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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2d materials↗
DOE OSTI2024

2024 roadmap on magnetic microscopy techniques and their applications in materials science

Considering the growing interest in magnetic materials for unconventional computing, data storage, and sensor applications, there is active research not only on material synthesis but also characterisation of their properties. In addition to structural and integral magnetic characterisations, imaging of magnetisation patterns, current distributions and magnetic fields at nano- and microscale is of major importance to understand the material responses and qualify them for specific applications. In this roadmap, we aim to cover a broad portfolio of techniques to perform nano- and microscale magnetic imaging using superconducting quantum interference devices, spin centre and Hall effect magnetometries, scanning probe microscopies, x-ray- and electron-based methods as well as magnetooptics and nanoscale magnetic resonance imaging. The roadmap is aimed as a single access point of information for experts in the field as well as the young generation of students outlining prospects of the development of magnetic imaging technologies for the upcoming decade with a focus on physics, materials science, and chemistry of planar, three-dimensional and geometrically curved objects of different material classes including two-dimensional materials, complex oxides, semi-metals, multiferroics, skyrmions, antiferromagnets, frustrated magnets, magnetic molecules/nanoparticles, ionic conductors, superconductors, spintronic and spinorbitronic materials.

2D materials↗
DOE OSTI2025

Additive manufacturing of metal matrix composites

Although Metal matrix composites (MMCs) are superior to most sought-after metallic alloys, their challenging fabricability has limited their widespread use in bulk-form applications. Among the many advanced fabrication techniques, Additive Manufacturing (AM), owing to its unique capabilities to produce near-net shapes, has drawn significant traction in the past two decades, especially for materials that are difficult to process using traditional methods. However, unlike pure metal/alloy systems, MMCs are highly sensitive to the processing conditions prevailing in AM techniques due to factors such as the high melting point of reinforcement particles and the potential for in-situ reactions. Therefore, it may be a while before metal matrix composites are commercially produced via AM. This review will discuss the current state-of-the-art design, fabricability, and performance of various additively manufactured MMCs. A particular focus will be on microstructural evolution and microstructure-property relationships. The most employed AM techniques, such as directed energy deposition, powder bed fusion, binder jetting, sheet lamination, and solid-state friction stir processing, are fundamentally different in terms of thermo-kinetics, forming the perspective for this review. A detailed comparison of microstructural evolution and process parameter optimization, including feedstock preparation methods and the role of machine learning and modeling among the different AM processes, is also presented. Finally, a critical evaluation of emerging AM technologies for MMCs is also provided, highlighting their potential advantages and challenges.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2021

Computational design of quantum defects in two-dimensional materials

We report missing atoms or atom substitutions (point defects) in crystal lattices in two-dimensional (2D) materials are potential hosts for emerging quantum technologies, such as single-photon emitters and spin quantum bits (qubits). First-principles-guided design of quantum defects in 2D materials is paving the way for rational spin qubit discovery. Here we discuss the frontier of first-principles theory development and the challenges in predicting the critical physical properties of point defects in 2D materials for quantum information technology, in particular for optoelectronic and spin-optotronic properties. Strong many-body interactions at reduced dimensionality require advanced electronic structure methods beyond mean-field theory. The great challenges for developing theoretical methods that are appropriate for strongly correlated defect states, as well as general approaches for predicting spin relaxation and the decoherence time of spin defects, are yet to be addressed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

The role of pre-existing heterogeneities in materials under shock and spall

There has been a challenge for many decades to understand how heterogeneities influence the behavior of materials under shock loading, eventually leading to spall formation and failure. Experimental, analytical, and computational techniques have matured to the point where systematic studies of materials with complex microstructures under shock loading and the associated failure mechanisms are feasible. This is enabled by more accurate diagnostics as well as characterization methods. As interest in complex materials grows, understanding and predicting the role of heterogeneities in determining the dynamic behavior becomes crucial. Early computational studies, hydrocodes, in particular, historically preclude any irregularities in the form of defects and impurities in the material microstructure for the sake of simplification and to retain the hydrodynamic conservation equations. Contemporary computational methods, notably molecular dynamics simulations, can overcome this limitation by incorporating inhomogeneities albeit at a much lower length and time scale. This review discusses literature that has focused on investigating the role of various imperfections in the shock and spall behavior, emphasizing mainly heterogeneities such as second-phase particles, inclusions, and voids under both shock compression and release. Pre-existing defects are found in most engineering materials, ranging from thermodynamically necessary vacancies, to interstitial and dislocation, to microstructural features such as inclusions, second phase particles, voids, grain boundaries, and triple junctions. This literature review explores the interaction of these heterogeneities under shock loading during compression and release. Systematic characterization of material heterogeneities before and after shock loading, along with direct measurements of Hugoniot elastic limit and spall strength, allows for more generalized theories to be formulated. Further, continuous improvement toward time-resolved, in situ experimental data strengthens the ability to elucidate upon results gathered from simulations and analytical models, thus improving the overall ability to understand and predict how materials behave under dynamic loading.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Uncertainty quantification in multivariable regression for material property prediction with Bayesian neural networks

With the increased use of data-driven approaches and machine learning-based methods in material science, the importance of reliable uncertainty quantification (UQ) of the predicted variables for informed decision-making cannot be overstated. UQ in material property prediction poses unique challenges, including multi-scale and multi-physics nature of materials, intricate interactions between numerous factors, limited availability of large curated datasets, etc. In this work, we introduce a physics-informed Bayesian Neural Networks (BNNs) approach for UQ, which integrates knowledge from governing laws in materials to guide the models toward physically consistent predictions. To evaluate the approach, we present case studies for predicting the creep rupture life of steel alloys. Experimental validation with three datasets of creep tests demonstrates that this method produces point predictions and uncertainty estimations that are competitive or exceed the performance of conventional UQ methods such as Gaussian Process Regression. Additionally, we evaluate the suitability of employing UQ in an active learning scenario and report competitive performance. The most promising framework for creep life prediction is BNNs based on Markov Chain Monte Carlo approximation of the posterior distribution of network parameters, as it provided more reliable results in comparison to BNNs based on variational inference approximation or related NNs with probabilistic outputs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multi–length scale characterization of point defects in thermally oxidized, proton irradiated iron oxides

A key for the success of safe nuclear power generation system is to consider structural materials that are economical, meet mechanical property needs, possess good corrosion resistance, and are radiation tolerant. Nevertheless, fundamental insights that elucidate the details of radiation damage on materials corrosion performance are lacking. This includes the behavior of surface oxides which often regulate corrosion. For example, it is unclear how non-equilibrium point defects, oxide structure, mass transport in oxides, and subsequent oxidation behavior are altered by the radiation. Here, in this work, some of the effects of proton irradiation on the attributes of point defects, iron oxide microstructures, and the physical nature of the oxidation product were correlated with corrosion behavior. Iron oxides, fabricated by thermal oxidation in air at 400°C and 800°C for 1 h, were subjected to 200 keV, 0.03 dpa (displacements per atom) of proton irradiation, and subjected to corrosion reactivity assessment using AC and DC electrochemical methods. Experimental methods that target materials information at different length scales, such as positron annihilation spectroscopy (atomistic), transmission electron microscopy (mesoscopic), and electrochemical methods (macroscopic), were coupled to shed light on the impact of radiation-induced defect modifications and structural changes in oxides on corrosion reactivity which ultimately affects durability in harsh environments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The role of electron correlations in the electronic structure of putative Chern magnet TbMn6Sn6

Abstract A member of the RMn 6 Sn 6 rare-earth family materials, TbMn 6 Sn 6 , recently showed experimental signatures of the realization of a quantum-limit Chern magnet. In this work, we use quantum Monte Carlo (QMC) and density functional theory with Hubbard U (DFT + U ) calculations to examine the electronic structure of TbMn 6 Sn 6 . To do so, we optimize accurate, correlation-consistent pseudopotentials for Tb and Sn using coupled-cluster and configuration–interaction (CI) methods. We find that DFT + U and single-reference QMC calculations suffer from the same overestimation of the magnetic moments as meta-GGA and hybrid density functional approximations. Our findings point to the need for improved orbitals/wavefunctions for this class of materials, such as natural orbitals from CI, or for the inclusion of multi-reference effects that capture the static correlations for an accurate prediction of magnetic properties. DFT + U with Mn magnetic moments adjusted to the experiment predict the Dirac crossing in bulk to be close to the Fermi level, within ~120 meV, in agreement with the experiments. Our non-stoichiometric slab calculations show that the Dirac crossing approaches even closer to the Fermi level, suggesting the possible realization of Chern magnetism in this limit.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The oxygen stable isotope composition of CRM 125-A UO 2 standard reference material

While there is a clear need for standardized reference materials for analytical calibrations and for inter-laboratory comparisons, there are not currently any for the oxygen stable isotopic composition of uranium oxides. In this paper we summarize the results from four laboratories by seven different methods of oxygen stable isotope analyses using fluorination techniques of CRM 125-A UO 2 Standard Reference Material. We synthesize these data and methods to arrive at a consensus oxygen stable isotope composition for CRM 125-A $δ$ 18 O = -9.63‰ (±0.29‰) VSMOW. We discuss methodological differences between analytical approaches, including furnace vs laser heating, fluorination using BrF 5 or ClF 3 , as well as calibration strategies. We highlight the potential effects of calibration scale compression from single-point calibrations using reference material with $δ$ 18 O values having a large relative difference from the sample being analyzed. We demonstrate how calibration scale compression can yield differences in calibrated $δ$ 18 O values up to ~2‰ for samples with ~20‰ difference from a single reference material, if the calibration slope of different analytical systems differs by 0.1. In conclusion, we suggest the use of liquid water calibration standards sealed in silver capillary tubes for multi-point calibrations of fluorination analysis systems.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Grain boundary enhanced UN and U3Si2 pellets with improved oxidation resistance

A method of forming a water resistant boundary on a fissile material for use in a water cooled nuclear reactor is described. The method comprises mixing a powdered fissile material selected from the group consisting of UN and U 3 Si 2 with an additive selected from oxidation resistant materials having a melting or softening point lower than the sintering temperature of the fissile material, pressing the mixed fissile and additive materials into a pellet, sintering the pellet to a temperature greater than the melting point of the additive. Alternatively, if the melting point of the oxidation resistant particles is greater than the sintering temperature of UN or U 3 Si 2 , then the oxidation resistant particles can have a particle size distribution less than that of the UN or U 3 Si 2 .

Lahoda, Edward J.↗
DOE OSTI2023

Accelerating self-consistent field iterations in Kohn-Sham density functional theory using a low-rank approximation of the dielectric matrix

We present an efficient preconditioning technique for accelerating the fixed-point iteration in real-space Kohn-Sham density functional theory (DFT) calculations. The preconditioner uses a low-rank approximation of the dielectric matrix (LRDM) based on Gâteaux derivatives of the residual of fixed-point iteration along appropriately chosen direction functions. We develop a computationally efficient method to evaluate these Gâteaux derivatives in conjunction with the Chebyshev filtered subspace iteration procedure, an approach widely used in large-scale Kohn-Sham DFT calculations. Further, we propose a variant of LRDM preconditioner based on adaptive accumulation of low-rank approximations from previous self-consistent field iterations, and also extend the LRDM preconditioner to spin-polarized Kohn-Sham DFT calculations. We demonstrate the robustness and efficiency of the LRDM preconditioner against other widely used preconditioners on a range of benchmark systems with sizes ranging from ~100 to 1100 atoms (~500–20,000 electrons). The benchmark systems include various combinations of metal-insulating-semiconducting heterogeneous material systems, nanoparticles with localized d orbitals near the Fermi energy, nanofilm with metal dopants, and magnetic systems. In all benchmark systems, the LRDM preconditioner converges robustly within 20–30 iterations. In contrast, other widely used preconditioners show slow convergence in many cases, as well as divergence of the fixed-point iteration in some cases. Lastly, we demonstrate the computational efficiency afforded by the LRDM method, with up to 3.4-fold reduction in computational cost for the total ground-state calculation compared to other preconditioners.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Experimental Fabrication of Porous Additive Manufactured Material

Nuclear industries can benefit from materials that can perform well mechanically and thermally in high temperature and corrosion environments. Functionally graded materials (FGM) are materials manufactured with complex spatial, structural, and chemical compositions, creating components predesigned with tailored microstructural and mechanical properties. Porosity-graded FGMs are designed to introduce pores into a component’s structure as a mechanism to increase bulk or surface material performance, such as stress accommodation and negative thermal conductivity. Additive manufacturing (AM) techniques such as laser energy net shape (LENS) and wire arc additive manufacturing (WAAM), excel in high energy density, point-to-point metal deposition, and present in combination with other combinatorial approaches, exciting methods to manufacture porous FGM components. This project is also examining plasma jet printing as another means for method evaluations for smaller scale graded components. This study explores AM FGM process parameters and combinatorial fabrication methodologies for stainless steel components functionally graded in porosity levels. Preliminary characterization results are provided to attest the feasibility of the combinational fabrication techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Metal forming and working of stabilized nanocrystalline Cu-Ta for electrical contacts

The commercialization of nanocrystalline metals and alloys is currently entering a renaissance period. Many of the processing and consolidation challenges that have haunted them are now more fully understood, opening the doors for stabilized nanocrystalline metals to be produced on a bulk scale. While challenges remain, the increased volume at which these materials are being supplied is for the first time allowing for investigations into more traditional methods of metal working, such as extruding, rolling, forming, and forging. Recently, the manufacturing science has been developed to allow nanocrystalline Cu-Ta alloys to progress to this point. This article therefore builds upon the last decade of evolutionary progression within the family of stabilized nanocrystalline Cu-Ta alloys by presenting some of the first findings related to scaled powder synthesis, production of billets, thin sheets, and foils. Here, the mechanical performance and physical properties relevant to forming electrical contacts and pins including, tensile, J-integral fracture toughness, Charpy Impact, bi-axial tension, and conductivity are reported. This introductory investigation into forming such a novel material, provides evidence to these alloys potential at bridging the gap between being a scientific curiosity to that of a real engineering material.

36 MATERIALS SCIENCE↗
DOE OSTI2025

BACKFLIP: A Comparison of Market-Benchmark Backsheet Technologies to Novel Non-Fluoro-Based Coextruded Materials and Their Correlation and Impact on PV Module Degradation Rates: Final Results of the Study at 4000 Hours or 2 Years

As the photovoltaic (PV) industry is rapidly expanding around the world, there has been an increasing interest in extending the lifespan of PV modules. Concern has also emerged regarding the recyclability of modules and their component materials, including fluoropolymer-based backsheets. Laminated polyethylene-terephthalate (PET) core backsheets have traditionally been used in the PV industry, but new, co-extruded polyolefin (PO) backsheets show promise as an improved alternative. Mini-module and coupon samples of seven different backsheets (made of layers including contemporary PET and fluoropolymers, novel PO, and polyamide (PA) materials) were run through hygrometric- or UV photolytic-accelerated aging to identify and better understand each material's degradation modes and the backsheets' field reliability. In addition to the artificial aging, the natural weathering methods used in this study are described. The comprehensive set of chemical, mechanical, and structural characterizations at intermittent read points in this study is presented, including: visual appearance and color; gloss; mechanical tensile testing; I-V performance; electroluminescence (EL) imaging; dielectric breakdown; FTIR-chemical structure; X-ray-polymer structure (WAXS); and DSC-crystalline content. After 4000 h of accelerated aging or 2y of outdoor aging, a strong correlation occurs between initial physical characteristics (mechanical tensile test) and operating performance (EL and I-V characteristics).

14 SOLAR ENERGY↗
DOE OSTI2021

Elastic Wave Propagation in Curvilinear Coordinates with Mesh Refinement Interfaces by a Fourth Order Finite Difference Method

In this work, we develop a fourth order accurate finite difference method for the three dimensional elastic wave equation in isotropic media with the piecewise smooth material property. In our model, the material property can be discontinuous at curved interfaces. The governing equations are discretized in second order form on curvilinear meshes by using a fourth order finite difference operator satisfying a summation-by-parts property. The method is energy stable and high order accurate. The highlight is that mesh sizes can be chosen according to the velocity structure of the material so that computational efficiency is improved. At the mesh refinement interfaces with hanging nodes, physical interface conditions are imposed by using ghost points and interpolation. With a fourth order predictor-corrector time integrator, the fully discrete scheme is energy conserving. Numerical experiments are presented to verify the fourth order convergence rate and the energy conserving property.

58 GEOSCIENCES↗
DOE OSTI2021

Design Optimization for Printed Melt Wire Arrays Encapsulation

As part of the Nuclear Energy Enabling Technology (NEET) Advanced Sensor and Instrumentation (ASI) Program, Idaho National Laboratory (INL) has recently established in-house capabilities to fabricate and test new advanced-manufactured sensors for measuring peak irradiation temperature within a nuclear test reactor. Although methods of real-time temperature monitoring, such as thermocouples, may be used, the complexity of feedthroughs and attachments to collect real-time measurements greatly increases the cost of the experiment. Instead, passive monitoring techniques may be used for peak- temperature measurement that exploit the melting point of well-characterized materials (standard melt wires) to infer peak reactor temperatures. However, limited available space for instrumentation during experiments introduces an additional challenge. To accommodate this, INL has expanded its temperature- detection instrumentation capabilities to include advanced manufactured (AM) melt wires for peak irradiation temperature measurements. These melt wires can determine peak temperatures while also accommodate space limitations in irradiation experiments. In an effort to improve performance reliability of AM meltwire capabilities, a process was developed and tested to identify the significance of entrapping a high purity inert atmosphere within the packaging of printed melt wire arrays. The materials used in this study were aluminum, zinc, and tin encapsulated in high purity helium within a stainless steel (SS) 316 container. Tin, with a low melting point of approximately 230°C, Zn with a mid-melting point of approximately 420°C, and Al with a high melting point of approximately 660°C. This report describes the design, fabrication process, furnace testing and X-ray Computed Tomography (XCT) evaluation. Results show a successful outcome in creating an inert gas encapsulation and high-resolution evaluation methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

High efficiency, high-current laser-driven electron injector (CRADA Final Report)

Owing to ultra-high fields sustainable in a plasma, laser-plasma accelerator technology enables compact, high-brightness, sources of electron beams. This work investigates novel electron injection methods. Key to this research is to understand laser energy and pointing stability and to develop methods and techniques to control fluctuations. This project benefits other areas of scientific inquiry by developing a high-repetition rate, high-brightness electron source for probing materials and ultra-fast processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗