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DOE OSTI2024

X-ray linear dichroic tomography of crystallographic and topological defects

Abstract The functionality of materials is determined by their composition 1–4 and microstructure, that is, the distribution and orientation of crystalline grains, grain boundaries and the defects within them 5,6 . Until now, characterization techniques that map the distribution of grains, their orientation and the presence of defects have been limited to surface investigations, to spatial resolutions of a few hundred nanometres or to systems of thickness around 100 nm, thus requiring destructive sample preparation for measurements and preventing the study of system-representative volumes or the investigation of materials under operational conditions 7–15 . Here we present X-ray linear dichroic orientation tomography (XL-DOT), a quantitative, non-invasive technique that allows for an intragranular and intergranular characterization of extended polycrystalline and non-crystalline 16 materials in three dimensions. We present the detailed characterization of a polycrystalline sample of vanadium pentoxide (V 2 O 5 ), a key catalyst in the production of sulfuric acid 17 . We determine the nanoscale composition, microstructure and crystal orientation throughout the polycrystalline sample with 73 nm spatial resolution. We identify and characterize grains, as well as twist, tilt and twin grain boundaries. We further observe the creation and annihilation of topological defects promoted by the presence of volume crystallographic defects. The non-destructive and spectroscopic nature of our method opens the door to operando combined chemical and microstructural investigations 11,18 of functional materials, including energy, mechanical and quantum materials.

Science & Technology - Other Topics↗

DOE OSTI2026

Localizing tetrahedral aluminum in nitrate-bearing gibbsite to constrain defect-impurity coupling

The enhanced radiolytic stability of gibbsite (α-Al(OH) 3 ) containing trace nitrate (NO 3 − ) is a phenomenon in nuclear waste management, but its structural origins remain unresolved. Motivated by the detection of minority tetrahedral aluminum (T d ) defects in synthetic gibbsite, we hypothesized that these sites may participate in NO 3 − retention or mediate H 2 suppression. To evaluate this, we combined orthogonal techniques comprised of spatially selective solid-state 27 Al MAS NMR, comparative spectroscopy, and density functional theory (DFT) modeling. Paramagnetic editing and dynamic nuclear polarization (DNP) MAS NMR confirm that T d defects are confined to the particle interior. DFT calculations reveal no energetic stabilization of NO 3 − near T d sites. Comparative NMR analysis shows that T d is also present in chloride-bearing gibbsite, which exhibits high radiolytic hydrogen yields. These three independent disqualifications rule out T d as a structural contributor to nitrate-mediated suppression and narrow the scope of defect-driven explanations. The findings redirect mechanistic attention away from coordination defects and toward redox-active impurity pathways, providing a refined foundation for understanding radiation tolerance in Al(OH) 3 .

Graham, Trent R. [Pacific Northwest National Labor↗

DOE OSTI2025

Hybridization of colloidal handlebodies with singular defects and topological solitons in chiral liquid crystals

Topology can manifest itself in colloids when quantified by invariants like Euler characteristics of nonzero-genus colloidal surfaces, albeit spherical colloidal particles are most often studied, and colloidal particles with complex topology are rarely considered. On the other hand, singular defects and topological solitons often define the physical behavior of the molecular alignment director fields in liquid crystals. Interestingly, nematic liquid crystalline dispersions of colloidal particles allow for probing the interplay between topologies of surfaces and fields, but only a limited number of such cases have been explored so far. Here, we study the hybridization of topological solitons, singular defects, and topologically nontrivial colloidal particles with the genus of surfaces different from zero in a chiral nematic liquid crystal phase. Hybridization occurs when distortions separately induced by colloidal particles and LC solitons overlap, leading to energy minimization-driven redistribution of director field deformations and defects. As a result, hybrid director configurations emerge, combining topological features from both components. We uncover a host of director field configurations complying with topological theorems, which can be controlled by applying electric fields. Rotational and translational dynamics arise due to the nonreciprocal evolution of the director fields in response to alternating electric fields of different frequencies. These findings help define a platform for controlling topologically hyper-complex colloidal structures and dynamics with electrically reconfigurable singular defects and topological solitons induced by colloidal handlebodies.

Lee, Jun-Yong [Hiroshima Univ. (Japan)]↗

DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗

DOE OSTI2026

Correlation of coercivity, microstructure, and surface defects in HDDR-processed Nd-Fe-B powders for bonded magnet applications

Hydrogenation-Disproportionation-Desorption-Recombination (HDDR) is an effective method for producing high coercivity, anisotropic powder from either fresh Nd-Fe-B alloy or recycled Nd-Fe-B magnets for use in bonded magnets. We investigated the impact of surface defects on the coercivity of HDDR-processed Nd-Fe-B using scanning electron microscopy (SEM), magnetic measurements, and micromagnetic simulations. We observed that coercivity decreases as particle size reduces, with SEM revealing surface defects and the detachment of Nd 2 Fe 14 B grains and Nd-rich phases from the particle surface. Micromagnetic simulations indicate that demagnetization initiates at the particle surface, where these defects are most concentrated, leading to reduced coercivity. The reduction in squareness of demagnetization curve, knee point field and coercivity for smaller HDDR particles is attributed to an increased specific surface area, which exhibits reduced nucleation field and weak domain wall pinning field during magnetization reversal. By addressing the role of surface defects in coercivity degradation, this study provides insights for improving both new powder production and recycling strategies, ultimately leading to enhanced performance of bonded magnets and contributing to more sustainable practices in the rare earth supply chain. One potential strategy to enhance the performance of HDDR Nd-Fe-B materials involves reducing the fraction of fine particles ($<$35 µm) and promoting the formation of grain boundary phases on particle surfaces.

Liu, Xubo B. [Ames Laboratory (AMES), Ames, IA (Un↗

DOE OSTI2024

Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation

In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-to-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughput.

Yin, Keyi↗

DOE OSTI2025

Defects vibrations engineering for enhancing interfacial thermal transport in polymer composites

To push upper boundaries of thermal conductivity in polymer composites, understanding of thermal transport mechanisms is crucial. Despite extensive simulations, systematic experimental investigation on thermal transport in polymer composites is limited. To better understand thermal transport processes, we design polymer composites with perfect fillers (graphite) and defective fillers (graphite oxide), using polyvinyl alcohol (PVA) as a matrix model. Measured thermal conductivities of ~1.38 ± 0.22 W m -1 K -1 in PVA/defective filler composites is higher than those of ~0.86 ± 0.21 W m -1 K -1 in PVA/perfect filler composites, while measured thermal conductivities in defective fillers are lower than those of perfect fillers. We identify how thermal transport occurs across heterogeneous interfaces. Thermal transport measurements, neutron scattering, quantum mechanical modeling, and molecular dynamics simulations reveal that vibrational coupling between PVA and defective fillers at PVA/filler interfaces enhances thermal conductivity, suggesting that defects in polymer composites improve thermal transport by promoting this vibrational coupling.

42 ENGINEERING↗

DOE OSTI2026

Optical suppression of defect-related photoluminescence in GeSn

Reports of photoluminescence from GeSn grown on Ge substrates by molecular beam epitaxy have been limited. We find that one limiting factor to observing photoluminescence is due to localized defect states marked by photoluminescence at 2400 nm and originating from the Ge substrate and buffer layer. In this study, we report on an optical study utilizing doped Ge(001) substrates to effectively suppress defect-related photoluminescence in GeSn layers by filling localized defect trap states. For this experiment, a GeSn layer with Sn content up to 10.5 ± 0.5% was grown on a doped Ge(001) substrate. Analysis of the physics of the photoluminescence spectrum collected from the GeSn thin film shows an emission at the expected wavelength of 2300 nm for 10.5 ± 0.5% Sn content and the absence of the typically observed defect-related signal at 2400 nm. This understanding is further confirmed using short-pulse optical excitation of the GeSn grown on undoped Ge substrates.

Chemical vapor deposition↗

DOE OSTI2026

Point defects in semiconductors: Friends and foes for quantum technologies

Point defects in semiconductors are both a curse and a blessing in microelectronics: they enable the control of electrical conductivity through doping, yet can also act as trapping and recombination centers that degrade device performance. In quantum information science, defects play a similarly dual role. They can be harnessed as spin–photon interfaces enabling the coupling of electronic and nuclear spins to light and the creation of distributed entanglement for quantum networks or used as atomistic scale sensors for quantum sensing. At the same time, defects are a major source of decoherence for superconducting qubits, one of the leading quantum computing platforms. This article discusses how a deeper materials-level understanding of defects can guide the design of improved quantum devices for communication, sensing, and computation.

Zhu, Yizhi [Rice University, Houston, TX (United S↗

DOE OSTI2024

Approach and rotation of reconnecting topological defect lines in liquid crystal

Topological defects are a universal concept across many disciplines, such as crystallography, liquid-crystalline physics, low-temperature physics, cosmology, and even biology. In nematic liquid crystals, topological defects called disclinations have been widely studied. For their three-dimensional (3D) dynamics, however, only recently have theoretical approaches dealing with fully 3D configurations been reported. Further, recent experiments have observed 3D disclination line reconnections, a phenomenon characteristic of defect line dynamics, but detailed discussions were limited to the case of approximately parallel defects. In this paper, we focus on the case of two disclination lines that approach at finite angles and lie in separate planes, a more fundamentally 3D reconnection configuration. Observing and analyzing such reconnection events, we find the square-root law of the distance between disclinations and the decrease of the interdisclination angle over time. We compare the experimental results with theory and find qualitative agreement on the scaling of distance and angle with time, but quantitative disagreement on distance and angle relative mobilities. To probe this disagreement, we derive the equations of motion for systems with reduced twist constant and also carry out simulations for this case. These, together with the experimental results, suggest that deformations of disclinations may be responsible for the disagreement.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Defect Detection Model Development for Large Scale Thermoplastic Printing

Large-format additive manufacturing (LFAM) offers several advantages, including high throughput, cost-effective pellet-fed extrusion, and the capability to produce large-scale structures. The main pain points of LFAM include start and stops during the printing process, warpage, long layer times that lead to bead freezing, and bead separation due to shrinkage. These issues can lead to overfill, underfill and buildup of material in different sections of a print. This can lead to hidden defects embedded within the printed layers, or even ultimate failure of the printed structure. This ensures these defects can only be identified through nondestructive testing (NDT) inspection methods after printing, which can be timely and costly. Aligned Vision work specializes in 2D projectors with visual inspection systems and machine learning. Traditionally system is used for composite layup and layup inspections. In this work we used the LFAM system at Oak Ridge National Laboratory to create defect rich samples. The Aligned Vision inspection system then performed in-situ monitoring of the print process after each part was printed. This in-situ vision inspection system was used to develop a layer-by-layer inspection model that looks for overfill, underfill, and the buildup of defects using only a camera-based vision system. This leads to the assurance of high-quality production components.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Establishing defect-property relationships for 2D-nanomaterials (Final technical report)

Studies of new families of two-dimensional nanomaterials (2DNMs) have established that they possess unique properties that diverge from those of their bulk counterparts. This project aimed to determine how tolerant 2DNMs are to extreme photon and particle fluxes and to identify the mechanisms governing their radiation response. Early work indicated that graphene is not as representative of other 2DNMs as previously assumed; however, the origin of this difference remained unclear. To address these knowledge gaps, this project investigated the physical processes occurring at multiple length scales in transition metal dichalcogenides (TMDs) and quantified their structural stability and property evolution under far-from-equilibrium conditions. In-situ and ex-situ ion and electron irradiations were performed to directly control and monitor defect formation in TMDs. Complementary density functional theory (DFT) and molecular dynamics (MD) simulations were employed to elucidate the mechanisms of defect generation and evolution. The outcomes of this work established mechanistic understanding of irradiation-induced defect formation in 2DNMs, quantified the radiation tolerance of TMDs, and built a fundamental knowledge base for correlating defect structures with material properties. Collectively, these results provide new insights into the stability of low-dimensional materials in extreme environments and enable the predictive design of radiation-tolerant 2DNMs.

2D materials↗

DOE OSTI2025

Machine Learning Thermodynamics And Kinetics of Defects For Accelerated Materials Discovery

Atomistic defects play a pivotal role in functional and structural materials’ performance across a myriad of technology applications. Quantitative prediction of the thermodynamics and kinetics of defect formation and migration, respectively, typically requires accurate but expensive first-principles approaches, such as density functional theory (DFT). Their computational expense limits the throughput needed to perform high-throughput materials discovery/screening exercises or to perform materials modeling tasks relying on extensive sampling techniques. Therefore, in this Sandia National Laboratories Laboratory Directed Research and Development (LDRD) project (Project #229366), we developed a variety of machine learning techniques, trained on density functional theory calculations, to accelerate the discovery and modeling of materials in which vacancy and interstitial defects primarily dictate material performance. These include applications such as metal oxides for water-splitting or mixed ionic-electronic conduction, metal hydrides for hydrogen storage, and transition metal dichalcogenides for electronics, and the approaches developed herein can further be applied to many other domains that similarly depend on materials’ thermodynamic and kinetic defect properties for their desired functionality.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A New Route Toward Atomically Flat and Defect-Free Ge/SiGe Planar Heterostructures

Germanium-based planar heterostructures are emerging as versatile platforms for realizing quantum devices. In particular, planar Ge/SiGe quantum wells (QWs) host hole states with exceptionally high mobility and strong, electrically tunable spin–orbit interactions, enabling full electrical control of quantum information. A key requirement for these systems is the growth of microscopic, defect-free, atomically flat Ge QW heterostructures on relaxed or reverse-graded SiGe buffer layers, as well as on commercial Ge substrates. While several physical deposition techniques have demonstrated high-quality planar Ge/SiGe QWs, a major challenge remains: minimizing defect density typically requires high growth temperatures, which are incompatible with standard CMOS process flows. Here, we present a convenient low-temperature process for realizing high-quality planar SiGe/Ge heterostructures using a combination of thermal and electron-beam evaporation. We systematically map the effects of ex-situ and in-situ substrate preparation protocols, growth temperature, and post-deposition annealing conditions, and correlate these parameters with surface roughness and defect density. We find that in-situ oxide desorption conditions and post-annealing parameters have the most pronounced impact on improving surface quality. Under optimized conditions, we achieve atomically smooth surfaces with root-mean-square roughness σrms ≤ 10 Å and negligible defect density. Interestingly, thermally evaporated Ge layers exhibit oriented triangular crystallites that elongate upon post-annealing in the presence of high Ge vapor pressure. These results demonstrate that this simple, low-temperature deposition approach is a viable and effective route for achieving high-quality Ge QW heterostructures, with strong potential for scalable quantum computing and sensing applications.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗

DOE OSTI2026

A New Route Toward Atomically Flat and Defect-Free Ge/SiGe Planar Heterostructures

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗

DOE OSTI2025

You Only Look Once v5 and Multi-Template Matching for Small-Crack Defect Detection on Metal Surfaces

This paper compares the performance of Deep Learning (DL) and multi-template matching (MTM) models for detecting small defects. DL models extract distinguishing features of objects but require a large dataset of images. In contrast, alternative computer vision techniques like MTM need a relatively small dataset. The lack of large datasets for small metal-surface defects has inhibited the adoption of automation in small-defect detection in remanufacturing settings. This motivated this preliminary study to compare template-based approaches, like MTM, with feature-based approaches, such as DL models, for small-defect detection on an initial laboratory and remanufacturing industry dataset. This study used You Only Look Once v5 (YOLOv5) as the DL model and compared its performance against the MTM model for small-crack detection. The findings of our preliminary investigation are as follows: (i) YOLOv5 demonstrated higher performance than MTM in detecting small cracks; (ii) an extra-large variant of YOLOv5 outperformed a small-size variant; (iii) the size and object variety of the data are crucial in achieving robust pre-trained weights for use in transfer learning; and (iv) enhanced image resolution contributes to precise object detection.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Low-Temperature Annealing of Nanoscale Defects in Polycrystalline Graphite

Polycrystalline graphite contains multi-scale defects, which are difficult to anneal thermally because of the extremely high temperatures involved in the manufacturing process. In this study, we demonstrate annealing of nuclear graphite NBG-18 at temperatures below 28 °C, exploiting the electron wind force, a non-thermal stimulus. High current density pulses were passed through the specimens with a very low-duty cycle so that the electron momentum could mobilize the defects without heating the specimen. The effectiveness of this technique is presented with a significant decrease in electrical resistivity, defect counts from X-ray computed tomography, Raman spectroscopy, and nanoindentation-based mechanical characterization. Such multi-modal evidence highlights the feasibility of nanoscale defect control at temperatures about two orders of magnitude below the graphitization temperature.

Liu, Gongyuan↗

NASA NTRS1971

The observation of structural defects in neutron-irradiated lithium-doped silicon solar cells

Electron microscopy has been used to observe the distribution and morphology of lattice defects introduced into lithium-doped silicon solar cells by neutron irradiation. Upon etching the surface of the solar cells after irradiation, crater-like defects are observed that are thought to be associated with the space charge region around vacancy clusters. Thermal annealing experiments showed that the crater defects were stable in the temperature range 300 to 1200 K in all of the lithium-doped samples. Some annealing of the crater defects was observed to occur in the undoped cells which were irradiated at the lowest doses.

Sargent, G. A.↗