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At least 703 records · Page 39

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE

Revealing the complex chemistry of grain boundaries in K-doped BaFe 2 As 2 with atom probe tomography

Iron-based superconductors have attractive properties for high-field applications, but there is a lack of understanding of the effect of grain boundary chemistry on the in-field performance. The near atomic-scale resolution, ppm sensitivity and 3D analysis offered by atom probe tomography make it a powerful tool to investigate the nanoscale structure and chemistry of these defects in fine-grained K-doped BaFe 2 As 2 samples. A computational method to systematically extract and compare the Gibbsian interfacial excess of chemical species across grain boundaries has been explored in this work. The robustness of the method has been tested by evaluating the effects of selected variables on simulated APT datasets. The accuracy and precision of the calculated Gibbsian interfacial excess were found to be stable over a range of analysis conditions: varying grain boundary widths and detection efficiencies, spatial precisions below 1.5 nm, and bin widths between 1.2 and 1.6 nm. For the K-doped BaFe 2 As 2 samples studied, segregation of As, Ba, K and impurities of O, Na, and Sb were found at grain boundaries. The Gibbsian excess values were found to vary widely between different boundaries, showing the complexity of the grain boundary chemistry in this material. Possible links between the observed critical current density (Jc) of these samples and their nano- and micro-structure have also been investigated and discussed.

36 MATERIALS SCIENCE

Radiation-induced segregation in dilute Fe–Cr: A rate-theory framework for the Cr enrichment–depletion transition at the grain boundary

Radiation-induced segregation (RIS) poses a significant challenge for ferritic Fe–Cr alloys under irradiation, as it can compromise mechanical integrity and increase susceptibility to intergranular corrosion. Yet, the mechanisms governing Cr segregation remain incompletely understood. Here, in this study, we present a physics-based rate-theory model parameterized using self-consistent mean field theory-based Onsager transport coefficients to investigate RIS at the grain boundary in dilute Fe-(0.1 at. %) Cr. Under equal production rates of vacancies and self-interstitial atoms (SIA), and their equal absorption rates by bulk dislocations, the model simulates the experimentally observed transition from Cr enrichment at low temperatures to depletion at higher temperatures. Under these unbiased conditions, systematic investigation reveals that while temperature-dependent transport properties dictate the segregation direction, dose rate, grain size, and dislocation density only influence the magnitude and spatial extent of Cr segregation. However, under more realistic conditions of preferential vacancy production within damage cascade and/or preferential SIA absorption by bulk dislocations, the enrichment-to-depletion transition shifts to lower temperatures. Our findings demonstrate that RIS predictions based solely on transport coefficients are valid only under symmetric point defect flux conditions, and that biases in defect production and absorption must be considered for accurate predictions. This work provides a mechanistic framework for understanding RIS in ferritic alloys and informs alloy design for advanced nuclear systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Impact of absorption due to zero-field splitting on loss in dielectrics: A case study in sapphire

The coherence times of superconducting qubits are limited by loss mechanisms, whose microscopic origins have remained elusive. We propose a mechanism caused by transitions between zero-field-split states of paramagnetic impurities or defects. We derive the absorption cross section for a magnetic dipole transition and apply it to calculate the bulk loss tangent. For Cr, Fe, and V impurities in sapphire, we find loss tangents at 4.5 GHz in the range of 10 −9 –10 −8 , comparable to the loss measured in experiments. This value suggests that magnetic loss may be a limiting factor in the coherence times of superconducting qubits.

36 MATERIALS SCIENCE

Interface morphology and dislocation-mediated processes during rapid solidification of thin films

Rapid solidification experiments have, in recent years, revealed a wealth of new microstructural phenomena that suggest a strong connection between the kinetics of solidification and the crystalline structures that emerge as a result. In this work, we investigate the interplay between interface morphology and defect-mediated processes during rapid solidification conditions using a Phase Field Crystal (PFC) model, enabling us to simultaneously and efficiently explore the physics of solidification and elasto-plasticity in the formalism of a single-field theory. We predict that there are two mechanisms by which dislocations emitted directly from the solid–liquid interface induce orientation gradients as well as the formation of subgrain boundaries within a single solidifying cell. We relate these mechanisms to the morphology of the moving solid–liquid interface and identify a suitable control parameter in the PFC model with which we can go between said morphologies by effectively changing the relative strength of the capillary length and kinetic coefficients of the solid–liquid interface. Thus, we are able to provide mechanistic explanations for several microstructural features (with an emphasis on orientation gradients and subgrain boundaries) observed during the rapid solidification of pure materials. We also provide a simple explanation for the formation of “jagged” subgrain boundaries, which is consistent with our experimental observations in rapidly solidified samples of Aluminum, whose mechanisms have thus far been unknown.

Interface morphology

Toward a Machine Learning Approach to Interpreting X-ray Spectra of Trace Impurities by Converting XANES to EXAFS

The fact that the photoabsorption spectrum of a material contains information about the atomic structure, commonly understood in terms of multiple scattering theory, is the basis of the popular extended X-ray absorption spectroscopy (EXAFS) technique. How much of the same structural information is present in other complementary spectroscopic signals is not obvious. Here we use a machine learning approach to demonstrate that within theoretical models that accurately predict the EXAFS signal, the extended near-edge region does indeed contain the EXAFS-accessible structural information. We do this by exhibiting deep operator neural networks (DeepONets) that have learned the relationship between the extended and near edge portions of the X-ray absorption spectrum to predict the former from the latter. We find that we can accurately predict the EXAFS spectrum between 6 and 14 Å –1 from the first 6 Å –1 (≈100 eV) of the absorption spectrum of Cu 2 + substitutional defects in the Fe 3+ mineral hematite (α-Fe 2 O 3 ). This surprising finding implies that theoretical analyses of X-ray absorption spectra could be implemented that extract the same conclusions as high-quality EXAFS studies from spectra collected over a much smaller range of photon energies. This relaxes a host of experimental limitations related to the X-ray source and measurement sample, including collection time, minimum dopant concentration, source brilliance, and energy range. We describe the theoretical data sets and DeepONet construction and show that the resulting DeepONets produce EXAFS that recovers linear combination fits to experimental data with accuracy approaching the original ab initio calculations. We discuss the implications of our findings for minor constituent characterization and for understanding the information content of spectroscopic data more broadly, including how this approach might be applied to measured experimental spectra. In conclusion, to encourage similar efforts, the simulated X-ray spectra, machine learning, and fitting code are publicly available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Scale Invariance of Hot Spot Formation in TATB High Explosives

Shock-induced detonation of insensitive high explosives based on 1,3,5-triamino-2,4,6-trinitrobenzene starts with formation of hot spots at microstructural defects but has eluded atomistic modeling treatment at micron length scales. To this end, we performed multimicron scale all-atom molecular dynamics (MD) simulations of hot spots that form during the collapse of cylindrical pores with diameters between 10 and 300 nm. Our MD simulations show that hot spots formed at pores larger than 20 nm exhibit temperature fields with scale-invariant features for sizes up to at least 300 nm. Through a continuum-based grain-scale modeling framework, we span and extend beyond the size scales currently accessible to MD and find that hot spot scale invariance is a general feature that arises when the mechanical strength is insensitive to strain rate. Finally, our results demonstrate the applicability of all-atom MD to simulate the complicated dynamical evolution of micron-sized systems and bolster confidence in insights from MD simulations of materials that exhibit strength with negligible rate dependence over the relevant intervals.

36 MATERIALS SCIENCE

Quantification of Oxygen Vacancies in SrFe0.5Cr0.5O3−δ Thin Films: Correlating Lattice Expansion with Oxidation State Variability

Oxygen vacancies (VO), even in the dilute regime, can significantly impact the physical and chemical properties of complex oxides. It is however challenging to reliably detect and adequately quantify such defects in thin film samples where the VO concentration and distribution may further vary in response to interfacial strain. Here, we present a method to quantify VO concentrations in SrFe0.5Cr0.5O3−δ (SFCO) epitaxial thin films. Through coherent Bragg rod analysis, X-ray absorption spectroscopy, and theoretical modeling, we systematically correlate the c-axis lattice expansion detected in SFCO films with a VO concentration gradient. Our results reveal a nearly linear relationship between oxygen off-stoichiometry and out-of-plane lattice expansion in coherently strained SFCO films, with δ increasing from 0.32 to 0.52 and the lattice expanding by ∼1.0%. Moreover, a significant decrease in Cr oxidation state (from Cr5+ to Cr3+) is observed as the VO concentration increases, while the Fe oxidation state remains fixed at Fe3+. Our findings provide a reliable way to quantify oxygen stoichiometry in complex oxides, offering a pathway to design materials with precisely tailored structure–property relationships.

Hossain, Mohammad Delower

Impact of amorphous pockets on displacement damage evolution in silicon

Silicon has long been known to exhibit amorphization in response to heavy particle bombardment. For doses below the total amorphization threshold, partial amorphization is observed in the form of scattered amorphous pockets. While extensive research has gone into modeling the formation and evolution of amorphous pockets in response to irradiation, no studies yet investigate their impact on the evolution of other damage such as interstitial supersaturation and clustering. In this study, we survey the impact of amorphous pockets on defect evolution in silicon when treated as static sinks. MD is first used to show that amorphous pockets provide energetically favorable sites for point defects relative to the crystalline bulk, supporting the hypothesis that they act as sinks. A 0-D cluster dynamics model is then constructed, taking an interstitial clustering model from the literature and including amorphous pockets as a sink species. We conduct our survey for temperatures between 30 and 400 °C and sink strengths between 1 to 6 x 10 10 cm −2 . Both implantation- and radiation-induced damage states are investigated using interstitial and vacancy concentrations as initial condition variables. We find that, due to the differing migration rates of the interstitial and the vacancy, amorphous pockets have a non-monotonic impact on the final damage state depending on the effective sink strength of the amorphous pockets, resulting in increased damage formation in regimes of intermediate amorphization. In conclusion, this result emphasizes the important role of amorphous pockets in governing the evolution of damage in partially amorphized crystalline materials.

36 MATERIALS SCIENCE

Liquid crystal torons in Poiseuille-like flows

Three-dimensional (3D) simulations of the structure of liquid crystal (LC) torons, topologically protected distortions of the LC director field, under material flows are rare but essential in microfluidic applications. Here, we show that torons adopt a steady-state configuration at low flow velocity before disintegrating at higher velocities, in line with experimental results. Furthermore, we show that under partial slip conditions at the boundaries, the flow induces a reversible elongation of the torons, also consistent with the experimental observations. These results are in contrast with previous simulation results for 2D skyrmions under similar flow conditions, highlighting the need for a 3D description of this LC soliton in relation to its coupling to the material flow. These findings pave the way for future studies of other topological solitons, like hopfions and heliknotons, in flowing soft matter systems.

Science & Technology - Other Topics

Radiation Tolerance of Nanoporous Gadolinium Titanate

Defect sinks play a crucial role in reducing radiation-induced damage accumulation, but their effectiveness varies. This study directly compares the efficacy of grain boundaries and pores (free surfaces) in gadolinium titanate (Gd 2 Ti 2 O 7 ) using in situ ion irradiation transmission electron microscopy (TEM). A unique sample configuration is developed, where each of the three distinct regions, each containing only one primary sink of interest, is in the same TEM lamella for simultaneous irradiation. Regular assessments of crystallinity in each region via nanobeam electron diffraction show that, at both room temperature and 600°C, free surface (pore) defect sinks are more effective than grain boundaries in capturing radiation-induced defects and delaying the onset of amorphization. These findings have significant implications for further microstructural engineering and the design of radiation-resistant microstructures.

36 MATERIALS SCIENCE

Seamlessly joining length scales: From atomistic thermal graphs to anisotropic continuum conductivity

Thermal transport in complex solids is governed by local structure, defects, and anisotropy, yet most continuum models still rely on oversimplified and homogenized conductivities. Here, we bridge atomistic and continuum descriptions by building finite element (FE) models directly from the site-projected thermal conductivity (SPTC), an atomic-level decomposition of the Green–Kubo thermal conductivity. We introduce a toolkit, the “Simulator Collection for Atomic-to-Continuum Scales (SCACS)”, which uses a graph neural network to predict SPTC on large atomic structures, coarse-grains these fields into anisotropic conductivity tensors, and embeds them into the heat-flow FE equation with a customized, anisotropy-aware adaptive mesh refinement scheme. Applied to silicon nanostructures, the resulting FE models act as representative volume elements, reproduce bulk conductivities, and capture interfacial and defect-driven anisotropy while maintaining thermodynamic consistency. Additionally, SCACS predicts experimental conductance trends and fields. This work demonstrates a general route for transferring atomistic transport information into device-scale thermal simulations with physics-based approximations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Atoms-to-devices models for post-irradiation annealing kinetics in III-V semiconductors

Understanding atomic displacement damage and propagating this understanding into validated defect-aware radiation damage models is a critical step toward achieving predictive, atoms-to-systems assessment of radiation vulnerabilities of microelectronics. These models are essential for evaluating the performance and reliability of nuclear stockpile components or space-based electronics (satellites). The goal of this project was to bridge a fundamental science gap between defect spectroscopies and atomistic modeling of radiation-induced defects on the one hand, and simulations of device response on the other hand, to develop predictive defect-aware damage models for high-fidelity device simulations of radiation-damaged III-V semiconductors.

36 MATERIALS SCIENCE

Molecular dynamics study of grain boundaries as defect sinks under irradiation in LiAlO 2 and LiAl 5 O 8

Lithium aluminate ceramics, LiAlO 2 and LiAl 5 O 8 , show promise in nuclear environments due to their excellent radiation tolerance. Molecular dynamics simulations investigate grain boundaries (GB) and their role in defect evolution. Results reveal that GBs act as efficient defect sinks, with Li and Al atoms exhibiting distinct behaviors during displacement cascades. Tritium migration in LiAlO 2 is also studied, showing rapid diffusion and stable configurations with oxygen, corroborated by ab initio simulations from the literature. The calculated tritium diffusion coefficient of 1.33 × 10 - ¹⁴ m²/s aligns with the literature, validating the model. LiAl 5 O 8 demonstrates superior defect healing compared to LiAlO 2 , attributed to enhanced atomic transfer between grains and GBs. These findings reveal key insights into defect dynamics, providing essential insights for their application in tritium-producing burnable absorber rods (TPBARs).

36 MATERIALS SCIENCE

Anomalous elastic softening in ferroelectric hafnia under pressure

his study employs first-principles density-functional theory (DFT) calculations to explore the elastic and mechanical properties of ferroelectric hafnia (HfO 2 ) in its polar orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase under varying hydrostatic pressure conditions up to 30 GPa. Utilizing a plane-wave basis set and Perdew-Burke-Ernzerhof generalized-gradient approximation for solids in our DFT calculations, we investigate both pure and yttrium-substituted HfO 2 . Our findings reveal an anomalous reduction in the 𝐶 33 component of the elastic tensor with increasing pressure, which becomes significant above 15 GPa and signals a potential pressure-driven structural phase transition at higher pressure. The analysis of atomic displacements under pressure sheds light on the unusual mechanical behavior and phase stability of this material. Additionally, we observe a transition from an indirect band gap to a direct band gap with increasing pressure, which could have significant implications for optical applications. Here, the effects of yttrium substitution on the mechanical and electronic properties are further examined, revealing that yttrium substitution softens the elastic response of this material and reduces the electronic band gap. These results enhance our understanding of elastic and mechanical responses of ferroelectric hafnia and its potential for applications in microelectronics, piezoelectric devices, and nonvolatile ferroelectric random-access memories. Further experimental validation is recommended to confirm our predictions and explore the practical implications of the observed phase transitions and electronic behavior of the ferroelectric hafnia under high-pressure conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

How Proton Incorporation Reshapes Lattice Dynamics In BaSnO 3 ‐Type Proton Conductors

Proton conduction in acceptor-doped perovskites is fundamentally a vibronic process: mobile H + and D + do not move independently, but dynamically co-vibrate with the surrounding oxygen–metal framework. Direct experimental evidence for this behavior is presented using in situ 119⁢ 𝑆⁢𝑛 nuclear resonance vibrational spectroscopy (NRVS) on hydrated, deuterated, and dry 𝐵⁢𝑎⁢𝑆⁢𝑛 1−𝑥⁢ 𝑌 𝑥 ⁢𝑂 3−𝛿 . Hydration induces systematic redistributions in the Sn-projected phonon density of states (PDOS), including an upshift of the first spectral moment by about 0.4 meV, indicating a stiffening of the extended Sn–O network. H/D isotopic substitution leaves the Sn-projected PDOS largely unchanged, with only subtle isotope-dependent spectral reweighting, demonstrating that protonic degrees of freedom are not localized oscillators but are embedded in collective lattice modes. These results are rationalized using a classical coupled proton–phonon oscillator model that links the observed PDOS variations to changes in effective force constants and vibrational mass terms. The model captures how H + and D + participate in cooperative lattice dynamics rather than forming isolated OH/OD entities. Overall, NRVS probes proton–lattice coupling in ceramic proton conductors and quantitatively describes how protonic defects modulate host lattice dynamics to enable phonon-assisted long-range proton transport.

36 MATERIALS SCIENCE

Predicting Selective Laser Printing Print Quality of Polymer Powders through Melt Flow Index

Selective Laser Sintering (SLS) uses a precisely controlled laser to fuse polymer powder to build complex 3D shapes. While SLS covers a wide application space, the processing knowledge of polymer powder is limited, restricting the number of commercial powders available. This study serves to expand the processing knowledge of polypropylene and polyethylene in parallel with a “mature” SLS feedstock, nylon, through melt flow index (MFI) characterization. Differential Scanning Calorimetry (DSC) was used to explore the sintering window of the polymers. Polyethylene and polypropylene exhibited a relatively narrow sintering window between 4 – 5 °C, whereas the sintering window of nylon was much wider, between 23 – 24 °C. This suggests that the print quality between polyethylene and polypropylene would be similar; however, X-ray computed tomography revealed a higher volume of print defects, voids, and de lamination in polyethylene than in polypropylene. MFI analysis provided additional insight into the difference in print quality, as the MFI of polyethylene was 7.16 g/10 min, 9.95 g/10 min for polypropylene, and 17.23 g/10 min for nylon. MFI is inversely correlated to melt viscosity, and a low melt viscosity is desired for proper coalescing between the layers and particles. These results suggest that MFI is a promising tool, in conjunction with traditional thermal analysis, for screening candidate powder feedstocks for SLS and optimization of print parameters for novel powders.

36 MATERIALS SCIENCE

Σ3(111) Grain Boundaries Accelerate Hydrogen Insertion into Palladium Nanostructures

Grain boundaries (GBs) are frequently implicated as key defect structures facilitating metal hydride formation, yet their specific role remains poorly understood due to their structural complexity. Here, we investigate hydrogen insertion in Pd nanostructures enriched with well-defined Σ3(111) GBs (Pd GB ) synthesized via electrolysis-driven nanoparticle assembly. In situ synchrotron X-ray diffraction reveals that Pd GB exhibits dramatically accelerated hydriding and dehydriding kinetics compared with ligand-free and ligand-capped Pd nanoparticles with similar crystallite sizes. Strain mapping using environmental transmission electron microscopy shows that strain is highly localized at GBs and intensifies upon hydrogen exposure, indicating preferential hydrogen insertion along GB sites. Density functional theory calculations provide mechanistic insight supporting these findings, showing that hydrogen insertion near Σ3(111) GBs is energetically more favorable and that tensile strain lowers insertion barriers. Furthermore, these results provide atomic-level insights into the role of GBs in hydride formation and suggest new design strategies for GB-engineered Pd-based functional materials.

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