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Neutron shielding materials are a critical area of development for nuclear fusion technology. In the compact spherical tokamak, shielding efficiency improvements are particularly needed because of severe space constraints. The most spatially restricted component is the central column shield. It must protect the superconducting magnets from excessive radiation-induced degradation, but also from associated heating, so that energy consumption of the cryogenic systems is kept to an acceptable level. Recent simulations show that tungsten carbide and its composites form an attractive class of neutron-attenuating materials. In this paper, the key structure-property relationships of these materials are assessed, as they relate to generic materials challenges for plasma-facing materials. We first consider some fundamental materials properties of monolithic tungsten carbide including thermal transport, mechanical properties and plasma interaction. WC is found to have generally favourable properties compared to metallic tungsten shields. We then report progress on the development of a new candidate cermet material, WC-FeCr. Recent results on its accident safety, thermo-mechanical properties, and irradiation behaviour are presented. This review also highlights the need for further study, particularly in the areas of irradiation damage and hydrogen trapping. This article is part of a discussion meeting issue 'Fusion energy using tokamaks: can development be accelerated?'.
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Accurately identifying and extracting clusters from atom probe tomography (APT) reconstructions is extremely challenging, yet critical to many applications. Currently, the most prevalent approach to detect clusters is the maximum separation method, a heuristic that relies heavily upon parameters manually chosen by the user. In this work, a new clustering algorithm, Gaussian mixture model Expectation Maximization Algorithm (GEMA), was developed. GEMA utilizes a Gaussian mixture model to probabilistically distinguish clusters from random fluctuations in the matrix. This machine learning approach maximizes the data likelihood via expectation maximization: given atomic positions, the algorithm learns the position, size, and width of each cluster. A key advantage of GEMA is that atoms are probabilistically assigned to clusters, thus reflecting scientifically meaningful uncertainty regarding atoms located near precipitate/matrix interfaces. GEMA outperforms the maximum separation method in cluster detection accuracy when applied to several realistically simulated data sets. Lastly, GEMA was successfully applied to real APT data.
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An automated procedure has been developed for the reconstruction of field ion microscopy (FIM) data that maintains its atomistic nature. FIM characterizes individual atoms on the specimen's surface, evolving subject to field evaporation, in a series of two-dimensional (2D) images. Its unique spatial resolution enables direct imaging of crystal defects as small as single vacancies. To fully exploit FIM's potential, automated analysis tools are required. The reconstruction algorithm developed here relies on minimal assumptions and is sensitive to atomic coordinates of all imaged atoms. It tracks the atoms across a sequence of images, allocating each to its respective crystallographic plane. The result is a highly accurate 3D lattice-resolved reconstruction. The procedure is applied to over 2000 tungsten atoms, including ion-implanted planes. The approach is further adapted to analyze carbides in a steel matrix, demonstrating its applicability to a range of materials. A vast amount of information is collected during the experiment that can underpin advanced analyses such as automated detection of "out of sequence" events, subangstrom surface displacements and defects effects on neighboring atoms. These analyses have the potential to reveal new insights into the field evaporation process and contribute to improving accuracy and scope of 3D FIM and atom probe characterization.
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Radiation damage in tungsten and a tungsten-tantalum alloy, both of relevance to nuclear fusion research, has been characterized using a combination of field ion microscopy (FIM) imaging and atom probe tomography (APT). While APT provides 3D analytical imaging with sub-nanometer resolution, FIM is capable of imaging the arrangements of single atoms on a crystal lattice and has the potential to provide insights into radiation induced crystal damage, all the way down to its smallest manifestation--a single vacancy. This paper demonstrates the strength of combining these characterization techniques. In ion implanted tungsten, it was found that atomic scale lattice damage is best imaged using FIM. In certain cases, APT reveals an identifiable imprint in the data via the segregation of solute and impurities and trajectory aberrations. In a W-5at%Ta alloy, a combined APT-FIM study was able to determine the atomic distribution of tantalum inside the tungsten matrix. An indirect method was implemented to identify tantalum atoms inside the tungsten matrix in FIM images. By tracing irregularities in the evaporation sequence of atoms imaged with FIM, this method enables the benefit of FIM's atomic resolution in chemical distinction between the two species.
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Atom probe is a nanoscale technique for creating three-dimensional spatially and chemically resolved point datasets, primarily of metallic or semiconductor materials. While atom probe can achieve local high-level resolution, the spatial coherence of the technique is highly dependent upon the evaporative physics in the material and can often result in large geometric distortions in experimental results. The distortions originate from uncertainties in the projection function between the field evaporating specimen and the ion detector. Here we explore the possibility of continuum numerical approximations to the evaporative behavior during an atom probe experiment, and the subsequent propagation of ions to the detector, with particular emphasis placed on the solution of axisymmetric systems, such as isolated particles and multilayer systems. Ultimately, this method may prove critical in rapid modeling of tip shape evolution in atom probe tomography, which itself is a key factor in the rapid generation of spatially accurate reconstructions in atom probe datasets.
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Atom Probe Tomography (APT) is extensively used for the analysis of RPV steels. However, many different analysis methods and cluster search parameters are used, making comparisons between different datasets difficult. Suitable d(max) and N(min) parameters for the maximum separation method are investigated. In a randomised distribution of solute there is a finite probability that a group of more than N(min) solute ions exists within the d(max) distance. The same is true for experimental datasets from samples which have been thermally aged or irradiated, however these background clusters are not the result of ageing, they are purely statistically random co-incidences. A method is presented for identifying such "background" statistical clusters in real APT data sets, based upon their size and composition, which allows for improved sensitivity to small clusters.
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Oxide nanoclusters in a consolidated Fe-14Cr-2W-0.3Ti-0.3Y2O3 ODS steel and in the alloy powder after mechanical alloying (but before consolidation) are investigated by atom probe tomography (APT). The maximum separation method is a standard method to define and characterise clusters from within APT data, but this work shows that the extent of clustering between the two materials is sufficiently different that the nanoclusters in the mechanically alloyed powder and in the consolidated material cannot be compared directly using the same cluster selection parameters. As the cluster selection parameters influence the size and composition of the clusters significantly, a procedure to optimise the input parameters for the maximum separation method is proposed by sweeping the d(max) and N(min) parameter space. By applying this method of cluster parameter selection combined with a 'matrix correction' to account for trajectory aberrations, differences in the oxide nanoclusters can then be reliably quantified.
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Formic acid (HCOOH) has great potential as an in situ source of hydrogen for fuel cells, because it offers high energy density, is non-toxic and can be safely handled in aqueous solution. So far, there has been a lack of solid catalysts that are sufficiently active and/or selective for hydrogen production from formic acid at room temperature. Here, we report that Ag nanoparticles coated with a thin layer of Pd atoms can significantly enhance the production of H2 from formic acid at ambient temperature. Atom probe tomography confirmed that the nanoparticles have a core-shell configuration, with the shell containing between 1 and 10 layers of Pd atoms. The Pd shell contains terrace sites and is electronically promoted by the Ag core, leading to significantly enhanced catalytic properties. Our nanocatalysts could be used in the development of micro polymer electrolyte membrane fuel cells for portable devices and could also be applied in the promotion of other catalytic reactions under mild conditions.
Asunto(s)
Suministros de Energía Eléctrica , Formiatos/química , Hidrógeno/química , Nanopartículas del Metal/química , Catálisis , Espectroscopía de Resonancia Magnética , Oxidación-Reducción , Paladio/química , Plata/química , TemperaturaRESUMEN
A temporal evolution of clusters associated with age hardening behavior in a Cu-Ni-P alloy during ageing at 250 °C for up to 100 ks after solution treatment has been carried out. A three-dimensional atom probe (3DAP) analysis has showed that Ni-P clusters are present in the as-quenched condition, and that the cluster density increases as the ageing time increases. The clusters have a wide range of Ni/P ratios when they are relatively small, whereas larger clusters exhibit a narrow distribution of the Ni/P ratio, approaching a ratio of approximately two. These results would indicate that the clusters with various Ni/P ratios form at the early stage of precipitation and the ratio approaches a value identical to that of the equilibrium phase at 250 °C as the clusters enlarge during ageing.
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The nature of the initial carbides formed during the early stages of the tempering of steels is still a matter of debate. Conventionally, the main transition carbide is described as epsilon carbide, with a composition of approximately Fe(2.4)C. However, earlier one-dimensional atom probe (1DAP) results indicated the existence of carbon-rich regions having much lower carbon contents, with maxima of around 10at%. There was some uncertainty about the interpretation of the 1DAP results, because of possible problems with alignment of the aperture and with trajectory aberration effects. We have therefore re-visited this topic, using the three-dimensional (3D) atom probe, and studying both a model Fe-Ni-C alloy and a well-known engineering steel (AISI4340). We demonstrate that, for both materials, low-temperature (20-150 degrees C) aging produces carbon-rich regions with average peak carbon contents of up to 10%. We show for the first time the three-dimensional structure of these carbon-rich regions, and demonstrate that fine-scale faulting exists within them.
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Zirconium alloys are used in the nuclear industry as fuel rod cladding. They are chosen for this role because of their good mechanical properties and low thermal neutron absorption. Oxidation of these alloys by coolant is one of the chief limiting factors of the fuel burn-up efficiency. The aim of the present study is to understand these oxidation mechanisms. As a first step, a fundamental study of the oxidation of commercially pure zirconium has been conducted using the 3D atom probe (3DAP). The current generation of 3DAPs allows both voltage and laser pulsing, providing data sets of many millions of ions. According to the literature the only stable oxide of zirconium is ZrO(2). However, the 3DAP shows that an initial layer a few nanometres thick forms with a composition of ZrO(1-)(x) when subjected to light oxidation. This result confirms and extends the work of Wadman et al. [Colloque de Physique 50 (1989) C8 303; Journal de Physique, 11 (1988) C6 49] and Wadman and Andrén [in: C.M. Euchen, A.M. Garde (Eds.), Zirconium in the Nuclear Industry: Ninth Symposium, ASTM STP 1132, ASTM, USA, 1991, p. 461], who used 1DAP techniques, obtaining reduced data sets. Segregation of hydrogen to the metal-oxide interface and a distinct ZrH phase were observed in this study. A novel kinetics study of the room temperature oxidation of zirconium showed the ZrO layer to be non-protective over the time period investigated (up to 1h).
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Over the last few years there have been significant developments in the field of three-dimensional atom probe (3DAP) analysis. This article reviews some of the technical compromises that have led to different instrument designs and the recent improvements in performance. An instrument has now been developed, based around a novel reflectron configuration combining both energy compensation and focusing elements, that yields a large field of view and very high mass resolution. The use of laser pulsing in the 3DAP, together with developments in specimen preparation methods using a focused ion-beam instrument, have led to a significant widening in the range of materials science problems that can be addressed with the 3DAP. Recent studies of semiconductor materials and devices are described.