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At least 811 records · Page 45

Radiological Scouting, Monitoring and Inspection Using Drones

Human populations and natural ecosystems are bound to be exposed to ionizing radiation from the deposition of artificial radionuclides resulting from nuclear accidents, nuclear devices or radiological dispersive devices (“dirty bombs”). On the other hand, Naturally Occurring Radioactive Material industries such as phosphate production or uranium mining, contribute to the on site storage of residuals with enhanced concentrations of natural radionuclides. Therefore, in the context of the European agreements concerning nuclear energy, namely the European Atomic Energy Community Treaty, monitoring is an essential feature of the environmental radiological surveillance. In this work, we obtain 3D maps from outdoor scenarios, and complete such maps with measured radiation levels and with its radionuclide signature. In such scenarios, we face challenges such as unknown and rough terrain, limited number of sampled locations and the need for different sensors and therefore different tasks. We propose a radiological solution for scouting, monitoring and inspecting an area of interest, using a fleet of drones and a controlling ground station. First, we scout an area with a Light Detection and Ranging sensor onboard a drone to accurately 3D-map the area. Then, we monitor that area with a Geiger–Müller Counter at a low-vertical distance from the ground to produce a radiological (heat)map that is overlaid on the 3D map of the scenario. Next, we identify the hotspots of radiation, and inspect them in detail using a drone by landing on them, to reveal its radionuclide signature using a Cadmium–Zinc–Telluride detector. We present the algorithms used to implement such tasks both at the ground station and on the drones. The three mission phases were validated using actual experiments in three different outdoor scenarios. We conclude that drones can not only perform the mission efficiently, but in general they are faster and as reliable as personnel on the ground.

Pinto, Luís Ramos (ORCID:0000000319975484)↗

Unveiling and Mapping Polymorphs in Fluorite Y2TiO5 Using 4D-STEM and Unsupervised Machine Learning

Y2TiO5 belongs to the Ln2TiO5 (Ln = lanthanide or Y) family of ceramic materials and exhibits a range of desirable material properties such as radiation tolerance, frustrated magnetism, and large dielectric constant. However, understanding the complex crystal structure of Y2TiO5 remains elusive, given that Y2TiO5 can adopt multiple polymorphs such as cubic, orthorhombic, and hexagonal phases within the lattice. In this work, we report a detailed structural analysis of Y2TiO5 using four-dimensional scanning transmission electron microscopy coupled with unsupervised machine learning. The pyrochlore nanodomains, characterized by the ordered arrangement of yttrium cations on the A site of their A2BO5 structure, are present within the matrix of a predominantly fluorite-structured Y2TiO5 along with a third polymorph, the hexagonal phase. The pyrochlore phase is found to form 2 nm boundary regions around hexagonal phase stacking faults, highlighting the potential influence of the hexagonal phase on the occurrence and distribution of the pyrochlore phase. Lastly, we identify a unique pyrochlore phase with asymmetric arrangement of cation ordering along a single planar direction. Our findings provide invaluable insights into the possible mechanisms stabilizing pyrochlore nanodomains within the fluorite lattice of Y2TiO5.

36 MATERIALS SCIENCE↗

From atomistic models to machine learning: Predictive design of nanocarbons under extreme conditions

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but holds significant potential for the development of controlled synthesis pathways. While detonation shockwaves provide the high-pressure, high-temperature environment required for nanodiamond formation, subsequent cooling and decompression dictate whether the diamond phase is preserved or transformed into other nanocarbon structures. Here, in this study, we employ GPU-accelerated reactive molecular dynamics (ReaxFF) simulations to investigate the graphitization and structural remodeling of detonation nanodiamond under nonlinear quench and pressure-release trajectories. We further investigate how the initial nanodiamond morphology; cuboctahedral, octahedral, or hexagonal prism influences the resulting transformation products. Evolution of nanostructure, allotrope (via simulated x-ray diffraction), carbon hybridization, and ring statistics are tracked during a two-stage quench from 5000 K to 60 GPa. Rapid cooling combined with slow decompression optimizes cubic diamond retention, whereas slow cooling with rapid pressure release promotes surface-to-core graphitization, producing concentric sp 2 -hybridized layers and hollowed inner shells. Octahedral nanodiamonds evolve into carbon nano-onions, initially forming bucky diamonds that progressively transform into fully sp 2 -hybridized structures, while hexagonal prisms preferentially form parallel-stacked graphite layers resembling carbon dots. Transient hexagonal diamond (lonsdaleite) emerges as an interfacial phase, suggesting potential reversibility in the shock-induced graphite-to-diamond transformation pathway transformation route. To extend predictive capabilities, we trained machine learning (ML) regressors on over 10 5 node-hours of molecular dynamics (MD) trajectories. A multilayer perceptron (MLP) model reliably predicts the number of graphitized layers from temperature–pressure trajectories with a coefficient of determination (R 2 ) exceeding 0.90. This high predictive fidelity enables efficient, high-throughput mapping of the synthesis parameter space for optimized graphitization outcomes. Collectively, morphological control combined with optimized quench–decompression conditions promote the selective synthesis of nanocarbon allotropes. This work establishes a data-driven framework for the rational, a priori design of carbon nanomaterials for applications in energy storage, sensing, and biomedicine.

Detonation nanodiamond remodeling↗

SDSS-IV MaStar: theoretical atmospheric parameters for the MaNGA stellar library

ABSTRACT We calculate the fundamental stellar parameters effective temperature, surface gravity, and iron abundance – Teff, log g, [Fe/H] – for the final release of the Mapping Nearby Galaxies at APO (MaNGA) Stellar Library (MaStar), containing 59 266 per-visit-spectra for 24 290 unique stars at intermediate resolution (R ∼ 1800) and high S/N (median = 96). We fit theoretical spectra from model atmospheres by both MARCS and BOSZ-ATLAS9 to the observed MaStar spectra, using the full spectral fitting code pPXF. We further employ a Bayesian approach, using a Markov Chain Monte Carlo (MCMC) technique to map the parameter space and obtain uncertainties. Originally in this paper, we cross match MaStar observations with Gaia photometry, which enable us to set reliable priors and identify outliers according to stellar evolution. In parallel to the parameter determination, we calculate corresponding stellar population models to test the reliability of the parameters for each stellar evolutionary phase. We further assess our procedure by determining parameters for standard stars such as the Sun and Vega and by comparing our parameters with those determined in the literature from high-resolution spectroscopy (APOGEE and SEGUE) and from lower resolution matching template (LAMOST). The comparisons, considering the different methodologies and S/N of the literature surveys, are favourable in all cases. Our final parameter catalogue for MaStar cover the following ranges: 2592 ≤ Teff ≤ 32 983 K; −0.7 ≤ log g ≤ 5.4 dex; −2.9 ≤ [Fe/H] ≤ 1.0 dex and will be available with the last SDSS-IV Data Release, in 2021 December.

79 ASTRONOMY AND ASTROPHYSICS↗

Local and long-range atomic/magnetic structure of non-stoichiometric spinel iron oxide nanocrystallites

Spinel iron oxide nanoparticles of different mean sizes in the range 10–25 nm have been prepared by surfactant-free up-scalable near- and super-critical hydrothermal synthesis pathways and characterized using a wide range of advanced structural characterization methods to provide a highly detailed structural description. The atomic structure is examined by combined Rietveld analysis of synchrotron powder X-ray diffraction (PXRD) data and time-of-flight neutron powder-diffraction (NPD) data. The local atomic ordering is further analysed by pair distribution function (PDF) analysis of both X-ray and neutron total-scattering data. It is observed that a non-stoichiometric structural model based on a tetragonal γ-Fe 2 O 3 phase with vacancy ordering in the structure (space group P 4 3 2 1 2) yields the best fit to the PXRD and total-scattering data. Detailed peak-profile analysis reveals a shorter coherence length for the superstructure, which may be attributed to the vacancy-ordered domains being smaller than the size of the crystallites and/or the presence of anti-phase boundaries, faulting or other disorder effects. The intermediate stoichiometry between that of γ-Fe 2 O 3 and Fe 3 O 4 is confirmed by refinement of the Fe/O stoichiometry in the scattering data and quantitative analysis of Mössbauer spectra. The structural characterization is complemented by nano/micro-structural analysis using transmission electron microscopy (TEM), elemental mapping using scanning TEM, energy-dispersive X-ray spectroscopy and the measurement of macroscopic magnetic properties using vibrating sample magnetometry. Notably, no evidence is found of a Fe 3 O 4 /γ-Fe 2 O 3 core-shell nanostructure being present, which had previously been suggested for non-stoichiometric spinel iron oxide nanoparticles. Finally, the study is concluded using the magnetic PDF (mPDF) method to model the neutron total-scattering data and determine the local magnetic ordering and magnetic domain sizes in the iron oxide nanoparticles. The mPDF data analysis reveals ferrimagnetic collinear ordering of the spins in the structure and the magnetic domain sizes to be ∼60–70% of the total nanoparticle sizes. The present study is the first in which mPDF analysis has been applied to magnetic nanoparticles, establishing a successful precedent for future studies of magnetic nanoparticles using this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Chemical Environment and Structural Variations in High Entropy Oxide Thin Film Probed with Electron Microscopy

For this work, we employ analytical transmission electron microscopy (TEM) to correlate the structural and chemical environment variations within a stacked epitaxial thin film of the high entropy oxide (HEO) Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 O (J14), with two layers grown at different substrate temperatures (500 and 200 °C) using pulsed laser deposition (PLD). Electron diffraction and atomically resolved STEM imaging reveal the difference in out-of-plane lattice parameters in the stacked thin film, which is further quantified on a larger scale using four-dimensional STEM (4D-STEM). In the layer deposited at a lower temperature, electron energy loss spectroscopy (EELS) mapping indicates drastic changes in the oxidation states and bonding environment for Co ions, and energy-dispersive X-ray spectroscopy (EDX) mapping detects more significant cation deficiency. Ab initio density functional theory (DFT) calculations validate that vacancies on the cation sublattice of J14 result in significant electronic and structural changes. The experimental and computational analyses indicate that low temperatures during film growth result in cation deficiency, an altered chemical environment, and reduced lattice parameters while maintaining a single phase. Our results demonstrate that the complex correlation of configurational entropy, kinetics, and thermodynamics can be utilized for accessing a range of metastable configurations in HEO materials without altering cation proportions, enabling further engineering of functional properties of HEO materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Upper and lower bounds on phase-space rearrangements

Broad classes of plasma phenomena can be understood in terms of phase-space rearrangements. For example, the net effect of a wave–particle interaction may consist of moving populations of particles from one region of phase space to another. Different phenomena drive rearrangements that obey different rules. When those rules can be specified, it is possible to calculate bounds that limit the possible effects the rearrangement could have (such as limits on how much energy can be extracted from the particles). This leads to two problems. The first is to understand the mapping between the allowed class of rearrangements and the possible outcomes that these rearrangements can have on the overall distribution. The second is to understand which rules are appropriate for which physical systems. There has been recent progress on both fronts, but a variety of interesting questions remain unanswered.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Lifetime of Almost Strong Edge-Mode Operators in One-Dimensional, Interacting, Symmetry Protected Topological Phases

Almost strong edge-mode operators arising at the boundaries of certain interacting one-dimensional symmetry protected topological phases with Z 2 symmetry have infinite temperature lifetimes that are nonperturbatively long in the integrability breaking terms, making them promising as bits for quantum information processing. We extract the lifetime of these edge-mode operators for small system sizes as well as in the thermodynamic limit. For the latter, a Lanczos scheme is employed to map the operator dynamics to a one-dimensional tight-binding model of a single particle in Krylov space. We suggest this model to be that of a spatially inhomogeneous Su-Schrieffer-Heeger model with a hopping amplitude that increases away from the boundary, and a dimerization that decreases away from the boundary. We associate this dimerized or staggered structure with the existence of the almost strong mode. Thus, the short time dynamics of the almost strong mode is that of the edge mode of the Su-Schrieffer-Heeger model, while the long time dynamics involves decay due to tunneling out of that mode, followed by chaotic operator spreading. Furthermore, we show that competing scattering processes can lead to interference effects that can significantly enhance the lifetime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Vapor phase deposition of alumina on interior surfaces of tritium storage containers

Efficient tritium management and containment are critical challenges for nuclear fusion. To mitigate issues related to permeation into structural materials and isotopic exchange with protium, permeation barriers must be applied to the nonplanar internal surfaces of tritium handling components. In this study, we developed an atomic layer deposition (ALD) system to deposit films on canisters used to store and transport tritium. Growth conditions for deposition of Al 2 O 3 were mapped spatially along the length of a canister using silicon witness samples characterized by ellipsometry, atomic force microscopy, and x-ray reflectivity (XRR). We identified ALD process windows for growth at temperatures between 100 and 140 °C. Furthermore, we compared films grown on our Si witness samples to those grown on polished stainless steel 316 (SS316). X-ray photoelectron spectroscopy indicates two distinct chemical states for the alumina, while XRR confirms that the overall growth rate is similar to the 1.1 Å/cycle that we observed on the Si witness samples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Symplectic machine learning model for fast simulation of space-charge effects

Symplectic simulation of space-charge effects is crucial for the design and operation of high-intensity particle accelerators. Traditional methods for simulating these effects are often computationally expensive, resulting in significant overhead. In this work, we introduce a generative model based on a U-Net architecture within a generative adversarial network framework to efficiently simulate space-charge effects. The model is trained to predict the transverse multiparticle space-charge Hamiltonian, which can be physically computed using a gridless spectral method. The one-step symplectic transverse transfer map for the particles is then obtained by differentiating the predicted Hamiltonian. Benchmarking results demonstrate that this generative model achieves an order of magnitude higher computational efficiency compared to the spectral method, providing a highly efficient alternative for simulating space-charge effects with a large number of particles. By maintaining symplecticity, the model effectively preserves the phase-space structure and mitigates nonphysical errors in long-term simulations. This model has been integrated into jutrack, a novel autodifferentiable accelerator modeling code developed in the julia programming language.

Beam code development & simulation techniques↗

Engineering infinite-range SU($\textit{n}$) interactions with spin-orbit-coupled fermions in an optical lattice

Here, we study multilevel fermions in an optical lattice described by the Hubbard model with on-site SU($\textit{n}$) -symmetric interactions. We show that in an appropriate parameter regime this system can be mapped onto a spin model with all-to-all SU($\textit{n}$)-symmetric couplings. Raman pulses that address internal spin states modify the atomic dispersion relation and induce spin-orbit coupling, which can act as a synthetic inhomogeneous magnetic field that competes with the SU($\textit{n}$) exchange interactions. We investigate the mean-field dynamical phase diagram of the resulting model as a function of $\textit{n}$ and different initial configurations that are accessible with Raman pulses. Consistent with previous studies for $\textit{n}$ = 2 , we find that for some initial states the spin model exhibits two distinct dynamical phases that obey simple scaling relations with $\textit{n}$. Moreover, for $\textit{n}$ > 2 we find that dynamical behavior can be highly sensitive to initial intraspin coherences. Our predictions are readily testable in current experiments with ultracold alkaline-earth-metal(-like) atoms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dual-RNA-sequencing to elucidate the interactions between sorghum and Colletotrichum sublineola

In warm and humid regions, the productivity of sorghum is significantly limited by the fungal hemibiotrophic pathogen Colletotrichum sublineola , the causal agent of anthracnose, a problematic disease of sorghum ( Sorghum bicolor (L.) Moench) that can result in grain and biomass yield losses of up to 50%. Despite available genomic resources of both the host and fungal pathogen, the molecular basis of sorghum− C. sublineola interactions are poorly understood. By employing a dual-RNA sequencing approach, the molecular crosstalk between sorghum and C. sublineola can be elucidated. In this study, we examined the transcriptomes of four resistant sorghum accessions from the sorghum association panel (SAP) at varying time points post-infection with C. sublineola . Approximately 0.3% and 93% of the reads mapped to the genomes of C. sublineola and Sorghum bicolor , respectively. Expression profiling of in vitro versus in planta C. sublineola at 1-, 3-, and 5-days post-infection (dpi) indicated that genes encoding secreted candidate effectors, carbohydrate-active enzymes (CAZymes), and membrane transporters increased in expression during the transition from the biotrophic to the necrotrophic phase (3 dpi). The hallmark of the pathogen-associated molecular pattern (PAMP)-triggered immunity in sorghum includes the production of reactive oxygen species (ROS) and phytoalexins. The majority of effector candidates secreted by C. sublineola were predicted to be localized in the host apoplast, where they could interfere with the PAMP-triggered immunity response, specifically in the host ROS signaling pathway. The genes encoding critical molecular factors influencing pathogenicity identified in this study are a useful resource for subsequent genetic experiments aimed at validating their contributions to pathogen virulence. This comprehensive study not only provides a better understanding of the biology of C. sublineola but also supports the long-term goal of developing resistant sorghum cultivars.

Vela, Saddie↗

Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time

The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗

A rotorcraft in-flight ice detection framework using computational aeroacoustics and Bayesian neural networks

Abstract This work develops a novel ice detection framework specifically suitable for rotorcraft using computational aeroacoustics and Bayesian neural networks. In an offline phase of the work, the acoustic signature of glaze and rime ice shapes on an oscillating wing are computed. In addition, the aerodynamic performance indicators corresponding to the ice shapes are also monitored. These performance indicators include the lift, drag, and moment coefficients. A Bayesian neural network is subsequently trained using projected Stein variational gradient descent to create a mapping from the acoustic signature generated by the iced wings to predict their performance indicators along with quantified uncertainty that is highly important for time- and safety-critical decision-making scenarios. While the training is carried out fully offline, usage of the Bayesian neural network to make predictions can be conducted rapidly online allowing for an ice detection system that can be used in real time and in-flight.

42 ENGINEERING↗

Task Sharing of Proton Incorporation in Vertically Aligned Nanocomposite Triple Conductors: Growth, Structure, and Surface Exchange Kinetics

As protonic ceramic electrolysis cells emerge for efficient H 2 production, there is a need to develop air electrode materials enabling fast, durable steam splitting and proton incorporation. Single-phase triple conductors may fail to satisfy the myriad performance/stability requirements, and their critical charge-carriers (holes, oxygen vacancies, and protons) are in competition, limiting their concentrations. Instead, we propose task-sharing, vertically aligned nanocomposites (VANs), comprising a proton conductor (BaZr 0.9 Y 0.1 O 3-δ ) and a redox-active mixed ionic electronic conductor (Ce 0.9 Pr 0.1 O 2-δ ), that may enable rapid proton surface exchange at the solid–gas interface and transport along the solid–solid heterointerfaces. We grew VANs by pulsed laser deposition and investigated the interplay between their processing conditions, structure, and proton and oxygen surface exchange kinetics. We varied the substrate temperature, laser repetition rate, laser fluence, and processing oxygen pressure. The crystallinity and phases were characterized by grazing-incidence X-ray diffraction, and the strain and structural order as a function of depth were evaluated by angle-dependent synchrotron X-ray pair distribution function analysis. To evaluate the potential for interdiffusion, the formation energies of substitutional defects were simulated with density functional theory. Corresponding structural analysis and elemental mapping were performed by scanning/transmission electron microscopy, energy-dispersive X-ray spectroscopy, and electron energy-loss spectroscopy, indicating distinct nanoscale compositional regions with a hierarchical structure embedded in individual VANs columns and minimal interdiffusion across a bilayer film. Proton and oxygen surface exchange coefficients (k H , k O ) and polarization resistances were evaluated by electrical and optical relaxations and impedance spectroscopy of VAN-incorporated protonic ceramic electrochemical cells, respectively, at 400–500 °C, demonstrating values comparable to some of the best-known triple and mixed conductors.

36 MATERIALS SCIENCE↗

Exploring the First High-Entropy Thin Film Libraries: Composition Spread-Controlled Crystalline Structure

Thin films of two types of high-entropy oxides (HEOs) have been deposited on 76.2 mm Si wafers using combinatorial sputter deposition. In one type of the oxides, (MgZnMnCoNi)O x , all the metals have a stable divalent oxidation state and similar cationic radii. In the second type of oxides, (CrFeMnCoNi)O x , the metals are more diverse in the atomic radius and valence state, and have good solubility in their sub-binary and ternary oxide systems. Therefore, the resulting HEO thin films were characterized using several high-throughput analytical techniques. The microstructure, composition, and electrical conductivity obtained on defined grid maps were obtained for the first time across large compositional ranges. The crystalline structure of the films was observed as a function of the metallic elements in the composition spreads, that is, the Mn and Zn in (MgZnMnCoNi)O x and Mn and Ni in (CrFeMnCoNi)O x . The (MgZnMnCoNi)O x sample was observed to form two-phase structures, except single spinel structure was found in (MgZnMnCoNi)O x over a range of Mn > 12 at. % and Zn < 44 at. %, while (CrFeMnCoNi)O x was always observed to form two-phase structures. Composition-controlled crystalline structure is not only experimentally demonstrated but also supported by density function theory calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emergent mystery in the Kondo insulator samarium hexaboride

Samarium hexaboride (SmB 6 ) is an example of a Kondo insulator, in which strong electron correlations cause a band gap to open. SmB 6 hosts both a bulk insulating state and a conductive surface state. Within a Fermi-liquid framework, the strongly correlated ground-state electronic structure can be mapped to a simple state resembling a topological insulator. Although uncertainties remain, many experiments provide compelling evidence that the conductive surface states have a topological origin. However, the bulk behavior is less well understood and some experiments indicate bulk in-gap states. This has inspired the development of many theories that predict the emergence of new bulk quantum phases beyond Landau’s Fermi-liquid model. We review the current progress on understanding both the surface and the bulk states, especially the experimental evidence for each. A mystery centres on the existence of the bulk in-gap states and why they appear in some experiments but not others. Adding to the mystery is why quantum oscillations in SmB6 appear only in magnetization but not in resistivity. Here, we conclude by elaborating on three questions: why SmB 6 is worth studying, what can be done to move forwards and what other correlated insulators could give additional insight.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microstructural examination of interactions between chromia-based refractory and nuclear glass in a melter

This study shows the effects of nuclear waste glass production on Monofrax K-3 refractory corrosion. A continuously fed research-scale melter containing an Fe- and Ni-rich simulated nuclear waste feed with borosilicate glass-forming chemicals was cyclically melted at 1150°C and idled at 1050°C for a total of 11 weeks. Chemical maps using scanning electron microscopy show the interactions between the quenched melt and the refractory. Nanoscale X-ray-computed tomography was used for a three-dimensional visualization of certain parts of the interface. Unreacted K-3 consists of primarily corundum (Al,Cr) 2 O 3 and spinel (Fe 2+ ,Mg)(Al,Cr) 2 O 4 interlocking crystalline phases. Some of the Cr from the refractory interacts with the Ni and Fe from the melt to form a reaction layer comprising (Ni,Fe 2+ )(Cr,Fe 3+ ) 2 O 4 spinel crystals. Simultaneously, melt components (Na,Si) infiltrate into the refractory. This interaction proceeds at the expense of the integrity of the refractory structure. Intact refractory grains (e.g., (Al,Cr) 2 O 3 ) as well as the reaction layer itself can lose mechanical integrity and spall off into the melt, especially near the top of the melter. As the reaction layer can be a protective boundary for the refractory against further melt infiltration, a reduction in the reaction layer thickness allows an increase in refractory corrosion.

36 MATERIALS SCIENCE↗