Spark plasma sintering of tungsten-based WTaVCr refractory high entropy alloys for nuclear fusion applications
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Vacuum pumps have been used for tritium processing since the 1940s following the isolation of pure tritium. The largest problem facing tritium vacuum pumps is the tritium radioactive decay. The beta particles, recoil energy, and subsequent radical formations are detrimental to most carbon-based materials. Carbon materials, such as plastics, elastomers, carbon fiber, activated carbon, etc., react with tritium to form methane and in the process strip material from the carbonbased material. Other reactions can be self-catalyzing, as is the case with nitrogen and tritium forming tritiated ammonia at room temperature and pressure. Tritium also readily isotopically exchanges with surface -OH groups, increasing the amount of protium in the gas stream while creating a tritium holdup on the surface. Metals are the preferred material when working with tritium, but tritium will permeate into and through almost all metals at some point. The entrapped tritium can decay inside the metal, creating local helium distortions that can impact the structural properties above and beyond the hydrogen embrittlement issue tritium can cause.
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This study explores the feasibility of fabricating cryogenic austenitic steel JK2LB via both laser-based directed energy deposition (laser-DED) and arc-based directed energy deposition (arc-DED) additive manufacturing processes for potential application in fusion reactors. JK2LB, a low-nickel, high-manganese stainless steel developed for ITER, offers excellent cryogenic toughness, radiation resistance, and decay-to-clearance characteristics. Although JK2LB was originally designed to endure cyclic stresses at cryogenic temperatures in tokamaks, its low-temperature mechanical integrity and radiation tolerance also make it a promising candidate for structural components, such as the coil case/support structure in nonplanar high-temperature superconducting magnet assemblies in stellarators. Directed energy deposition (DED) additive manufacturing was selected for this study due to its capability to fabricate large structures with complex geometries. Here, to address the long lead time and high cost associated with acquiring conventional JK2LB solid wire, JK2LB powder-cored wire was developed as the feedstock material. Testing blocks were then fabricated using both wire-fed laser-DED and arc-DED processes. Microstructural and compositional analyses revealed that both DED approaches yield fully austenitic phase and columnar grain structures. Mechanical testing at room temperature revealed that both DED routes achieved yield strength and elongation comparable to those of conventionally processed JK2LB via vacuum melting, electroslag remelting, extrusion, and drawing, though ultimate tensile strength was reduced due to Mn loss and large columnar grains. As a study mainly focusing on the additive manufacturing process, this work demonstrates the potential of additive manufacturing for fusion energy applications and provides a basis for optimization and future cryogenic mechanical evaluation.
Refractory high-entropy alloys (HEAs) are promising candidates for next-generation nuclear applications, particularly fusion reactors, due to their excellent high-temperature mechanical properties and irradiation resistance. Here, the microstructure and mechanical behavior were investigated for an equimolar WTaTiVZr HEA, designed from a palette of low-activation elements. The as-cast alloy exhibited a dendritic microstructure composed of W-Ta rich dendrites and Zr-Ti-V rich inter-dendritic regions, both possessing a body-centered cubic (BCC) crystal structure. Room temperature bulk compression tests showed ultra-high strength of around 1.6 GPa and plastic strain ~6%, with fracture surfaces showing cleavage facets. The alloy also demonstrated excellent high-temperature strength of ~650 MPa at 500 °C. Scratch-based fracture toughness was ~38 MPa√m for the as-cast WTaTiVZr HEA compared to ~25 MPa√m for commercially used pure tungsten. This higher value of fracture toughness indicates superior damage tolerance relative to commercially used pure tungsten. These results highlight the alloy’s potential as a low-activation structural material for high-temperature plasma-facing components (PFCs) in fusion reactors.
The International Symposium on Liquid Metals Applications for Fusion (ISLA) aims to assemble scientists and engineers engaged in research on lithium and liquid metal applications for fusion devices, facilitating discussions on recent advancements and challenges in an open forum to support the development of viable fusion reactors. The 8th International Symposium on Liquid Metals Applications for Fusion (ISLA-8) was organized by the Institute of Plasma Physics, Chinese Academy of Sciences, from 8 to 12 September 2024, in Hefei, China. The symposium was attended by over 70 participants, marking one of the highest attendance figures in the series. A total of 68 presentations were delivered, including 59 presented on-site, while the remainder were conducted online. The participants represented 10 countries, namely China, Japan, the Netherlands, Russia, the USA, the Czech Republic, Italy, Thailand, Spain, and Germany. The symposium covered 10 topics, structured into 13 sessions. Additionally, an opening session provided an overview of the current symposium, while a closing session summarized reports from each session chair.
Supported by the world magnetic fusion research community, a series of International Symposia on Liquid metals Applications for fusion (ISLA) have been held biannually since 2010. The 7th edition (ISLA-7) was held for the period from 12 December through 16 December 2022, at Chubu University located in Kasugai, Aichi, Japan. For the first time in the history of this series of symposia, ISLA-7 was held in a hybrid fashion, due to the COVID-19 situation. The total number of the participants was 60, 34 out of whom attended the symposium in person, and the rest participated online. As to the presentation statistics, 29 papers were presented in person, whereas 21 presentations were delivered online but real-time by the presenters in China, Spain, the UK, and the USA. Both of the presentations delivered in person and online were recorded, and the video has been shared by all participants. These participants represent 11 countries: China, Czech, Italy, Japan, Latvia, Netherlands, Russia, Thailand, the UK, and the USA. All these numbers are among the largest in this series of symposia. Covered by these presentations are; in session-2, program overviews and liquid metal research review; in session-3, liquid metal flows, and MHD issues; in session-4, liquid metal facilities; in sessions-5 and 6, liquid metal experiments and modeling; in session-7, divertor physics and heat flux mitigation; in session-8, plasma and liquid metals interactions; in session-9 liquid metal plasma-facing components, erosion, and wettability. In addition, there were an opening session whereby several opening addresses were delivered and also a closing session where all technical session summaries were presented by the respective session chairs.
This document represents a final report on the Department of Energy (DOE) Office of Science, Office of Fusion Energy Science (OFES) Grant Entitled “Development and Qualification of Advanced Alloys Used in High Helium and Displacement Damage Service for Fusion Energy Applications” (DE-FG02-94ER54275). This grant has been funded since 1994, by a series of five and three-year renewals. We express our deep appreciation for the long-standing support by OFES for our fusion materials research. The latest three-year renewal was awarded in 2019. This renewal subsequently received a 1- year no-cost extension, followed by another funded 1-year phaseout period. Here, we focus on this five-year effort. The final report is composed of 35 Fusion Semiannual Reports covering the period from 2019 to 2024. In addition, Appendix A lists 158 fusion materials papers published since 1994, with the partial, or full, support of the OFES program. We note that, as metrics of their high impact, these papers have received a total of 8582 citations, with an average of 54 per paper.
Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.
This deposit contains the raw data for reproducing research results of the paper Multimodal Super-Resolution: Discovering hidden physics and its application to fusion plasmas. The main contribution of this work is to utilize machine learning techniques to reconstruct and enhance the resolution of a diagnostic measurement from other available diagnostics in a system. The proposed techniques is called Diag2Diag.
Application of axial seed magnetic fields in the range 20-100 T that compress to greater than 10,000 T (100 MG) under typical NIF implosion conditions may significantly relax the conditions required for ignition and propagating burn in NIF ignition targets that are degraded by hydrodynamic instabilities. Such magnetic fields can: (a) permit the recovery of ignition, or at least significant alpha particle heating, in submarginal NIF targets that would otherwise fail because of adverse hydrodynamic instability growth, (b) permit the attainment of ignition in conventional cryogenic layered solid-DT targets redesigned to operate under reduced drive conditions, (c) permit the attainment of volumetric ignition in simpler, room-temperature single-shell DT gas capsules, and (d) ameliorate adverse hohlraum plasma conditions during laser drive and capsule compression. In general, an applied magnetic field should always improve the ignition condition for any NIF ignition target design.
Application of axial seed magnetic fields in the range 20-100 T that compress to greater than 10,000 T (100 MG) under typical NIF implosion conditions may significantly relax the conditions required for ignition and propagating burn in NIF ignition targets that are degraded by hydrodynamic instabilities. Such magnetic fields can: (a) permit the recovery of ignition, or at least significant alpha particle heating, in submarginal NIF targets that would otherwise fail because of adverse hydrodynamic instability growth, (b) permit the attainment of ignition in conventional cryogenic layered solid-DT targets redesigned to operate under reduced drive conditions, (c) permit the attainment of volumetric ignition in simpler, room-temperature single-shell DT gas capsules, and (d) ameliorate adverse hohlraum plasma conditions during laser drive and capsule compression. In general, an applied magnetic field should always improve the ignition condition for any NIF ignition target design.
Polymer foams play a critical role in contemporary inertial fusion energy (IFE) target designs by enhancing energy yield and optimizing implosion dynamics. However, the lack of high-resolution characterization of the nanostructure of these foams restricts progress in fusion science. In this work, we demonstrate the first high-resolution three-dimensional (3D) reconstruction of a low-density, Si-doped polymer foam fabricated via two-photon polymerization, using ptychographic x-ray computed tomography (PXCT) at an x-ray free electron laser (XFEL). This imaging method reconstructs two-dimensional (2D) attenuation and phase information at multiple sample angles that are combined into a 3D density map used to extract local mass density and determine structural dimensions. We achieve a 2D spatial resolution of 19 ± 3 nm on a high-contrast Ronchi pattern target and 78.7 ± 3 nm for low-contrast polymer foams, marking a significant advancement for XFEL-based ptychography of low-density materials. Furthermore, our experimental results reveal an average foam strut thickness of 1.17 ± 0.4 μm, consistent with fabrication expectations, and a reconstructed average mass density of 0.35 g/cc, aligning closely with the predicted density of 0.29 g/cc. These findings provide important insights for improving foam design and refining radiation hydrodynamics modeling in future IFE experiments. Our study establishes PXCT at an XFEL as a powerful tool for high-resolution characterization of fusion-relevant materials, paving the way for enhanced target performance in IFE research.
Here we assessed the hydrogen migration and redistribution model implemented in the BISON fuel performance code for component-level tritium transport applications in fusion and fission example scenarios. We developed BISON models of an ITER heat exchanger, light water reactor fuel cladding, and a fluoride salt cooled high temperature reactor heat exchanger. Reasonable agreement between reported values in reference studies and BISON predictions demonstrated the ability of the BISON models to predict tritium transport behavior through steel materials. Next, sensitivity and uncertainty analysis was used to understand key parameter sensitivities within the BISON model for evaluation of tritium migration and redistribution. . The sensitivity analysis showed that the diffusivity activation energy was the most important parameter and that the heat of transport was the least important parameter for tritium migration in steels. Overall, the capabilities of the BISON code for component level modeling of tritium transport are promising.
Tungsten and tungsten heavy alloys (WHAs), known for their remarkably high hardness, durability, and corrosion resistance, play a critical role in the thriving development of nuclear fusion reactors in recent years. However, the exploration in tungsten alloys for the nuclear-related applications has been limited by the difficulty of manufacturing and the complexity of experiments to reproduce the environment of nuclear reaction. Therefore, this project aims to utilize nanoscale simulation methods such as density functional theory (DFT) and molecular dynamics (MD) with the help of machine learning techniques to not only understand the mechanisms of tungsten alloys but also allow us to computationally predict their mechanical behaviors under extreme environments. One critical problem of the application of WHAs in nuclear reactors is the surface melting. In the current design of the SPARC reactor, the WHA, W97Ni2.1Fe0.9 or W97NiFe, is chosen to be the first wall components to confine the plasma where the particles are fiercely moving and colliding into each other to create nuclear fusion reaction. This process will generate extremely high heat flux onto these WHA tiles, leaving high surface temperature that could possibly melt the surface of the WHA tiles, As illustrated in Fig. 1(a). a laser experiment previously done illustrates that a rough surface damage would be made after the surface melting where the matrix area mainly composed of nickel and iron as shown in Fig. 1(b), will first melt and then leave vacancies between these tungsten grains. Unfortunately, these kinds of roughness on the first-wall components could be deadly to the plasma inside a Tokmak reactor because the heat that is supposed to dissipate at a designed ratio through the tiles may in turn be excessively absorbed and accumulated on any uneven area of the surface, which will eventually make the whole nuclear reaction fail. In this project, we will introduce a machine learning potential, Allegro, based on DFT calculation and then build a MD model for W-Ni-Fe alloys.
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