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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 19 records

Characterization of Long-term Service Coal Combustion Power Plant Extreme Environment Materials

The technical goal of this project is to develop a comprehensive database of mechanical properties, alloy microstructures, and to a lesser extent, the oxidation/corrosion behavior of coal-fired power plant components, such as boiler tubing, steam headers and steam piping, which have been in long-term service (at least 100,000 operating hours, and preferably more than 200,000 operating hours) under the operating conditions of high temperatures and high mechanical stresses where creep, fatigue, steam-side oxidation, and fireside corrosion are life-limiting factors. The components included in the database will include the following types of high temperature alloys: creep strength enhanced ferritic (CSEF) steels, 300-series H-grade stainless steels, and dissimilar metal welds (DMWs).

Characterization↗

Characterization of Long-Term Service Coal Combustion Power Plant Extreme Environment Materials

The objective of this DOE-sponsored project was to develop a comprehensive database of mechanical properties, alloy microstructures, and to a lesser extent, the oxidation/corrosion behaviors of coal-fired power plant components, such as boiler tubing, steam headers, and steam piping, which had been in service for at least 100,000 operating hours (preferably more than 200,000 operating hours) under the operating conditions of high temperatures and high mechanical stresses where creep, fatigue, steam-side oxidation, and fireside corrosion were life-limiting factors. The components included in this database consisted of ferritic steels, creep strength enhanced ferritic (CSEF) steels, and 300-series H-grade stainless steels, as well as dissimilar metal welds (DMWs) among these types of materials. As a result of extensive metallurgical characterization and mechanical testing performed in this project, a comprehensive database on mechanical properties and detailed quantitative microstructural information was successfully developed for several long-term serviced EEM components. Such a database can be used by material research communities to develop, calibrate, refine, and validate mechanical behaviors, models, and other assessment tools for accurate prediction of remaining life of major components under similar EEM operating conditions.

20 FOSSIL-FUELED POWER PLANTS↗

Characterization of advanced nuclear materials under extreme environments

The performance of materials under extreme environments poses important fundamental questions about the behavior of condensed matter under far-from-equilibrium conditions. These conditions create challenges in materials design, testing and evaluation. One important aspect of advancing nuclear power is the discovery and investigation of new classes of materials able to withstand the harsh environments in nuclear reactors. However, investigating and understanding the performance of these materials requires sophisticated tools and characterization techniques and skills. Furthermore, the goal of this special issue is to present recent research on the characterization of the response of candidate advanced nuclear materials to extreme environments.

36 MATERIALS SCIENCE↗

Will high-entropy carbides and borides be enabling materials for extreme environments?

Abstract The concept of multi-principal component has created promising opportunities for the development of novel high-entropy ceramics for extreme environments encountered in advanced turbine engines, nuclear reactors, and hypersonic vehicles, as it expands the compositional space of ceramic materials with tailored properties within a single-phase solid solution. The unique physical properties of some high-entropy carbides and borides, such as higher hardness, high-temperature strength, lower thermal conductivity, and improved irradiation resistance than the constitute ceramics, have been observed. These promising properties may be attributed to the compositional complexity, atomic-level disorder, lattice distortion, and other fundamental processes related to defect formation and phonon scattering. This manuscript serves as a critical review of the recent progress in high-entropy carbides and borides, focusing on synthesis and evaluations of their performance in extreme high-temperature, irradiation, and gaseous environments.

36 MATERIALS SCIENCE↗

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

artificial intelligence↗

Development of self-sensing materials for extreme environments based on metamaterial concept and additive manufacturing

Structural health monitoring of an engineered component in a harsh environment is critical for multiple DOE missions including nuclear fuel cycle, subsurface energy production/storage, and energy conversion. Supported by a seeding Laboratory Directed Research & Development (LDRD) project, we have explored a new concept for structural health monitoring by introducing a self-sensing capability into structural components. The concept is based on two recent technological advances: metamaterials and additive manufacturing. A self-sensing capability can be engineered by embedding a metastructure, for example, a sheet of electromagnetic resonators, either metallic or dielectric, into a material component. This embedment can now be realized using 3-D printing. The precise geometry of the embedded metastructure determines how the material interacts with an incident electromagnetic wave. Any change in the structure of the material (e.g., straining, degradation, etc.) would inevitably perturbate the embedded metastructures or metasurface array and therefore alter the electromagnetic response of the material, thus resulting in a frequency shift of a reflection spectrum that can be detected passively and remotely. This new sensing approach eliminates complicated environmental shielding, in-situ power supply, and wire routing that are generally required by the existing active-circuit-based sensors. The work documented in this report has preliminarily demonstrated the feasibility of the proposed concept. The work has established the needed simulation tools and experimental capabilities for future studies.

36 MATERIALS SCIENCE↗

Unmasking f -electron physics: Exploring novel phases of actinide materials using extreme environments [Slides]

There are a multitude of compounds to study. Actinide-based systems stand out as being especially attractive, because they have been shown to be a deep reservoir for exotic phenomena (e.g., heavy fermion behavior, unconventional superconductivity, unconventional magnetism, topological states) that originate from their 5f-electron states.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY↗

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Thermal-Mechanical Analysis of an Additive Manufacturing Ceramic Heat Exchanger for High-Temperature Recuperator in a sCO2 Power System

Supercritical CO2 (sCO2) Brayton power cycle can be configured in a closed-loop power system and has a potentially high cycle efficiency. Compactness and high efficiency of a sCO2 power block make the sCO2 Brayton cycle a versatile power cycle in broad applications. While many heat sources are of sufficient intensity to produce high temperature working fluids to achieve high cycle efficiency, the thermal-mechanical stability of traditional materials (e.g., steels and nickel-based superalloys) used in construction of heat exchangers and turbine components limits the operating conditions and thus thermodynamic efficiency of the system. This effort seeks to establish the viability of ceramic heat exchanger technologies for the most extreme operating conditions envisioned for power generation and other high temperature processes. Heat exchangers constructed from ultra-high temperature ceramics, a class of extreme environment materials featuring melting points (Tmp.) above 3000 degrees C, is particularly appealing for sCO2 Brayton cycles given their ultra-low creep rates and very high retained strength at low homologous temperatures (i.e., T < 0.5 Tmp., or at least 1500 degrees C). To translate these materials properties to ultra-high temperature heat exchangers, innovations are required in ceramic manufacturing techniques to realize the complex architectures featured in compact heat exchangers with high power density. With appropriate processing, ZrB2-SiC based compositions can be sintered to near full density and shaped into complex topologies via ceramic additive manufacturing methods. This paper analyzes heat exchanger designs and explores thermal-mechanical implications of the operating environment. Thermal flow, heat transfer, and conjugate mechanical analyses provide insights into benefits and risks associated with the design approach.

additive manufacturing↗

Materials Degradation in Extreme Environments: Novel In-situ Measurements of Cracking in Molten Salt

The safety and reliability of next-gen reactors, i.e. molten salt reactors (MSR), depends on materials performance and longevity in extreme environments, yet no in-situ, validated measurement techniques for environmentally assisted cracking (EAC), one potential degradation mechanism, exist for these conditions. This project combined the use of in-situ direct current potential drop (DCPD) crack growth rate determination applied to a horizontal load frame with high temperature fittings and novel sample geometries to enable evaluation in MSR environments and develop a full in-situ SCC measurement capability for extreme environments (high conductivity and elevated T), necessary to predict materials reliability. A successful demonstration of DCPD measurement in molten NaNO 3 /KNO 3 salts at 340 o C was accomplished and validated through post-test fractography imaging. This is the first ever public example, to the authors knowledge, of an in-situ crack growth rate measurement in a molten salt environment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Component level modeling of materials degradation for insights into operational flexibility of Existing Coal Power Plants

Increasingly, coal-fired power plants are required to balance power grids by compensating for the variable electricity supply from renewable energy sources. Fossil-fueled power plants, originally designed to be base loaded, will increasingly need to operate on a load following or cyclic basis. This demanding requirement for operational flexibility needs insights into accelerated material degradation arising due to the harsh operating conditions (e.g., fatigue, early oxide exfoliation due to stresses) along with current damage mechanisms (fireside corrosion, creep and erosion) observed in service. Our research objective is to develop component level modeling toolkit for materials-based degradation for two key mechanisms that can accelerate with cyclic operations. In more detail, this includes the fireside corrosion/steam oxidation/erosion/creep/fatigue of superheaters/reheaters and steam pipework and also the water droplet erosion/ fatigue of last stage steam turbine blades degradation mechanisms, that demand routine and sometimes unplanned maintenance and repair. The innovation is in developing a computational fluid dynamics/finite element (CFD/FE) modeling toolkit for the component level models of the boilers and low-pressure steam turbines in coal power plants that can tackle multidisciplinary failure mechanisms occurring concurrently for extreme environment materials. Lifetime assessment in such environments also needs to account for the unit-specific analyses, operational history and fuel feedstock; this can only be obtained by destructive analysis of components. This, in turn, enables validation of the model toolkits utilizing service feedback data, improving the probability of time/temperature dependent life prediction.

20 FOSSIL-FUELED POWER PLANTS↗

mystic : software for autonomous discovery and design under uncertainty

Throughout the diverse range of science and engineering applications, there is a growing desire to develop computational methods that can reliably predict the behavior of complex systems. Specifically, there is a strategic need for tools that can robustly forecast the behavior of complex physical systems, where data may be high-dimensional, noisy, or sparse, and models of the system may be time-dependent or include uncertainty. We use mystic to build tools that leverage statistical learning, physics-informed learning, and active learning in the efficient generation of reliably predictive surrogates for complex physical systems. mystic is a robust, proven, open-source optimization and uncertainty quantification toolkit with over a decade of use in the design and optimization of neutron instrumentation, solar-powered drones, and gasguns, and in iterative tuning of models for Raman spectroscopy and elastoplastic materials strength. Recent developments have focused on automated learning of statistically robust surrogates under uncertainty, with applications in materials in extreme environments, nanostructures, materials simulations and strength models, and the failure of shielding under particle radiation. In 2020, McKerns demonstrated active learning of optimally robust surrogates with respect to new simulated data for molecular dynamics simulations of materials mixing in warm dense matter, and is currently applying active learning to the automated steering of particle accelerator beams and the optimal design and control of quantum optical sensor instrumentation.

42 ENGINEERING↗

High Throughput Computational Framework of Materials Properties for Extreme Environments

This project aims to establish a framework capable of efficiently predicting the properties of structural materials for service in harsh environments over a wide range of temperatures and over long periods of time. The approach is to develop and integrate high throughput first-principles calculations in combination with machine learning (ML) methods, perform high throughput CALPHAD (calculations of phase diagrams) modeling, and carry out finite element method (FEM) simulations. Relevant to high temperature service in fossil power system, nickel-based superalloys such as Inconel 740 and Haynes 282 as well as the associated (Ni-Cr-Co)-Al-C-Fe-Mn-Mo-Nb-Si-Ti system, were investigated. The present framework was built on the concept of phase-based property data, in which properties of individual phases are modeled as a function of internal and external independent variables. This project established an open-source infrastructure with the following capabilities: (1) High throughput implementation of first-principles calculations at finite temperatures and variable compositions using both accurate phonon calculations and the efficient Debye model for thermodynamic properties, elastic constants, diffusion coefficients, vacancy formation, stacking and twin faults, and dislocation mobility; i.e., using the developed code DFTTK; (2) Machine learning capabilities to predict the above properties so that the number of first-principles calculations can be significantly reduced; e.g., using the developed code SIPFENN; (3) High throughput CALPHAD modeling of the above properties as a function of temperature and composition using our unique capability based on ESPEI and PyCalphad; (4) New capabilities to predict the stress-strain behavior of individual phases; and (5) New models for tensile strength prediction in common FEM software with the crystal plasticity finite element simulations (CPFEM).

, Ni-based superalloys↗

Materials properties characterization in the most extreme environments

Abstract There is an ever-increasing need for material systems to operate in the most extreme environments encountered in space exploration, energy production, and propulsion systems. To effectively design materials to reliably operate in extreme environments, we need an array of tools to both sustain lab-scale extreme conditions and then probe the materials properties across a variety of length and time scales. Within this article, we examine the state-of-the-art experimental systems for testing materials under extreme environments and highlight the limitations of these approaches. We focus on three areas: (1) extreme temperatures, (2) extreme mechanical testing, and (3) chemically hostile environments. Within these areas, we identify six opportunities for instrument and technique development that are poised to dramatically impact the further understanding and development of next-generation materials for extreme environments. Graphical abstract

Schreiber, Daniel K.↗