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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A New Residual Strain Mapping Program Using Energy Dispersive X-Ray Diffraction at the Advanced Photon Source

Here, the ability to non-destructively map the residual strain field inside an engineering component is important for predicting its fatigue life or developing processing methods to prevent failure or enhance performance. In this paper, we describe a new residual strain mapping program at the Advanced Photon Source, Argonne National Laboratory. The new program is based on energy dispersive x-ray diffraction (EDXRD). It is capable of non-destructively penetrating a several- cm thick polycrystalline sample fabricated from engineering alloys using high-energy x-rays and measuring the residual strain field with mm or better spatial resolution and approximately ±1 x 10 -4 strain resolution. A multi-element detector array is employed to measure multiple strain components simultaneously. The residual strain mapping setup is augmented with a high-energy tomography capability, allowing precise alignment of the material volume of interest for residual strain mapping and providing a complementary view of the structure to understand the measured strain field. These measurement capabilities are demonstrated using several strain mapping examples ranging from polycrystalline structural alloys to biological materials. We also provide some guidance for the future users of the program for a successful residual strain mapping experiment. We are expanding the capabilities of the new setup with various in situ capabilities including thermo-mechanical loading.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

CLARIFYING THE NEXUS BETWEEN LIFE CYCLE ASSESSMENT AND CIRCULARITY INDICATORS: A SETAC/ACLCA INTEREST GROUP

Purpose Improving the circularity of resources is important to the sustainability of consumer goods. Current research has indicated that circularity practices and circular economy (CE) methods do not always reduce environmental impacts. The aim of this research is to investigate the adoption of the life cycle assessment (LCA) methodology to improve the environmental impacts of circularity practices. Methods As part of the Society for Environmental Toxicology And Chemistry (SETAC) forum, an interest group (IG) on Circularity and LCA was formed in partnership with the American Center for Life Cycle Assessment (ACLCA) to tackle methodological and technical issues related to circularity in LCA. The IG’s research approach is summarized in four key steps: defining goals and objectives, literature review and gap analysis, ideation, and experimentation. The twelve active persons within this IG meet monthly and have been divided into four sub-working groups (sub-WGs) so that complementary tasks can be completed concurrently in an effective manner. Each sub-WG meets monthly and reports back to the main group for collaboration and brainstorming to meet the research objectives. Results and discussion First, the sub-WG #1, focusing on the “pool of circularity and LCA-based indicators”, analyzed the complementarity between two of the most used circularity indicators and LCA. Second, the sub-WG #2, working on the “evaluation of CE loops performance through LCA”, built a mind map of pain points that reflect the challenges that the LCA practitioners face when combining LCA with CE approaches. Third, the sub-WG #3, dealing with the “trade-offs between circularity and sustainability”, highlighted key alignments and/or conflicts between circularity and sustainability performance depending on the scope, product, industry, or system of analysis. Fourth, the sub-WG #4, focusing on “business and industrial cases”, plans to leverage the knowledge base developed within this IG to develop use cases documenting the benefits and challenges associated with CE-related loops modeling in LCA. Conclusions The first findings of this SETAC/ACLCA IG provide a state-of-the-art overview of the synergists of LCA methodology and the CE measurement frameworks reported in the literature. To move forward and capitalize on the first findings, one valuable point will be to discuss and provide concrete solutions to the pain points that emerged when considering circularity in LCA. Eventually, the knowledge base and resources created within this IG ultimately aim to support the proper application of LCA for practitioners in CE contexts, and could provide relevant inputs for the ISO Technical Committee ISO/TC 323 working on the upcoming standard for the measurement of CE performance.

Life cycle assessment, circular economy, circulari↗
DOE OSTI2021

Constraining self-interacting dark matter with the full dataset of PandaX-II

Self-interacting dark matter (SIDM) is a leading candidate proposed to solve discrepancies between predictions of the prevailing cold dark matter theory and observations of galaxies. Many SIDM models predict the existence of a light force carrier that mediates strong dark matter self-interactions. If the mediator couples to the standard model particles, it could produce characteristic signals in dark matter direct detection experiments. We report searches for signals of SIDM models with a light mediator using the full dataset of the PandaX-II experiment, basing on a total exposure of 132 tonne-days. No significant excess over background is found, and our likelihood analysis leads to a strong upper limit on the dark matter-nucleon coupling strength. We further combine the PandaX-II constraints and those from observations of the light element abundances in the early universe, and show that direct detection and cosmological probes can provide complementary constraints on dark matter models with a light mediator.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Revealing the Subsurface Basal $\langle$a$\rangle$ Dislocation Activity in Magnesium Through Lattice Rotation Analysis

A method was proposed in this study to reveal the subsurface basal dislocation activity in Mg-Y alloy and determine the corresponding Burgers vector. This is achieved by correlating the slip directions of dislocations to the lattice rotation represented by the {0001} pole figure. The identified basal slip system by this approach was verified by micro-Laue diffraction. This method can be applied as a complementary method to the conventional slip trace analysis to study the dislocation behavior of Mg alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

In-Situ Synchrotron X-Ray Diffraction of Ultrasonic Microstructural Refinement During Solidification in a Commercial Al–Si–Mg Alloy

This study reports the first use of in-situ synchrotron X-ray diffraction (SXRD) to study the effects of ultrasonic melt processing (USMP) on phase and grain size evolution during solidification in a commercial Al–Si–Mg casting alloy. USMP is a technique that, when applied to aluminum as it solidifies, can be used to refine the local microstructure of large-scale castings. Analysis of the in-situ SXRD data to estimate the average grain size of primary α-Al grains during USMP demonstrates that USMP slows the growth rate of α-Al grains and reduces grain size by 36 pct. Furthermore, there is also evidence that USMP causes the primary α-Al grains to move relative to the X-ray beam; such motion increases the probability of primary α-Al grains colliding and fragmenting. This movement becomes constrained at the onset of the Al–Si binary eutectic, suggesting that USMP ceases to effectively refine the microstructure once the Al–Si binary eutectic begins to form. Complementary laboratory-scale X-ray diffraction (XRD) data were used to correlate the lattice parameters of the α-Al and Si (D-A4) phases with temperature to estimate cooling rate during solidification. Thus, this study can guide the design of novel castings with spatially distributed fine-grained regions produced using local ultrasonic processing.

Aluminum Alloys↗
DOE OSTI2021

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Advances in Multimodal Characterization of Structural Materials

The myriad detectors and instruments now available for materials characterization provide researchers with an ever-growing suite of tools to probe material behavior. Progress in the development of instrumentation and workflows that enable the collection, and leverage the potential, of various data modalities have provided novel insights into material behavior. Using data across multiple length scales, or performing complementary analyses of in situ and ex situ data, can help reveal a more complete picture of dynamic processes or material structure. However, the accurate combination, or fusion, of these disparate data modalities presents new challenges. Differences in resolution, as well as the varying length scales at which physical phenomena are exploited to generate these data, necessitate novel approaches to accurately interpret and combine these data. Furthermore, the papers within this special topic focus on the collection and fusion of multimodal data to better understand structural materials. From new frameworks and workflows for data segmentation and analysis, process monitoring, enhancing simulations, or interrogating mechanical response, these papers reveal the potential benefits of utilizing multimodal data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The In Situ Ion Irradiation Toolbox: Time-Resolved Structure and Property Measurements

Abstract The dynamic interactions of ions with matter drive a host of complex evolution mechanisms, requiring monitoring on short spatial and temporal scales to gain a full picture of a material response. Understanding the evolution of materials under ion irradiation and displacement damage is vital for many fields, including semiconductor processing, nuclear reactors, and space systems. Despite materials in service having a dynamic response to radiation damage, typical characterization is performed post-irradiation, washing out all information from transient processes. Characterizing active processes in situ during irradiation allows the mechanisms at play during the dynamic ion-material interaction process to be deciphered. In this review, we examine the in situ characterization techniques utilized for examining material structure, composition, and property evolution under ion irradiation. Covering analyses of microstructure, surface composition, and material properties, this work offers a perspective on the recent advances in methods for in situ monitoring of materials under ion irradiation, including a future outlook examining the role of complementary and combined characterization techniques in understanding dynamic materials evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Toward Discord : Code for Simulating Continuous Spin Systems

A new computational tool to simulate classical spin systems with frustrated crystal structures is presented. Complementary single- and cluster-spin flip algorithms are implemented to calculate the diffuse scattering patterns, spin-pair correlations, and thermodynamic quantities. Test cases of geometrically frustrated kagome, pyrochlore, and cubic systems are detailed. Two recent scientific cases are also shown here. This new method, together with recent developments of the rmc-discord package (https://github.com/zjmorgan/rmc-discord), represent integrated and strategic step in a complete forward and reverse Monte Carlo framework discord.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deformation Mechanism Transition in Additively Manufactured Compositionally Graded Fe-Base Alloys

Microstructure-dependent deformation and fracture behavior was investigated for an additively manufactured compositionally graded alloy (CGA) printed using the laser-directed energy deposition (L-DED) method to explore an alternative approach for dissimilar metal joints in nuclear energy systems. The electron backscatter diffraction (EBSD) maps from scanning electron microscopy (SEM) display a clear microstructural transition with decreasing austenite-forming elements (Ni and Mn), from an austenite (γ) dominant structure, to a complex composite structure containing ferrite (α), martensite (α') and retained austenite, and then to a fully ferritic structure. EBSD data were recorded in situ during tensile testing in SEM, and the evolution of the deformation mechanism and microstructure was characterized using Kikuchi diffraction pattern analysis. Complementary analysis for high-resolution features was also performed using scanning transmission electron microscopy (STEM). The Ni/Mn-rich austenite-dominant microstructures showed a complex deformation mechanism of two-step martensitic transformation (γ→ε→α'), whereas the minor austenite phase retained in the ferrite and/or martensite matrix showed a single transformation route (γ→α'). Ordinary dislocation glide and twinning via partial dislocation glide were observed in the austenite deformation. Meanwhile, the ferrite and martensite grains deformed mainly by ordinary dislocation slips and grain rotation. Furthermore, static tensile fracture was also highly dependent on local composition and phase constituents.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Defect Thermodynamics and Transport Properties of Proton Conducting Oxide BaZr 1–x Y x O 3–δ (x ≤ 0.1) Guided by Density Functional Theory Modeling

Density functional theory-based thermodynamic modeling was performed to determine the effect of humidity and H 2 /O 2 gas pressure on the defect chemistry and transport properties of proton conducting oxide BaZr 1-x Y x O 3-δ (x ≤ 0.1) in the temperature range of 800–1200K, relevant for solid oxide fuel/electrolysis cell applications. The first-principles charge defect analysis was carried out to obtain the defect energetic ensembles as a function of Fermi level as well as the dependence of the hydration and oxidation reaction energies on complex defect-dopant configurations. It is shown that oxygen vacancies introduced to compensate for the extra Ba vacancies may cause a slight increase in the concentration of hydroxyl and proton species upon hydration of Ba deficient BaZr 1-x Y x O 3-δ , while the overall proton diffusivity is predicted to decrease with increased proton hopping barriers upon trapping near the Ba vacancies. The developed defect model is further demonstrated to be able to describe the bulk defect chemistry and transport properties of BaZr 0.9 Y 0.1 O 3-δ under the solid oxide cell operating conditions. Finally, the theoretical framework developed in this work further allows the inclusion of configurational, energetic and electronic characteristics of the defects that can be used as a complementary tool to experimental measurements for testing various mechanistic pathways or to provide essential mechanistic data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future

Abstract As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) “Resolution Revolution” made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.

Burley, Stephen K. (ORCID:0000000224879713)↗
DOE OSTI2025

Text Mining for Process–Structure–Properties Relationships in Metals

With the advent of large language models (LLMs), the vast unstructured text within millions of academic papers is increasingly accessible for materials discovery—although significant challenges remain. While LLMs offer promising few- and zero-shot learning capabilities, particularly valuable in the materials domain where expert annotations are scarce, general-purpose LLMs often fail to address key materials-specific queries without further adaptation. To bridge this gap, fine-tuning LLMs on human-labeled data is essential for effective structured knowledge extraction (Liu in The Importance of Human-Labeled Data in the Era of LLMs, 2023). Here, in this study, we introduce a novel annotation schema designed to extract generic process–structure–properties relationships from scientific literature. We demonstrate the utility of this approach using a dataset of 128 abstracts, with annotations drawn from two distinct domains: high-temperature materials (Domain I) and uncertainty quantification in simulating materials microstructure (Domain II). Initially, we developed a conditional random field (CRF) model based on MatBERT—a domain-specific BERT variant—and evaluated its performance on Domain I. Subsequently, we compared this model with a fine-tuned LLM (GPT-4o from OpenAI) under identical conditions. Our results indicate that fine-tuning LLMs can significantly improve entity extraction performance over the BERT-CRF baseline on Domain I. However, when additional examples from Domain II were incorporated, the performance of the BERT-CRF model became comparable to that of the GPT-4o model. These findings underscore the potential of our schema for structured knowledge extraction and highlight the complementary strengths of both modeling approaches.

Materials science↗
DOE OSTI2022

Integration of Large-Scale Electrical Imaging into Geological Framework Development and Refinement

Geologic framework models (GFMs) are critical to the construction of reliable simulation models of groundwater flow and contaminant transport. To support GFM development, direct information (e.g., core samples, fluid samples, hydraulic testing) tends to be sparse and separated by large distances relative to the spatial scales of aquifer heterogeneity. There are additional challenges associated with highly contaminated legacy waste sites, where drilling is particularly costly, and invasive sampling requires specialized handling and disposal of hazardous materials. At these sites in particular, non-invasive geophysical imaging can play an important role in filling spatial gaps between boreholes and reducing characterization costs by optimizing and minimizing the number of necessary boreholes. Here this paper presents a case study demonstrating the use of large-scale (> 30 km 2 ) electrical mapping to identify hydrostratigraphy and potential paleochannels at the Hanford Site, located in Washington State, USA. In two field campaigns, over 36 line-kilometers of electrical resistivity tomography (ERT) data were collected along 14 transects. ERT surveys were sited and performed to image critical aspects (e.g., paleochannels, stratigraphic contacts) of the subsurface, demonstrating a general workflow for integrating ERT with GFM development. Inconsistencies between the GFM and ERT were catalogued to provide a basis for future site characterization using complementary geophysical methods and (or) direct sampling.

58 GEOSCIENCES↗
DOE OSTI2026

Quantifying atmospheric carbon removal at pulp and paper mills: a life cycle assessment across system boundaries

The pulp and paper industry is a promising yet underexplored platform for large-scale carbon dioxide removal (CDR) due to its use of biogenic feedstocks and production of concentrated CO 2 emissions from point sources. This study presents the first comprehensive life cycle assessment (LCA) of retrofitting an amine-based carbon capture and storage (CCS) system into a representative virgin kraft pulp and paper mill in the Southeastern U.S. We evaluate carbon removal across five system configurations, applying both static and dynamic LCA methods under multiple functional units: CO 2 captured, biomass input, and paper output. Results show that CCS retrofits can convert a conventional mill from a net emitter into a net carbon sink, with total removal efficiencies from 17% to 92% (metric tonnes of CO 2 removed per metric tonne of CO 2 available for removal under selected boundary conditions). When carbon removal is normalized to the quantity of biogenic CO 2 captured—a narrow, gate-to-gate system boundary that considers only CCS facility emissions—removal efficiencies reached as high as 92%. The use of such narrow boundaries aligns with precedents in traditional LCA methodology, where gate-to-gate assessments are commonly applied to isolate process-level performance and allocate emissions accordingly, providing a consistent basis for comparison across technologies. Under broader cradle-to-grave boundaries—which begin tracking carbon at the point of its physical removal from the atmosphere via photosynthesis in the forest, and extend to include upstream forest operations, mill-wide emissions, and downstream product decomposition—efficiencies declined, ranging from 17% to 46% under static assumptions and dropping to 12% when accounting for dynamic biogenic carbon fluxes over time. These results underscore how system boundary definitions influence reported outcomes, while also illustrating the complementary roles of narrow and broad perspectives for different decision-making contexts.

09 BIOMASS FUELS↗
DOE OSTI2025

Leveraging operator learning to accelerate convergence of the preconditioned conjugate gradient method

We propose a new deflation strategy to accelerate the convergence of the preconditioned conjugate gradient (PCG) method for solving parametric large-scale linear systems of equations. Unlike traditional deflation techniques that rely on eigenvector approximations or recycled Krylov subspaces, we generate the deflation subspaces using operator learning, specifically the Deep Operator Network (DeepONet). To this aim, we introduce two complementary approaches for assembling the deflation operators. The first approach approximates near-null space vectors of the discrete PDE operator using the basis functions learned by the DeepONet. The second approach directly leverages solutions predicted by the DeepONet. To further enhance convergence, we also propose several strategies for prescribing the sparsity pattern of the deflation operator. Here, a comprehensive set of numerical experiments encompassing steady-state, time-dependent, scalar, and vector-valued problems posed on both structured and unstructured geometries is presented and demonstrates the effectiveness of the proposed DeepONet-based deflated PCG method, as well as its generalization across a wide range of model parameters and problem resolutions.

Deflation↗
DOE OSTI2021

Applications of Strain-Coupled Magnetoelectric Composites

This article deals with research, development and future directions of magnetoelectric composites for practical devices applications. In the past 20 years there has been a surge of research in the area of multiferroics (MF) and magnetoelectrics (ME) due to their potential to replace existing technologies based only on ferroelectric or ferromagnetic materials. Some of the magnetoelectric composites show exceptionally high potential in the area of magnetic field sensors, however, work remains before commercialization can be realized. The cross coupling among various ferroic parameters in magnetoelectric composites is several orders higher than single phase magetoelectrics, which make its favorable for low detection (nT or pT) magnetic field sensors. Advances in both layered structures or controlled three-dimensional matrix composites for applications as magnetoelectric nonvolatile memory elements are both required. Robust cross-coupling among various parameters with more than four logic states and its compatibility with complementary-symmetry metal–oxide–semiconductor (CMOS) technology are the main requirements for heterostructure magnetoelectric thin films. The major hurdles in the area of magnetoelectric nonvolatile memory elements are poor interfacial properties and weak magnetoelectric coupling for high density fast read and write processes. Another potential area is strained coupled magneto-electric composites where magnetostriction mediated dimensional change in the magnetic layer effectively modulate the change in the dimension of piezoelectric layers via piezostriction, which leads to a strong ME coupling where their coupling magnitude is sufficient for magnetic field sensors. Energy harvesters based on magnetoelectric composites are also intriguing concepts to capture various types of waste energy, in the form mechanical vibration, pressure, wind energy, hydrothermal and waste temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advances in arene alkylation and alkenylation catalyzed by transition metal complexes based on ruthenium, nickel, palladium, platinum, rhodium and iridium

Over the past several years, significant advancements have been made for transition metal catalyzed arene alkylation and alkenylation that operate by metal mediated arene C–H activation. These catalytic processes provide a route for arene alkylation and alkenylation that is complementary to traditional acid catalyzed reactions (e.g., Friedel-Crafts reactions and zeolite-based arene alkylations). Catalysts from Groups 8, 9 and 10 have dominated new developments. As a result, this monograph will overview advancements for catalytic arene alkylation and alkenylation for hydrocarbon substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗