro-scale, such as surface oxidation. In this poster, recent advancements to the PuMA software are detailed, including the full refactoring of PuMA into v3.0, a new module to compute heat conduction in anisotropic materials, a particle method for simulating molecular beam experiments, a new finite-volume Laplace solver, complex fibrous material generation, woven material generation, and a coupling of PuMA with the DAKOTA software for advanced statistics.

PuMA↗
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

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 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

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗
NASA NTRSDate not supplied

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗
DOE OSTI2016

Microstructural analysis and thermoelectric properties of Sn-Al co-doped ZnO ceramics

Sn-Al co-doped polycrystalline ZnO ceramics were prepared by sintering in air. Phase and microstructure analysis was performed by X-ray diffraction and SEM-EDS and thermoelectric properties were measured. XRD analysis showed a ZnO primary phase as well as secondary phase peaks due to the formation of a Zn{sub 2}SnO{sub 4} spinel phase or SnO{sub 2}(ZnO:Sn-Al){sub m} intergrowth phase. SEM analysis revealed a dense microstructure with a small number of nanometric pores, consistent with the measured density of 5.48 g/cm{sup 3}. An activated electrical conductivity characteristic of a semiconducting material was observed as well as a negative Seebeck coefficient with both values increasing in absolute value from RT to 730 °C. The power factor had a maximum value of 3.73×10{sup −4} W m{sup −1} K{sup −2} at 730 °C. Thermal conductivity measurements showed a significant reduction over the measured temperature range compared to undoped ZnO. This could be attributed to grain size reduction, the formation of a nanoscale secondary phase or a reduction in crystallinity caused by Sn-Al co-doping. A maximum ZT of 0.06 was obtained at 750 °C for the Sn-Al co-doped ZnO ceramics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Growth of faceted SiC nanostructures using vapor phase condensation: Microstructural analysis

Highlights: • Synthesis of nanocrystalline SiC using thermal plasma route. • XRD data indicates presence of both α- and β-SiC polytypes with β-SiC as the major content. • HRTEM and SAED analysis reveals polytypic arrangement with stacking faults SiC nanoparticles. • TEM micrograph reveals presence of faceted structures such as hexagonal, triangular, triangular pyramidal structure. - Abstract: The paper emphasizes the morphological and microstructural analysis of SiC nanostructures grown by thermal plasma assisted gas phase condensation process. High Resolution Transmission Electron Microscopic and Selected Area Electron Diffraction studies are used to analyze the growth directions and the polytypic arrangement with stacking faults in the as synthesized SiC nanoparticles. The results help in understanding the hierarchical poly-types related to the observed geometries and showed the presence of both α- and β-SiC polytypes. The microstructural study is supported by X-Ray diffraction and UV–Visible absorption spectroscopic studies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

Electrical and microstructure analysis of nickel-based low-resistance ohmic contacts to n-GaSb

Ultra low resistance ohmic contacts are fabricated on n-GaSb grown by molecular beam epitaxy. Different doping concentrations and n-GaSb thicknesses are studied to understand the tunneling transport mechanism between the metal contacts and the semiconductor. Different contact metallization and anneal process windows are investigated to achieve optimal penetration depth of Au in GaSb for low resistances. The fabrication, electrical characterization, and microstructure analysis of the metal-semiconductor interfaces created during ohmic contact formation are discussed. The characterization techniques include cross-sectional transmission electron microscopy and energy dispersive spectroscopy. Specific transfer resistances down to 0.1 Ω mm and specific contact resistances of 1 × 10{sup −6} Ω cm{sup 2} are observed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Microstructural analysis on cleavage fracture in pearlitic steels

Microstructural features controlling cleavage fracture in pearlitic structures were investigated by means of scanning electron microscopy and electron backscattered diffraction. It was found that pearlite block size corresponds well to the cleavage facet size, and a single cleavage facet usually contains multiple pearlite colonies. Pearlite block size and cleavage facet size decrease with the refinement of prior austenite grain size, while pearlite colony size only changes slightly. The cleavage crack can largely deflect at block boundaries rather than at colony boundaries. Pearlite block can act as the dominant substructure on cleavage crack propagation in pearlitic steels. - Highlights: •The cleavage crack propagation path in pearlitic structures was analyzed by EBSD. •Pearlite block boundaries can effectively hinder the crack propagation. •Pearlite block size corresponds well to the cleavage facet size. •A single cleavage facet usually contains multiple pearlite colonies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A microstructural analysis of aluminum buildup during thermomechanical processing

Highlights: • Microstructure of roll coating developed on a ground steel work roll was examined. • Roll coating was formed during the 20 pass hot rolling schedule of an Al-Mg alloy. • The roll coating had a complex layered nanocrystalline and amorphous structure. • The roll coating layers were composed of metallic Al, porous MgO and C. • Work roll debris, Fe and Cr, were observed embedded within the roll coating. - Abstract: The microstructure and composition of a roll coating built-up on an AISI M2 steel work roll during a 20 pass hot rolling schedule using a laboratory rolling tribo-simulator with a roll-on-block configuration was examined. The AISI M2 steel work roll was characterized by grinding grooves and possessed a surface roughness (R{sub a}) of 0.17 μm. The roll coating developed under these lubricated conditions was discontinuous, patchy and streaked out in the rolling direction. The microstructure and chemical composition of the material transfer that made up the roll coating was analysed and revealed to possess a complex composite microstructure consisting of nanocrystalline aluminum, nanocrystalline/amorphous MgO and amorphous carbon layers. The nanocrystalline MgO layers were porous structures lying between the solid metallic aluminum layers. Debris particles from the wear of the work roll were detected embedded within the carbon layer and at the base of the roll coating. The microstructure of the roll coating appear to be determined by the deformation conditions experienced during the rolling process, while its composition is dependent on the composition of the rolled alloy, the work roll and the lubrication conditions employed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗