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At least 631 records · Page 35

Determination of the structure of lithium niobosilicate glasses by molecular dynamics simulation with a new Nb-O potential

A partial charge empirical potential for the Nb-O pair has been developed based on existing parameters of other pairs in a Teter potential to enable molecular dynamics simulations of both lithium niobate crystal and lithium niobosilicate glasses. The developed potential is capable of describing structural features of lithium niobosilicate glasses in a wide composition range, including niobium coordination number and bond length, density, bond angle distribution, polyhedral distribution and fraction of bridging oxygen. Furthermore, the results obtained using this new potential show good agreement with experimental data of density and structure from Raman spectroscopy of lithium niobosilicate glasses and X-ray absorption spectroscopy near Nb K-edge.

36 MATERIALS SCIENCE↗

Graph neural networks predict energetic and mechanical properties for models of solid solution metal alloy phases

Here, we developed a PyTorch-based architecture called HydraGNN that implements graph convolutional neural networks (GCNNs) to predict the formation energy and the bulk modulus for models of solid solution alloys for various atomic crystal structures and relaxed volumes. We trained the GCNN surrogate model on a dataset for nickel–niobium (NiNb) generated by the embedded atom model (EAM) empirical interatomic potential for demonstration purposes. The dataset was generated by calculating the formation energy and the bulk modulus as a prototypical elastic property for optimized geometries starting from initial body-centered cubic (BCC), face-centered cubic (FCC), and hexagonal compact packed (HCP) crystal structures, with configurations spanning the possible compositional range for each of the three types of initial crystal structures. Numerical results show that the GCNN model effectively predicts both the formation energy and the bulk modulus as function of the optimized crystal structure, relaxed volume, and configurational entropy of the model structures for solid solution alloys.

36 MATERIALS SCIENCE↗

Operation of helium sub-atmospheric multistage cryogenic centrifugal compressor trains: Part 1 – Steady state modeling and speed ratio selection

Helium cryogenic systems which can provide cooling below the normal boiling point of helium (approximately 4.2 K) are often required by superconducting radio-frequency niobium resonators utilized in modern high-energy particle accelerators. Achieving temperatures below 4.2 K generally involves operating a cryogenic vessel with liquid helium under sub-atmospheric conditions, thereby lowering the saturation pressure and corresponding saturation temperature. Over the last several decades, multi-stage cryogenic centrifugal compressor trains (CC’s) have been operated efficiently and reliably within large-scale cryogenic systems to continuously evacuate helium vapor generated by a device within the vessel, maintaining sub-atmospheric conditions in the vessel while pressurizing the return vapor to above atmospheric conditions. Traditionally, these CC systems have been operated using empirically derived control philosophies and insight gathered from previous operational experience. Recent efforts at the Facility for Rare Isotope Beams (FRIB) have been aimed at the development of a theoretical basis to characterize the operation of multi-stage cryogenic centrifugal compressor train and utilizing predictive model results to generate control parameters. The objective of this research was identifying operational points which adequately balance cryogenic system efficiency, stability, and overall ease of operation. Furthermore, this manuscript provides an overview of the predictive model development, characterization of the FRIB cryogenic centrifugal compressors and implementation of the predicted performance results during steady-state system operation.

Compressor train control↗

Ionic Interdiffusion at Cathode|Solid-Electrolyte Interface: A Machine Learning–Assisted Multiscale Investigation and Mitigation Strategies

Future lithium batteries are expected to use solid electrolytes to achieve higher energy density and fast charge capabilities. However, most solid electrolytes are thermodynamically unstable against layered oxide cathodes. In this study, the stability of LiCoO2 (LCO) cathode with Li10GeP2S12 (LGPS) solid electrolyte is investigated using ab initio molecular dynamics (AIMD) and machine learning molecular dynamics (MLMD). The propensity of ionic interdiffusion, formation of a passivating interphase layer, and corresponding decay in cell performance is addressed using a continuum model. Large-scale MLMD simulations confirm that the LCO|LGPS interface permits interdiffusion of cobalt (Co) and other ionic species, leading to the formation and growth of a resistive interphase and to dramatic capacity fade even in the first cycle. We examine the literature evidence that incorporating a thin layer of LiNb0.5Ta0.5O3 (LNTO) between LCO and LGPS prevents the interdiffusion of ions. Atomistic simulations suggest that substituting lithium (Li) in LNTO with Co is thermodynamically unfavorable, thereby inhibiting ionic interdiffusion. The stable Nb5+/Ta5+ states form a rigid metal-oxide framework, which consequently also prevents the substitution of niobium (Nb) or tantalum (Ta). However, continuum-level analysis suggests that the higher mechanical stiffness of LNTO can lead to interfacial delamination between the LCO and LNTO. This phenomenon reduces the effectiveness of the protective layer. This paper, therefore, highlights the need to develop novel interlayers that balance low ionic interdiffusion with low mechanical stiffness.

Ncube, Musawenkosi K.↗

Dual-scale folding in cutting of commercially pure aluminum alloys

We examine a, hitherto, little-studied and curious machining chip morphology, with tell-tale signs of folding at two different length scales, that is common in cutting of certain ductile and highly strain-hardening metals like soft aluminum alloys, tantalum and niobium. This chip morphology does not appear in the usual catalogues of common chip types. The mechanics of formation of the “dual-scale folded chip” is studied in model material systems of commercially pure aluminum alloys (AA 1100 and AA 8040), that prominently exhibit this chip morphology. The flow, folding and associated plastic instabilities are investigated using micro/macro structure observations of the chip in a plane-strain cutting framework, with high-speed in situ imaging and image analysis of material flow; and force measurements. The smaller-scale folding is shown to develop in the primary deformation zone while the larger-scale folding occurs as the chip traverses the rake face of the tool. The resulting chip is composed of irregularly-spaced large folds, superimposed onto which are the quasi periodic small folds. The representative wavelengths of the two folds differ on average by an order of magnitude, 0.1 mm vs. 2 mm. The observations reveal a direct coupling between the material flow and chip morphology, and how specific attributes of the dual-scale folded chip arise from the flow mechanism. Plastic buckling is found to play a key role in the folding at both length scales. The small-scale folds are characteristic of a sinuous plastic flow mode, while the large-scale folding is characterized by buckling and stick-slip along the tool rake face, triggered by adhesive pinning of the chip to the tool. Important consequences of the dualscale folding are very large cutting forces, and force oscillations of large amplitude, despite the alloys being very soft, only ~ 25 HV. Here, the dual-scale folding is why many of these alloys are classified as “gummy” to machine. Since the dual-scale folded chip is associated with large cutting forces and poor surface quality, there is much to be gained by disrupting this flow type in practical machining applications. Methods for controlling the folding to improve machining performance with the gummy alloys are briefly discussed.

36 MATERIALS SCIENCE↗

Ultra-high temperature testing and performance of L-PBF C103

Additive Manufacturing (AM) of refractory alloys is gaining traction as a materials processing route for components subject to extreme temperature environments. Due to the low oxidation resistance of refractory alloys, novel methods for evaluating their elevated temperature performance must be developed. In this work, a Gleeble® 3800 thermomechanical load frame was modified to evaluate the mechanical properties of laser powder bed fusion (L-PBF) consolidated niobium alloy C103 ranging from room temperature (RT) to 1400 °C. The fixturing and sample geometry were designed to accommodate Joule heating and prevent damage to the test chamber. Oxidation of the samples was minimized via testing in vacuum level of 1E-5 Torr. Ultimate tensile strength (UTS), yield strength (YS), elongation, and strain-hardening behavior were determined as a function of temperature. L-PBF C103 presented an average UTS of ∼650 MPa and over 25 % elongation at RT. Above RT, the UTS and YS dropped then leveled off from 500 °C to 1000 °C with values ranging from ∼400 MPa to ∼460 MPa, which is consistent with dynamic strain aging observed in this class of alloys. The strength rapidly declined after 1200 °C to ∼150 MPa at 1400 °C. Fractography indicated ductile fractures for the C103 at all test temperatures, and Electron Backscatter Diffraction (EBSD) analysis revealed a textured microstructure and the presence of dynamic recrystallization within the necked region of the sample tested at 1400 °C.

33 ADVANCED PROPULSION SYSTEMS↗

High-throughput oxidation screening and down-selection of refractory high entropy alloys in the Al-Cr-Mo-Nb-Ta-Ti system

Rapid experimentation and characterization are ever-present needs in the discovery of high entropy alloys. High entropy alloy systems are difficult to survey with systematic composition sweeps using traditional synthesis methods. The number of distinct compositions in even a four-element system is experimentally intractable. Exploration of these, and higher-element systems, necessitates thermodynamic prediction coupled with an automated sample creation method and a rapid screening methodology to effectively down-select alloys with targeted properties. As a result, a high-throughput method for evaluating the oxidation performance of refractory high entropy alloys was developed and tested. The six-element system of aluminum, chromium, molybdenum, niobium, tantalum, and titanium was evaluated for single phase stability and short-duration oxidation resistance. Target compositions were initially determined via thermodynamic predictions of single-phase stability across a wide temperature range. A twenty-five-sample build plate was produced using directed energy deposition additive manufacturing. After fabrication, the twenty-five 1 cm 3 samples were heat treated and characterized for composition and phase identification. The build plate was exposed to a high temperature oxidizing environment at 1000 °C for three hours. After oxidation, the composition, morphology, and chemistry of the oxides formed were characterized. Of the twenty-five samples produced, nine exhibited a favorable oxidation response, from which a single-phase BCC alloy at a composition of Al 13 Cr 7 Mo 19 Nb 18 Ta 26 Ti 17 was identified as the alloy with the most protective oxidation coating with a thin, adherent oxide scale. Finally, the complete experimental down-selection—from machine setup to final alloy identification—required approximately 45 labor hours, demonstrating a rapid validation for alloy discovery.

Additive manufacturing↗

Impact of microstructure on elastic properties in the alloy Ti-42Al-8.5 Nb

The microstructure of a γ-TiAl alloy containing niobium undergoes continuous transformations during annealing at 550 °C. These take place within the α 2 -phase of lamellar (α 2 +γ) colonies. We have characterized these changes by transmission electron microscopy and made a correlation to the elastic constants determined by resonant ultrasonic spectroscopy during in-situ annealing at the same temperature. Further, the results show a continuous increase of the E-modulus. This can be attributed to elastic strains acting within α 2 lamellae as a result of lattice transformations. After 5000h, a thermodynamic equilibrium was established with equal fractions of α 2 -phase and O-phase that differ only in lattice symmetry and Nb content. Generally, the presence of O-phase should contribute to lower elastic moduli, however in the present case the evolving microstructural characteristics were responsible for the observed increase in the E-modulus.

36 MATERIALS SCIENCE↗

Non-local large-strain FFT-based formulation and its application to interface-dominated plasticity of nano-metallic laminates

Here, this paper presents a novel formulation and its robust numerical implementation of strain-gradient (SG) crystal plasticity within a large-strain (LS) elasto-viscoplastic (EVP) fast Fourier transform (FFT)-based micromechanical model. The resulting non-local SG-LS-EVPFFT formulation is used to model and understand the process of kink band formation during layer-parallel compression of nano-metallic laminates (NMLs). NMLs are layered composites with nanoscale thicknesses, thus requiring consideration of the interaction between dislocations and interfaces within the micromechanical model. The length-scale parameter of the SG model is calibrated by simulating a double pile-up and comparing predictions to analytical solution. This required new expressions for the defect energy, resulting in more accurate double pile-up predictions. The calibrated SG-LS-EVPFFT model is then used to simulate layer-parallel compression of copper-niobium NML. Formation of kink bands is predicted, and the model is used to rationalize the microscopic mechanisms enabling the formation process. It is found that accumulation of dislocations at interfaces leads to activation of layer-parallel slip, which in turn leads to kink band formation.

36 MATERIALS SCIENCE↗

Structure of the pellet-cladding interaction layer of a high-burnup Zr-Nb-O nuclear fuel cladding

Here, structure of the pellet/cladding-interaction (PCI) layer of a high-burnup nuclear fuel with niobium-bearing cladding was investigated using modern transmission electron microscopy (TEM) techniques. Morphology of the PCI consisted of uniform zirconia layer on the cladding side and finger-like features towards to the ceramic fuel. The PCI layer showed a complex microstructure that constitutes three distinct zirconia layers formed by two zirconia phases. From cladding to fuel, monoclinic, tetragonal, and another tetragonal phase were determined via TEM diffraction patterns and precession electron diffraction (PED) using ASTAR microscopy platform (AMP). Characterizations showed that monoclinic and tetragonal phases close to the cladding were crack-free, but the tetragonal layer adjacent to the fuel contained cracks and pores. Presence of the monoclinic layer suggested that its formation involved the gaseous diffusion of oxygen below threshold dose of fission product damage before the fuel/cladding contact occurred. Furthermore, high-resolution TEM revealed compound phase of (U,Zr)O 2 at fringes of zirconia fingers on the fuel side.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Layer dissolution in accumulative roll bonded bulk Zr/Nb multilayers under heavy-ion irradiation

In this work, the heavy-ion irradiation behavior of bulk zirconium-niobium multilayered composites was investigated up to large doses. Multilayers with an average individual layer thicknesses ranging between 15 and 80 nm were synthesized by accumulative roll bonding technique. The irradiation was performed with a defocused 7 MeV Zr 2+ ion beam at 500 °C. The maximum dose achieved was ~145 dpa at the depth of ~1.5 μm from the irradiated surface. Sub-surface microstructural damage and the chemical redistribution were characterized by transmission electron microscopy and energy dispersive spectroscopy, respectively. Irrespective of the layer thicknesses, the irradiation condition caused layer instability and the extent of damage varied with the dose levels. Doses lesser than ~60 dpa caused layer fragmentation and greater than ~60 dpa resulted in layer dissolution. The chemical mixing of layers occur to a depth of ~1 μm, consuming multiple bi-layer periods. Despite the elevated irradiation temperature (500 °C) and a slightly positive heat of mixing (+6 kJ/mol), no phase separation was observed and single-phase was retained in the mixed region. The results demonstrate that chemical mixing was facilitated by the liquid phase miscibility of Zr and Nb, which propelled the interdiffusion within the thermal spikes towards mixing.

36 MATERIALS SCIENCE↗

Mobility assessment of the BCC and carbide phases in the C-Nb, C-U and Nb-U systems

Uranium carbides with refractory metal additions are considered for Gen IV nuclear reactors and nuclear thermal propulsion as fuels for their high-temperature and corrosion resistant properties. Understanding kinetic effects that dictate microstructural evolution during fabrication and operating conditions is essential to advance technological development of these fuels. This work presents the development of an atomic mobility database for C-Nb-U systems based off available experimental data supported with ab-initio methods. The mobility assessments and uncertainty quantification (using Markov chain Monte Carlo) were conducted in the Kawin software. Carbon diffusion is considered dominant, as metal diffusion is much slower, with niobium diffusion being even slower and rate limiting than uranium metal. We provide a comprehensive and self-consistent thermo-kinetic database that is validated by diffusion couple simulations through Kawin. In conclusion, this enables prediction of microstructural and phase evolution critical for the development and lifetime assessment of next generation nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Solidification cracking of refractory alloys: a computational and machine learning study to investigate composition-dependence for improved weldability and additive manufacturability

Large-batch numerical, CALculation of PHAse Diagrams (CALPHAD)-based solidification cracking calculations are performed and then analyzed with machine learning methods to generate models that relate chemistry of refractory alloys to cracking susceptibility. Kou’s solidification cracking index is used to study the refractory alloys including O, N, C binary mixtures with Mo, Ta, Nb, and W, the molybdenum-based TZM, Niobium-based C103, and Tantalum-based T111 and Ta-10 W, as well as hypothetical refractory ternary alloys. Findings strongly validate Kou’s Crack Susceptibility Index (CSI) against Varestraint test data for Nb- and Ta-based alloys, establishing CSI thresholds where refractory alloys with CSI < 15,000 K are likely weldable, CSI > 15,000 K are prone to cracking, and CSI > 25,000 K are likely unweldable (or unprintable). Furthermore, interstitial elements C, N, and O significantly increase crack susceptibility, with some existing material specifications coinciding with peak cracking susceptibility concentrations. Finally, machine learning-derived elemental potency factors enable rapid prediction of CSI from alloy chemistry for C103, TZM, Ta-10 W, and T-111 alloys. These results provide practical guidance for feedstock selection, powder reuse limits, and alloy specification amendments for welding and additive manufacturing applications.

36 MATERIALS SCIENCE↗

Superconducting nanowires as high-rate photon detectors in strong magnetic fields

Superconducting nanowire single photon detectors are capable of single-photon detection across a large spectral range, with near unity detection efficiency, picosecond timing jitter, and sub-10 µm position resolution at rates as high as 10 9 counts/s. In an effort to bring this technology into nuclear physics experiments, we fabricate Niobium Nitride nanowire detectors using novel material preparation methods and test their performance in strong magnetic fields. Furthermore, we demonstrate that these devices are capable of detection of 400 nm wavelength photons with saturated internal quantum efficiency at liquid helium temperatures and in magnetic fields potentially up to 8 T at high rates and with nearly zero dark counts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Finite element modeling of electropolishing of radio frequency dipole Nb crab cavity in hydrofluoric-sulfuric acid electrolyte

The superior performance of niobium superconducting radio frequency (SRF) cavities is achieved through meticulous surface treatment, notably via chemical electropolishing, ensuring exceptionally smooth surfaces. While this technique has been extensively employed for cylindrically symmetric structures, addressing more intricate geometries poses significant challenges in achieving uniform polishing and controlled material removal, especially when moving away from retractable cathodes. This presents a multifaceted electrochemical, thermal, and fluid dynamics conundrum. A prime example is the 197 MHz radio frequency dipole (RFD) crabbing cavity proposed for the Electron Ion Collider (EIC) project, exemplifying such complex structures. Our groundbreaking work integrates the localized oxide thickness variation, considering its impact on current distribution and Joule heating, within the framework of multi-physics modeling using the COMSOL® simulation suite. This approach was applied to a comprehensive model of the RFD cavity, allowing us to investigate optimal external cooling water flow conditions necessary for achieving desirable outcomes. In conclusion, this illustrates the increasing utility of such multi-physics codes to greatly aid in designing solutions to challenging processing requirements for increasingly complex accelerator cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulation and measurement of the dynamic strain response in a prototypical spallation target

The Second Target Station (STS) at the Spallation Neutron Source (SNS) will address emerging scientific challenges by providing a source of intense cold neutrons to instruments optimized for this source. The STS target will use rotating tungsten blocks and will receive 1.3 GeV proton beam pulses from the SNS accelerator at a repetition rate of 15 Hz. The facility life is planned for 40 years, and each target assembly life is expected to be approximately 10 years. An accurate strain prediction is then critical for fatigue life assessment of STS target blocks because they will be subject to approximately 10 8 beam pulses per lifetime. As an R&D activity, the Los Alamos Neutron Science Center (LANSCE) Weapons Neutron Research (WNR) Target 2 (Blue Room) facility was used to test the strain response of prototypical target blocks to the thermal shock of a proton pulse. The blue room was well suited for a pulsed proton beam impact test of subscale STS target blocks; the 800 MeV proton energy is approximately 60 % of the 1.3 GeV proton energy expected from the SNS accelerator to the STS. The LANSCE Proton Storage Ring (PSR) and SNS are both short-pulse proton beam sources with nominal pulse widths of 250 ns and 661 ns, respectively, so the energy deposition in the target occurs in <1 μs pulse duration. Strain measurements on the outer surface of three target blocks (bare tungsten, tantalum-clad tungsten, niobium-clad tungsten) were recorded for comparison against neutronics and structural simulations. In conclusion, this experiment and the supporting simulations satisfied the following primary research goals for the STS target.

Dynamic strain response↗

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Conditioning the Surface and Bulk of High-Nickel Cathodes with a Nb Coating: An In Situ X-ray Study

Surface coating is commonly employed by industries to improve the cycling and thermal stability of high-nickel (Ni) transition metal (TM) layered cathodes for their practical use in lithium-ion batteries. Niobium (Nb) coating or substitution has been shown to be effective in stabilizing LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes; in addition, the electrochemical performance of the final products varies depending on the postprocessing. In this follow-up study, we use in situ synchrotron X-ray diffraction to investigate the kinetic processes and the involved structural evolution in Nb-coated NMC811 upon heat treatment. Furthermore, quantitative structure analysis reveals thermally driven concurrent changes in the bulk and surface, in particular, the phase evolution of the coating layer and Nb/TM interdiffusion that facilitates penetration of Nb into the bulk and particle growth at the increased temperatures. Findings from this study highlight the new opportunities for the intended control of the structure and surface properties of high-Ni cathodes through surface coating in conjunction with postprocessing.

36 MATERIALS SCIENCE↗