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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Static and dynamic topological defects in the domain textures in the helical antiferromagnet Ni 2 ⁢CoTeO 6

Real-space Bragg coherent x-ray-diffractive imaging unveils the formation of bubble and stripe antiferromagnetic (AFM) phase domains on the surface of Ni 2 ⁢CoTeO 6 single crystal. The stripe domains exhibit dislocation-type topological defects. The defects typically form as defect-antidefect pairs and can be created or annihilated by temperature changes and local heating. Thermal fluctuations of the AFM domain walls are observed near the Néel temperature. Topological defect pairs dynamically form and disappear in the fluctuating state. These observations provide a real-space perspective on the dynamics of the AFM phase transition in a helical antiferromagnet. Finally, the remarkable tunability of AFM domain walls in a helical antiferromagnet underscores their potential for AFM spintronics applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sub-millisecond keyhole pore detection in laser powder bed fusion using sound and light sensors and machine learning

Laser powder bed fusion is a mainstream additive manufacturing technology widely used to manufacture complex parts in prominent sectors, including aerospace, biomedical, and automotive industries. However, during the printing process, the presence of an unstable vapor depression can lead to a type of defect called keyhole porosity, which is detrimental to the part quality. In this study, we developed an effective approach to locally detect the generation of keyhole pores during the printing process by leveraging machine learning and a suite of optical and acoustic sensors. Simultaneous synchrotron x-ray imaging allows the direct visualization of pore generation events inside the sample, offering high-fidelity ground truth. A neural network model adopting SqueezeNet architecture using single-sensor data was developed to evaluate the fidelity of each sensor for capturing keyhole pore generation events. Our comparative study shows that the near infrared images gave the highest prediction accuracy, followed by 100 kHz and 20 kHz microphones, and the photodiode sensitive to processing laser wavelength had the lowest accuracy. Using a single sensor, over 90% prediction accuracy can be achieved with a temporal resolution as short as 0.1 ms. A data fusion scheme was also developed with features extracted using SqueezeNet neural network architecture and classification using different machine learning algorithms. Our work demonstrates the correlation between the characteristic optical and acoustic emissions and the keyhole oscillation behavior, and thereby provides strong physics support for the machine learning approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantum stabilization and flat hydrogen-based bands of nitrogen-doped lutetium hydride

We explore the electronic and structural properties of Lu-H-N structures with specific N,H ordering due to their remarkably narrow hydrogen-based bands at the Fermi level. Although exhibits a classical instability persisting up to 17 GPa, it is anharmonically stable near ambient pressure when accounting for quantum nuclear effects. The presence of flat bands near is understood to arise from destructive quantum interference between and surrounding orbitals, with certain types of defects leaving the flat bands unaffected. The results suggest that if this system is superconducting, there is an optimal pressure near ambient where the superconducting is maximized by anharmonically stabilized low-frequency and nonadiabatically coupled high-frequency hydrogen modes. Despite the metastability of this structure, its dynamical stability when modeled beyond a classical harmonic approach suggests the narrow bands near do not cause structural distortions in certain Lu-H-N stoichiometries.

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

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Toward Quality Control in Perovskite Solar Cell Fabrication: Spot-Like Processing Defects Disrupt Charge Transport Layers and Promote Ag Metal Electrode Intrusion

Metal halide perovskite (MHP) photovoltaics provide high efficiencies with less stringent processing requirements than traditional photovoltaic materials. However, processing related defects must be suppressed as they can lead to decreases in initial device efficiency and potentially compromise long-term device operation. In this work we investigate morphological defects in MHP devices using luminescence imaging followed by in-depth structural and composition analysis using electron microscopy-based methods. We identify several different classes of spot-like processing-related defects and observe that a single device structure may contain multiple types of these defects. The presence of these defects in devices with different layer structures and absorber chemistries makes them relevant to the perovskite photovoltaic community as a whole. The defects are associated with voids in the perovskite layer, inclusions (glass, migrated Ag, dust), thickness variations, hole transport layer disruption with anomalous crystal growth, and electron transport layer disruptions that could allow Ag intrusion and lead to local shunts. As perovskite photovoltaic technology matures, mitigation of such defects is critical to improving not only initial performance but also the long-term stability required for industrial applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Near-Infrared Emission from Sulfur Heteroatom Defects in Single-Walled Carbon Nanotubes

Quantum defects introduced into single-walled carbon nanotubes (SWCNTs) that support near-infrared emission are promising candidates for many applications. Here, we present a type of quantum defect in which sulfur atoms are incorporated into the crystal lattice of SWCNTs through their reactions with a mild reducing agent, sodium dithionite. When radical anions generated by sodium dithionites react with (6,5)-SWCNTs, two new emission features emerge at 1120 and 1250 nm. Comparing these spectral features with density functional theory calculation results, we attribute them to defects with episulfide or thioether structures. Here, by investigating the influences of reaction conditions including reactant concentration, light irradiation, and solvent type, we identify the reaction mechanism between SWCNTs and sodium dithionite and achieve good control over defect densities. Due to the intrinsic reactivity of sulfur species, the sulfur-containing quantum defects discovered here may facilitate the introduction of more complex and functionally diverse moieties into SWCNTs.

Anions↗
DOE OSTI2025

First-principles elucidation of defect-mediated Li transport in hexagonal boron nitride

Hexagonal boron nitride (hBN) is a promising candidate as a protective membrane or separator in Li-ion and Li–S batteries, given its excellent chemical stability, mechanical robustness, and high thermal conductivity. In addition, hBN can be functionalized by introducing defects and dopants, or be directly integrated into other active components of batteries, which further augments its appeal to the field. Here, we use first-principles simulations to evaluate the role of atomic defects in hBN in regulating the Li-ion diffusion mechanism and associated kinetics. Specifically, the following four distinct types of vacancy defects are considered: isolated single B and N vacancies, a B–N vacancy pair, and a B 3 N vacancy cluster. It is found that these defect sites generally favor Li intercalation and out-of-plane diffusion but slow down in-plane Li-ion diffusion due to a strong Li trapping effect at the defect sites. Such a trapping effect is, however, highly local such that it does not necessarily affect the overall Li-ion conductivity in defected hBN layers. The present systematic evaluation of the impact of atomic defects on Li ion migration and accompanied charge analysis of hBN lattice in response to Li-ion diffusion provide a mechanistic understanding of Li-ion transport behavior in defected hBN and highlight the potential of defect engineering to achieve optimal material performance.

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

Novosphingobium aromaticivorans LigR coordinates transcription of genes involved in metabolism of multiple types of aromatics

Aromatic compounds are a ubiquitous and diverse family of chemicals with functions as biomolecules, natural products, industrial chemicals, and pollutants. Novosphingobium aromaticivorans DSM 12444 uses multiple inducible pathways to catabolize H-, G-, and S-type aromatics that contain zero, one, or two methoxy groups, respectively. Here, we obtain a systems-level view of the transcriptional control of its aromatic metabolic pathways. Several in vitro analyses found that a N. aromaticivorans homolog of the Sphingobium lignivorans SYK-6 transcription factor LigR bound genomic DNA upstream of genes involved in metabolism of multiple aromatic types. We found that a ΔLigR mutant had growth defects on all three types of aromatics as sole carbon sources. Transcriptomic analysis revealed that LigR was required to increase expression of gene products that function in metabolism of all three aromatic types. We also found that, in media containing both glucose and an aromatic carbon source, the ΔLigR mutant directed intermediates through alternative aromatic metabolic pathways. Protein-DNA binding assays showed that N. aromaticivorans LigR binds immediately upstream of promoters of genes involved in aromatic metabolism. We found that N. aromaticivorans LigR coordinates the expression of enzymes that function in the catabolism of H-, G-, and S-type aromatics, and that there are differences in the role of LigR in N. aromaticivorans and S. lignivorans. A comparative genomic analysis predicted that LigR homologs and the aromatic-metabolizing genes that it directly regulates are often co-localized in the genomes of Sphingomonadales, but often not found in this arrangement in many other known aromatic metabolizing bacteria.

Aromatic Compound Degradation↗
DOE OSTI2025

Electrochemical Oxidation in Garnet-Type Solid Electrolyte by Formation of Point Defects

All-solid-state batteries hold greater promise for improving safety and energy density over conventional battery technology employing organic liquid electrolytes. One of the required features of a Li + conducting solid electrolyte is electrochemical stability, attained thermodynamically or kinetically, within the targeted operating voltage and temperature ranges. Therefore, understanding of the oxidative or reductive degradation mechanism is important to allow the design of stable solid electrolyte materials. This work contributes to building an understanding of the oxidative degradation mechanism in lithium solid electrolytes at cell operating conditions. Here, we have focused on resolving the oxidative decomposition mechanism of Al-doped lithium garnet Li 6.28 Al 0.24 La 3 Zr 2 O 12 (LLZO) as a state-of-the-art inorganic ceramic electrolyte. By combining experimental and computational analyses, we show that oxidation of LLZO occurs by simultaneous loss of oxygen and lithium from the structure, resulting in substoichiometric LLZO, at a moderate temperature (80 °C) and a high electrode potential (4.3 V vs Li/Li + ). Based on X-ray absorption and diffraction analyses, we find that the zirconium coordination shells in LLZO contract while the crystal structure experiences positive chemical strain upon electrochemical oxidation. The results from ex situ structural characterization of both the local structure and crystal symmetry are supported by a substoichiometric LLZO with lithium and oxygen vacancies, modeled by density functional theory (DFT) calculations. These chemical and structural changes in LLZO suppress effective lithium-ion conductivity by an order of magnitude. Formation of lithium and oxygen vacancies in LLZO upon electrochemical oxidation is different from prior thermodynamic predictions of phase decomposition of LLZO. The difference here is that the experiments were conducted at near-room temperature, which can hinder the kinetics of phase separation, and thus, the resultant LLZO solid electrolyte is still single-phase but substoichiometric in Li and O. In conclusion, these findings contribute an important degradation mechanism of the electrolyte, relevant for practical operational conditions of solid-state batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Atomic-scale visualization of defect-induced localized vibrations in GaN

Phonon engineering is crucial for thermal management in GaN-based power devices, where phonon-defect interactions limit performance. However, detecting nanoscale phonon transport constrained by III-nitride defects is challenging due to limited spatial resolution. Here, we used advanced scanning transmission electron microscopy and electron energy loss spectroscopy to examine vibrational modes in a prismatic stacking fault in GaN. By comparing experimental results with ab initio calculations, we identified three types of defect-derived modes: localized defect modes, a confined bulk mode, and a fully extended mode. Additionally, the PSF exhibits a smaller phonon energy gap and lower acoustic sound speeds than defect-free GaN, suggesting reduced thermal conductivity. Our study elucidates the vibrational behavior of a GaN defect via advanced characterization methods and highlights properties that may affect thermal behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2026

TEM Approaches for Microstructure-Informed Prediction of Mechanical Properties in Structural Alloys

Predicting the mechanical performance of structural alloys from their evolving microstructure remains a major challenge in materials science, particularly for nuclear structural materials, where irradiation-induced defects span multiple types and length scales and interact through complex mechanisms. The dispersed barrier hardening (DBH) [1] and Friedel–Kroupa–Hirsch (FKH) [2,3] models have been widely used to evaluate the hardening contributions of individual obstacles and to estimate tensile strength from quantified microstructures; however, when multiple size-dependent obstacles coexist and evolve, predicting temperature-dependent tensile strength becomes significantly more complex, and a fully consistent hardening model is still lacking. Transmission electron microscopy (TEM) plays a central role in refining hardening models and enabling predictive assessments of tensile strength evolution by providing quantitative characterization of dislocations, irradiation-induced defects (e.g., dislocation loops and cavities), precipitates, and grain structure (Fig. 1.). These experimentally measured defect densities are incorporated into physically based hardening models with size- and shape- dependent obstacle strengths [4], using root-sum-square superposition for obstacles of comparable strength and linear superposition for dissimilar ones [5]. In addition, recent advances in TEM [6-8], including high-resolution imaging, 4D-STEM strain mapping, EDS/EELS elemental analysis, and flash-polishing-based TEM specimen preparation and extraction-replica methods (Fig. 2), further improve the accuracy of microstructural quantification. By comparison with prior studies as well as our own results, we show that when TEM-derived microstructural information is carefully integrated with physically grounded hardening models, yield strength (or irradiation-induced hardening) measured at room temperature can be predicted with good quantitative agreement across multiple alloy classes. In-situ TEM combined with high-temperature mechanical testing represents an important next step for refining hardening models by directly probing dislocation–obstacle interactions across varying irradiation doses and temperatures [9]. Because the barrier strength factor (α) depends on both temperature and obstacle size, it should not be treated as a constant fitting parameter; rather, it must be explicitly evaluated to achieve physically meaningful predictions of mechanical behaviour at operating temperatures. This presentation therefore discusses why all strengthening contributions (e.g., Peierls stress, solid-solution strengthening, voids, bubbles, dislocation loops, dislocation lines, and grain boundaries) must be considered collectively, why appropriate superposition methods are essential when obstacles possess different barrier strength factors, how hardness measurements can be meaningfully related to tensile properties, and how TEM-derived microstructural information can be systematically incorporated into hardening models. More broadly, it outlines a pathway toward microstructure-informed prediction of mechanical properties and supports the goal of establishing science-based tools for evaluating structural materials in extreme environments [10].

Lin, Yan-Ru [ORNL] (ORCID:0000000339991473)↗
DOE OSTI2024

Phonon modal analysis of thermal transport in ThO 2 with point defects using equilibrium molecular dynamics

Defects can significantly degrade the thermal conductivity of ThO 2 , an advanced nuclear fuel material as well as a surrogate for other fluorite-structured materials. Here, we investigate how point defects in ThO 2 impact phonon mode-resolved thermal transport. By incorporating phonon modes from lattice dynamics, we decompose the trajectory and heat flux to phonon normal mode space and extract key phonon properties, including phonon relaxation times and their contributions to thermal conductivity. We implement two methods. The first method is based on the Green Kubo formalism to resolve the contribution of each phonon mode to thermal conductivity. The second resolves the lifetime of individual phonon modes and the thermal conductivity is calculated using the Boltzmann transport equation within relaxation time approximation. Notably, a lower contribution of acoustic modes is revealed compared to perturbative approaches considering only three-phonon scattering processes. The effects of four types of point defects are evaluated. The strongest impact on a reduction in thermal conductivity is from Th interstitials, followed by Th vacancies. O interstitials/vacancies have a similar impact, albeit smaller than defects on the thorium sublattice. These observations are consistent with previous studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Stacking fault analysis for the early-stages of PVT growth of 4H-SiC crystals

Here, four types of stacking fault formation mechanisms are identified and discussed for early stage PVT growth of 4H-SiC crystals: Type 1: Shockley / double Shockley stacking fault formation inside the facet; Type 2: Stacking fault formation via 2D nucleation; Type 3: Frank + Shockley (S) stacking fault formation due to deflection of threading mixed dislocation (TMD) by macrosteps; Type 4: “Carrot” defect formation related to overgrowth of the terrace formed by separation of 3c/4 and c/4 step risers after deflection of a TMD by vicinal steps. The results help further reduction of defect generation in 4H-SiC substrates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Local p‐ and n‐Type Doping of an Oxide Semiconductor via Electric‐Field‐Driven Defect Migration

Layered oxides exhibit high ionic mobility and chemical flexibility, attracting interest as cathode materials for lithium-ion batteries and the pairing of hydrogen production and carbon capture. Recently, layered oxides emerged as highly tunable semiconductors. For example, by introducing anti-Frenkel defects, the electronic hopping conductance in hexagonal manganites is increased locally by orders of magnitude. Here, local acceptor and donor doping in Er(Mn,Ti)O3 is demonstrated, facilitated by the controlled splitting of anti-Frenkel defects under applied d.c. voltage. By combining density functional theory calculations, scanning probe microscopy, atom probe tomography, and scanning transmission electron microscopy, it is shown that the oxygen defects can readily be moved through the layered crystal structure, leading to nano-sized interstitial-rich (p-type) and vacancy-rich (n-type) regions. The resulting pattern is comparable to dipolar npn-junctions and stable on the timescale of days. These findings reveal the possibility of temporarily functionalizing oxide semiconductors at the nanoscale, giving additional opportunities for the field of oxide electronics and the development of transient electronics in general.

He, Jiali↗
DOE OSTI2026

A foundation model for non-destructive defect identification from vibrational spectra

Defects are ubiquitous in solids and strongly influence materials’ functional properties. However, non-destructive characterization and quantification of defects, especially when multiple types coexist, remain a long-standing challenge. Here, we introduce DefectNet, a foundation machine learning model that predicts the chemical identity and concentration of substitutional point defects with multiple coexisting elements directly from vibrational spectra, specifically phonon density-of-states (PDoS). Trained on over 16,000 simulated spectra from 2,000 semiconductors, DefectNet employs a tailored attention mechanism to identify up to six distinct defect elements at concentrations ranging from 0.2% to 25%. The model generalizes well to unseen crystals across 56 elements and can be fine-tuned on experimental data. Validation using inelastic scattering measurements of SiGe alloys and MgB 2 superconductor demonstrates its accuracy and transferability. Furthermore, our work establishes vibrational spectroscopy as a viable, non-destructive probe for bulk point defect quantification, and highlights the promise of foundation models in data-driven defect engineering.

artificial intelligence↗
DOE OSTI2024

Analysis of differential scanning calorimetry data for aged plutonium

Differential scanning calorimetry data for samples of a 52 year old plutonium alloy with 3.3 at. % Ga that were heated beyond the melting point is analyzed using transition state theory to find activation energies for the δ to ε and ε to liquid phase transitions. A Bayesian statistical method involving a Gaussian process model is used to find mean values and confidence intervals for the activation energies. The activation energy for the δ to ε phase transition increases by 3.3 ± 3.8% per decade, relative to the case when all age related plutonium lattice point defects have been removed through annealing. The corresponding increase in activation energy for the ε to liquid transition is shown to be 7.1 ± 1.8% per decade. It is postulated that the change in activation energy with age for both phase transitions is caused, in part, by the accumulation of the same type of lattice point defects associated with the observed increase in elastic bulk modulus over time.

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

Self-compensation of group-V acceptors in CdTe

Cadmium Telluride is at the core of an important thin-film technology for photovoltaics that is already commercially available, yet the CdTe-based solar cell efficiency remains limited at 22%, well below the theoretical limit of ~30%. Increasing the hole concentration is crucial for higher efficiency, and group-V elements such as As, P, and Sb are potential dopants as they are shallow acceptors. Nevertheless, group-V doped p-type CdTe often exhibits low doping activation, and the compensation source remains debated. Here, we performed hybrid density functional calculations with spin-orbit coupling to investigate possible sources of hole compensation in group-V doped CdTe. First, regarding possible self-compensation of the group-V dopants, we find that the formation of AX centers is unlikely since they are found to be unstable relative to the shallow acceptor forms. However, if the group-V dopants come in during growth (such as dimer molecules As2, P2, and Sb2), we find that the impurity atoms, which would occupy nearest neighbor sites, maintain the V-V bonds, limiting the hole density. For the native defects, our study reveals that Cd interstitial is the lowest energy donor defect in p-type CdTe. Still, it has a small migration barrier of 0.5 eV, making it highly mobile and unstable at room temperature. The Te vacancy is the next lowest formation energy donor. The migration barrier of 1.4 eV indicates that the Te vacancy is stable at room temperature. The antisite CdTe is also a donor, with low formation energy and stable at room temperature, potentially limiting the hole concentration. Our results, therefore, shed light on possible compensation centers and some guidance on how to avoid them.

14 SOLAR ENERGY↗