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At least 19 records

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 2

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 3

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 4

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗

Wave propagation in composite media and material characterization

Characteristics of wave propagation in an undamaged composite medium are influenced by many factors, the most important of which are: microstructure, constituent properties, interfaces, residual stress fields, and ply lay-ups. Measurements of wave velocities, attenuation, and dispersion provide a powerful tool for nondestructive evaluation of these properties. Recent developments are reviewed for modeling ultrasonic wave propagation in fiber and particle-reinforced composite media. Additionally, some modeling studies are reviewed for the effects of interfaces and layering on attenuation and dispersion. These studies indicate possible ways of characterizing material properties by ultrasonic means.

Datta, Subhendu K.↗

Materials Characterization, Prediction, and Control Project: Characterization of 316L Stainless Steel after Solid Phase Processing using Ultrasonic NDE Method

The Pacific Northwest National Laboratory undertook the Materials Characterization, Prediction, and Control Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). A motivation of the Materials Characterization, Prediction, and Control Project was to demonstrate ultrasonic testing as a nondestructive evaluation method to complement traditional destructive methods for characterizing material microstructure with emphasis on grain size determination using a method that may have future applications for real-time inline process monitoring. The objective of the work described in this report is to establish the process and an analysis method for measuring grain sizes of polycrystalline metals with ultrafine grains using ultrasonic shear wave backscattering, building on prior studies on coarser-grained material. The work involves five tasks: Measured ultrasonic backscattering experimentally for a series of 316L stainless steel specimens with various grain sizes made by friction stir processing. Calculated ultrasonic backscattering coefficients from experimental data based on a physical measurement model. Measured ground truth grain sizes of the specimens from electron backscatter diffraction grain boundary images using a generalization of the ASTM E112 (ASTM 2021) intercept method. Built a curve of ultrasonic backscattering coefficients versus the ground truth intercept-based grain sizes to determine the correlation between mean grain sizes and ultrasonic measurements. Demonstrated the ability of using the correlation curve to deduce grain sizes with measured ultrasonic backscattering coefficients for a few 316L stainless steel specimens whose grain sizes were unknown beforehand but were targeted to be an extrapolation to larger grain sizes than used to formulate the correlation curves. Experimental procedures and computational algorithms are developed and validated for these tasks. This work establishes an ultrasonic technique for characterizing material microstructure with ultrafine grains that are often resulted by solid-phase processing. The technique is nondestructive, and it has the potential to be used for real time inline process monitoring. This work successfully demonstrates the viability of an ultrasonic nondestructive evaluation method for microstructural characterization of material having ultrafine grain structure (as small as 1?mm) and produced by an advanced manufacturing method. This includes a demonstration of the method to extrapolate to other conditions. While not demonstrated here, the method is expected to be viable for in-line, or near-inline, process monitoring in advanced manufacturing applications with suitable consideration for access of instrumentation to the material being manufactured.

316 L Stainless Steel↗

Real-time X-ray Diffraction: Applications to Materials Characterization

With the high speed growth of materials it becomes necessary to develop measuring systems which also have the capabilities of characterizing these materials at high speeds. One of the conventional techniques of characterizing materials was X-ray diffraction. Film, which is the oldest method of recording the X-ray diffraction phenomenon, is not quite adequate in most circumstances to record fast changing events. Even though conventional proportional counters and scintillation counters can provide the speed necessary to record these changing events, they lack the ability to provide image information which may be important in some types of experiment or production arrangements. A selected number of novel applications of using X-ray diffraction to characterize materials in real-time are discussed. Also, device characteristics of some X-ray intensifiers useful in instantaneous X-ray diffraction applications briefly presented. Real-time X-ray diffraction experiments with the incorporation of image X-ray intensification add a new dimension in the characterization of materials. The uses of real-time image intensification in laboratory and production arrangements are quite unlimited and their application depends more upon the ingenuity of the scientist or engineer.

Rosemeier, R. G.↗

Materials characterization on efforts for ablative materials

Experimental efforts to develop a new procedure to measure char depth in carbon phenolic nozzle material are described. Using a Shor Type D Durometer, hardness profiles were mapped across post fired sample blocks and specimens from a fired rocket nozzle. Linear regression was used to estimate the char depth. Results are compared to those obtained from computed tomography in a comparative experiment. There was no significant difference in the depth estimates obtained by the two methods.

Tytula, Thomas P.↗

NDE for Material Characterization in Aeronautic and Space Applications

This paper describes selected nondestructive evaluation (NDE) approaches that were developed or tailored at the NASA Glenn Research Center for characterizing advanced material systems. The emphasis is on high-temperature aerospace propulsion applications. The material systems include monolithic ceramics, superalloys, and high temperature composites. In the aeronautic area, the highlights are cooled ceramic plate structures for turbine applications, F-TiAl blade materials for low-pressure turbines, thermoelastic stress analysis (TSA) for residual stress measurements in titanium based and nickel based engine materials, and acousto ultrasonics (AU) for creep damage assessment in nickel-based alloys. In the space area, examples consist of cooled carbon-carbon composites for gas generator combustors and flywheel rotors composed of carbon fiber reinforced polymer matrix composites for energy storage on the international space station (ISS). The role of NDE in solving manufacturing problems, the effect of defects on structural behavior, and the use of NDE-based finite element modeling are discussed. NDE technology needs for improved microelectronic and mechanical systems as well as health monitoring of micro-materials and components are briefly discussed.

Baaklini, George Y.↗

Nondestructive Evaluation Approaches Developed for Material Characterization in Aeronautics and Space Applications

At the NASA Glenn Research Center, nondestructive evaluation (NDE) approaches were developed or tailored for characterizing advanced material systems. The emphasis was on high-temperature aerospace propulsion applications. The material systems included monolithic ceramics, superalloys, and high-temperature composites. In the aeronautics area, the major applications were cooled ceramic plate structures for turbine applications, gamma-TiAl blade materials for low-pressure turbines, thermoelastic stress analysis for residual stress measurements in titanium-based and nickel-based engine materials, and acousto-ultrasonics for creep damage assessment in nickel-based alloys. In the space area, applications consisted of cooled carbon-carbon composites for gas generator combustors and flywheel rotors composed of carbon-fiber-reinforced polymer matrix composites for energy storage on the International Space Station.

Baaklini, George Y.↗

Smart Optical Material Characterization System and Method

Disclosed is a system and method for characterizing optical materials, using steps and equipment for generating a coherent laser light, filtering the light to remove high order spatial components, collecting the filtered light and forming a parallel light beam, splitting the parallel beam into a first direction and a second direction wherein the parallel beam travelling in the second direction travels toward the material sample so that the parallel beam passes through the sample, applying various physical quantities to the sample, reflecting the beam travelling in the first direction to produce a first reflected beam, reflecting the beam that passes through the sample to produce a second reflected beam that travels back through the sample, combining the second reflected beam after it travels back though the sample with the first reflected beam, sensing the light beam produced by combining the first and second reflected beams, and processing the sensed beam to determine sample characteristics and properties.

Choi, Sang Hyouk↗

Improved Methods for Hyperelastic Material Characterizations Based on Uniaxial, Radial-Biaxial, and Strip-Biaxial Test Data

This report concerns the different analytical methods used for material characterizations of hyperelastic silicone rubber, a potential candidate elastomer for aerospace applications. To establish the constitutive equations for the silicon rubber, strain-energy gradients (material constants) must be determined from experiments. Earlier experiments by Blatz-Ko showed that the material constants of natural rubber determined from different stress fields were different. Therefore, in the current material characterization, uniaxial, equalbiaxial, and strip-biaxial tensile tests were conducted. Based on the resulting stress-stretch data, the material constants were determined by using a trendline on the stress-difference plots and energy plots, and also the MSC-Marc ® curve-fitting method. The results confirm that the material constants determined from uniaxial and biaxial stress fields are indeed different. The material constants determined from the equal-biaxial energy plots and from the MSC-Marc ® combined-curve-fitting method were found to be extremely close, and can be considered as universal material constants for establishing the constitutive equations for the silicone rubber under any stress field. The results of this report show that a uniaxially stretched specimen became slightly anisotropic due to crystallization of polymer molecular chains, and that equal-biaxial and strip-biaxial testing must be conducted to fully understand the material properties of hyperelastic materials.

William L Ko↗

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗

Material characterization and modeling with shear ography

Shearography has emerged as a useful technique for nondestructible evaluation and materials characterization of aerospace materials. A suitable candidate for the technique is to determine the response of debonds on foam-metal interfaces such as the TPS system on the External Tank. The main thrust is to develop a model which allows valid interpretation of shearographic information on TPS type systems. Confirmation of the model with shearographic data will be performed.

Workman, Gary L.↗

Neutron and photon in-vivo materials characterization at the evolving plasma-material interface in plasma-burning fusion environments

This report includes the first set of MOSS data collected in the context of fusion-relevant plasma-material interactions. The data collected show that the surface curvature and stress irreversibly change during low-energy deuterium ion irradiation. This holds for both tungsten thin films, bulk tungsten, and single-crystal silicon. Meanwhile, argon irradiation did not produce this same effect. The surface morphology of the exposed samples was virtually identical regardless of gas species. There were, however, some surface chemistry differences between argon-exposed and deuterium-exposed samples, mainly concerning the oxide states of the W4f XPS signal. The changes in surface chemistry could be due to hydrogen dynamics on the tungsten surfaces, though further investigation will be required with in-situ irradiation and analysis. The changes in surface stress could also not be explained by temperature alone, as the temperature reached during the ion irradiations was too low to induce non-elastic strain. With this in mind, deuterium retention in the materials could change the surface curvature and stress. To confirm this, further work will be needed to quantify the change in curvature and relate it to ion flux, fluence, and deuterium retention. Unfortunately, when this work was conducted, the experimental setup for thermal desorption spectroscopy was not operating correctly, and that work could not be included in this dissertation. Despite experimental difficulties, this work shows the first results of a promising technique to study deuterium dynamics in tungsten-based reconstituted thin films.

36 MATERIALS SCIENCE↗

Materials Characterization of Electron Beam Melted Ti-6Al-4V

An in-depth material characterization of Electron Beam Melted (EBM) Ti-6Al-4V material has been completed on samples fabricated on an ARCAM A2X EBM machine. The specimens were fabricated under eight separate builds with the material divided into two lots for material testing purposes. Hot Isostatic Pressing (HIP) was utilized to close porosity from fabrication and also served as a material heat treatment to obtain the desired microstructure. The changes in the microstructure and chemistry from the powder to pre-HIP and post-HIP material have been analyzed. Several nondestructive evaluation (NDE) techniques were utilized to characterize the samples both before and after HIP. The test matrix included tensile, high cycle fatigue, low cycle fatigue, fracture toughness, and fatigue crack growth at cryogenic, room, and elevated temperatures. The mechanical properties of the EBM Ti-6Al-4V are compared to conventional Ti-6Al-4V in the annealed condition. Fractography was performed to determine failure initiation site. The EBM Ti-6Al-4V had similar or superior mechanical properties compared to conventionally manufactured Ti-6Al-4V.

Titanium↗

Materials Characterization of Electron Beam Melted Ti-6Al-4V

An in-depth material characterization of Electron Beam Melted (EBM) Ti-6Al-4V material has been completed. Hot Isostatic Pressing (HIP) was utilized to close porosity from fabrication and also served as a material heat treatment to obtain the desired microstructure. The changes in the microstructure and chemistry from the powder to pre-HIP and post-HIP material have been analyzed. Computed tomography (CT) scans indicated porosity closure during HIP and high-density inclusions scattered throughout the specimens. The results of tensile and high cycle fatigue (HCF) testing are compared to conventional Ti-6Al-4V. The EBM Ti-6Al-4V had similar or superior mechanical properties compared to conventionally manufactured Ti-6Al-4V.

Titanium↗