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At least 1,459 records · Page 81

Vapor transport growth of MnBi 2 Te 4 and related compounds

Motivated by fine tuning of the magnetic and topological properties of MnBi 2 Te 4 via defect engineering, in this work, we report the crystal growth of MnBi 2 Te 4 and related compounds using vapor transport method and crystal characterization by measuring elemental ratio, magnetic and transport properties, and scanning tunneling microscopy. For the growth of MnBi 2 Te 4 single crystals, I 2 , MnI 2 , MnCl 2 , TeCl 4 , and MoCl 5 are all effective transport agents; chemical transportation occurs faster in the presence of iodides than chlorides. We further successfully grow MnSb 2 Te 4 , MnBi 2-x Sb x Te 4 , and Sb-doped MnBi 4 Te 7 crystals. A small temperature gradient< 20°C between the hot and cold ends of the growth ampoule is critical for the successful crystal growth of MnBi 2 Te 4 and related compounds. Compared to flux grown crystals, vapor transported crystals tend to be Mn stoichiometric, and Sb-bearing compositions have more Mn/Sb site mixing. The vapor transport growth provides a new materials synthesis approach to fine tune the magnetic and topological properties of these intrinsic magnetic topological insulators where controlling defects is vital.

36 MATERIALS SCIENCE↗

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗

Single crystal growth of 67%BiFeO 3 -33%BaTiO 3 solution by the floating zone method

Here, the growth conditions and the resultant grain morphologies and phase purities from floating-zone growth of 67%BiFeO 3 -33%BaTiO 3 (BF-33BT) single crystals are reported. We find two formidable challenges for the growth. First, a low-melting point constituent leads to a pre-melt zone in the feed-rod that adversely affects growth stability. Second, constitutional super-cooling (CSC), which was found to lead to dendritic and columnar features in the grain morphology, necessitates slow traveling rates during growth. Both challenges were addressed by modifications to the floating-zone furnace that steepened the temperature gradient at the melt-solid interfaces. Slow growth was also required to counter the effects of CSC. Single crystals with typical dimensions of hundreds of microns have been obtained which possess high quality and are suitable for detailed structural studies.

36 MATERIALS SCIENCE↗

Strength-ductility synergy through microstructural and compositional heterogeneity in directed energy deposition additive manufacturing of face-centered cubic materials

Directed energy deposition (DED) is an additive manufacturing (AM) process based on welding technology and offers the advantages of large build volume, high deposition rate, and ability to fabricate multi-material parts. Epitaxial continuous columnar grain growth is a characteristic microstructural feature of DED processed alloys. In this study, a bamboo-like microstructure (periodic alternation of equiaxed and columnar structure) was produced by adopting an intermittent deposition strategy in 316L stainless steel and Inconel 625. The formation of a bamboo-like alternating microstructure was confirmed through electron backscattered diffraction (EBSD) analysis. Hardness mapping showed that the columnar to equiaxed transition (CET) occurred at the region right below the fusion line. A finite element (FE) model was used to investigate the relationship between the temperature gradient (G) and the solidification rate (R). The FE model showed a low G/R ratio at the region right below the interface promoting the CET. The grain size and material-dependent deformation behaviors are analyzed using digital image correlation (DIC). The lower deformation on the fine-grain regions observed in DIC analysis is attributed to a higher strain hardening rate, which is confirmed through dislocation density analysis on a tensile-interrupted specimen. The periodically alternating grain size coupled with the microstructural changes caused by intermittent deposition strategy result in a better strength-ductility synergy in both single-material and bimetallic specimens.

36 MATERIALS SCIENCE↗

Modeling and simulation of oxygen transport in high burnup LWR fuel

We have developed a formulation for oxygen transport in uranium dioxide nuclear fuel that accounts for the effects of irradiation. The overall simulation combines the evolving isotopic composition, thermochemistry, and oxygen transport in irradiated fuel. The driving forces for oxygen transport are computed from local thermodynamic equilibrium calculations and account for the effects of temperature gradients and composition, including fission products. The proposed method provides a mechanism for including complex thermodynamic models of nuclear fuel in modeling of mass redistribution, and alleviates difficulties associated with the common thermodiffusion formulation. Here, the transport model has been implemented within the nuclear fuel performance code BISON utilizing the thermochemistry code Thermochimica, with burnup calculations provided by the ORIGEN isotopic transmutation code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Experimental results of conductive inserts to reduce nuclear fuel temperature during nuclear volumetric heating

Advanced fuel designs that incorporate thinner fuel UO2 pellets interspaced by high thermal conductivity inserts have been proposed, with the primary goals of reducing peak centerline temperatures and temperature gradients across fuel pellets and enhancing heat transfer from the fuel to the coolant. An initial series of experiments has been performed on this design, including laboratory experiments and a series of experiments using the Idaho National Laboratory (INL) Transient Reactor Test (TREAT) Facility, the latter of which compared thermal gradient driven fracture of standard pellet designs with that in the proposed advanced fuel design. Although reducing fracture is not the primary objective of the new fuel design, the lower thermal gradients are expected to reduce fracture, so it can serve as an indicator of the thermal behavior of this fuel in the reactor. The in-reactor tests were conducted at multiple linear heat generation rates and confirm the expected result that fracture in both the standard and advanced fuel pellets occurs during the first ramp to power in standard light-water reactor conditions. Post-irradiation examination of the experiment material was performed and included quantification of the extent of fracture in the fuel pellets. It was found that the advanced-design pellets reduce the extent of fracture in a statistically significant way. This confirms the expected behavior predicted by two-dimensional axisymmetric models of this experiment. Here in this study is an important first experimental confirmation of the efficacy of the proposed inserts for achieving their desired effect on the thermal behavior of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Porosity evolution in proton irradiated microfine-grained POCO graphite

This work investigated the porosity evolution of POCO ZXF-5Q graphite that has been irradiated by 340 kW, 120 GeV protons inside NT02 target system in Fermilab's NuMI beamline. This POCO graphite has undergone direct bulk dimensional swelling at low dose irradiation and its local microstructural change is still not well-understood during this process. In this work, the (sub-) micrometre scale porosity from six locations across proton beam fluence and temperature gradients have been studied using focused ion beam-scanning electron microscopy (FIB-SEM) tomography. Here, a deep learning-based tomographic image segmentation technique has been established and implemented for porosity segmentation and quantification. It has been found that there is a decrease in the total volumetric percentage of the porosity at proton beam centre (~ 8 – 8.4 vol.%), by comparing to un-irradiated POCO (~ 12 – 13vol.%) and to beam 2σ and 5σ radii (~ 12vol.%). This decrease in porosity volume percentage was found to be caused by the reduction in pores with volumes > 0.1 μm 3 induced by material bulk dimensional swelling at proton beam centre area. The porosity reduction in relation to dimensional change and irradiation creep was discussed among with other contributing factors, and further investigations through well-controlled irradiation experiment are still needed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analysis of radially resolved thermal conductivity in high burnup mixed oxide fuel and comparison to thermal conductivity correlations implemented in fuel performance codes

The thermal diffusivity and thermal conductivity of high burnup (19 % FIMA) mixed oxide (U, Pu)O 2 nuclear fuel has been measured along the radial direction using a thermoreflectance-based method. Measured thermal conductivity exhibits a notable radial variation consistent with the expectations that a large temperature gradient across the annular fuel pellet leads to a heterogeneous microstructure. A common fuel performance model of thermal conductivity, the Lucuta-Inoue model, is used to analyze the measured thermal conductivity profile. Further, this model adequately captures the radial dependence of thermal conductivity except in the periphery. The analysis suggests that the characteristic radial shape of the thermal conductivity profile follows the burnup profile within the fuel pin. In the periphery, the high burnup structure is formed and the conductivity model, not capturing this effect, likely overestimates the thermal conductivity.

36 MATERIALS SCIENCE↗

Fracture toughness measurement of ceramics with fuel pellet geometry

The crack initiation of nuclear fuel pellets, driven by extreme temperature gradients, is a critical factor impacting reactor performance. Although this fact is widely acknowledged, there is limited fracture toughness data for specimens with representative geometry and fabricated using relevant processing methods. Here, to address this, a new chevron-notched short-rod specimen configuration with diameter and length both equal to 10 mm, representative of a conventional fuel pellet and tested in tension, was developed in an attempt to validly measure Mode I fracture toughness, K Ic . Test calibration was carried out by testing polycrystalline ZrO 2 , SiC, and Si 3 N 4 ceramics fabricated with conventional fuel pellet geometry and known fracture toughnesses. The results suggest that the method described in this paper produces valid K Ic measurements using conventional ceramic fuel pellets.

Ceramics↗

Thermoelectrics: From longitudinal to transverse

Thermoelectric power generation is a promising technology to realize a sustainable society because it directly converts thermal energy into electricity in a solid. Conventional thermoelectric generation is driven by the Seebeck effect, discovered by T.J. Seebeck in 1821, in which a charge current J c is generated in the direction parallel to a temperature gradient ∇T, the longitudinal geometry. Here, the ratio between the generated longitudinal electromotive force and applied ∇T is defined as the Seebeck coefficient. As shown in Figure 1A, a thermoelectric module based on the Seebeck effect typically consists of many pairs (128 for a 12V unit) of p-type and n-type conductors alternately arranged and connected in series. Since the Seebeck coefficient of a p-type (n-type) conductor is positive (negative), the thermopower in each element adds to the total output in the Seebeck module. This configuration is needed to achieve a practical voltage because each element only supplies millivolts but limits the use of thermoelectric generators. The efficiency of thermoelectric generators is characterized by the thermoelectric figure of merit, zT. Despite a 3-fold improvement in zT resulting from materials research over the last two decades, little progress has been made in their practical use; this is ascribed to the technological challenges in contact technology. The contacts on the hot side are subject to thermal degradation. All contacts (512 for a 12V unit) add electrical and thermal contact resistances that reduce the device efficiency to a fraction of that promised by the materials.

30 DIRECT ENERGY CONVERSION↗

The effects of advanced spectral line shapes on atmospheric carbon dioxide retrievals

Line shape effects such as speed-dependence and collisional (Dicke) narrowing are manifest in high signal-to-noise ratio laboratory spectra for a wide range of molecular species and sample conditions. However, these effects are usually neglected in spectroscopic models used in remote sensing of atmospheric greenhouse gases. Here, in this study, we examine the effects of line profile choice on laboratory spectra and XCO 2 values retrieved from Total Carbon Column Observing Network (TCCON) spectra. To this end, we utilize limiting cases of the Hartmann-Tran profile (HTP) with shape parameters recently measured by cavity ring-down spectroscopy. Significant differences highlighting the importance of including speed-dependence effects in forward models were observed both in scaling retrievals as well as profile retrievals. However, because of uncertainties associated with the atmospheric temperature gradient, it was not possible to extract accurate carbon column profiles even with inclusion of these new line shape parameters and advanced line profiles.

54 ENVIRONMENTAL SCIENCES↗

Understanding fission gas bubble distribution, lanthanide transportation, and thermal conductivity degradation in neutron-irradiated α-U using machine learning

U—10Zr based metallic nuclear fuel is the leading candidate for next-generation sodium-cooled fast reactors in the United States. US research reactors have used and tested this fuel type since the 1960s and accumulated considerable experience and knowledge about the fuel performance. Most of the knowledge, however, remains empirical. The lack of mechanistic understanding of fuel performance puts a large burden on proof through experimental verification for the qualification of U—10Zr fuel for commercial use. Further, this paper proposes an image data-driven machine learning approach, coupled with domain knowledge provided by advanced post irradiation examination, to provide unprecedented quantified insights into the morphology, size, density and the connectivity of fission gas bubbles and their effects on the fission product transportation and thermal conductivity. Specifically, we developed a method to automatically detect, extract statistics, and classify ~19,000 fission gas bubbles into different categories, and quantitatively link the data to lanthanide transportation through connected bubbles and degradation of thermal conductivity along the radial temperature gradient in a neutron irradiated U—10Zr annular fuel. Results indicate the approach can be modified to study other irradiation effects, such as secondary phase redistribution and gaseous fuel swelling in other irradiated nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Segmentation and Classification of Fission as Pores in Reactor Irradiated Annular U–10Zr Metallic Fuel Using Machine Learning Models

Metallic fuels, particularly U—10Zr, are promising candidates for next-generation sodium-cooled fast reactors. Irradiation of nuclear fuels in reactors can lead to the formation of solid and gas fission product which subsequently forms microstructural pores, deteriorating fuel performance. Due to the massive amount of pores and complex phases formed, a quantitative description of fission gas pores is not yet available, preventing the development of microstructure-informed fuel performance modeling for fuel qualification. This paper applied a pre-trained deep learning model to ~10,260 high magnification scanning electron microscopy images. This method increased the accuracy of fission gas pore segmentation and allows statistical features to be extracted which cannot be achieved manually. A pre-trained decision tree model worked on the segemenation results and further classified the pores into different categories to produce a correlation between the pores, movement of lanthanides, and temperature gradient during irradiation. Finally, this paper emphasizes the potentials of machine learning models to accelerate fuel research, development, and qualification for advanced reactors.

36 MATERIALS SCIENCE↗

Additively manufactured tantalum microstructures

Additively manufacturing tantalum is a challenging process in which obstacles are stemming from the high melting temperature and susceptibility to oxidation of tantalum. In this paper, several combinations of deposition parameters were considered in an effort to obtain fully dense additively manufactured tantalum produced on an EOSINT M280 DMLS system. Deposition parameters significantly affect the resulting microstructure of additively manufactured tantalum, altering grain morphology, grain size, crystallographic preferred orientation, and deposition porosity. Due to the nature of the laser sintering process applied, which implies large directional temperature gradients, the resulting microstructures were strongly columnar along the building direction. Microstructural differences for different deposition conditions manifested themselves in both grain morphology and preferred crystal orientations in the columnar grains. Deposition speed and laser power were important parameters to consider for obtaining porosity-free material. Finally, stripe width had the most significant effect on grain growth.

36 MATERIALS SCIENCE↗

Evaluating the Ratio of Electron and Hole Mobilities from a Single Bulk Sample Using Photo-Seebeck Effect

When a semiconductor is under photoexcitation, the voltage response to a temperature gradient is the photo-Seebeck effect. In this work, we study this effect, focusing on the contribution from transport of photo-excited carriers. We demonstrate that by combining photo-Seebeck with photoconductivity measurements, one can determine the ratio between electron and hole mobilities, and hence both of them when one is known. This is found for the case of defect-free samples, where no detail on the absorbance, carrier lifetime or recombination is necessary. Our method reported here does not require chemical doping, which could introduce defects and is often not feasible. It applies to both thin film and bulk samples. Experiment wise, photo-Seebeck effect is relatively easy to implement, or added to existing systems. In a broader context, for semiconductors with significant influence from defects, our result suggests that the photo-Seebeck behavior can still be understood. In this case another photo-transport property is necessary, in order to identify the mobilities of carriers and information regarding the defects. This framework integrates the information from photoexcitation and thermal gradients to provide a general method to determine fundamental electronic properties of materials.

36 MATERIALS SCIENCE↗

Calibrated helium and carbon ion flow measurements in the DIII-D divertor plasma

To explore the influence of drifts on ion flows in the DIII-D divertor and Scrape-Off-Layer (SOL), a calibrated Coherence Imaging System (CIS) views the lower divertor. A new tuneable calibration laser and precision wavemeter provide the rest wavelength for CIII 465 nm plasma emissions resulting in ≤ 1 km/s uncertainty in ion velocities that are in the range of 30 km/s in the divertor plasma. The 2-D line-integrated velocity images have been tomographically inverted to obtain maps of ion velocity. Both He + and C 2+ ion velocity maps were measured in both directions of the toroidal magnetic field B T , and C 2+ images were obtained in attached and detached L- and H-mode plasmas. The measured C 2+ velocities are in the range of 20-30km/s and are compared with UEDGE modeling with full drifts. While He II as a main ion is expected to be entrained in the plasma flow, the C 2+ impurity flow involves the competition between the frictional and ion temperature gradient forces. Both the CIS data and UEDGE modeling agree that the C 2+ flow is towards the divertor plates, but flips with the direction of B T . In general, the experimental C 2+ emission and flow profiles have a wider spatial extent than the UEDGE modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗