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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In-Situ and Ex-Situ Studies on the Morphology Changes of Polymer Pipeline Materials for Use in Hydrogen Gas Environments

The US natural gas infrastructure is a national asset that could be used to deliver hydrogen and hydrogen blends of natural gas as a pathway to reduce carbon emissions. The distribution system comprises nearly 50% plastic pipe composed of medium- and high-density polyethylene materials (MDPE and HDPE). While these materials perform adequately for natural gas, research on their hydrogen compatibility is essential to understand if any immediate and long-term risks are associated with hydrogen addition. The Blended Gas CRADA, a HyBlend project, has established a comprehensive test method for evaluating MDPE and HDPE of various plastic resin compositions of pipeline material in pure hydrogen and 20% hydrogen/80% methane blends. Both in-situ and ex-situ measurements were performed to capture hydrogen-induced changes in the polyethylene material's crystalline, amorphous and their interphase regions. We investigated MDPE and HDPE pipeline materials made from different polymer resin systems to evaluate the effects of hydrogen gas. The materials were characterized by their density, diffusion coefficient, free volume ratio, and degree of crystallinity. Various advanced characterization methods, including in situ NMR, ex situ XRD, ex situ DSC, and ex situ TDA, were used to analyze the effects of changes in crystalline, amorphous, and interphase regions due to gas exposure. Time-dependent post-decompression quasi-static tensile tests were conducted to explore the effects of gas exposure time on the mechanical behavior of the pipe materials. This work will highlight the time sensitivities during and after gas exposure. The correlation between gas-induced polyethylene morphology changes and the associated material performance will be addressed for the intended applications. These studies will show that polyethylene resin composition and material exposure are important factors when considering whether hydrogen gas affects pipeline materials positively or negatively.

Simmons, Kevin L.↗
DOE OSTI2024

Evaluating Optical Techniques to Characterize Solid State Samples for the Pu-238 Supply Program

This report documents steps that have been taken to establish advanced characterization capabilities for solid-state samples to support the 238 Pu Supply Program. The program has already invested significantly in spectroscopy and online monitoring development for liquid processes. Many of the data, analytical methods, and equipment could also be leveraged for the analysis of Np/Pu oxides and Np pellets to help classify material properties and link them to operations. The techniques described in this work include diffuse reflectance spectroscopy (DRS), Raman spectroscopy, and laser-induced breakdown spectroscopy (LIBS). Each technique is sensitive to various chemical and/or elemental species and can provide complimentary information to more standard methods such as powder x-ray diffraction and scanning electron microscopy. These options are remotely deployable via fiber-optic cables. DRS and Raman spectroscopy are already approved for glove box and hot cell work, but LIBS requires US Department of Energy approval for incorporation. Raman spectroscopy does require laser shielding, which means that DRS is the easiest method to implement. However, each technique provides complimentary data, and the most robust sample characterization could be achieved when all three, among other methods, are harnessed together. This report documents some of the progress made testing these capabilities, some of the challenges, and next steps to optimize the technology and integration strategies.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Advanced Data Science Model for Detecting Intelligent Malware

This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.

42 ENGINEERING↗
DOE OSTI2022

Innovative Method for Welding in Generation 3 CSP to Enable Reliable Manufacturing of Solar Receivers to withstand Daily Cycling at Temperatures Above 700°C (Final Technical Report)

Inconel® Alloy 740H® (alloy 740H) was the first age-hardenable nickel-based alloy approved by the ASME Boiler & Pressure Vessel Code for use in pressure-boundary applications. Over the past ~20 years the alloy has been optimized for weldability and high-temperature stability, approved for use in different applications. Development of a supply chain combined with the advantageous properties of the alloy (high-temperature creep strength, oxidation and corrosion resistance, etc.) have resulted in the alloy being applied to new high-temperature power cycle demonstration projects, and of particular interest are applications to concentrating solar power (CSP) to enable higher-efficiency Generation 3 CSP systems and the corresponding supercritical CO 2 (sCO 2 ) power cycle components (heat exchangers, piping, etc.). The high allowable stresses of alloy 740H also make it a desirable material for current Generation 2 CSP solar power receivers to improve cyclic capability and/or reduce receiver height. Recent experiences in demonstration projects utilizing alloy 740H identified cracking issues during welding and fabrication. In this project, a detailed study was done to confirm and clarify the Stress Relaxation Cracking (SRxC) mechanism, also known as stress relief cracking or strain-age cracking (SAC), during post-weld heat-treatment (PWHT). This involved detailed microscopy and advanced characterization to understand the root cause(s) of three failures obtained from industry. Based in-part on these findings, a targeted laboratory based SRxC test method was utilized to evaluate variables such as heat-to-heat variations, strain level, PWHT temperature, and starting material condition on three heats of alloy 740H. Industrial shop welding of cold-worked plates was also conducted. The research showed the following: SRxC was confirmed as the cracking mechanism for all field failures; Stress state (from residual stresses, constraint, deformation, and local stress concentrations) was playing a significant role in field failures and laboratory testing confirmed increasing susceptibility for all heats with increasing strain levels. High levels of microstructural strain were identified at crack initiation locations, in some cases leading to local recrystallization; Precipitate free zones (PFZs) at grain boundaries were found at relaxation cracks and crack initiation locations uniquely associated with SRxC in alloy 740H. Laboratory testing reproduced this microstructural feature which had only previously been reported in long-term creep testing of weldments. Advanced nano-scale characterization confirmed the presence of a moving boundary leading to coarsening of precipitates and PFZs where damage accumulated; The research suggested heat-to-heat variations due to local chemistry and processing may influence SRxC susceptibility, but more work is needed to fully clarify these effects. To disseminate the key learnings from this research to the scientific and engineering communities and alloy 740H end users, multiple technical publications and presentations were made, an industrial alloy 740H users meeting was held, and a new industry guideline specification document which can be directly implemented by end-users of alloy 740H was produced.

14 SOLAR ENERGY↗
DOE OSTI2024

Multi-Modal Characterization of Interfacial Corrosion of Ni-based Alloys in Chloride-based Molten Salts

The United States Department of Energy (DOE) is committed to the advancement of nuclear reactor technology through initiatives such as the Advanced Reactor Development Program (ARDP), to diversify the United States energy portfolio towards more sustainable energy options. The ARDP includes demonstration by industry partners of molten salt fast reactors (MSRs). Construction of molten salt reactor technology requires qualified nuclear structural materials. Unfortunately, there are no current materials that meet current qualification requirements dictated by the Nuclear Regulatory Commission for construction of MSRs. Adapting current structural material qualifications requires expansion of our current knowledgebase on corrosion performance. In this investigation, we assess microstructural changes in a Ni-based superalloy after exposure to a chloride-containing salt system through a correlated multi-modal approach combining several advanced characterization techniques. Namely we will highlight the impact of grain boundary phenomena at the onset of corrosion attack, including the role of intergranular crack propagation and development of internal corrosion products. The findings from this investigation will further expand our assessment of the corrosion performance of structural materials being investigated for construction of MSR components.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Inorganometallic Catalyst Design Center (ICDC) EFRC Accomplishments

The ICDC focused largely on heterogeneous catalysis of oxidative chemical transformations, especially those that came to prominence as natural gas (wet shale gas) supplanted crude oil as the primary feedstock in North America for carbon-based manufacturing of commodity chemicals. Driven by fracking-enabled access to enormous stores of shale-trapped wet gas, the feedstock change from oil to gas enabled a shift away from high-temperature catalytic breakdown of large hydrocarbons to catalytic build-up of C4, C3, C2, and C1 into desired intermediates, but now at much more modest temperatures. In turn, the much lower thermal force accompanying these kinds of reactions facilitates catalyst stabilization and characterization, including operando characterization, while slowing on-stream catalyst evolution (i.e., preserving catalyst structure), accommodating catalyst complexity, and enabling creation of uniform arrays of heterogeneous catalysts with single-atom or near-single-atom precision—at least for model systems. Together these features have proven to be a boon to hypothesis-driven catalysis science and to experimentally testable computation-based design advances and mechanism explication. The ICDC has greatly facilitated the integration of catalyst synthesis, advanced characterization, performance assessment, and computational elucidation—with advances in each of these realms spurring achievements in catalysis science and complementary realms.

03 NATURAL GAS↗
DOE OSTI2023

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineering Innovations, Challenges, and Opportunities for Lignocellulosic Biorefineries: Leveraging Biobased Polymer Production

Alternative polymer feedstocks are highly desirable to address environmental, social, and security concerns associated with petrochemical-based materials. Lignocellulosic biomass (LCB) has emerged as one critical feedstock in this regard because it is an abundant and ubiquitous renewable resource. LCB can be deconstructed to generate valuable fuels, chemicals, and small molecules/oligomers that are amenable to modification and polymerization. However, the diversity of LCB complicates the evaluation of biorefinery concepts in areas including process scale-up, production outputs, plant economics, and life-cycle management. We discuss aspects of current LCB biorefinery research with a focus on the major process stages, including feedstock selection, fractionation/deconstruction, and characterization, along with product purification, functionalization, and polymerization to manufacture valuable macromolecular materials. We highlight opportunities to valorize underutilized and complex feedstocks, leverage advanced characterization techniques to predict and manage biorefinery outputs, and increase the fraction of biomass converted into valuable products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Rational design of heterogeneous single-site catalysts via surface organometallic chemistry

Single-site heterogeneous catalysts offer an attractive route to unite the molecular precision of homogeneous catalysis with the durability and practical advantages of solids. Surface organometallic chemistry (SOMC) provides a particularly powerful strategy for this purpose by grafting molecular precursors onto tailored surfaces and converting support functionalities into ligand environments for isolated metal centers. As a result, SOMC brings the language and logic of coordination chemistry to heterogeneous catalysis, where the support becomes an integral part of the active site coordination sphere. This Review surveys recent progress in the rational design of SOMC-derived single-site catalysts, with emphasis on synthetic routes, post synthetic transformations, and the deliberate tuning of catalytic behavior through metal-support interactions. Discussions are made on how support identity, hydroxyl topology, acidity, and redox activity shape the geometry, electronic structure, and oxidation state of supported metal sites, as well as how these factors determine activity, selectivity, and stability. We also examine a central limitation of these systems: despite their molecularly informed design, supported single sites often exist as structurally distributed ensembles rather than uniform species, particularly on amorphous supports. This site heterogeneity, along with catalyst dynamics under operating conditions, remains a major barrier to definitive structure-activity relationships. Therefore, emerging approaches that combine advanced characterization, first-principles modeling, ensemble kinetics, and machine learning to resolve active-site structure and guide catalyst development are highlighted. Together, these advances position SOMC as a versatile coordination chemistry framework for the predictive design of heterogeneous catalysts with well-defined molecularly tailored active sites.

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

Revolutionizing Waste Management: AI-Powered Real-Time Characterization for Efficient Handling of Non-Recyclable Municipal Solid Waste

According to EPA, -300 MM tons of municipal solid waste (MSW) was available in the US as of 2018. Of that total material, nearly 50% was landfilled resulting in a significant loss for the potential to convert its energy value into cost effective and sustainable biofuels. Redirecting this material away from the landfill and into conversion ready feedstock for energy generation can directly address DOE's selling price < $2.50/GGE while securing the US national energy independence [1]. However, the paramount challenges in any rational fuel conversion strategy are understanding the chemical makeup, quality and associated calorific value of the MSW. Understanding these parameters is critical in achieving any acceptable fuel conversion and requires rapid characterization followed by accurate separation technologies. Therefore, we are proposing to address the rapid characterization by building a non-invasive, rapid, and highly accurate Artificial Intelligence (AI)-enabled spectrometric/optical approach augmented with multi-sensory information for advanced characterization of domestic heterogeneous MSW. North Carolina State University (NCSU) and the National Renewable Energy Laboratory (NREL), in partnership with strong support from the Town of Cary and IBM, Inc., will closely work together to implement this ground-breaking technology for the effective characterization of MSW for sustainable and affordable production of conversion-ready feedstocks, while solving the environment issue of planetary proportions.

artificial intelligence↗
DOE OSTI2021

Key Learnings from Hydraulic Fracturing Test Site - 2 (HFTS-2), Delaware Basin

Hydraulic fractures (HF) play a dominant role in oil and gas production from unconventional reservoirs, fracture characteristics, geometry, and extent are generally not well known and are typically inferred from various monitoring methods or subsurface models. The Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp formation of the Permian (Delaware) Basin. HFTS-2, a unique joint industry program (JIP) that brings together government, academia, and industry, focused on field data acquisition and interpretation. The project has built a comprehensive HF research dataset that includes microseismic (MS), 1,500 ft of core, diagnostic formation injection tests (DFIT), fluid characterization, advanced logs, geochemistry, downhole gauges, varying completions, and permanent fiber optic (FO) cable in vertical and horizontal wells. These data were integrated and used to characterize HF geometry/dimensions and resulting depletion profiles, gain insights for completion design, and achieve a better understanding of parent well depletion effects on child well performance. The analysis and integration of the comprehensive HFTS-2 diagnostics dataset provide insights for optimal well placement and completions and improves understanding about the effects of parent well depletion. Furthermore, this dataset can be used to blind test and develop subsurface workflows for unconventional resources. Key learnings from HFTS-2 and the new technologies tested can easily be transferred to other unconventional plays.

58 GEOSCIENCES↗
DOE OSTI2023

Report on initial development of a database of nuclear graphite characteristics based on microstructural characterization

This report outlines the current and future efforts to produce a comprehensive library of microstructures of nuclear graphite and carbon-based materials that are candidate materials for nuclear applications in the United States. This library must contain extensive characterizations of unirradiated graphite materials, a guide to some of the techniques used to characterize graphite, a compendium of characterization data of neutron-irradiated or oxidized material, and a compendium of microstructural information of carbon-based materials. These characterization efforts are being conducted at various length scales to understand these complex materials’ local structure and property relationships. Achieving this goal requires further developing or adapting advanced characterization techniques that capture graphite’s most relevant characteristics. Some of the general objectives of this project are to aid with the material selection, licensing, management, and core assessments of a graphite core by documenting the unirradiated microstructure of relevant grades or by characterizing the evolution of the microstructure under the reactor environment. Moreover, this project aims to provide additional information, guidelines for characterizing graphite, and a protocol to assess a nuclear graphite grade. This report also summarizes some of the initial results and some of the techniques commonly used to characterize nuclear graphite.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Power Electronics and Electric Machines

The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.

advanced gate drivers↗
DOE OSTI2023

Multi-Scale Characterization of Porosity and Cracks in Silicon Carbide Cladding after Transient Reactor Test Facility Irradiation

Silicon carbide (SiC) ceramic matrix composite (CMC) cladding is currently being pursued as one of the leading candidates for accident-tolerant fuel (ATF) cladding for light water reactor applications. The morphology of fabrication defects, including the size and shape of voids, is one of the key challenges that impacts cladding performance and guarantees reactor safety. Therefore, quantification of defects’ size, location, distribution, and leak paths is critical to determining SiC CMC in-core performance. This research aims to provide quantitative insight into the defect’s distribution under multi-scale characterization at different length scales before and after different Transient Reactor Test Facility (TREAT) irradiation tests. A non-destructive multi-scale evaluation of irradiated SiC will help to assess critical microstructural defects from production and/or experimental testing to better understand and predict overall cladding performance. X-ray computed tomography (XCT), a non-destructive, data-rich characterization technique, is combined with lower length scale electronic microscopic characterization, which provides microscale morphology and structural characterization. This paper discusses a fully automatic workflow to detect and analyze SiC-SiC defects using image processing techniques on 3D X-ray images. Following the XCT data analysis, advanced characterizations from focused ion beam (FIB) and transmission electron microscopy (TEM) were conducted to verify the findings from the XCT data, especially quantitative results from local nano-scale TEM 3D tomography data, which were utilized to complement the 3D XCT results. In this work, three SiC samples (two irradiated and one unirradiated) provided by General Atomics are investigated. The irradiated samples were irradiated in a way that was expected to induce cracking, and indeed, the automated workflow developed in this work was able to successfully identify and characterize the defects formation in the irradiated samples while detecting no observed cracking in the unirradiated sample. These results demonstrate the value of automated XCT tools to better understand the damage and damage propagation in SiC-SiC structures for nuclear applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Advanced Power Electronics and Electric Machines

NLR's advanced power electronics and electric machines (APEEM) research group develops world-class experimental and modeling capabilities to design and evaluate efficient and reliable power electronics and electric machines, as well as innovative thermal management systems to maximize their performance. They also design, fabricate, and characterize advanced power electronics packaging and are developing state-of-health monitoring techniques.

25 ENERGY STORAGE↗
DOE OSTI2025

X‐Ray Absorption Studies of Local Structure of Dilute Ionic Species in Molten Salts

Molten salts are crucial materials with exceptional properties that make them suitable for applications such as heat transfer media, coolants, and liquid fuels in molten salt nuclear reactors and the concentrated solar power industry. Understanding their properties requires unraveling the intricate mysteries of their structure. To achieve this, advanced characterization tools are essential. Among various techniques, X‐ray absorption fine structure (XAFS) stands out as a versatile method capable of studying the structure of molten salts under in situ conditions. This review highlights recent advancements in the application of XAFS for investigating the local structure of molten salts, discusses its limitations and potential improvements, and explores complementary approaches such as simulations, machine learning, and correlative experimental methods.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Recent Progress in Solid‐State Lithium Batteries through Cathode Microstructure Engineering

A high‐performance cathode is necessary to realize the great potentials of solid‐state batteries such as high energy density and long cycle life. It is also needed to validate electrolyte performance, which is lacking. Currently, cathodes for solid‐state batteries are thinner and have lower cathode active material content than their lithium‐ion battery counterpart, resulting from insufficient conductivity and limiting the battery energy density. This review article provides an overview of recent development in cathode microstructures and their impact on battery properties, including compatibility between cathode and electrolyte, cathode architecture design, interface engineering, correlation between material properties, cathode processing approaches, and performance, as well as the advanced characterization methods used to understand the above correlations . Some perspectives on future development are shared including utilizing in situ and operando characterization tools to better understand dynamic evolution of the cathode/electrolyte interface, adapting artificial intelligence and machine learning to design and optimize cathode structures. The article is aimed to promote research interest on cathode development and advance solid‐state battery technologies.

cathode engineering↗
DOE OSTI2025

Cross-scale modeling and experimental integration for advancing cathode electrolyte interphase studies in high energy density lithium-ion batteries

Electrochemical interfaces are critical to the performance and durability of lithium-ion batteries (LIBs). The solid electrode-electrolyte interphase (SEI and CEI) structures that form during cycling can passivate reactive surfaces, ensuring safe operation, but also may contribute to performance degradation. Understanding the microscopic factors influencing interphase formation, growth, and evolution is essential for balanced battery design. While significant research has focused on the anode-electrolyte interphase (SEI), the cathode-electrolyte interphase (CEI) remains less explored, despite its importance in high-voltage and advanced battery technologies. Challenges in conducting in-situ or operando experiments arise from the occluded nature of these interfaces and the long timescales involved, often leading to biased interpretations. A validated multi-scale, multi-physics modeling approach, integrated with advanced characterization techniques, can effectively elucidate the intrinsic stability of electrolyte and cathode surfaces, the impact of chemical heterogeneity, and the role of microstructural features on CEI performance. In conclusion, this article reviews current modeling and simulation strategies for studying CEI in advanced LIBs and highlights opportunities for future methodological advancements and experimental integration.

Cathode-electrolyte interphase↗