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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Toward accurate prediction of partial-penetration laser weld performance informed by three-dimensional characterization – Part II: μCT based finite element simulations

The mechanical behavior of partial-penetration laser welds exhibits significant variability in engineering quantities such as strength and apparent ductility. Understanding the root cause of this variability is important when using such welds in engineering designs. In Part II of this work, we develop finite element simulations with geometry derived from micro-computed tomography (μCT) scans of partial-penetration 304L stainless steel laser welds that were analyzed in Part I. We use these models to study the effects of the welds’ small-scale geometry, including porosity and weld depth variability, on the structural performance metrics of weld ductility and strength under quasi-static tensile loading. We show that this small-scale geometry is the primary cause of the observed variability for these mechanical response quantities. Additionally, we explore the sensitivity of model results to the conversion of the μCT data to discretized model geometry using different segmentation algorithms, and to the effect of small-scale geometry simplifications for pore shape and weld root texture. The modeling approach outlined and results of this work may be applicable to other material systems with small-scale geometric features and defects, such as additively manufactured materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Beam Hardening Artifact Reduction in X-Ray CT Reconstruction of 3D Printed Metal Parts Leveraging Deep Learning and CAD Models

Nondestructive evaluation (NDE) of additively manufactured (AM) parts is important for understanding the impacts of various process parameters and qualifying the built part. X-ray computed tomography (XCT) has played a critical role in rapid NDE and characterization of AM parts. However, XCT of metal AM parts can be challenging because of artifacts produced by standard reconstruction algorithms as a result of a confounding effect called “beam hardening.” Beam hardening artifacts complicate the analysis of XCT images and adversely impact the process of detecting defects, such as pores and cracks, which is key to ensuring the quality of the parts being printed. In this work, we propose a novel framework based on using available computer-aided design (CAD) models for parts to be manufactured, accurate XCT simulations, and a deep-neural network to produce high-quality XCT reconstructions from data that are affected by noise and beam hardening. Using extensive experiments with simulated data sets, we demonstrate that our method can significantly improve the reconstruction quality, thereby enabling better detection of defects compared with the state of the art. We also present promising preliminary results of applying the deep networks trained using CAD models to experimental data obtained from XCT of an AM jet-engine turbine blade.

Ziabari, Amir↗
DOE OSTI2023

Atomistic models of In and Ga diffusion in Cu(In,Ga)Se 2

To improve the performance of Cu(In,Ga)Se 2 thin-film photovoltaic devices, a robust understanding of the dominant diffusion pathways of the alloy species In and Ga is needed. Here, the most probable defect complexes and mechanisms for In and Ga diffusion are identified with the aid of density functional theory. The binding energies and migration barriers for these complexes are calculated in bulk CuInSe 2 and CuGaSe 2 . Analytic models and kinetic lattice Monte Carlo simulations are employed to predict the diffusivity of In and Ga under variations in composition and temperature. Here, we find that a model based on coulombic interactions between group III antisites and vacancies on the Cu-sublattice produces results that match well with experiment.

14 SOLAR ENERGY↗
DOE OSTI2019

Linking the Codependence of Grain Boundary Structure and Density to Defect Evolution Mechanisms during Radiation Damage

There is little understanding of the direct link between grain boundary character and density, and defect denuded zones. For example, the role of reduced grain size to the nanocrystalline regime and subsequent increase in grain boundary density is not fully understood in the context of dislocation or void behavior near grain boundaries. In addition, little is understood experimentally on how defect absorption changes the structure of the grain boundary during irradiation and may play a role in the migration of defects and solutes. This work aims to define a framework for understanding the origin of radiation damage mechanisms in model BCC and FCC nanocrystalline materials, on which a foundation of radiation tolerant material development can be built. The key questions that will be addressed by this work are: 1. What is the influence of GB density and GB character (GBC) on radiation damage accumulation near grain boundaries in model nanocrystalline FCC and BCC alloys; how are these two effects connected? 2. In the context of radiation induced segregation (RIS), what effect does species dependent interstitial diffusion have on the GB chemistry in light of these two dependencies? 3. How does grain boundary sink efficiency evolve with radiation over time? In situ and analytical transmission electron microscopy techniques are used to study both pure and alloy nanocrystalline materials under irradiation. TEM samples prepared from thin films will be irradiated in-situ, allowing for dynamic observation of the behavior of the alloy under ion irradiation. The key findings from this program were (1) the control of thin film texture via sputtering; (2) the development of characterization tools for defects and grain boundary quantification; (3) the development of new techniques for defect characterization toward high throughput analysis; (4) a mapped out parameter space for defect evolution as a function of grain size and grain boundary character; and finally (5) an indication of sink efficiency and its stability during irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Validated Reactive Force Field Quantifies MXene Interfacial Properties, Mechanics, and Thermal Transport

MXenes combine rich surface chemistry, mechanical strength, and high conductivity for a multitude of emerging applications. Predictive modeling supports accelerated materials designs and has been limited by the absence of validated and transferable force fields. Here, we introduce an interpretable, reactive INTERFACE force field (IFF and IFF-R) for Ti 3 C 2 T x MXenes that is trained based on chemical knowledge and achieves quantitative agreement with experiments across lattice parameters (<0.5%), density (<0.2%), liquid contact angles, Raman spectra, and the in-plane elastic modulus (∼320 GPa). The models cover surface terminations from hydroxyl (−OH) to fluorine (−F) groups and are extensible to other chemistries. We introduce pH-resolved surface chemistry and identify dopamine adsorption mechanisms at MXene–aqueous interfaces supported by QCM-D and UV–Vis experiments. The data reveal coplanar and perpendicular binding modes and concentration-dependent multilayer assembly. We predict previously inaccessible properties, including termination-dependent cleavage energies, interlayer shear moduli and dynamic shear failure, nanoindentation and brittle fracture, anisotropic in-plane and out-of-plane thermal conductivities, including the role of defects. Agreement with available experimental data is consistently close and exceeds DFT accuracy across the benchmark properties examined. The IFF/IFF-R model is compatible with CHARMM, AMBER, OPLS, and CVFF force fields for simulations of MXenes with diverse surface terminations, electrolyte interfaces, biointerfaces, and polymer composites without additional parameters. Parameter sets, 3D models, and analysis scripts are provided for community use. The validated, reactive, and transferable IFF framework facilitates predictive design of MXene-based films, membranes, sensing interfaces, and composites.

MXene↗
DOE OSTI2021

Stability and molecular pathways to the formation of spin defects in silicon carbide

Abstract Spin defects in wide-bandgap semiconductors provide a promising platform to create qubits for quantum technologies. Their synthesis, however, presents considerable challenges, and the mechanisms responsible for their generation or annihilation are poorly understood. Here, we elucidate spin defect formation processes in a binary crystal for a key qubit candidate—the divacancy complex (VV) in silicon carbide (SiC). Using atomistic models, enhanced sampling simulations, and density functional theory calculations, we find that VV formation is a thermally activated process that competes with the conversion of silicon (V Si ) to carbon monovacancies (V C ), and that VV reorientation can occur without dissociation. We also find that increasing the concentration of V Si relative to V C favors the formation of divacancies. Moreover, we identify pathways to create spin defects consisting of antisite-double vacancy complexes and determine their electronic properties. The detailed view of the mechanisms that underpin the formation and dynamics of spin defects presented here may facilitate the realization of qubits in an industrially relevant material.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Changes in Hydrogen Concentration and Defect State Density at the Poly-Si/SiOx/c-Si Interface Due to Firing

We determined the density of defect states of poly-Si/SiOx/c-Si junctions featuring a wet chemical interfacial oxide from lifetime measurements using the MarcoPOLO model to calculate recombination and contact resistance in poly-Si/SiOx/c-Si-junctions. In samples that did not receive any hydrogen treatment, the Dit,cSi is about 2 × 1012 cm-2 eV1 before firing and rises to 3–7 × 1012 cm2 eV1 during firing at measured peak temperatures between 620 °C and 863 °C. To address the question of why AlOx/SiNy stacks in contrast to pure SiNy layers for hydrogenation during firing provides better passivation quality, we have measured the hydrogen concentrations at the poly-Si/SiOx/c-Si interface as a function of AlOx layer thickness and compared these to J0 and calculated Dit,c-Si values. We observe an increase of the hydrogen concentration at the SiOx/c-Si interface upon firing as a function of the firing temperature that exceeds the defect concentrations at the interface several times. However, the AlOx layer thickness appears to cause an increase in hydrogen concentration at the SiOx/c-Si interface in these samples rather than exhibiting a hydrogen blocking property.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene

Abstract We present a way to dramatically accelerate Gaussian process models for interatomic force fields based on many-body kernels by mapping both forces and uncertainties onto functions of low-dimensional features. This allows for automated active learning of models combining near-quantum accuracy, built-in uncertainty, and constant cost of evaluation that is comparable to classical analytical models, capable of simulating millions of atoms. Using this approach, we perform large-scale molecular dynamics simulations of the stability of the stanene monolayer. We discover an unusual phase transformation mechanism of 2D stanene, where ripples lead to nucleation of bilayer defects, densification into a disordered multilayer structure, followed by formation of bulk liquid at high temperature or nucleation and growth of the 3D bcc crystal at low temperature. The presented method opens possibilities for rapid development of fast accurate uncertainty-aware models for simulating long-time large-scale dynamics of complex materials.

Chemistry↗
DOE OSTI2022

Visualization of defect induced in-gap states in monolayer MoS 2

Atomic-scale intrinsic defects play a key role in controlling functional electronic properties of two-dimensional (2D) materials. Here, we present a low-temperature scanning–tunneling microscopy and spectroscopy investigation of a common point-defect in monolayer molybdenum disulfide (MoS 2 ). We employ a sample preparation method in which the film surface is never exposed to air so that the native dangling bonds surrounding the defects in the film are preserved. Molybdenum vacancies are identified by their three characteristic in-gap resonances by combining scanning–tunneling measurements with parallel Green’s function-based theoretical modeling. The relative energy shifts between the various in-gap states allow us to identify a relative charge difference between two of the observed vacancies. The role of the substrate on the band structure of the defective MoS 2 monolayer is unveiled. Our study highlights the effects of the substrate on the in-gap states of common defects found in MoS 2 providing a pathway in designing and optimizing 2D materials for electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Defect-induced magnetism and Yu-Shiba-Rusinov states in twisted bilayer graphene

Atomic defects have a significant impact on the low-energy properties of graphene systems. By means of first-principles calculations and tight-binding models we provide evidence that chemical impurities modify both the normal and the superconducting states of twisted bilayer graphene. Here, a single hydrogen atom attached to the bilayer surface yields a triple-point crossing, whereas self-doping and threefold symmetry breaking are created by a vacant site. Both types of defects lead to time-reversal symmetry breaking and the creation of local magnetic moments. Hydrogen-induced magnetism is found to exist also at the doping levels where superconductivity appears in magic-angle graphene superlattices. As a result, the coexistence of superconducting order and defect-induced magnetism yields in-gap Yu-Shiba-Rusinov excitations in magic-angle twisted bilayer graphene.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scanning X-Ray Diffraction Microscopy for Diamond Quantum Sensing

An understanding of nano- and microscale crystal strain in chemical-vapor-deposition diamond is crucial to the advancement of diamond quantum technologies. In particular, the presence of such strain and its characterization presents a challenge to diamond-based quantum sensing and information applications-as well as for future dark-matter detectors, where the directional information about incoming particles is encoded in crystal strain. Here, we exploit nanofocused scanning x-ray diffraction microscopy to quantitatively measure crystal deformation from defects in diamond with high spatial and strain resolution. The combination of information from multiple Bragg angles allows stereoscopic three-dimensional modeling of strain-feature geometry; the diffraction results are validated via comparison to optical measurements of the strain tensor based on spin-state-dependent spectroscopy of ensembles of nitrogen-vacancy centers in the diamond. Finally, our results demonstrate both strain and spatial resolution sufficient for directional detection of dark matter via x-ray measurement of crystal strain and provide a promising tool for diamond growth analysis and improvement of defect-based sensing.

42 ENGINEERING↗
DOE OSTI2023

Formation of Amorphous Carbon Multi‐Walled Nanotubes from Random Initial Configurations

Amorphous carbon nanotubes (a‐CNT) with up to four walls and sizes ranging from 200 to 3200 atoms have been simulated, starting from initial random configurations and using the Gaussian Approximation Potential. The important variables (like density, height, and diameter) required to successfully simulate a‐CNTs were predicted with the machine learning random forest technique. The width of the a‐CNT models ranged between 0.55–2 nm with an average inter‐wall spacing of 0.31 nm. The topological defects in a‐CNTs were analyzed and new defect configurations were observed. The electronic density of states and localization in these phases were discussed and delocalized electrons in the π subspace were identified as an important factor for inter‐layer cohesion. Spatial projection of the electronic conductivity favors axial transport along connecting hexagons, while non‐hexagonal parts of the network either hinder or bifurcate the electronic transport. A vibrational density of states was calculated and is potentially an experimentally comparable fingerprint of the material. The appearance of a low‐frequency radial breathing mode was discussed and the thermal conductivity at 300 K was estimated using the Green‐Kubo formula.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

In Situ Micro-Pillar Compression to Examine Radiation-Induced Hardening Mechanisms of FeCrAl Alloys

Here, the effects of 5 MeV Fe 2+ ion irradiation at 300°C on the microstructure evolution and deformation behavior of a FeCrAl C26M alloy are presented. It has been found that dislocation loop density increases an order of magnitude from 1 dpa to 16 dpa irradiations, whereas, the dislocation loop size saturates with increasing damage. Micropillars, 600 nm in diameter and 1.3 µm in height, were fabricated and compressed inside grains with <001>, <011> and <111> crystallographic orientations, respectively. {112} <111> has been identified as the primary slip system in both unirradiated and irradiated alloy. The increase in yield stress after irradiation is observed with measurable variation along <001> and <011> vs. along <111>. By applying the Orowan dispersed barrier model, the increase of yield stress is found mainly due to the slip resistance of radiation generated defect loops. Detailed transmission electron microscopy (TEM) studies were performed to quantify the Burgers vector and the distribution of irradiation induced dislocations at elevated strains. It is revealed that localized shear instability is caused by avalanche slip events of ½<111> dislocations gliding out of tested pillars. Simultaneously, a large number of sessile/immobile <100> dislocations formed in the vicinity of slip band, leading to the hardening at elevated strains.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Revealing the effect of local stresses on twin growth mechanisms in titanium using synchrotron X-ray diffraction

Deformation twinning has a significant impact on the evolution of microstructure and mechanical response in hexagonal close packed (hcp) metals. Understanding the physical mechanisms associated with twin nucleation and growth processes is important to enable the broad use of hcp metals. While both nucleation and growth are conditioned by the local stress state, few studies have quantified it in bulk deformed samples. In this study, we reveal the effects of local stresses on twin thickening using in-situ synchrotron experiments with differential aperture X-ray microscopy. High purity Ti is deformed under four-point bending to activate {1012} tensile twins. Further, 3D stress fields with a spatial resolution of 0.5μm are mapped in the vicinity of low and high macroscopic Schmid factor (MSF) twins growing inside a grain. Reconciling this experimental analysis with recent twin growth models reveals that the growth of low MSF twins is limited by the nucleation of twin growth defects in the high-purity Ti sample. While growth-inducing defect nucleation may occur in many places on the interface of the high resolved shear stress (RSS)/MSF twin, the nucleation rate of twinning disconnections for the low MSF twin is high only at the end of the twin near a stress concentration. Once nucleated, these defects easily propagate into lower RSS regions of the grain resulting in twin growth. This work highlights the importance of stress concentrations not only for twin (embryo) nucleation, but also to the growth process of twins, particularly in low MSF twins.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Vacancies in graphene: an application of adiabatic quantum optimization

Quantum annealers have grown in complexity to the point that quantum computations involving a few thousand qubits are now possible. In this paper, with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits the ground state as well as the excited states found by the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. Furthermore, this approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical–chemical interest.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Detecting impurity-specific effects on structure and radiolytic hydrogen production in aluminum hydroxide

While radiolytic hydrogen (H 2 ) generation is an intrinsic property of aqueous and mineral radiolysis in nuclear waste systems, detection of the sub-ns events leading to H 2 generation is challenging. Interfacial processes involving key mineral phases in the sludge, e.g., gibbsite (α-Al(OH) 3 ), have been implicated, with impurities affecting the amount of H 2 generated. To understand why gibbsite synthesized from nitrate precursors produces less H 2 than gibbsite from chloride precursors, we paired 27 Al multiple quantum magic angle spinning (MQMAS) NMR spectroscopy to determine structural heterogeneity with transverse-field muon spin rotation (TF-μSR) to probe electron availability. MQMAS revealed greater structural disorder in the gibbsite synthesized with nitrate (NO 3 -gibbsite). Correspondingly, TF-μSR showed a larger diamagnetic fraction for NO 3 -gibbsite, indicating reduced persistence of μ + -electron bound states (muonium or other radicals) and thus fewer electrons available for reaction on the sub-ns timescale. This establishes a correlation between impurity-induced disorder and electron loss. The diamagnetic fraction serves as a signature for these sub-ns events, as it provides a key constraint for predictive models without currently resolving whether the electron is lost to direct chemical scavenging or trapping at lattice defects.

Graham, Trent R. [Pacific Northwest National Labor↗
DOE OSTI2022

Physics-based model of irradiation creep for ferritic materials under fusion energy operation conditions

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this paper, we develop a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. Here, we carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum with average recoil energies of 20 keV and a damage dose rate of ≈3×10 –7 dpa/s at temperatures between 300 and 800 K.

36 MATERIALS SCIENCE↗