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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

First-principles investigation of structure-property relationships in stable and metastable MXenes

Understanding the structure–property relationships in layered transition-metal carbides or nitrides, known as MXenes, is of critical importance for their rational design, synthesis, and application. However, the vast chemical and structural diversity of MXenes, stemming from their wide range of M and X elements, surface terminations, and different atomic coordination environments, makes it challenging to clearly understand these structure–property relationships. Here, in this work, we perform first-principles density functional theory (DFT) calculations and molecular dynamics (MD) simulations to comprehensively investigate the stability and a variety of physical properties of MXenes with different coordination environments. Using Ti- and Mo-based carbide MXenes as model systems, energetic calculations reveal that Ti-based MXenes are most stable in octahedral coordination, whereas Mo-based MXenes preferentially adopt prismatic coordination. This fundamental difference in preferred atomic coordination gives rise to markedly distinct properties between these two systems as a function of the fraction of octahedral and prismatic sites. For instance, the in-plane stiffness of Ti-based MXenes increases as octahedral coordination becomes dominant, but it decreases in the Mo-based MXenes under the same conditions. Additional stability analyses based on mechanical, lattice-dynamical, and temperature-dependent thermodynamic properties demonstrate that many metastable MXenes not only satisfy the strict stability criteria but can also undergo phase transitions among different structures and even become stabilized at elevated temperatures. Although surface terminations, such as F and O atoms, do not alter the energetic ordering or the overall stiffness trends among stable and metastable MXenes, they influence other material properties. For instance, O termination can induce semiconducting behavior in both stable and metastable Ti 2 ⁢CO 2 MXenes. This study significantly advances the fundamental understanding of structure–property relationships in MXenes and provides valuable guidance for developing coordination-based design principles to precisely engineer MXenes with improved properties.

Oyeniran, Noah [University of Alabama, Tuscaloosa,↗
DOE OSTI2023

Local structural investigation of non-crystalline materials at high pressure: the case of GeO 2 glass

Abstract Local structures play a crucial role in the structural polyamorphism and novel electronic properties of amorphous materials, but their accurate measurement at high pressure remains a formidable challenge. In this article, we use the local structure of network-forming GeO 2 glass as an example, to present our recent approaches and advances in high-energy x-ray diffraction, high-pressure x-ray absorption fine structure, and ab initio first-principles density functional theory calculations and simulations. Although GeO 2 glass is one of the best studied materials in the field of high pressure research due to its importance in glass theory and geophysical significance, there are still some long-standing puzzles, such as the existence of appreciable distinct fivefold [5] Ge coordination at low pressure and the sixfold-plus [6+] Ge coordination at ultrahigh pressure. Our work sheds light on the origin of pressure-induced polyamorphism of GeO 2 glass, and the [5] Ge polyhedral units may be the dominant species in the densification mechanism of network-forming glasses from tetrahedral to octahedral amorphous structures.

Physics↗
DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces

Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of querying the materials space is significant. Traditional BO methodologies typically utilize conventional Gaussian Processes (cGPs) to model the relationships between material inputs and properties, as well as correlations within the input space. However, cGP-BO approaches often fall short in multi-objective optimization scenarios, where they are unable to fully exploit correlations between distinct material properties. Leveraging these correlations can significantly enhance the discovery process, as information about one property can inform and improve predictions about others. Here, this study addresses this limitation by employing advanced kernel structures to capture and model multi-dimensional property correlations through multi-task (MTGPs) or deep Gaussian Processes (DGPs), thus accelerating the discovery process. We demonstrate the effectiveness of MTGP-BO and DGP-BO in rapidly and robustly solving complex materials design challenges that occur within the context of complex multi-objective optimization over FCC FeCrNiCoCu high entropy alloy (HEA) spaces, where traditional cGP-BO approaches fail. Furthermore, we highlight how the differential costs associated with querying various material properties can be strategically leveraged to make the materials discovery process more cost-efficient.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Irradiation-induced chemical disordering in ceramics: The case of SiC

Chemical disordering is one feature of damage that occurs in irradiation environments and is common in ceramic compounds. This paper reviews irradiation-induced chemical disordering in SiC-based materials at elevated temperatures. Here the results were obtained using advanced analytical tools to characterize atomistic defects and to evaluate the chemistry of defect clusters and homonuclear bond structures. Finally, this paper demonstrates that chemical disordering is crucial to understanding microstructural stability and establishing a mechanistic modeling of microstructural evolution of irradiated SiC.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Directed self-assembly of block copolymers for high-precision patterning in the era of extreme ultraviolet lithography

Extreme ultraviolet (EUV) lithography enables unprecedented resolution in semiconductor patterning but faces critical challenges in developing resist materials that achieve high-precision at economically viable throughput. Directed self-assembly (DSA) of block copolymers (BCPs) offers a promising solution for pattern rectification by leveraging thermodynamically determined domain structures to decouple BCP pattern quality from the imperfect original lithographic pattern. This prospective presents an overview of recent progress on the EUV + DSA strategy, covering advances in BCP material design, processing, metrology, and pattern transfer. We highlight recent advances in high-χ BCPs with perpendicular orientation and domain spacings compatible with EUV dimensions, leveraging A-b-(B-r-C) architectures. We also discuss progress in chemical pre-pattern fabrication using both positive- and negative tone resists, along with processing strategies to minimize defects and roughness based on BCP thermodynamics and assembly kinetics. We further examine metrology platforms for characterizing the thermodynamics of BCP materials and quantifying the size and shape of BCP domains. Lastly, we review pattern transfer strategies for generating functional inorganic masks suitable for semiconductor manufacturing. Together, these advances highlight the potential of DSA to complement EUV lithography, offering a pathway to address critical challenges in achieving high-precision patterning for the semiconductor industry.

Lee, Kyunghyeon [Univ. of Chicago, IL (United Stat↗
DOE OSTI2024

Ultrathin Microporous Transport Layers: Implications for Low Catalyst Loadings, Thin Membranes, and High Current Density Operation for Proton Exchange Membrane Electrolysis

Porous transport layers (PTL) and their surface properties have the potential to improve the performance of proton exchange membrane water electrolyzers (PEMWE), which is imperative to reduce feedstock costs and lead to their widespread implementation. This work introduces a novel generation of titanium microporous layers (MPLs) with ultra-low thicknesses of approx. 20 um which reduces raw material costs. They also feature advanced interfacial properties tailored to maximize catalyst utilization at low Ir-loadings. The bulk morphology and surface properties of the hierarchically structured PTLs are assessed by X-ray tomographic microscopy. The low surface roughness of the MPL allows the use of thinner membranes since it minimizes possible deformations in the membrane. Cells containing the MPLs outperformed those containing state-of-the-art commercially available PTL materials by up to 100 mV at 7 A cm-2 in combination with low-loaded catalyst-coated membranes of 0.4 mgIr cm-2. Hydrogen crossover is also reduced, especially at low current densities, leading to a larger turndown ratio which can enable more cost-effective operating strategies. Finally, these rationally designed MPLs also lead to high catalyst utilization by overcoming the naturally occurring high in-plane resistance of low-loaded catalyst layers.

hydrogen crossover↗
DOE OSTI2025

Flux Upcycling of Degraded Layered Cathodes to LiNi x Mn y Co z O 2 (NMCs) with Gradient Transition Metal Distribution

The rising demand for lithium-ion batteries (LIBs) has intensified the need for efficient recycling methods to address both supply chain constraints and environmental impacts. Direct upcycling, distinguished by its ability to achieve both the structural and compositional integrity of cathode materials, has gained prominence as a sustainable alternative to conventional pyrometallurgical and hydrometallurgical processes. However, the current direct upcycling methods are typically limited by incorporating Li and/or Ni, significantly constraining the adaptability across diverse LiNi x Mn y Co z O 2 (NMCs). Here, in this study, a versatile molten salt approach is reported that expands the scope of direct upcycling by enabling simultaneous incorporation of Li, Ni, and Mn. This methodology facilitates flexible conversion among diverse NMC compositions, including non-stoichiometric Co/Mn systems such as upcycling degraded LiCoO 2 (D-LCO), LiNi 1/3 Mn 1/3 Co 1/3 O 2 (D-NMC111), LiNi 0.8 Mn 0.1 Co 0.1 O 2 (D-NMC811) to surface Mn enriched NMC111, LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532), and NMC811, respectively. The gradient transition metal distribution in upcycled products, characterized by Mn-enriched outer layers and Co/Ni-enriched cores enhances the interfacial stability of NMC cathodes, addressing critical challenges in long-term performance and structural integrity. These results highlight the potential of flux methods for advancing the upcycling of spent cathodes and producing high-performance materials for next-generation LIBs applications.

lithium -ion batteries↗
DOE OSTI2022

NNSA Advanced Photon Source Sector Opportunities Workshop (Workshop Summary)

An NNSA-Argonne National Laboratory workshop to define NNSA and external partner mission needs and opportunities at the Advanced Photon Source was held February 15-17, 2022. This workshop summary provides a fresh look at NNSA’s evolving mission needs, partner agency and university interests, x-ray photon characteristics, and technical requirements to meet those needs. The workshop was organized according to four breakout groups: Coupling dynamic drivers to a synchrotron, High explosives and chemical sciences, Process-structure-performance: X-ray experiments to understand materials behaviors, and Process-structure-performance: manufacturing and aging. This summary report describes the workshop outcomes, and the preliminary conceptual design for a dedicated Defense Materials Science Sector (DMSS) at the Advanced Photon Source.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nanomechanics and Electronic Structure of Organic Photovoltaics in Real Application Conditions by Advanced Scanning Probe Microscopy (Final Technical Report for Project DE-SC0018041)

This project report consists of the following three sections: A.) Investigation of Charge Transport Properties in Semiconducting Conjugated Polymer Blends Using Computational Chemistry and Experiments: This section provides unpublished but valuable research results that correlate the electronic structure of PCBM:PCDTBT organic photovoltaic systems with their current-voltage characteristics. The presentation is structured in the form of a scientific publication. B.) Scanning Probe Microscopy Methodology Development Efforts for Organic Photovoltaic Materials: This section summarizes various published works focusing on advancements in scanning probe microscopy methods. Each sub-section corresponds to a scientific publication for which the abstract and citation are provided. C.) Other Publications Supported by the Project: This section lists additional published works partially supported by the project, which are not included in the previous two sections.

36 MATERIALS SCIENCE↗
DOE OSTI2023

One-dimensional alignment of defects in a flexible metal-organic framework

Crystalline materials are often considered to have rigid periodic lattices, while soft materials are associated with flexibility and nonperiodicity. The continuous evolution of metal-organic frameworks (MOFs) has erased the boundaries between these two distinct conceptions. Flexibility, disorder, and defects have been found to be abundant in MOF materials with imperfect crystallinity, and their intricate interplay is poorly understood because of the limited strategies for characterizing disordered structures. Here, we apply advanced nuclear magnetic resonance spectroscopy to elucidate the mesoscale structures in a defective MOF with a semicrystalline lattice. We show that engineered defects can tune the degree of lattice flexibility by combining both ordered and disordered compartments. The one-dimensional alignment of correlated defects is the key for the reversible topological transition. The unique matrix is featured with both rigid framework of nanoporosity and flexible linkage of high swellability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sensitivity Study of Multiscale and Phenomenological Elasto-Viscoplastic Grade 91 Material Models for Component-Scale Response

Many advanced nuclear reactor concepts currently being developed are targeting higher operating temperatures relative to the current fleet of light water nuclear reactors, for efficiency gains and other operational considerations. The design of high temperature structural components with reliable long-term operational performance will depend on material models that accurately capture the inelastic deformation mechanisms active in these environments. In this work, we perform a detailed parameter sensitivity analysis of two unified elasto-viscoplastic Grade 91 material models capable of capturing long term high temperature creep deformation. The first model is a phenomelogical material model from the Nuclear Engineering Material Library (NEML) developed at Argonne National Lab. The NEML model parameters and their uncertainty were fit to a range of Grade 91 experimental data using Bayesian Markov Chain Monte Carlo analysis. The second model is a LAROMance data-driven surrogate material model developed at Los Alamos National Lab. The LAROMance model is fit to a large database of responses produced by a mechanistic crystal plasticity based polycrystal model. Parameters for the LAROMance surrogate material model reflect the pedigree of the Grade 91 microstructure. Both material models have been integrated into the Grizzly code, based on the open-source MOOSE multiphysics simulation framework, to simulate both the progression of aging mechanisms and the effects of that aging on nuclear power plant structures. Grizzly is used analyze a three-dimensional Grade 91 piping system to compare the long-term inelastic response predicted by these two fundamentally different models and assess the sensitivity of the material model input parameters on this quantity of interest.

42 ENGINEERING↗
DOE OSTI2025

Singly occupied 4⁢𝑓 antiferromagnetic insulators: CePO 4 and CeVO 4

Rare-earth containing wide band gap oxides, which provide spin-photon interface and narrow linewidth optical emission, are getting significant attention as the most promising candidate materials in advancing quantum transduction and memories. Here, in this work, from ab initio calculations, we identify antiferromagnetic ground states in structurally preferred monoclinic CePO 4 and tetragonal CeVO 4 exhibiting localized occupied and unoccupied Ce 4⁢𝑓 states with 4⁢𝑓−4⁢𝑓 transition characteristics. Interestingly, in CePO 4 , O 2⁢𝑝 and P 3⁢𝑝 states hybridize negligibly with Ce 4⁢𝑓 states, while in CeVO 4 , V 3⁢𝑑 and O 2⁢𝑝 states hybridize and appear as extended states in between the occupied and unoccupied Ce 4⁢𝑓 states. Here, phonon calculations and analysis identify and differentiate Raman active phonon modes along with the spin phonon coupling of Ce in both CePO 4 and CeVO 4 that ultimately lead to different 4⁢𝑓 ground-state crystal-field multiplets, which are critical to accurately describe electronic transitions for foundational quantum transduction and memories. Further, the identified 𝐶 1 site symmetry of Ce, lacking inversion symmetry in CePO 4 , is relevant for quantum memories and 𝐷 2⁢𝑑 site symmetry of Ce exhibiting inversion symmetry in CeVO 4 is relevant for quantum transduction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Molecularly Functionalized Electrodes for Efficient Electrochemical Water Remediation

Here, the development and investigation of materials that leverage unique interfacial effects on electronic structure and redox chemistry are likely to play an outstanding role in advanced technologies for wastewater treatment. Here, the use of surface functionalization of metal oxides with a Ru(II)poly(pyridyl) complex was reported as a way to create hybrid assemblies with optimized electrochemical performance for water remediation, superior to those that could be achieved with the molecular catalyst or metal-oxide electrodes used individually. Mechanistic analysis demonstrated that the molecularly functionalized electrodes could suppress the formation of hydroxyl radicals (i. e., the dominant remediation pathway for bare metal-oxide electrodes), allowing the water remediation to proceed through the highly oxidizing Ru 3+ ions in the surface-bound complexes. Furthermore, the underlying metal-oxide substrates played a crucial role in altering the electronic structure and electrochemical properties of the surface-bound catalyst, such that the competing side reaction (i. e., water splitting) was largely inhibited.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Light-induced switchable adsorption in azobenzene- and stilbene-based porous materials

Despite the long history of porous materials as adsorbates, fundamental limitations remain regarding the efficient capture and release of the gas molecules, with the working capacity of the material often overlooked. In microporous materials, the uptake is dominated by low-pressure adsorption, with much of this being at pressures below the minimum working threshold for many gas utilization processes. Thus, research has focused on several advances in porous materials, including photoresponsive organic units for light-induced switchable adsorption. This process utilizes light to trigger structural or electronic changes, alter the gas uptake, and change the working capacity. Additionally, while a relatively recent development, there is a significant body of research regarding the use of light to control gas storage performance.

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

Upcycling of Polystyrene Waste to Poly(ionic liquid) Materials

The C–H functionalization of commodity polymers could be a promising approach for upcycling plastic waste into advanced materials, which can alter the properties of the original materials through the introduction of different functionalities onto the existing backbone structures. In this study, waste polystyrene (PS) was modified by Friedel–Crafts acylation using 4-chlorobutyryl chloride (4-CBC) followed by reaction with N-alkylimidazoles to form cationic polyelectrolytes. These methods provide access to what are essentially poly(ionic liquid) (poly(IL)) materials with properties that are distinctly different from those of the PS from which they were formed. In one notable example, the glass transition temperature (T g ) of imidazolium-functionalized PS was ∼16 °C, which is a nearly 90 °C reduction from PS. This is also evidenced by macroscopic mechanical properties where the poly(IL) product is highly elastic in stark contrast to brittle PS. Moreover, the resulting ionomers showed self-healing behaviors in the presence of a “free” IL further contributing to the utility of the materials. Here, the methods in this work can open opportunities to utilize waste PS to obtain a vast array of poly(IL) materials with highly tailored structures and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Intermediate-Term Thermal Aging Effect Evaluation for Grade 92 and 316L at The LWR Relevant Temperature

Life extension of the existing nuclear reactors imposes accumulated damages, such as higher fluences and longer period of corrosion, to structural materials, which would result in significant challenges to the traditional reactor materials such as type 304 and 316 stainless steels. Advanced alloys with superior radiation resistance will increase safety margins, design flexibility, and economics for not only the life extension of the existing fleet but also new builds with advanced reactor designs. The Electric Power Research Institute (EPRI) teamed up with Department of Energy (DOE) on the Advanced Radiation Resistant Materials (ARRM) program, aiming to develop and test degradation resistant alloys from current commercial alloy specifications by 2021 to a new advanced alloy with superior degradation resistance in light water reactor (LWR)-relevant environments by 2024. Based on a comprehensive microstructure and property screening performed in Phase-1 of the ARRM program, a total of five alloys, together with 316L and X-750 as references, were down-selected for Phase-2 neutron irradiation studies. Because thermal aging could exert a synergistic effect on neutron irradiation due to the low neutron damage rate on the order of 10 –7 displacements per atom per second (dpa/s), Grade 92 (one of the five down-selected alloys) and two heats of 316L were selected in this task to study the effect of aging at 350°C for 12.5–12.7 kh on microstructure and mechanical properties. The aging time is approximately corresponding to 5 dpa neutron irradiation, which can be served as a reference for the 5-dpa-irradiated samples of the alloys to help understand the independent neutron damage influence on microstructure and mechanical properties. Optical microscopy and scanning electron microscopy were used for microstructural characterization. Hardness, tensile, Charpy impact toughness, and fracture toughness in the ductile regime of the aged samples were examined. The aging of Grade 92 led to the formation of many Laves phase in sizes of ~100–200 nm and resulted in some reduction in hardness and yield/ultimate tensile strength with some increases in uniform and total plastic elongations, which may have helped the enhancement of Charpy impact toughness, e.g., ~4 J increase in upper-shelf energy and 20.5°C reduction in ductile-brittle transition temperature compared with the unaged condition. The fracture toughness of the aged Grade 92 showed decent toughness of ~303 MPa√m (K Jq ) with ~87 tearing modulus at 22°C, which reduced to ~241 MPa√m (~20% reduction) with ~75 tearing modulus at 300°C. The two heats of 316L are differentiated by their amounts of δ-ferrite, i.e., ~1 vol% in heat T1103 and ~4 vol% in heat N5B8. The two heats of 316L were subjected to 15% cold work (CW) as this condition is often used in nuclear reactors to help trapping radiation-induced defects and thus postpone the steady state swelling stage. The aging did not result in any noticeable microstructure changes, except for possible segregations at grain boundaries that need to be further investigated. The aging resulted in slight reduction in hardness of 316L-T1103 and slight increase in hardness of 316L-N5B8, which is consistent with their tensile testing results. The 15%CW might have introduced some inhomogeneity, resulting in large standard deviations in hardness, which were reduced after the aging. The aged 316L followed the same trend as the unaged condition for the strength and elongation results from the tensile testing. Minimum elongations appeared within ~300–600°C, above which the elongations seem to increase. Unlike the negligible or minor changes in microstructure, hardness and tensile results of the two heats of 316L, their fracture toughness showed noticeable difference. The aged 316L-T1103 showed good toughness of ~350 MPa√m with ~80 tearing modulus at 22°C, which reduced to ~271 MPa√m (~23% reduction) with ~83 tearing modulus at 300°C. In contrast, the aged 316L-N5B8 showed lower toughness of ~244 MPa√m with ~53 tearing modulus at 22°C, which reduced to ~180 MPa√m (~26% reduction) with ~31 tearing modulus at 300°C. The preliminary results indicate that the presence of high volume of δ-ferrite would noticeable impair fracture toughness although it may not influence hardness and tensile properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗