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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Increased Defect Resistance and Ordering in MnBi 2 (Se 1– x Te x ) 4 via Accurate Diffusion Monte Carlo

Stabilizing materials and controlling defect formation remain key challenges in materials science, particularly for theory, where small energy differences must be resolved for accurate predictions. Here, we applied state-of-the-art theoretical methods to topological materials, focusing on MnBi 2 Te 4 (MBT), which is a promising intrinsic magnetic topological insulator. Antisite defects in MBT alter its electronic structure and magnetism, degrading topological properties and causing experimental inconsistencies. Using diffusion Monte Carlo and density functional theory, we investigated the thermodynamic stability and defect formation in MBT, MnBi 2 Se 4 (MBS), and MnBi 2 (Se 1–x Te x ) 4 . We found that MnBi 2 Se 2 Te 2 can be stable at finite temperatures, with higher defect formation energies due to stronger Mn–Se bonding and reduced internal strain. Se preferentially substitutes Te near Mn instead of Te in the outer layer, encouraging long-range ordering when incorporated. For MnBi 2 (Se 1–x Te x ) 4 , cluster expansion phase diagrams revealed solid solution behavior when x <0.5 and phase separation for larger x. MBT and MBS are topological insulators; therefore, the MnBi 2 (Se 1–x Te x ) 4 family could offer tunable topological behavior and improved stability.

MnBi2Te4↗
DOE OSTI2025

Single nuclear spin detection and control in a van der Waals material

Optically active spin defects in solids are leading candidates for quantum sensing and quantum networking. Recently, single spin defects were discovered in hexagonal boron nitride (hBN), a layered van der Waals (vdW) material. Owing to its two-dimensional structure, hBN allows spin defects to be positioned closer to target samples than in three-dimensional crystals, making it ideal for atomic-scale quantum sensing, including nuclear magnetic resonance (NMR) of single molecules. However, the chemical structures of these defects remain unknown and detecting a single nuclear spin with a hBN spin defect has been elusive. Here we report the creation of single spin defects in hBN using 13 C ion implantation and the identification of three distinct defect types based on hyperfine interactions. We observed both S = 1/2 and S = 1 spin states within a single hBN spin defect. We demonstrated atomic-scale NMR and coherent control of individual nuclear spins in a vdW material, with a π-gate fidelity up to 99.75% at room temperature. By comparing experimental results with density functional theory (DFT) calculations, we propose chemical structures for these spin defects. Our work advances the understanding of single spin defects in hBN and provides a pathway to enhance quantum sensing using hBN spin defects with nuclear spins as quantum memories.

Quantum metrology↗
DOE OSTI2015

Identification of defect-related emissions in ZnO hybrid materials

ZnO hybrid materials with singly precipitated ZnO nanocrystals embedded in the glass surface were fabricated by melt-quenching method followed by the annealing process. A series of samples containing different densities and species of intrinsic defects were obtained under different annealing conditions in a controllable manner, which was an ideal platform to identify the complicated defect origins. By employing photoluminescence (PL), excitation-dependent PL, PL excitation (PLE), and Raman spectroscopy, the radiative transitions of visible emission bands at around 401, 490, and 528 nm were unambiguously involved with zinc interstitial-related defect levels as initial states, and the corresponding terminal states were suggested to be valence band, oxygen vacancies, and zinc vacancies, respectively. This study may deepen the fundamental understanding of defect-related emissions and physics in ZnO and benefit potential applications of ZnO hybrid materials in optoelectronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A deep learning model for automatic analysis of cavities in irradiated materials

Transmission electron microscopy (TEM) is a commonly used technique in materials science for defect investigation. Quantitative analysis of defects is important for understanding the properties of a material, but manual analysis of TEM micrographs can be time-consuming and prone to error, especially when the defects have irregular shapes rather than spherical shapes. Many existing methods or deep learning models do not handle a wide range of sizes for the same object type within a single image. In this work, we present a framework that enables users to train an instance segmentation model called Mask R- CNN on any microstructure dataset, perform multi-detection on the same image at different scales, and obtain properties (e.g., size, area) of the objects based on the desired shape (e.g., circle, ellipse, rectangle). Additionally, we have developed a parallel detection module that uses multiple GPUs to increase the efficiency of the object detection process. We demonstrate the capabilities of our framework using a set of TEM images of cavities with different shapes, size distributions, and background contrasts. Finally, we show that the performance of our model in terms of density, size, and swelling of the cavities is comparable to the human average and that our model achieves the highest recall value compared to existing methods due to the use of image multi-rescaling.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Preparation and characterization of the rod-shaped stibnite

Highlights: • A facile route to synthesize large-scale rod-like Sb{sub 2}S{sub 3} micro-wires was presented. • A deep analysis conjoint between band tails, band gap alteration and electrical model. • The band gap is 1.75 eV which may hold for solar energy conversion. - Abstract: Stibnite (Sb{sub 2}S{sub 3}) micro-wires have been grown on glass substrates by sulfuration of Sb thermal evaporated film in a vacuum sealed tube in presence of sulfur powder at 300 °C for 6 h. X-ray diffraction and Raman spectroscopy techniques indicate that the synthesized micro-wires have an orthorhombic structure. SEM micrographs show rod-shaped micro-wires with a typical length of several tens of micrometers and a diameter of the order of 0.5 μm. The absorption coefficient dependence on the photon energy in the UV–visible range revealed the existence of a direct transition with an energy band gap of about 1.7 eV. Moreover, the band tails and localized states which are related to the level of defects in the material will be presented. These parameters were determined from the exponential absorption profile. All these results have been evaluated and discussed in terms of alteration of band gap edge and electrical measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗
DOE OSTI2026

Thermodynamics of Bimetallic Joints between Titanium and Tantalum Produced by Laser Powder Bed Fusion

Laser powder bed fusion (LBPF) is currently the most mature metal additive manufacturing (AM) technology. While it does not have the same flexibility as directed energy deposition techniques to produce compositional gradients, LPBF can still be used to generate bimetallic parts by depositing one metal on a build plate made of another. Here, in this study, we print combinations of Ti-6Al-4V with Ta and characterize defects that occur at the interface. We use thermodynamic modeling to explain the formation of keyhole porosity and solidification cracks when Ta is built on a Ti baseplate, and the lack of defects when the materials are reversed. By understanding the mechanisms that lead to defect formation, the methodology demonstrated here can be applied to other material systems to efficiently design bimetallic LPBF processes.

36 MATERIALS SCIENCE↗
DOE OSTI2015

CASTING DEFECT MODELING IN AN INTEGRATED COMPUTATIONAL MATERIALS ENGINEERING APPROACH

To accelerate the introduction of new cast alloys, the simultaneous modeling and simulation of multiphysical phenomena needs to be considered in the design and optimization of mechanical properties of cast components. The required models related to casting defects, such as microporosity and hot tears, are reviewed. Three aluminum alloys are considered A356, 356 and 319. The data on calculated solidification shrinkage is presented and its effects on microporosity levels discussed. Examples are given for predicting microporosity defects and microstructure distribution for a plate casting. Models to predict fatigue life and yield stress are briefly highlighted here for the sake of completion and to illustrate how the length scales of the microstructure features as well as porosity defects are taken into account for modeling the mechanical properties. Thus, the data on casting defects, including microstructure features, is crucial for evaluating the final performance-related properties of the component. ACKNOWLEDGEMENTS This work was performed under a Cooperative Research and Development Agreement (CRADA) with the Nemak Inc., and Chrysler Co. for the project "High Performance Cast Aluminum Alloys for Next Generation Passenger Vehicle Engines. The author would also like to thank Amit Shyam for reviewing the paper and Andres Rodriguez of Nemak Inc. Research sponsored by the U. S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, as part of the Propulsion Materials Program under contract DE-AC05-00OR22725 with UT-Battelle, LLC. Part of this research was conducted through the Oak Ridge National Laboratory's High Temperature Materials Laboratory User Program, which is sponsored by the U. S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Program.

Sabau, Adrian S↗
DOE OSTI2019

Multichannel filter application of a magnetized cold plasma defect in periodic structure of ZnS/TiO{sub 2} materials

In this article, transmission spectra of multilayer structure of zinc sulfide (ZnS) and titanium dioxide (TiO{sub 2}) with defect of magnetized cold plasma (MCP) have been calculated theoretically by using characteristics transfer matrix method. The transmission spectra versus frequency have been analyzed for symmetric and asymmetric structure. Due to have a multiple band gaps in the asymmetric structure, we have taken the asymmetric structure for analysis with the parameters of MCP and the thicknesses of the dielectric materials. It is well known that magnetized cold plasma is an abnormal material because the permittivity changes with applied external magnetic field, and shows tunable photonic band gap for permittivity of the MCP. Now, the transmission spectra of the asymmetric structure versus frequency by inserting one or two magnetized cold plasma layer were analyzed with the variation of incident angles, the parameters of MCP, and the thicknesses of ZnS and TiO{sub 2} material. The analyzed transmission spectra of asymmetric structure with the variation of electron density, thicknesses of dielectric materials were obtained better results with defect of two plasma layers as compare to the defect of one layer of plasma. These obtained results reveal that the defect of two magnetized cold plasma layers of one dimensional asymmetric structure of ZnS, TiO{sub 2} may be used for the tunable multichannel filter at microwave region.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Assessing the Impact of Point Defects on Molecular Diffusion in ZIF-8 Using Molecular Simulations

Because defects are ubiquitous in materials, they may play an important role in affecting the performance of materials in practical applications. In this paper, we investigate the influence of point defects on the diffusion of molecules including water, hydrocarbons, and acid gases in zeolitic imidazolate framework-8 (ZIF-8) using molecular simulations. To make these simulations possible, we introduce a force field that extends previous descriptions of pristine ZIF-8 to include experimentally relevant point defects. In general, the point defects we examined increase the local hopping rate for molecular diffusion, suggesting that low concentrations of these defects will not dominate long-range molecular diffusion in ZIF-8.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Defect Chemistry in High‐Voltage Cathode Materials for Lithium‐Ion Batteries

High-voltage cathodes (HVCs) have emerged as a paramount role for the next-generation high-energy-density lithium-ion batteries (LIBs). However, the pursuit of HVCs comes with inherent challenges related to defective structures, which significantly impact the electrochemical performance of LIBs. The current obstacle lies in the lack of a comprehensive understanding of defects and their precise effects. This perspective aims to provide insights into defect chemistry for governing HVCs. The classifications, formation mechanisms, and evolution of defects are outlined to explore the intricate relationship between defects and electrochemical behavior. The pressing need for cutting-edge characterization techniques that comprehensively investigate defects across various temporal and spatial scales is emphasized. Building on these fundamental understandings, engineering strategies such as composition tailoring, morphology design, interface modification, and structural control to mitigate or utilize defects are thoroughly discussed for enhanced HVCs performance. Furthermore, these insights are expected to provide vital guidelines for developing high-performance HVCs for next-generation high-energy lithium-ion batteries.

cross-scale characterization↗
DOE OSTI2015

Effect of tool pin features on process response variables during friction stir welding of dissimilar aluminum alloys

In this article, the effect of pin features and orientation/placement of the materials on advancing side were investigated for friction stir welding (FSW) of dissimilar aluminum alloys AA2050 and AA6061. Pins for FSW were produced with a 2.12 mm pitch thread having three flats/flutes. Three sets of rotational speed/welding speed were used to perform a series of welds in a butt joint arrangement. The results show that, joint quality, process response variables and welding temperature are highly affected by pin features and material orientation in FSW. Defect free joints with effective material transportation in the weld nugget zone were obtained when welding was performed with AA2050 on the advancing side. The tool also encounters less in-plane reaction force for welding with 2050 on the advancing side. Pin with thread+3 flats produces quality welds at low rotational and travel speed regardless of the location of alloys on advancing or retreating side.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Rhombohedral cubic semiconductor materials on trigonal substrate with single crystal properties and devices based on such materials

Growth conditions are developed, based on a temperature-dependent alignment model, to enable formation of cubic group IV, group II-V and group II-VI crystals in the [111] orientation on the basal (0001) plane of trigonal crystal substrates, controlled such that the volume percentage of primary twin crystal is reduced from about 40% to about 0.3%, compared to the majority single crystal. The control of stacking faults in this and other embodiments can yield single crystalline semiconductors based on these materials that are substantially without defects, or improved thermoelectric materials with twinned crystals for phonon scattering while maintaining electrical integrity. These methods can selectively yield a cubic-on-trigonal epitaxial semiconductor material in which the cubic layer is substantially either directly aligned, or 60 degrees-rotated from, the underlying trigonal material.

Park, Yeonjoon↗
NASA NTRSDate not supplied

Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques

Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of the subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography and ultrasound. The concept of the conflation of probability distributions is applied to combine the posterior distributions derived from thermography and ultrasound and the quality of the fused estimates are compared against the individual estimates against synthetic data that was created to mimic the inspection of a lap joint comprised of aluminum adherends.

thermal nondestructive evaluation↗
NASA NTRSDate not supplied

Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques

Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography, digital radiography, and ultrasound. The accuracy of the fused estimates are validated against data generated from synthetic specimens, and by comparison against high resolution X-ray computed tomography inspections of built specimens.

thermal nondestructive evaluation↗
DOE OSTI2024

Defects and Defect Engineering of Two-Dimensional Transition Metal Dichalcogenide (2D TMDC) Materials

As layered materials, transition metal dichalcogenides (TMDCs) are promising two-dimensional (2D) materials. Interestingly, the characteristics of these materials are transformed from bulk to monolayer. The atomically thin TMDC materials can be a good alternative to group III–V and graphene because of their emerging tunable electrical, optical, and magnetic properties. Although 2D monolayers from natural TMDC materials exhibit the purest form, they have intrinsic defects that limit their application. However, the synthesis of TMDC materials using the existing fabrication tools and techniques is also not immune to defects. Additionally, it is difficult to synthesize wafer-scale TMDC materials for a multitude of factors influencing grain growth mechanisms. While defect engineering techniques may reduce the percentage of defects, the available methods have constraints for healing defects at the desired level. Thus, this holistic review of 2D TMDC materials encapsulates the fundamental structure of TMDC materials, including different types of defects, named zero-dimensional (0D), one-dimensional (1D), and two-dimensional (2D). Moreover, the existing defect engineering methods that relate to both formation of and reduction in defects have been discussed. Finally, an attempt has been made to correlate the impact of defects and the properties of these TMDC materials.

2D materials↗
DOE OSTI2023

Comparative Study on Deep Learning Methods for Defect Identification and Classification in Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of composite aerostructure material. Furthermore, the methods developed here are both highly reliable with a top recall value of 98.63% as well as extremely efficient requiring an average of 4 seconds during the inferencing stage to evaluate new composites.

composites↗
DOE OSTI2018

Three-dimensional X-ray diffraction imaging of dislocations in polycrystalline metals under tensile loading

Abstract The nucleation and propagation of dislocations is an ubiquitous process that accompanies the plastic deformation of materials. Consequently, following the first visualization of dislocations over 50 years ago with the advent of the first transmission electron microscopes, significant effort has been invested in tailoring material response through defect engineering and control. To accomplish this more effectively, the ability to identify and characterize defect structure and strain following external stimulus is vital. Here, using X-ray Bragg coherent diffraction imaging, we describe the first direct 3D X-ray imaging of the strain field surrounding a line defect within a grain of free-standing nanocrystalline material following tensile loading. By integrating the observed 3D structure into an atomistic model, we show that the measured strain field corresponds to a screw dislocation.

36 MATERIALS SCIENCE↗