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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Robotics for Systems Integration in Buildings - Pilot Study of Viable Approaches to Install Hygrothermal and Rigid Electrical Systems: Preprint

The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been exploring the use of robotics to integrate hygrothermal, mechanical, electrical, and plumbing systems in prefabricated building assemblies (offsite construction) and 3D Printed buildings (onsite construction). Such multi-system integration tasks often require specialized robots and custom end-effectors for handling a range of rigid and non-rigid building components. This paper begins with a brief overview of the current state of robotics in construction, followed by a pilot study exploring the use of robotics to integrate a simple prototype multi-trade wall assembly composed of structural studs, hygrothermal layer, wall finishing, and electrical fixtures. The study was funded by the Department of Energy's (DOE) Advanced Materials and Manufacturing Technologies Office (AMMTO). Insights about the implementation of design for manufacturing and assembly (DfMA) principles in designing the prototype wall for robotic assembly, and selection of appropriate robotic end effector hardware for handling these components are included. Detailed comparison of computational toolpath simulations of the robotic assembly process and real-life demonstration of the same is presented. Finally, limitations and lessons learned from this study along with future research recommendations for robotic assembly of more complex multi-trade assemblies, including potential scenarios such as robotic outfitting of facilities in extra-terrestrial environments is included.

advanced manufacturing↗
DOE OSTI2025

Additively Manufactured Pressure Limiting Irradiation Capsule for the High Flux Isotope Reactor

The Advanced Materials and Manufacturing Technologies (AMMT) program previously demonstrated an additively manufactured (AM) irradiation capsule (commonly referred to as a “rabbit”) from 316H stainless steel (SS) for insertion into the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL)1. This report details efforts to design and fabricate an AM pressure limiting structure (PLS) into one of the end caps of a rabbit capsule and qualify it for insertion into HFIR. The PLS includes a thin cylindrical rupture wall, a shield, and internal supports to facilitate printing and ensure mechanical integrity. Its overall dimensions are 9-mm tall and 10-mm in diameter— equivalent to about one-fourth of the size of a AAA battery. The PLS maintains safe internal operating pressures for a rabbit capsule while in the reactor. Although this application is specific to HFIR, the approach lends itself to further applications in industrial, aeronautical, advanced space and power generation environments. Several PLS rabbits capsules have been successfully designed, fabricated, pressure tested, and qualified for future insertion into the HFIR for irradiation and post-irradiation evaluation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Multimorphic Materials: Spatially Tailoring Mechanical Properties via Selective Initiation of Interpenetrating Polymer Networks

Access to multimaterial polymers with spatially localized properties and robust interfaces is anticipated to enable new capabilities in soft robotics, such as smooth actuation for advanced medical and manufacturing technologies. Here, orthogonal initiation is used to create interpenetrating polymer networks (IPNs) with spatial control over morphology and mechanical properties. Base catalyzes the formation of a stiff and strong polyurethane, while blue LEDs initiate the formation of a soft and elastic polyacrylate. IPN morphology is controlled by when the LED is turned “on”, with large phase separation occurring for short time delays (≈1–2 min) and a mixed morphology for longer time delays (>5 min), which is supported by dynamic mechanical analysis, small angle X-ray scattering, and atomic force microscopy. Through tailoring morphology, tensile moduli and fracture toughness can be tuned across ≈1–2 orders of magnitude. Furthermore, a simple spring model is used to explain the observed mechanical behavior. Photopatterning produces “multimorphic” materials, where morphology is spatially localized with fine precision (<100 µm), while maintaining a uniform chemical composition throughout to mitigate interfacial failure. As a final demonstration, the fabrication of hinges represents a possible use case for multimorphic materials in soft robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of Interlayer Time-Lapse and Workability Retention on Printed Concrete Performance

The rapid advancement of additive manufacturing technologies for concrete construction requires further understanding of material performance and its relationship with print parameters such as interlayer time-lapse and workability retention during the print. Here this study addresses the effects of the time delay between consecutive extruded layers on the mechanical performance of printed concrete using a mix designed by Quikrete. A series of specimens were prepared with printing delays of 10, 15, 30, and 60 min. This work correlates the change in fracture properties, mechanical performance, and workability retention with the interlayer time-lapse between two consecutive concrete layers. Interlayer time-lapse is defined as the time difference in printing of two consequent layers of concrete. It affects individual properties differently based on the loading direction and test types, but it is consistent in terms of interlayer performance. The understanding of the effect of interlayer time-lapse on the fracture properties between two consecutive printed layers fills the knowledge gaps in printed concrete research. Therefore, this study can help researchers perform required optimization and safely estimate the performance of printed concrete.

3D printing↗
DOE OSTI2022

Direct ink write multi-material printing of PDMS-BTO composites with MWCNT electrodes for flexible force sensors

Here, with recent advances of additive manufacturing technology, direct ink write (DIW) printing has allowed to incorporate multi-material printing of various materials with freedom of design and complex geometric shapes to complete functional sensors in a one-step fabrication. This paper introduces the use of DIW 3D printing of polydimethylsiloxane (PDMS) with barium titanate (BTO) filler as stretchable composites with tunable piezoelectric properties that can be used for force sensors applications. To improve the bonding between stretchable piezoelectric composites and electrodes, multi-walled carbon nanotubes was included in the fabrication of electrodes at a fixed ratio of 11 wt. %. The alignment of the BTO dipoles was achieved through corona poling method, which applies an electric charge on the surface layer of the functional material, aligning the dipoles in the desired direction and thus gaining the piezoelectricity. Different BTO mixing ratios (10–50 wt. %) were evaluated in order to obtain tunable piezoelectric properties and compare the sensitivity with respect their elastic properties. Tensile testing and piezoelectric testing were carried out to characterize mechanical and piezoelectric properties. Results showed that fabricated PDMS with 50 wt. % BTO gave the highest piezoelectric coefficient (d 33 ) of 11.5 pC N -1 and with an output voltage of 385 mV under compression loading of >200 lbF. This demonstrates feasibility of using multi-material DIW printing to fabricate piezoelectric force sensors with integrated electrodes in one-step without compromising the flexibility of the material.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Low-cost & Energy Dense Batteries for Transportation

The project sought to explore development of novel polymer separator materials and additives for Li-S and Li-ion batteries that would solve critical failure modes and performance bottlenecks for these chemistries. This technology presented significant advanced manufacturing challenges and opportunities in getting to scale, including materials synthesis scale-up, large-area polymer processing techniques, electrode formulation, and the development of coin and pouch cells for electrochemical energy storage. Specific accomplishments included synthesis of organic molecular and polymer materials designed to solve outstanding challenges in electrochemical cells. The primary focus of new materials design was aimed at improving longevity, power, cost reduction, and environmental sustainability of said electrochemical devices. The project also involved assembly and characterization of electrochemical devices with standard galvanostatic and potentiostatic techniques as well as electrochemical impedance spectroscopy.

25 ENERGY STORAGE↗
DOE OSTI2020

Functional Photoresists for Energy Applications. Final Report

Monolithic ultralow-density porous bulk materials have recently attracted much interest due to many emerging applications in the areas of catalysis, energy storage and conversion, and thermal insulation. They are also important components of high energy density (HED) and inertial confinement fusion (ICF) targets. However, despite tremendous progress that has been made in the synthesis of porous materials, deterministic and independent control over microscopic architecture, density and composition remain key issues, and their integration in high precision devices requires cost and time-intensive mechanical machining that not only reduces reproducibility by generating debris but also limits the complexity of the 3D shapes that can be realized. In this project, we overcame these limitations by developing a universal templating capability that provides deterministic and independent control over density, composition, architecture, and macroscopic sample shape. This was achieved by developing the technology to 1) 3D print ultrahigh resolution, ultra-high precision polymeric micro-lattice templates, 2) coat these templates with the desired materials, and 3) removing the template (Fig. 1a). Atomic layer deposition (ALD) provides the atomic scale coating thickness accuracy required for precisely controlling density. While this templating approach had been demonstrated in prior work, limitations in suitable photoresists, 3D print technologies, print design, and template removal techniques did not allow the fabrication of millimeter-sized high-precision parts with sub-micron resolution. To enable this technology, we developed 1) two-photon polymerization (TPP) print designs that enable the fabrication of millimeter-sized, mechanically robust polymeric templates with sub-micron resolution and 2) a continuum level TPP printing simulation capability for additional print design guidance; 3) atomistic models to study photoresist polymerization kinetics and network topography, 4) refractive index matched polymeric and preceramic TPP photoresists, and 5) functional TPP photoresists including porous voxel structures and self-immolative polymer photoresist chemistries; and 6) damage free template removal techniques that enable the fabrication of defect-free high-precision low-density foam components. We also developed a templating approach for pure carbon microlattices with a unique tube-in-tube ligament morphology. As a test platform, we pursued the fabrication of foam liners that promise to further increase the neutron yield in indirect drive ICF experiments by improving implosion symmetry control and coupling between the laser and the deuterium-tritium fuel. This application requires fabrication and integration of a ultra-high precision, millimeter-sized, thin-walled (200-400 micrometer thick), low-density (10-30 mg/cc), high atomic number (high Z) cylindrical foam tube into the gold hohlraum of an indirect drive ICF target (Fig. 1b). While our hohlraum liner test case will mainly find application in HED and ICF experiments, the underlying science will also directly apply to previously developed nanoparticle and additive manufacturing technologies and will advance those techniques as well.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mechanical Properties of Additively Manufactured 316L Stainless Steel Before and After Neutron Irradiation–FY23

This report presents the observed mechanical behavior of the additively manufactured (AM) 316L stainless steel (SS) before and after neutron irradiation. In the Advanced Materials and Manufacturing Technologies (AMMT) program, a variety of mechanical and physical property data are generated and accumulated to assess the AM austenitic alloy for nuclear reactor applications. The testing and evaluation task in the FY 2023 focused on elucidating the effects of sampling location and build size on the mechanical properties of AM 316L SS (in stress-relieved condition) before and after neutron irradiation. The laser powder bed fusion (LPBF) process produced 316L plates of three distinct sizes from which SS-J3 miniature tensile specimens were machined from six different locations. The tensile specimens were irradiated in the High Flux Isotope Reactor (HFIR) normally to 2 and 10 dpa at the target temperatures of 300 °C and 600 °C. Post-irradiation tensile testing was performed at room temperature, 300 °C, and 600 °C. The mechanical properties of AM 316L SS were significantly influenced by the characteristic microstructures of printed materials, which include fine grains and high-density dislocations. Compared with the traditional 316L SS, AM 316L showed higher initial strength and lower ductility. Regardless of sampling location, the AM 316L steel retained relatively high strength and ductility to the highest irradiation dose. A prompt necking at yield (with little uniform ductility) was observed after irradiation at 300 °C but no embrittlement was observed up to 10 dpa. Ductilization by irradiation–the radiation-induced increase of ductility–was observed for the 600 °C irradiation only and it occurred in low dose range only. The neutron irradiation increased the data variation in many tensile property datasets, particularly after 600 °C irradiation, and no clear dependence of tensile properties on build thickness or sampling location was observed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of LPBF Steels for Nuclear Applications

This report provides an update on the prioritization of existing reactor materials for advanced manufacturing. This report is a Milestone 3 deliverable in FY2023, under work package CT-23AN130401 to support research and qualification activities supported by the Advanced Materials and Manufacturing Technologies (AMMT) program here at Argonne National Laboratory (ANL). The focus of FY23 for ANL included the determination of a decision criteria matrix for the prioritization of existing materials, the literature review of a select few Fe-based alloys, and working with vendors to obtain customized powders. The work package also includes fabricating test samples in a Renishaw AM400 Laser Powder Bed Fusion (LPBF) system and optimizing the process parameters. The major outcomes of this work package are: With collaborations from PNNL, ORNL, and INL, we were able to establish a decision criteria matrix containing a total of 6 categories and 31 different criteria. These will be used to downselect alloys for further evaluation; As part of that, 6 different Fe-based alloys were selected, 3 austenitic stainless steels (A709, D9, AFA) and 3 ferritic/martensitic steels (HT9, Grade 91, Grade 92). Customized powders were obtained from vendors in small quantities to fabricate initial prints to check printability of these specific alloys; A total of 72 single track experiments were performed on two alloy systems, 1 austenitic stainless steel (A709) and 1 ferritic/martensitic steel (Grade 91) in order to optimize the process parameters for the full 3d prints. The optimization led to the selection of 20 different processing conditions, 10 for each class of alloys; D9 and AFA alloys showed extensive cracking and porosity in the samples. This was due to less-than-ideal conditions present in the chamber during the deposition. A709 printed using the same process parameters showed almost fully dense samples with no noticeable porosity or any other defects. SEM and EBSD analysis revealed single phase FCC microstructure with cellular structure within the grains; HT9, Grade 91, Grade 92 alloys also showed no noticeable signs of cracking and ImageJ analysis showed porosity <0.5% in all conditions. While Grade 91 and Grade 92 showed single phase BCC microstructures, the presence of martensite laths was noted in HT9 alloy; Future work will include further characterization of these alloys to better understand the microstructural evolution during the 3d printing process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Report Outlining Computed Tomography Strategy and Microscopy Approach to Qualifying AM 316 Materials

This report is part of work package CR-22OR0406012, Automated, High-Throughput Materials Characterization Techniques , under the Advanced Materials and Manufacturing Technologies program (AMMT). The project’s primary objective is to leverage our AI-based rapid and high-throughput automated characterization framework to qualify additively manufactured 316 materials comprehensively, focusing on optimizing the additive manufacturing process and evaluating the performance of 3D-printed stainless steel components. This report outlines our strategy for leveraging the automated characterization process for qualifying 316H materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Promoting the Regulatory Acceptance of Combined Ion and Neutron Irradiation for Material Degradation in Nuclear Reactors

The Advanced Materials and Manufacturing Technologies (AMMT) program within the Department of Energy Office of Nuclear Energy has developed its current recommendation for promoting the use of combined ion and neutron irradiation data for the accelerated qualification of nuclear reactor materials. This plan is intended to provide a collaborative path forward that can be adopted by academia, national laboratories, and industry, and has been developed with input from the regulatory research arm of the U.S. Nuclear Regulatory Commission (NRC). In the context of nuclear energy, the U.S. Department of Energy is responsible for nuclear energy-related research and development and promotion of nuclear technologies, while the NRC is an independent regulatory agency responsible for the safety of the civilian use of nuclear technologies. These two agencies thus have distinct but interconnected roles regarding the development and deployment of nuclear technologies. As the needs for the nuclear energy industry continue to evolve in the 21st century, it is critical to set the pace for timely industry adoption of new technological solutions that also can be accepted by regulatory agencies. New ways of collecting and utilizing data for regulatory purposes have become a necessity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Education and Workforce Development for Critical Minerals and Materials Supply Chains (Workshop Report)

The Advanced Materials and Manufacturing Technologies Office (AMMTO) aims to improve the efficiency, productivity, environmental impact, and competitiveness of the manufacturing sector. Education and workforce development (EWD) efforts are essential for AMMTO to achieve these goals, and for this reason the current and future EWD landscape in the critical minerals and materials (CMM) sector requires renewed attention.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

High‐Throughput Computational Guided Development of Refractory Complex Concentrated Alloys‐based Composite

ULTIMATE is a leading-edge DOE program to develop ultrahigh temperature materials for gas turbine use in the aviation and power generation industries. This team, headquartered at West Virginia University and including collaborators from the National Energy Technology Laboratory and Advanced Manufacturing LLC, has developed a new class of ultra-high temperature Refractory Complex Concentrated Alloys-based Composites (RCCC) for high temperature applications such as combustion turbines used in the aerospace and energy industries. The RCCC consist of Refractory Complex Concentrated Alloys (RCCA) mixed with particles of Refractory High Entropy Carbides, to increase RCCA strength to withstand extreme conditions. These new materials optimize the balance among strength, creep (deformation), density, and stability at 1300 °C (2372 °F), while maintaining ductility once the alloy cools to room temperature. The research team has developed advanced manufacturing processes using the pulsed electric current and laser 3D printing to produce test coupons of these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Report on technical development in ANL for innovative creep testing and measurement

This report summarizes a research effort undertaken by Argonne National Laboratory to accelerate the development of creep data package for ASME code qualification. Progress on the fabrication of a 3-sample load train and the application of a direct current potential drop (DCPD) technique to measure large creep strains are reported. Specifically: (1) The 3-sample load train, with three sets of Linear Variable Differential Transformers (LVDT), has been fabricated and assembled. (2) A DCPD method for creep-strain measurement up to 50% has been demonstrated. The DCPD data matches very well to LVDT results, suggesting its potential application in future creep testing. The technical developments contribute towards shortening the time needed to generate a creep data package for an ASME code case of the laser powder bed fusion 316H stainless steel, an effort under the US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Radiation testing of AM materials [Slides]

This presentation discusses the combined irradiation testing methods, strategies, and high-level results of the Advanced Materials and Manufacturing Technologies program. Included are neutron irradiation, ion irradiation, and post-irradiation examination.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Defect Production and Microstructural Feature Impact for Radiation Damage in Additively Manufactured 316 Stainless Steel

This milestone presents multi-scale modeling research results for additively manufactured 316 stainless steel. A combination of phase field, cluster dynamics, molecular dynamics, and density functional theory with machine learning is used, allowing for predictions of radiation-driven microstructural evolution in additively manufactured 316 stainless steel over a range of temperatures, damage rates, neutron spectra, and microstructures, and supporting the development of combined ion and neutron irradiation for material qualification. Informed by ion irradiation and neutron irradiation results across the Advanced Materials and Manufacturing Technologies program, we investigate the unique aspects of radiation-driven microstructure evolution in additively manufactured 316 stainless steel. In particular, we focus on understanding the impact of carbon concentration (varying, for example, between the 316L and 316H standards) on void formation; radiation-induced segregation at dislocation cells and grain boundaries; and the evolution of dislocation loops and network dislocation populations. We find that the unique characteristics of the additively manufactured microstructures must be accounted for in understanding the evolution of dislocation populations under thermal and irradiation conditions, such as the variation in sink strengths arising due to the variation in dislocation density. We also find that the radiation-induced segregation of Cr and Ni to grain boundaries and cell walls differs due to the differences in their defect sink biases. We also find that increasing the Ni content can slow vacancy diffusion, which may provide a mechanism for the observed reduction in transient swelling rate for austenitic Fe-Cr-Ni alloys with increasing Ni content. In addition, ion irradiations have shown that increasing carbon content in 316 SS results in a larger population of smaller voids, suggesting reduced vacancy diffusion. Our results show that the carbon content of additively manufactured 316 SS has a significant impact on the migration rate of defect clusters. The presence of carbon atoms results in carbon-vacancy trapping, significantly reducing the diffusion rate of vacancies. Carbon atoms may also be trapped near the surface of a void, which may reduce void growth by trapping vacancies that diffuse toward the void.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗