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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
NASA NTRS1991

Characterizing mode I fatigue delamination of composite materials

Two techniques for characterizing fatigue delamination in double cantilever beams, the delamination growth onset method and the delamination growth and arrest method, are evaluated. Two glass/epoxy systems, S2/SP250 and S2/CE9000, were tested at R = 0.1 and R = 0.5. The values of the strain energy release rate threshold Delta G(Ith) for no onset of delamination growth until one million cycles were compared with the values of Delta G(I) at delamination arrest. The values at arrest were consistently higher because fiber bridging occurred in the tests. Normalizing Delta G(I) by the mode I value of interlaminar fracture toughness G(Ir) at the corresponding delta A gave values of Delta G(I)/G(Ir) at delamination arrest which were closer to the threshold values obtained from the Delta G-N technique. However, this normalization did not represent a generic materials characterization technique and did not allow for delamination onset predictions.

Martin, Roderick H.↗
NASA NTRS1989

Signal processing applied to photothermal techniques for materials characterization

There is a need to make noncontact measurements of material characteristics in the microgravity environment. Photothermal and photoacoustics techniques offer one approach for attaining this capability since lasers can be used to generate the required thermal or acoustic signals. The perturbations in the materials that can be used for characterization can be detected by optical reflectance, infrared detection or laser detection of photoacoustics. However, some of these laser techniques have disadvantages of either high energy pulsed excitation or low signal-to-noise ratio. Alternative signal processing techniques that have been developed can be applied to photothermal or photoacoustic instrumentation. One fully coherent spread spectrum signal processing technique is called time delay spectrometry (TDS). With TDS the system is excited using a combined frequency-time domain by employing a linear frequency sweep excitation function. The processed received signal can provide either frequency, phase or improved time resolution. This signal processing technique was shown to outperform other time selective techniques with respect to noise rejection and was recently applied to photothermal instrumentation. The technique yields the mathematical equivalent of pulses yet the input irradiances are orders of magnitude less than pulses with the concomitant reduction in perturbation of the sample and can increase the capability of photothermal methods for materials characterization.

Rooney, James A.↗
NASA NTRS2016

Composite Characterization Using Ultrasonic Wavefield Techniques

The large-scale use of composite components in aerospace applications is expected to continue due to the benefits of composite materials, such as reduced weight, increased strength, and tailorability. NASA's Advanced Composites Project (ACP) has the goals of reducing the timeline for certification of composite materials and enabling the expanded use of advanced composite materials. A key technical challenge area for accomplishing these goals is the need for nondestructive evaluation and materials characterization techniques that are optimized for rapid inspection and detailed defect/damage characterization in composite materials. This presentation will discuss ongoing research investigating the use of ultrasonic wavefield techniques for the characterization of defects such as fiber waviness and delamination damage. Ongoing work includes the development of realistic ultrasonic simulation tools for use in predicting the inspectability of composites and optimizing inspection methodologies. Recent studies on detecting/characterizing delamination damage and fiber waviness via wavefield methods will be described.

Leckey, Cara A. C.↗
DOE OSTI2023

Report Outlining Computed Tomography Strategy and Microscopy Approach to Qualifying AM 316 Materials

This report is part of work package CR-22OR0406012, Automated, High-Throughput Materials Characterization Techniques , under the Advanced Materials and Manufacturing Technologies program (AMMT). The project’s primary objective is to leverage our AI-based rapid and high-throughput automated characterization framework to qualify additively manufactured 316 materials comprehensively, focusing on optimizing the additive manufacturing process and evaluating the performance of 3D-printed stainless steel components. This report outlines our strategy for leveraging the automated characterization process for qualifying 316H materials.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Ultrasonic Characterization of Aerospace Composites

Composite materials have seen an increased use in aerospace in recent years and it is expected that this trend will continue due to the benefits of reduced weight, increased strength, and other factors. Ongoing work at NASA involves the investigation of the large-scale use of composites for spacecraft structures (SLS components, Orion Composite Crew Module, etc). NASA is also involved in work to enable the use of composites in advanced aircraft structures through the Advanced Composites Project (ACP). In both areas (space and aeronautics) there is a need for new nondestructive evaluation and materials characterization techniques that are appropriate for characterizing composite materials. This paper will present an overview of NASA's needs for characterizing aerospace composites, including a description of planned and ongoing work under ACP for the detection of composite defects such as fiber waviness, reduced bond strength, delamination damage, and microcracking. The research approaches include investigation of angle array, guided wave, and phase sensitive ultrasonic methods. The use of ultrasonic simulation tools for optimizing and developing methods will also be discussed.

Leckey, Cara↗
NASA NTRS2008

New Techniques in Characterization of Ferroelectric Materials

Two new techniques have been developed to characterize Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT) based ferroelectric single crystals: (i) electro-thermal imaging, and (ii) single crystal x-ray diffraction in the transmission mode. (i) Electro-thermal imaging is a remote sensing technique that can detect the polarization direction and poling state of a whole crystal slice. This imaging technique utilizes an IR camera to determine the field induced temperature change and does not require any special or destructive sample preparation. In the resulting images it is possible to distinguish regions of 180 deg domains. This powerful technique can be used remotely during poling to determine the poling state of the crystal to avoid over-poling that can result in inferior properties and/or cracking of the crystals. Electro-thermal imaging produced the first direct observations of polarization rotation. Under bipolar field, the domains near the corners were the first to switch direction. As the field increased above the coercive field, domains at the center part of the crystals switched direction. (ii) X-ray diffraction in the transmission mode has long been used in structure determination of organic crystals and proteins; however, it is not used much to characterize inorganic systems. 0.7Pb(Mg1/3Nb2/3)O3-0.3PbTiO3 single crystals were examined by this XRD technique for the first time, and a never-before-seen super-lattice was revealed with a doubling of the unit cell in all three directions, giving a cell volume eight times that of a traditional perovskite unit cell. The significance of the super-lattice peaks increased with poling, indicating a structural contribution to ordering. Lack of such observations by electron diffraction in the transmission electron microscope examinations suggests the presence of a bulk effect.

Sehirlioglu, Alp↗
DOE OSTI2023

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↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
NASA NTRS2023

Short-Transverse Tensile Fracture Behavior of Thick AA2219 Plate - Effects of Theta (Al2Cu) Particle Size and Distribution

An investigation was conducted to obtain a better understanding on the microstructural characteristics of 5-inch-thick AA2219-T87 plate material and the mechanism that led to the unexpected low ductility in the short-transverse (ST) orientation. Materials characterization techniques were utilized to observe the microstructure of fractured tensile specimens and remnant plate material. The mechanism and cause of low ST ductility in the thick plate material is presented and discussed in this report.

Short-Transverse Orientation↗
DOE OSTI2026

Identifying materials-level sources of performance variation in superconducting transmon qubits

The Superconducting Quantum Materials and Systems Center, a U. S. Department of Energy National Quantum Information Science Research Center, has conducted a comprehensive and coordinated study using superconducting transmon qubit chips with known performance metrics to identify the underlying materials-level sources of device-to-device performance variation. Following qubit coherence measurements, these qubits of varying base superconducting metals and substrates have been examined with various non-destructive and invasive material characterization techniques at Northwestern University, Ames National Laboratory, and Fermilab as part of a blind study. We find trends in variations of the depth of the etched substrate trench, the thickness of the surface oxide, and the geometry of the sidewall, which when combined, lead to correlations with the T1 lifetime across different qubits on the same chip. In addition, we provide a list of features that varied from device to device, for which the impact on performance requires further studies. Finally, we identify two low-temperature characterization techniques that may potentially serve as proxy tools for qubit measurements. These insights provide materials-oriented solutions to not only reduce performance variations across neighboring devices but also to engineer and fabricate devices with optimal geometries to achieve performance metrics beyond the state-of-the-art values.

Murthy, Akshay A. [Fermilab] (ORCID:00000001767768↗
NASA NTRS1997

Growth of Bulk Wide Bandgap Semiconductor Crystals and Their Potential Applications

Developments in bulk crystal growth research for electro-optical devices in the Center for Photonic Materials and Devices since its establishment have been reviewed. Purification processes and single crystal growth systems employing physical vapor transport and Bridgman methods were assembled and used to produce high purity and superior quality wide bandgap materials such as heavy metal halides and II-VI compound semiconductors. Comprehensive material characterization techniques have been employed to reveal the optical, electrical and thermodynamic properties of crystals, and the results were used to establish improved material processing procedures. Postgrowth treatments such as passivation, oxidation, chemical etching and metal contacting during the X-ray and gamma-ray device fabrication process have also been investigated and low noise threshold with improved energy resolution has been achieved.

Chen, Kuo-Tong↗
NASA NTRSDate not supplied

Recent Advances in LIBS for Real-Time Detection of Silicone Contaminants on CFRP Surfaces

Laser induced breakdown spectroscopy (LIBS) is a materials characterization technique that has been advanced and refined to provide in situ, real-time quality control of carbon fiber reinforced polymer (CFRP) surfaces. As part of an effort to improve process control for adhesive bonding, a LIBS system was designed and assembled at NASA Langley Research Center (LaRC) to enable detection of ultralow concentrations of silicone contamination on CFRP adherends. The LIBS instrument provides high sensitivity detection and quasi-nondestructive surface characterization of CFRP adherends prior to adhesive bonding. This review focuses on the advancements at LaRC using LIBS as a quality control tool for the detection of silicone contaminants for improved adhesive bonding reliability of CFRP materials. This work describes how the LIBS technique was advanced by analyzing the laser parameters, studying the laser-matter interactions, and performing time-resolved measurements to determine the optimal plasma conditions for elemental detection. In addition, LIBS results were compared to X-ray photoelectron spectroscopy data to enable quantitative analysis from analytical calibration curves. Examples are shown of how to perform surface mapping of silicone contamination. Finally, a brief discussion is also presented on LIBS instrumentation, recommendations for laser parameters and instrumentation components, and LIBS technique maturity.

Surface characterization, Carbon fiber reinforced ↗
NASA NTRSDate not supplied

Recent Advances in LIBS for Real-Time Detection of Silicone Contaminants on CFRP Surfaces

Laser induced breakdown spectroscopy (LIBS) is a materials characterization technique that has been advanced and refined to provide in situ, real-time quality control of carbon fiber reinforced polymer (CFRP) surfaces. As part of an effort to improve process control for adhesive bonding, aLIBS system was designed and assembled at the NASA Langley Research Center (LaRC) to enable detection of ultra low concentrations of silicone contamination on CFRP adherends. The LIBS instrument provides high sensitivity detection and quasi-nondestructive surface characterization ofCFRP adherends prior to adhesive bonding. This review focuses on the advancements at LaRC using LIBS as a quality control tool for the detection of silicone contaminants for improved adhesive bonding reliability of CFRP materials. This work describes how the LIBS technique was advanced by analyzing the laser parameters, studying the laser-matter interactions, and performing time-resolved measurements to determine the optimal plasma conditions for elemental detection. In addition, LIBS results were compared to X-ray photoelectron spectroscopy data to enable quantitative analysis from analytical calibration curves. Examples are shown of how to perform surface mapping of silicone contamination. Finally, a brief discussion is presented on LIBS instrumentation, recommendations for laser parameters and instrumentation components, and LIBS technique maturity

Rodolfo I. Ledesma↗
DOE OSTI2024

Isotopic gamma lines for identification of shielding materials

Identifying the constituting materials of concealed objects is crucial in a wide range of sectors, such as medical imaging, geophysics, nonproliferation, national security investigations, and so on. Existing methods face limitations, particularly when multiple materials are involved or when there are challenges posed by scattered radiation and large areal mass. Here we introduce a novel brute-force statistical approach for material identification using high spectral resolution detectors, such as HPGe. The method relies upon updated semianalytic formulae for computing uncollided flux from source of gamma radiation, shielded by a sequence of nested spherical or cylindrical materials. These semianalytical formulae make possible rapid flux estimation for material characterization via combinatorial search through all possible combinations of materials, using a high-resolution HPGe counting detector. An important prerequisite for the method is that the geometry of the objects is known (for example, from X-ray radiography). We demonstrate the viability of this material characterization technique in several use cases with both simulated and experimental data in spherical geometry.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Trace Fe activates perovskite nickelate OER catalysts in alkaline media via redox-active surface Ni species formed during electrocatalysis

The accurate description of activity trends among perovskite-oxide oxygen-evolution-reaction (OER) catalysts using electronic-structure descriptors requires that the bulk structure of the catalyst is comparable to that of the surface. Few studies have addressed the dynamic nature of the catalyst's structure during the OER and the consequential implications for understanding activity. Here, we use a combination of electrochemical and materials-characterization techniques to study the surface reconstruction and the associated formation of a new redox-active phase on LaNiO 3 particles, LaNiO 3 epitaxial films, and an analogous Ruddlesden-Popper phase, La 2 NiO 4 . Small, but characteristic, redox features corresponding to Ni redox in nominally amorphous NiO x H y are observed during cyclic voltammetry of these initially fully crystalline materials. The size of these redox features grows with prolonged cycling and contributes to an increased surface area as determined from electrochemical impedance spectroscopy (EIS). Here we find the OER activity is strongly dependent on soluble Fe species in the electrolyte, common impurities in alkaline media. These observations are consistent with the reconstruction of the crystalline surface to form NiO x H y species and subsequent activation by adsorption of Fe forming the well-known and extremely active NiFeO x H y OER catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Hygrothermal Aging and Thermomechanical Characterization of As-Manufactured Tidal Turbine Blade Composites

This study investigates the hygrothermal aging behavior and thermomechanical properties of as-manufactured glass fiber-reinforced epoxy and thermoplastic composite tidal turbine blades. The blades were previously deployed in a marine environment and subsequently analyzed through a comprehensive suite of material characterization techniques, including hygrothermal aging, dynamic mechanical analysis (DMA), tensile testing and X-ray computed tomography (XCT). Hygrothermal aging experiments revealed that while thermoplastic composites exhibited lower overall water absorption (0.78% vs. 0.47%), they had significantly higher diffusion coefficients than epoxy (2.1 vs. 12.1 × 10 −13 m 2 s −1 ), suggesting faster saturation in operational environments. DMA results demonstrated that water ingress caused plasticization in epoxy matrices, reducing the glass transition temperature and increasing damping (112 °C to 104 °C), while thermoplastic composites showed more stable thermal behavior (87 °C glass transition temperature). Tensile testing revealed substantial reductions in ultimate strength (>40%) for both materials after prolonged water exposure, with minimal change in elastic modulus, highlighting the role of matrix degradation over fiber reinforcement. XCT image analysis showed that both composites were manufactured with high quality: no large voids or cracks were present, and the degree of misalignment was low. These findings inform future marine renewable energy composite designs by emphasizing the critical influence of moisture on long-term structural integrity and the need for optimized material systems in harsh marine environments. This work provides a rare real-world comparison of epoxy and recyclable thermoplastic tidal turbine blades, showing how laboratory aging tests and advanced imaging reveal the influence of material and manufacturing choices on long-term marine durability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

An Internal Digital Image Correlation Technique for High-Strain Rate Dynamic Experiments

Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been extended to perform measurements on the interior of specimens for dynamic, full-scale laboratory experiments. This limitation restricts the scope of physics which can be investigated through DIC measurements, especially in the context of heterogeneous materials. The focus of this study is to develop a method for performing internal DIC measurements in dynamic experiments. The aim is to demonstrate its feasibility and accuracy across a range of stresses (up to 650 MPa), strain rates (10 3 - 10 6 s -1 ), and high-strain rate loading conditions (e.g., ramped and shock wave loading). Internal DIC is developed based on the concept of applying a speckle pattern at an inner-plane of a transparent specimen. The high-speed imaging configuration is coupled to the traditional dynamic experimental setups, and is focused on the internal speckle pattern. During the experiment, while the sample deforms dynamically, in-plane, two-dimensional deformations are measured via correlation of the internal speckle pattern. In this study, the viability and accuracy of the internal DIC technique is demonstrated for split-Hopkinson (Kolsky) pressure bar (SHPB) and plate impact experiments. The internal DIC experimental technique is successfully demonstrated in both the SHPB and plate impact experiments. In the SHPB setting, the accuracy of the technique is excellent throughout the deformation regime, with measurement noise of approximately 0.2% strain. In the case of plate impact experiments, the technique performs well, with error and measurement noise of 1% strain. The internal DIC technique has been developed and demonstrated to work well for full-scale dynamic high-strain rate and shock laboratory experiments, and the accuracy is quantified. Here, the technique can aid in investigating the physics and mechanics of the dynamic behavior of materials, including local deformation fields around dynamically loaded material heterogeneities.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Quantitative Characterization of Structural and Mechanical Properties of Boron Nitride Nanotubes in High Temperature Environments

The structural stability and mechanical integrity of boron nitride nanotubes (BNNTs) in high temperature environments are of importance in pursuit of their applications that are involved with extreme thermal processing and/or working conditions, but remain not well understood. In this paper, we perform an extensive study of the impacts of high temperature exposure on the structural and mechanical properties of BNNTs with a full structural size spectrum from nano- to micro- to macro-scale by using a variety of in situ and ex situ material characterization techniques. Atomic force microscopy (AFM) and high resolution transmission electron microscopy measurements reveal that the structures of individual BNNTs can survive at up to 850 °C in air and capture the signs of their structural degradation at 900 °C or above. In situ Raman spectroscopy measurements reveal that the BN bonds in BNNT micro-fibrils undergo substantial softening at elevated temperatures of up to 900 °C. The AFM-based nanomechanical compression measurements demonstrate that the mechanical integrity of individual BNNTs remain intact after being thermally baked at up to 850 °C in air. The studies reveal that BNNTs are structurally and mechanically stable materials in high temperature environments, which enables their usages in high temperature applications.

Chen, Xiaoming↗