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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals

One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating the enhancement of TT imaging capability using machine learning. In this work, we introduce a novel multi-task learning (MTL) approach, which simultaneously performs the classification of synthetic TT images, and segmentation of experimental scanning electron microscopy (SEM) images. Synthetic TT images are obtained from computer simulations of metallic structures with subsurface elliptical-shaped defects, while experimental SEM images are obtained from imaging of LPBF-printed stainless-steel coupons. MTL network is implemented as a shared U-net encoder between the classification and the segmentation tasks. Results of this study show that the MTL network performs better in both the classification of synthetic TT images and the segmentation of SEM images tasks, as compared to the conventional approach when the individual tasks are performed independently of each other.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic-scale identification of defects in alite

Crystallographic defects play a crucial role in cement hydration, with initial dissolution being dominated by the formation of etch pits that rely on the intersection of defects on surfaces. However, the defects present in cement particles have remained a mystery due to the lack of detailed direct observation at the atomic scale. In this study, we used scanning transmission electron microscopy to unravel the defects in alite particles at the single-atom level. Our observations identified different types of defects, including vacancies, doping, dislocations, rough surfaces, and grain boundaries. Atomic ordering in the alite crystal was further examined based on our single-atom recognition method. Our findings indicate that defects in cement particles may serve as reactive sites during the early hydration stage, facilitating the initial dissolution and providing nucleation sites for hydration products. Finally, this work provides insights into cement defect formation at the single-atom level and offers new opportunities in tuning the hydration process through defect engineering of cement particles.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation

Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Characterization of defect growth structures in ion plated films by scanning electron microscopy

Gold and copper films (0.2-2 micron thick) are ion plated on very smooth stainless steel 304 and mica surfaces. The deposited films are examined by SEM to identify the morphological growth of defects. Three types of coating defects are distinguished: nodular growth, abnormal or runaway growth, and spits. The potential nucleation sites for defect growth are analyzed to determine the cause of defect formation. It is found that nuclear growth is due to inherent surface microdefects, abnormal or runaway growth is due to external surface inclusions, and spits are due to nonuniform evaporation and ejection of droplets. All these defects have adverse effects on the coatings.

Spalvins, T.↗
DOE OSTI2020

Role of shell composition and morphology in achieving single-emitter photostability for green-emitting “giant” quantum dots

The use of the varied chemical reactivity of precursors to drive the production of a desired nanocrystal architecture has become a common method to grow thick-shell graded alloy quantum dots (QDs) with robust optical properties. Conclusions on their behavior assume the ideal chemical gradation and uniform particle composition. In this work, advanced analytical electron microscopy (high-resolution scanning transmission electron microscopy coupled with energy dispersive spectroscopy) is used to confirm the nature and extent of compositional gradation and these data are compared with performance behavior obtained from single-nanocrystal spectroscopy to elucidate structure, chemical-composition, and optical-property correlations. In particular, the evolution of the chemical structure and single-nanocrystal luminescence was determined for a time-series of graded-alloy “CdZnSSe/ZnS” core/shell QDs prepared in a single-pot reaction. In a separate step, thick (~6 monolayers) to giant (>14 monolayers) shells of ZnS were added to the alloyed QDs via a successive ionic layer adsorption and reaction (SILAR) process, and the impact of this shell on the optical performance was also assessed. By determining the degree of alloying for each component element on a per-particle basis, we observe that the actual product from the single-pot reaction is less “graded” in Cd and more so in Se than anticipated, with Se extending throughout the structure. The latter suggests much slower Se reaction kinetics than expected or an ability of Se to diffuse away from the initially nucleated core. It was also found that the subsequent growth of thick phase-pure ZnS shells by the SILAR method was required to significantly reduce blinking and photobleaching. However, correlated single-nanocrystal optical characterization and electron microscopy further revealed that these beneficial properties are only achieved if the thick ZnS shell is complete and without large lattice discontinuities. Thus, we identify the necessary structural design features that are required for ideal light emission properties in these green-visible emitting QDs.

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

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Co-extrusion of dissimilar Al alloys via shear assisted processing and extrusion

Cladded tubes are generally used where two distinct properties are required at the outer and inner part of a tube, for instance, strength and corrosion resistance. In this investigation, shear assisted processing and extrusion (ShAPE) was employed to fabricate bi-metallic tubes from 1100 and 7075, and 1100 and 2024 dissimilar Al alloy combinations. Surface defect-free bi-metallic tubes were fabricated via the ShAPE process. Detailed microstructural characterization of the interface and various locations of the cladded tubes were carried out using light and scanning electron microscopy techniques. A defect-free, metallurgically bonded interface between the cladded layer and high strength Al (7075 and 2024 Al) was observed. Furthermore, hardness and tensile properties of the cladded ShAPE tubes were examined in the as-extruded conditions.

Komarasamy, Mageshwari↗
DOE OSTI2020

Defect and structural evolution under high-energy ion irradiation informs battery materials design for extreme environments

Understanding defect evolution and structural transformations constitutes a prominent research frontier for ultimately controlling the electrochemical properties of advanced battery materials. Herein, for the first time, we utilize in situ high-energy Kr ion irradiation with transmission electron microscopy to monitor how defects and microstructures evolve in Na- and Li-layered cathodes with 3d transition metals. Our experimental and theoretical analyses reveal that Li-layered cathodes are more resistant to radiation-induced structural transformations, such as amorphization than Na-layered cathodes. The underlying mechanism is the facile formation of Li-transition metal antisite defects in Li-layered cathodes. The quantitative mathematical analysis of the dynamic bright-field imaging shows that defect clusters preferentially align along the Na/Li ion diffusion channels ( a-b planes), which is likely governed by the formation of dislocation loops. Our study provides critical insights into designing battery materials for extreme irradiation environments and understanding fundamental defect dynamics in layered oxides.

25 ENERGY STORAGE↗
DOE OSTI2022

Oxygen vacancy dynamics in monoclinic metallic VO 2 domain structures

It was demonstrated recently that the nano-optical and nanoelectronic properties of VO 2 can be spatially programmed through the local injection of oxygen vacancies by atomic force microscope writing. In this work, we study the dynamic evolution of the patterned domain structures as a function of the oxygen vacancy concentration and the time. A threshold doping level is identified that is critical for both the metal–insulator transition and the defect stabilization. The diffusion of oxygen vacancies in the monoclinic phase is also characterized, which is directly responsible for the short lifetimes of sub-100 nm domain structures. This information is imperative for the development of oxide nanoelectronics through defect manipulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Distribution of 7 Li implants in Nb films for a sterile neutrino search

The Beryllium-7 Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for sub-MeV sterile neutrinos by measuring the 7 Li recoil spectrum from 7 Be decay in Ta-based superconducting quantum sensors. Its sensitivity is limited by spectral broadening from interactions between 7 Be/ 7 Li and the Ta host material. This study investigates Nb as an alternative sensor material using scanning transmission electron microscopy (STEM) and atom probe tomography (APT) on 7 Li-implanted Nb films (∼0.5 at. %). STEM shows no 7 Li cluster formation and no implantation-induced microstructural degradation, while APT reveals some limited 7 Li segregation to grain boundaries. Although this segregation may slightly influence binding energies, it is unlikely to affect the broadening of the recoil spectrum significantly. These findings support Nb as a viable sensor material for future phases of the BeEST experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Atomic-scale imaging and charge state manipulation of NV centers by scanning tunneling microscopy

Nitrogen-vacancy (NV) centers in diamond are among the most promising solid-state qubit candidates, owing to their exceptionally long spin coherence times, efficient spin-photon coupling, room-temperature operation, and steadily advancing fabrication and integration techniques. Despite significant progress in the field, atomic-scale characterization and control of individual NV centers have remained elusive. In this work, we utilize a conductive graphene capping layer to enable direct imaging and manipulation of NV - defects via scanning tunneling microscopy (STM). By investigating over 40 individual NV - centers, we identify their spectroscopic signatures and spatial configurations. Our dI/dV conductance spectra reveal the ground state resonance approximately 300 meV below the Fermi level and density-of-states maps uncover a two-lobed wavefunction aligned along the [111] crystallographic direction. Remarkably, we demonstrate the ability to manipulate the charge state of the NV centers from NV - to NV 0 through STM tip-induced gating. This work represents a significant advance in the atomic-scale imaging, spectroscopic characterization, and charge-state manipulation of NV centers, potentially paving the way for future quantum device development.

Raghavan, Arjun [Univ. of Illinois at Urbana-Champ↗
DOE OSTI2020

Native defects in antiferromagnetic topological insulator MnBi 2 Te 4

Using scanning tunneling microscopy and spectroscopy, in this study we visualized the native defects in antiferromagnetic topological insulator MnBi 2 Te 4 . Two native defects, Mn Bi and Bi Te antisites, can be well resolved in the topographic images. Mn Bi tend to suppress the density of states at the conduction band edge. Spectroscopy imaging reveals a localized peaklike local density of state at ~ 80 meV below the Fermi energy. A careful inspection of topographic and spectroscopic images, combined with density functional theory calculation, suggests this results from Bi Mn antisites at Mn sites. The random distribution of Mn Bi and Bi Mn antisites results in spatial fluctuation of local density of states near the Fermi level in MnBi 2 Te 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .

Engineering↗
DOE OSTI2025

Single-Molecule Fluorescence Microscopy Reveals Energy Transfer Active versus Inactive Nanocrystal/Dye Conjugate Pairs

Defect-mediated energy transfer (EnT) is a radiative process that occurs between donor defect states in the forbidden bandgap of semiconductor nanocrystals (NCs) and dye molecules bound to their surfaces. The EnT efficiency depends on the number of dye molecules attached to each NC, the donor–acceptor distance, and the dipole orientation factor between the donor and acceptor, all of which vary across all individual NCs in a sample. While ensemble-level fluorescence spectroscopy measurements have provided average values for donor–acceptor distances, dye-to-NC ratios, and EnT rate constants, questions remain about the impact of donor/acceptor heterogeneity on observed EnT efficiencies. Notably, ensemble-level measurements cannot distinguish between bare NCs and EnT-active versus inactive NC/dye pairs in the same sample batch, limiting the ability to design systems with 100% EnT efficiency. To address this, we studied defect-mediated EnT between AlexaFluor 555 dye acceptors chemically bound to ZnO NC donors at the level of single molecules and single NCs. Interestingly, 20% of bound NC/dye pairs are EnT-inactive, likely contributing to residual defect photoluminescence (PL) observed in ensemble-level measurements and reducing overall EnT efficiency. Single particle-level ZnO defect PL and acceptor fluorescence trajectories exhibited distinct microfluctuations, which are absent in bare ZnO NCs. We hypothesized that our observations can be explained with a competitive dye fluorescence quenching pathway, possibly due to charge transfer between the excited state dye and the ZnO NC. Numerical simulations of single-molecule PL traces for this scenario produced microfluctuations consistent with the experimental results. These findings highlight the impact of sample heterogeneity on EnT processes and provide insights for designing light-harvesting systems with optimized EnT efficiency.

25 ENERGY STORAGE↗
DOE OSTI2021

Structural and magnetic properties of hard magnetic system Ce(Co 1 -Fe ) 4.4 Cu 0.6 (0 ≤ x ≤ 0.19)

The Ce(Co 1 -Fe ) 4.4 Cu 0.6 (0 ≤ x ≤ 0.19) is a composite, hard magnetic system that is based on the CaCu 5 -type structure (1:5). It shows both, unique magnetic and microstructural features that are essential for permanent magnets, e.g., exceptional squareness of the 2nd. quadrant of the magnetization loops and microstructural features typically needed for pinning. Samples solidified in alumina crucibles are coarse-grained and often clearly faceted and readily align in a magnetic field. X-ray, SEM, and TEM analyses show a 1:5-type single-phase material when quenched from high temperature, which, after heat treatment, transforms into a laminar coherent nanostructure through the formation of a dense array of extended intercalated regions. Furthermore, these extended intercalated regions are comprised of segments of the Ce 2 Ni 7 –type structure (2:7) which segregate into various closely related precipitates forming a nanostructure similar to the SmCo 5 - Sm 2 Co 17 composites seen in Sm-Co permanent magnets. Based on TEM and Lorentz microscopy of well-aligned single grain particles, the magnetic domains’ reversal mechanism is regulated by anisotropy fluctuations occurring along the easy direction of magnetization and strong exchange interactions between the matrix and defects (e.g.: stacking faults). Lorentz microscopy suggests the domain wall is not physically pinned by the defect, but rather is offset/deflected when it interacts with the defect. The Lorentz and magnetization data suggest that defects cause a bending of the moment away from the c axis inside the grains.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Persistent Structure and Frustrated Magnetism in High Entropy Rare-Earth Zirconates

The configurational complexity and distinct local atomic environments of high entropy oxides remain largely unexplored, leaving structure-property relationships and the hypothesis that the family offers rich tunability for applications ambiguous. This work investigates the influence of cation size and materials synthesis in determining the resulting structure and magnetic properties of a family of high entropy rare-earth zirconates (HEREZs, nominal composition RE 2 Zr 2 O 7 with RE = rare-earth element combinations including Eu, Gd, Tb, Dy, Ho, La, or Sc). Here, the structural characterization of the series is examined through synchrotron X-ray diffraction and pair distribution function analysis, and electron microscopy, demonstrating average defect-fluorite structures with considerable local disorder, in all samples. The surface morphology and particle sizes are found to vary significantly with preparation method, with irregular micron-sized particles formed by high temperature sintering routes, spherical nanoparticles resulting from chemical co-precipitation methods, and porous nanoparticle agglomerates resulting from polymer steric entrapment synthesis. In agreement with the disordered cation distribution found across all samples, magnetic measurements indicate that all synthesized HEREZs show frustrated magnetic behavior, as seen in a number of single-component RE 2 Zr 2 O 7 pyrochlore oxides. These findings advance the understanding of the local structure of high entropy oxides and demonstrate strategies for designing nanostructured morphologies in the class.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Atomic defects, functional groups and properties in MXenes

MXenes, a new family of functional two-dimensional (2D) materials, have shown great potential for an extensive variety of applications within the last decade. Atomic defects and functional groups in MXenes are known to have a tremendous influence on the functional properties. In this review, we focus on recent progress in the characterization of atomic defects and functional group chemistry in MXenes, and how to control them to directly influence various properties ( e.g ., electron transport, Li + adsorption, hydrogen evolution reaction (HER) activity, and magnetism) of 2D MXenes materials. Dynamic structural transformations such as oxidation and growth induced by atomic defects in MXenes are also discussed. The review thus provides perspectives on property optimization through atomic defect engineering, and bottom-up synthesis methods based on defect-assisted homoepitaxial growth of MXenes.

36 MATERIALS SCIENCE↗