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At least 1,585 records · Page 88

Dynamical edge modes and entanglement in Maxwell theory

Abstract Previous work on black hole partition functions and entanglement entropy suggests the existence of “edge” degrees of freedom living on the (stretched) horizon. We identify a local and “shrinkable” boundary condition on the stretched horizon that gives rise to such degrees of freedom. They can be interpreted as the Goldstone bosons of gauge transformations supported on the boundary, with the electric field component normal to the boundary as their symplectic conjugate. Applying the covariant phase space formalism for manifolds with boundary, we show that both the symplectic form and Hamiltonian exhibit a bulk-edge split. We then show that the thermal edge partition function is that of a codimension-two ghost compact scalar living on the horizon. In the context of a de Sitter static patch, this agrees with the edge partition functions found by Anninos et al. in arbitrary dimensions. It also yields a 4D entanglement entropy consistent with the conformal anomaly. Generalizing to Proca theory, we find that the prescription of Donnelly and Wall reproduces existing results for its edge partition function, while its classical phase space does not exhibit a bulk-edge split.

Physics↗

Synchrotron X-ray based particle image velocimetry to measure multiphase streamflow and densitometry

Synchrotron-based radiation techniques are increasingly used in the field of flow condition measurements. As a complicated multiphase flow, cavitation has been investigated in a wide variety of industrial fields, to prevent damages on spillways at large dams or intensify the bacteria eradication rate during water treatments. To control the detrimental effects of cavitating flows, the dynamics of and mechanisms affecting cavitation development shall be visualized and identified in real-time. Due to the large reflection and scattering effects of multiphase flow, standard visible-light imaging technologies cannot penetrate vapor bubbles and provide extremely limited information. In this study, the synchrotron source emitted high-flux X-ray pulses are used to capture flow motion and visualize internal structures with sufficiently high spatial and temporal resolutions. The image processing procedures on raw x-ray images are developed using 2D Fourier transform (FT) and wavelet transform (WT) to implement the contrast enhancement and de-noising. Through the edge detection algorithm, tracking either seeded particles or phase interfaces inside the opaque multiphase flow can be achieved to perform the particle image velocimetry. Further, with decomposing particle-only and particle-eliminated subplots from the X-ray phase-contrast image, the time-resolved velocity and void fraction fields are obtained simultaneously, paving a way for further flow condition analysis such as densitometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

CoSn-type NiIn1–xSbx (0 ≤ x ≤ 0.17): Site-Selective Substitution, Electronic Structure, Chemical Bonding, and Structural Transformation

CoSn-type intermetallic compounds have emerged as a model platform for Kagome-derived flat-band physics, where subtle chemical perturbations can strongly influence electronic structure and phase stability. Here, we present a combined experimental and theoretical study of Sb-substitution in CoSn-type NiIn1–xSbx (0 ≤ x ≤ 0.17) to elucidate the interplay between site selectivity, solubility limit, chemical bonding, and electronic structure. Rietveld refinements on Neutron powder diffraction data confirmed the selective Sb-substitution at the electron-rich In2 (2d) site forming the honeycomb substructure, while the In1 (1a) site within the Kagome layer remains exclusively occupied by In. Density functional theory (DFT) calculations revealed that pristine CoSn-type NiIn hosts Ni 3d-dominated flat bands near the Fermi level (EF), originating from the Kagome-like Ni substructure. Partial replacement of In by Sb within the honeycomb layer alters these flat-band features below EF, reducing the density of states and suppressing the flat-band topology near the Fermi level. Orbital-resolved electronic structure and chemical-bonding analyses show that Sb-substitution enhances Ni-p-block (In/Sb) covalency and optimizes charge compensation, stabilizing the CoSn-type structure up to the solubility limit x ≈ 0.17. Beyond the limit, the higher-Sb compositions show satellite reflections consistent with an incommensurately modulated phase. These results establish a link between site-selective chemical substitution, bonding optimization, and flat-band electronic structure evolution, providing fundamental insights into how chemical substitution influences the electronic properties of Kagome-based intermetallic compounds.

Roy, Nilanjan [National Institute of Technology Si↗

Gauging aromatic conjugation and charge delocalization in the aryl silanes Ph n SiH 4– n ( n = 0–4), with silicon K-edge XAS and TDDFT

In this work, Si K-edge X-ray absorption spectra (XAS) have been measured experimentally and calculated using time-dependent density functional theory (TDDFT) to investigate electronic structure in aryl silanes, PhnSiH 4– n ( n = 0–4). Adding aryl groups to SiH 4 splits the Si–H σ-antibonding orbitals into new orbitals with Si–Ph π-bonding (π b ) and π-antibonding (π*) character. Greater aryl substitution is reflected by increasingly intense Si 1s → πb and Si 1s → π* transitions, and weaker transitions into the Si–H and Si–C σ* orbitals. These observations are consistent with known trends in the hydride donor ability of aryl silanes, which is driven in part by the composition of the LUMOs and the accessibility of pathways for electron delocalization through aromatic conjugation. Methodology developed for liquid-phase Si K-edge XAS measurements on PhSiH 3 and Ph 2 SiH 2 will enable dynamic studies of chemical transformations involving siliconcontaining catalysts, intermediates, and substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Unitarity-Limit Expansion for Two Nucleons with Perturbative Pions: Digest and Ideas

Theorists love nontrivial fixed points. In the Unitarity Limit, the NN 𝑆-wave binding energies are zero, the scattering lengths infinite, Physics is universal, i.e. insensitive to details of the interactions, and observables display richer symmetries, namely invariance under both scaling and Wigner’s combined SU(4) transformation of spin and isospin. In “Pionless” EFT, both are explicitly but weakly broken and hence perturbative in the Unitarity Window (phase shifts 45° ≲ δ(k) ≲ 135°, i.e. momenta k≈mπ). This Unitarity Expansion provides strong hints that Nuclear Physics resides indeed in a sweet spot: bound weakly enough to be insensitive to the details of the nuclear interaction; and therefore interacting strongly enough that the NN scattering lengths are perturbatively close to the Unitarity Limit. In this paradigm change, NN details are less important than NNN interactions to explain the complexity and patterns of the nuclear chart. This presentation is a digest of the first quantitative exploration of corrections to this picture when pions are included [1] (see there for a more comprehensive list of references). Since the pion mass and decay constant introduce dimensionful scales in the NN system, they explicitly break the symmetries of the Unitarity fixed point. In χEFT, these symmetries must therefore be hidden and instead be classified as emergent.

Griesshammer, Harald W. [The George Washington Uni↗

Fate of arsenic during up to 4.5 years of aging of Fe III -As V coprecipitates at acidic pH: Effect of reaction media (Nitrate vs. Sulfate), Fe/As molar ratio, and pH

Iron-arsenate (Fe III -As V ) coprecipitate generated in acid mine drainage and hydrometallurgical practices is one of the potential sources of As contamination in the environment. However, the As behavior as well as the transformation process of the Fe III -As V coprecipitate is still not fully understood under acidic conditions. This work systematically studied the effect of reaction media (sulfate vs. nitrate), Fe/As molar ratios, and acidic pH values on the transformation rates, routes, and products of the Fe III -As V coprecipitates at different temperatures during up to 4.5 years of aging. X-ray diffraction (XRD), transmission electron spectroscopy (TEM), Raman spectroscopy, and extended X-ray absorption fine structure spectroscopy (EXAFS) results showed that the Fe III -As V coprecipitates with Fe/As = 2 transformed to scorodite at pH 4 in both sulfate and nitrate media with poorly crystalline ferric arsenate as precursor. In comparison, for the Fe/As = 4 samples, parascorodite and hematite were formed in sulfate and nitrate media, respectively. We note arsenic was released into the liquid phase during the aging process for the samples with Fe/As = 2 and 4. The aqueous As concentrations ([As] aq ) in sulfate media were larger than those in nitrate media for both the Fe/As = 2 and 4 samples. In addition, the transformation products were goethite and Na-jarosite at Fe/As = 8 and 16, pH 2.5 with the decrease of [As] aq . The results also indicated that 6-line ferrihydrite was a common intermediate for many Fe-As transformation processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In situ investigation of the deformation behaviors of Fe 20 Co 30 Cr 25 Ni 25 and Fe 20 Co 30 Cr 30 Ni 20 high entropy alloys by high-energy X-ray diffraction

In situ synchrotron-based high-energy X-ray diffraction (HE-XRD) technique was employed to investigate the mechanical behaviors and microstructural evolution of face-centered cubic (FCC) Fe 20 Co 30 Cr 25 Ni 25 and Fe 20 Co 30 Cr 30 Ni 20 high entropy alloys (HEAs) during tensile deformation. Fe 20 Co 30 Cr 30 Ni 20 HEA has a good combination of strength (ultimate tensile strength of 864 ± 35 MPa) and ductility (elongation of 0.627 ± 0.021). The HE-XRD investigation reveals that Fe 20 Co 30 Cr 30 Ni 20 HEA has the transformation-induced plasticity (TRIP) effect, which starts at a critical stress of ~555 MPa. Furthermore, transmission electron microscopy confirmed this deformation-induced new phase is hexagonal-close-packed structured ε-martensite, which follows an orientation relationship of {111} γ //(0001) ε , and (110) γ //[11 2 ¯ 0] ε with the FCC γ matrix. The observation of deformation twins in the deformed samples of the two studied HEAs proves that twinning-induced plasticity (TWIP) effect occurs in both HEAs. The combination of TRIP and TWIP effects lead to the high strength, large ductility and improved strain hardening behavior of Fe 20 Co 30 Cr 30 Ni 20 HEA.

36 MATERIALS SCIENCE↗

Influence of soluble oligomeric aluminum on precipitation in the Al-KOH-H2O system

The role of oligomeric aluminate (Al(OH)4-) species in the precipitation of aluminum phases such as gibbsite (a-Al(OH)3) from aqueous hydroxide solutions remains unclear and difficult to probe directly, despite its importance to developing accurate predictions of Al solubility in highly alkaline systems. Precipitation in this system entails a transition from predominantly tetrahedrally coordinated Al species in solution to octahedrally coordinated Al in gibbsite. Here we report a quantitative study of dissolved Al in the Al-KOH-H2O system using a combination of molecular spectroscopies. We established a relationship between changes in 27Al NMR chemical shifts and the relative intensity of Raman vibrational bands, indicative of variations in the ensemble speciation of Al in solution, and the formation of unique contact ion pair interactions with the aluminate dimer, Al2O(OH)62 . A strong correlation between the extent of Al oligomerization and the amount of solvated Al was demonstrated by systematically varying the KOH:Al molar ratio. The concentration of dissolved oligomeric Al in solution also directly impacted the particle size and morphology of gibbsite; high concentrations of dimeric Al2O(OH)62-, yielded smaller and more numerous anhedral to subhedral gibbsite particles, while low concentrations yielded fewer and larger euhedral gibbsite platelets. The collective observations suggest a key role of the Al2O(OH)62- dimer in promoting gibbsite precipitation from solution, where the potassium ion-paired dimer possibly catalyzes a more rapid transformation of Al coordination from tetrahedral in solution to octahedral in gibbsite.

Dembowski, Mateusz↗

Model of ramp compression of diamond from ab initio simulations

Ramp compression experiments characterize high-pressure states of matter at temperatures well below those present in shock compression. However, because temperature is typically not directly measured during ramp compression, it is uncertain how much heating occurs under these shock-free conditions. Here, we performed a series of ab initio simulations on carbon in order to match the density-stress measurements of Smith et al. [Smith et al., Nature (London) 511, 330 (2014)]. We considered isotropically as well as uniaxially compressed solid carbon in the diamond and BC8 phases, with and without defects, as well as liquid carbon. Our idealized model ascribes heating during ramp compression to an initially uniaxially compressed cell transforming isochorically into an isotropically (hydrostatic equivalent) compressed state having lower internal energy, hence higher temperature so as to conserve energy. Multiple such heating events can occur during a single ramp experiment, leading to higher temperatures than with isentropic compression. Comparison with experiments shows that heating alone does not explain the equation of state measurements on diamond, instead implying that a significant uniaxial stress component remains present at high compression. The temperature predictions of our ramp compression model remain to be verified with future laboratory measurements.

58 GEOSCIENCES↗

Chemical Modeling of the Capture of Radioiodine Species

Iodine is a common fission product resulting from the transmutation of uranium fuel in nuclear power reactors. The short-lived radioactive isotope, 131 I, with a half-life of around eight days, would be a particular health concern if released into the environment. Capture materials, such as activated carbon, are used routinely in nuclear power plants and medical isotope production facilities to remove this hazard during normal operations to reduce emissions to acceptable levels. Iodine, unlike other common fission products such as noble gases, is challenging because of the wide range of molecular forms and oxidation states (from +VII in IF 7 to -I in iodide) that it displays, which can interconvert both in the gas phase and in the solution phase for example. The work in this project is focused on three computational tasks. In the first, we consider the binding of iodine-containing molecules of varying oxidation states to the major component of activated carbon – pristine graphene-like sheets. The second task focused on molecular binding and possible chemical transformations resulting from the reaction of molecular iodine with chemical functional groups on the edge of the graphene sheets or surface defects in the sheet itself. The final task was associated with radiolytic breakdown of 131 I to 131 Xe in iodine containing molecules and investigated the resulting molecular fragmentation process both in the gas phase and on the graphene-like surface. For each of the tasks, the intent was to learn about the thermodynamics and kinetics of the chemical transformations and use the calculations to provide parameters for input into kinetic models describing these processes for interpretation of experimental data in future work.

07 ISOTOPE AND RADIATION SOURCES↗

In Situ High-Temperature Structural Analysis of High-Entropy Rare-Earth Sesquioxides

High-entropy rare-earth (RE) sesquioxides (RE 2 O 3 ) containing five cations in equimolar amounts have been investigated for a variety of applications, but little is known about their polymorphic behavior and coefficient of thermal expansion. Here, in this work, we evaluate the effect of the average ionic radius (AIR) on the polymorphism of high-entropy RE 2 O 3 . Powder samples of compositions 1 (Lu,Y,Ho,Nd,La) 2 O 3 (AIR = 0.938 Å) and 2 (Gd,Eu,Sm,Nd,La) 2 O 3 (AIR = 0.982 Å) were synthesized via a wet chemical method, and bead samples were prepared for aerodynamic levitation by melting the powders in a copper hearth. Structural transitions were monitored upon cooling from the melt to 1000 °C via in situ X-ray diffraction on aerodynamically levitated samples. The phase evolution was liquid, hexagonal H-type, and monoclinic B-type for composition 1 and liquid, cubic X-type, H-type, and B-type for composition 2. Based on their AIR, the general polymorphic transformations of the high-entropy RE 2 O 3 follow the trend of single-RE RE 2 O 3 , but the transition temperatures differ from those of single-RE RE 2 O 3 . The coefficient of thermal expansion values of the B-type phase of compositions 1 and 2 are similar to those of Gd 2 O 3 and previously published high-entropy RE 2 O 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.

36 MATERIALS SCIENCE↗

Modification of Lie's transform perturbation theory for charged particle motion in a magnetic field

It is pointed out that the conventional Lie transform perturbation theory for the guiding center motion of charged particles in a magnetic field needs to be modified for ordering inconsistency. There are two reasons. First, the ordering difference between the temporal variation of gyrophase and that of the other phase space coordinates needs to be taken into account. Second, it is also important to note that the parametric limit of the derivative of a function is not equivalent to the derivative of the limit function. When these facts are taken into account, the near identity transformation rule for one form related to the Lagrangian is modified. With the modified near identity transformation rule, the drift motion of charged particles can be described in the first order, instead of the second order and beyond through a tedious expansion process as in the conventional formulation. Here, this resolves the discrepancy between the direct and Lie transform treatments in the Lagrangian perturbation theory for charged particle motion in a magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of Numerical Models of the Offshore Wind Turbine From the Alpha Ventus Wind Farm Against Full-Scale Measurements Within OC5 Phase III

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project validates OWT models against the measurements recorded on a Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. The following operating conditions of the wind turbine were chosen for the validation: (1) idling below the cut-in wind speed, (2) rotor-nacelle assembly (RNA) rotation maneuver below the cut-in wind speed, (3) power production below and above the rated wind speed, and (4) shutdown. A number of validation load cases were defined based on these operating conditions. The following measurements were used for validation: (1) strains and accelerations recorded on the support structure and (2) pitch, yaw, and azimuth angles, generator speed, and electrical power recorded from the RNA. Strains were not directly available from the majority of the OWT simulation tools; therefore, strains were calculated based on out-of-plane bending moments, axial forces, and cross-sectional properties of the structural members. The simulation results and measurements were compared in terms of time series, discrete Fourier transforms, power spectral densities, and probability density functions of strains and accelerometers. A good match was achieved between the measurements and models setup by OC5 Phase III participants.

17 WIND ENERGY↗

Neural network surrogate models for equations of state

Equation of state (EOS) data provide necessary information for accurate multiphysics modeling, which is necessary for fields such as inertial confinement fusion. Here, we suggest a neural network surrogate model of energy and entropy and use thermodynamic relationships to derive other necessary thermodynamic EOS quantities. We incorporate phase information into the model by training a phase classifier and using phase-specific regression models, which improves the modal prediction accuracy. Our model predicts energy values to 1% relative error and entropy to 3.5% relative error in a log-transformed space. Although sound speed predictions require further improvement, the derived pressure values are accurate within 10% relative error. Our results suggest that neural network models can effectively model EOS for inertial confinement fusion simulation applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

TiN‐Au/HfO 2 ‐Au Multilayer Thin Films with Tunable Hyperbolic Optical Response

Abstract Hyperbolic metamaterials (HMM) possess significant anisotropic physical properties and tunability and thus find many applications in integrated photonic devices. HMMs consisting of metal and dielectric phases in either multilayer or vertically aligned nanocomposites (VAN) form are demonstrated with different hyperbolic properties. Herein, self‐assembled HfO 2 ‐Au/TiN‐Au multilayer thin films, combining both the multilayer and VAN designs, are demonstrated. Specifically, Au nanopillars embedded in HfO 2 and TiN layers forming the alternative layers of HfO 2 ‐Au VAN and TiN‐Au VAN. The HfO 2 and TiN layer thickness is carefully controlled by varying laser pulses during pulsed laser deposition (PLD). Interestingly, tunable anisotropic physical properties can be achieved by adjusting the bi‐layer thickness and the number of the bi‐layers. Type II optical hyperbolic dispersion can be obtained from high layer thickness structure (e.g., 20 nm), while it can be transformed into Type I optical hyperbolic dispersion by reducing the thickness to a proper value (e.g., 4 nm). This new nanoscale hybrid metamaterial structure with the three‐phase VAN design shows great potential for tailorable optical components in future integrated devices.

Chemistry↗

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. Here, the deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

36 MATERIALS SCIENCE↗