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At least 379 records · Page 21

Optimization of the Growth of the Van der Waals Materials Bi 2 Se 3 and (Bi 0.5 In 0.5 ) 2 Se 3 by Molecular Beam Epitaxy

The naturally existing chalcogenide Bi 2 Se 3 is topologically nontrivial due to the band inversion caused by the strong spin-orbit coupling inside the bulk of the material. Here, the surface states are spin polarized, protected by the time-inversion symmetry, and thus robust to the scattering caused by nonmagnetic defects. A high-purity topological insulator thin film can be easily grown via molecular beam epitaxy (MBE) on various substrates to enable novel electronics, optics, and spintronics applications. However, the unique surface state properties have historically been limited by the film quality, which is evaluated by crystallinity, surface morphology, and transport data. Here we propose and investigate different MBE growth strategies to improve the quality of Bi 2 Se 3 thin films grown by MBE. Based on the surface passivation status, we have classified the substrates into two categories, self-passivated or unpassivated, and determine the optimal growth mechanisms on the representative sapphire and GaAs, respectively. For Bi 2 Se 3 on GaAs, the surface passivation status determines the dominant growth mechanism. In the end, growths of the topological trivial insulator (Bi 0.5 In 0.5 ) 2 Se 3 (BIS) on GaAs are investigated following the protocols proposed.

36 MATERIALS SCIENCE↗

Structurally colored protease responsive nanoparticle hydrogels with degradation-directed assembly

A tunable protease responsive nanoparticle hydrogel (PRNH) that demonstrates large non-iridescent color changes due to a degradation-directed assembly of nanoparticles is reported. Structurally colored composites are fabricated with silica particles, 4-arm poly(ethylene glycol) norbornene (4PEGN), and a proteolytically degradable peptide. When placed in a protease solution, the peptide crosslinks degrade causing electrostatic binding and adsorption of the polymer to the particle surface which leads to the assembly of particles into compact amorphous arrays with structural color. The particle surface charge and size is investigated to probe their effect on the assembly mechanism. Interestingly, only PRNHs with highly negative particle surface charge exhibit color changes after degradation. Ultra-small angle X-ray scattering revealed that the particles become coated in polymer after degradation, producing a material with less order compared to the initial state. Altering the particle diameter modulates the composites’ color, and all sizes investigated (178–297 nm) undergo the degradation-directed assembly. Varying the amount of 4PEGN adjusts the swollen PRNH color and has no effect on the degradation-directed assembly. Finally, taken together, the effects of surface charge, particle size, and polymer concentration allow for the formulation of new design rules for fabricating tunable PRNHs that display vivid changes in structural color upon degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural basis of cell-surface signaling by a conserved sigma regulator in Gram-negative bacteria

Cell-surface signaling (CSS) in Gram-negative bacteria involves highly conserved regulatory pathways that optimize gene expression by transducing extracellular environmental signals to the cytoplasm via inner-membrane sigma regulators. The molecular details of ferric siderophore-mediated activation of the iron import machinery through a sigma regulator are unclear. Here, we present the 1.56 Å resolution structure of the periplasmic complex of the C-terminal CSS domain (CCSSD) of PupR, the sigma regulator in the Pseudomonas capeferrum pseudobactin BN7/8 transport system, and the N-terminal signaling domain (NTSD) of PupB, an outer-membrane TonB-dependent transducer. The structure revealed that the CCSSD consists of two subdomains: a juxta-membrane subdomain, which has a novel all-β-fold, followed by a secretin/TonB, short N-terminal subdomain at the C terminus of the CCSSD, a previously unobserved topological arrangement of this domain. Using affinity pulldown assays, isothermal titration calorimetry, and thermal denaturation CD spectroscopy, we show that both subdomains are required for binding the NTSD with micromolar affinity and that NTSD binding improves CCSSD stability. Our findings prompt us to present a revised model of CSS wherein the CCSSD:NTSD complex forms prior to ferric-siderophore binding. Upon siderophore binding, conformational changes in the CCSSD enable regulated intramembrane proteolysis of the sigma regulator, ultimately resulting in transcriptional regulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strain-Driven Surface Reactivity in Magnesium-Ion Battery Cathodes

Successful deployment of a Mg-ion battery requires cathodes that can achieve reversible Mg intercalation and high energy density. Recent theoretical and experimental studies indicated that the overall transport is likely limited by sluggish Mg transport at the cathode-electrolyte interface and not Mg diffusion through bulk. Here, in this work, we investigated the surface electrochemical activity of Mg ions by using a spinel-structured manganese oxide thin-film model system and in situ X-ray scattering. In combination with post-mortem microscopy analysis, we found that magnesium insertion was more favorable than subsequent extraction near the surface of the Mg x Mn 2 O 4 film, resulting in overmagnesiation, and eventually amorphization of the surface. This structural irreversibility and high overpotential required for Mg extraction could explain significant voltage hysteresis and Mg surface enrichment previously observed in bulk cathodes. Density functional theory calculations suggested that the tendency for the Mg surface enrichment could be associated with Mg diffusion kinetics, which varies with the strain state evolved due to constrained film volume change during Mg insertion and extraction. Particularly, out-of-plane Mg migration was predicted to be favorable in the tensile strain rather than in the compressive case.

25 ENERGY STORAGE↗

Inelastic Neutron Scattering Observation of Plasma-Promoted Nitrogen Reduction Intermediates on Ni/γ-Al 2 O 3

Plasma-assisted catalysis is an emerging technology for the atmospheric pressure and low bulk gas temperature synthesis of ammonia from molecular nitrogen and hydrogen. Direct evidence for plasma-induced surface reaction intermediates relevant to ammonia production, including surface hydrides and NH x (x = 1, 2, 3) species, has remained elusive. In this work, we report inelastic neutron scattering (INS) observations of alumina-supported Ni particles after treatment with N 2 and H 2 plasmas. INS experiments reveal the presence of NH x species and hydrides on Ni sites after exposure to sequential N 2 and H 2 plasma treatments. By separating exposure, we exclude the presence of plasma-phase reactions and demonstrate that these species are generated through plasma-facilitated surface reactions. Computed synthetic INS spectra of NH 3 , NH 2 and NH adsorbates on Ni support the experimental assignments of surface intermediates. The results directly implicate plasma stimulation of dinitrogen in generation of surface-bound nitrogen that participates in further hydrogenation reactions driven either thermally or with H 2 plasma.

36 MATERIALS SCIENCE↗

Bridging Structural and Chemical Insights: Integrating In Situ Electron Microscopy and X-ray Spectroscopy for Catalysis Research

Environmental transmission electron microscopy probes the local structure, composition, and chemistry of materials under gas environments, while ambient-pressure X-ray photoelectron spectroscopy provides ensemble chemical and electronic structure information in gaseous conditions. Both techniques utilize similar differential pumping schemes to mitigate electron scattering by the gas phase, allowing for unique opportunities to correlate gas–surface interactions across comparable pressure ranges. Their integration has advanced the understanding of various catalytic reactions, including the water–gas-shift reaction, CO oxidation, and surface passivation dynamics. In conclusion, this Mini-Review discusses their methodological advancements, challenges, and potential for further integration with other in situ techniques to address complex catalytic phenomena and guide catalyst design.

36 MATERIALS SCIENCE↗

Elucidating molecular scale interactions underlying the freezing behavior of salt solutions in silica nanopores

Elucidating the influence of nanoscale confinement on the freezing behavior of salt solutions is of fundamental interest to environmental security and materials science and engineering. Specific structural information such as the coordination environment of ions in confined aqueous medium, effects on the extended hexagonal network of water molecules and their mutual non-bonding interactions in confinement are sparse in the literature along with the change in the dynamical characteristics of water in the presence of ions. To address these knowledge gaps, the current study is focused on investigating the influence of reduced dimensionality arising from nanoscale confinement on the structural evolution of salt solutions on freezing and the associated fluid–surface interactions. In this regard, operando wide-angle X-ray scattering (WAXS) measurements and classical molecular dynamics (MD) simulations are conducted with water and 0.5 M CaCl 2 , MgCl 2 and KCl solutions confined in 4 nm sized SBA-15 silica pores upon cooling from 300 K to 200 K. The freezing point of the salt solutions is depressed to 235 K which is about 10 K lower than that of confined water. The translational dynamics of confined salt solutions indicates shifts in the fragile-to-strong dynamical crossover to a lower temperature compared to pure water. The strong electrostatic attraction between the cations and the surrounding water molecules contributes to the freezing point depression in confined salt solutions. These insights unlock the molecular-scale basis and mechanisms underlying the freezing behavior of confined salt solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A prescription for the asteroseismic surface correction

In asteroseismology, the surface effect refers to a disparity between the observed and the modelled frequencies in stars with solar-like oscillations. It originates from improper modelling of the surface layers. Correcting the surface effect usually requires using functions with free parameters, which are conventionally fitted to the observed frequencies. On the basis that the correction should vary smoothly across the H–R diagram, we parameterize it as a simple function of surface gravity, effective temperature, and metallicity. We determine this function by fitting a wide range of stars. The absolute amount of the surface correction decreases with luminosity, but the ratio between it and νmax increases, suggesting the surface effect is more important for red giants than dwarfs. Applying the prescription can eliminate unrealistic surface correction, which improves parameter estimations with stellar modelling. Using two open clusters, we found a reduction of scatter in the model-derived ages for each star in the same cluster. As an important application, we provide a new revision for the Δν scaling relation that, for the first time, accounts for the surface correction. The values of the correction factor, f Δν , are up to 2 percent smaller than those determined without the surface effect considered, suggesting decreases of up to 4 percent in radii and up to 8 percent in masses when using the asteroseismic scaling relations. This revision brings the asteroseismic properties into an agreement with those determined from eclipsing binaries. The new correction factor and the stellar models with the corrected frequencies are available at https://www.github.com/parallelpro/surface.

79 ASTRONOMY AND ASTROPHYSICS↗

Bayesian inference for plasmonic nanometrology

Here, we introduce a Bayesian method for the characterization of plasmonic nanoparticles, which is applicable to both near- and far-field problems. Designed to combine data generated from any photon-plasmon interaction experiment with physically motivated theoretical models, our approach leverages state-of-the-art Markov chain Monte Carlo sampling techniques and returns parameter estimates on nanometric scales. Simulated spectral data sets, describing resonant scattering of photons from ellipsoidal and toroidal nanoparticles, are explored as concrete examples of our approach, with the resulting Bayesian estimates showing excellent agreement with the ground truth, even under conditions of high statistical noise. By incorporating Bayes factors into the method as well, we reveal how model selection can determine which one of competing geometric shapes better explains the observed data. Our comprehensive nanometrology procedure can be tailored to a variety of light-particle interaction models, and its reliance on Bayesian inference furnishes automatic uncertainty quantification. In addition to applicability to a host of plasmonic configurations such as nanoparticle dimers, trimers, and array studies, it is proposed that the presented analysis can be extended to the quantum regime, where nonclassical photon statistics may provide additional insight for inference of scatterer properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Plasmonics in argentene

Merging concepts from the fields of ab initio materials science and nanophotonics, there is now an opportunity to engineer new photonic materials whose optical, transport, and scattering properties are tailored to attain thermodynamic and quantum limits. Here we present first-principles calculations predicting that Argentene, a single-crystalline hexagonal close-packed monolayer of Ag, can dramatically surpass the optical properties and electrical conductivity of conventional plasmonic materials. In the low-frequency limit, we show that the scattering rate and resistivity reduce by a factor of 3 compared to the bulk three-dimensional metal. Most importantly, the low scattering rate extends to optical frequencies in sharp contrast to, e.g., graphene, whose scattering rate increase drastically in the near-infrared range due to optical-phonon scattering. Combined with an intrinsically high carrier density, this facilitates highly confined surface plasmons extending to visible frequencies. We evaluate Argentene across three distinct figures of merit, in each outperforming the state-of-the-art, making it a valuable addition to the two-dimensional heterostructure toolkit for quantum optoelectronics.

36 MATERIALS SCIENCE↗

CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning

In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.

36 MATERIALS SCIENCE↗

Multiple origins of extra electron diffractions in fcc metals

Diffuse intensities in the electron diffraction patterns of concentrated face-centered cubic solid solutions have been widely attributed to chemical short-range order, although this connection has been recently questioned. This article explores the many nonordering origins of commonly reported features using a combination of experimental electron microscopy and multislice diffraction simulations, which suggest that diffuse intensities largely represent thermal and static displacement scattering. A number of observations may reflect additional contributions from planar defects, surface terminations incommensurate with bulk periodicity, or weaker dynamical effects.

36 MATERIALS SCIENCE↗

Wind Turbine Lightning Mitigation System Radar Cross Section Reduction

Modern wind turbines employ Lightning Mitigation Systems (LMSs) in order to reduce costly damages caused by lightning strikes. Lightning strikes on wind turbines occur frequently making LMS configurations a necessity. An LMS for a single turbine includes, among other equipment, cables running inside each blade, along the entire blade length. These cables are connected to various metallic receptors on the outside surface of the blades. The LMS cables can act as significant electromagnetic scatterers which may cause interference to radar systems. This interference may be mitigated by reducing the Radar Cross-Section (RCS) of the wind turbine's LMS. This report investigates proposed modifications to LMS cables in order to reduce the RCS when illuminated by Re locatable Over the Horizon Radar (ROTHR) systems which operate in the HF band (3 - 30 MHz). The proposed modifications include breaking up the LMS cables using spark gap connections, and changing the orientation of the LMS cable within the turbine blade. Both simulated analyses of such RCS mitigation techniques is provided as well as recommendations on further research.

17 WIND ENERGY↗

Hybrid Bio-Based Composites: Enabling Cellulose Nanofiber (CNF) Incorporation into Composites via Macroscale Natural Fiber Carriers

Cellulose nanofibers (CNFs) have significant potential in composites as additives to improve mechanical properties, melt rheology, and more. However, agglomeration of CNFs is a key challenge in composite melt processing as obtaining nano-level dispersion of CNFs often requires cost- and energy-intensive processes (e.g., solvent exchange or freeze drying) due to the strong hornification tendencies of CNF. Herein, we avoid these challenges by using a natural fiber carrier method to integrate CNF into thermoplastic composites. Fibers are co-dried to create a hybrid fiber feedstock for compounding in which natural fibers are decorated with dispersed nanofibers. The hybridized fibers result in up to a 24% increase in tensile strength and up to a 35% increase in Young’s modulus compared to composites only containing natural fibers. The lignocellulosic nanofibers are found to outperform their purely cellulosic counterpart, which is theorized to be due to either an increased propensity for fibrillation of the lignocellulosic fibers or the increased hydrophobicity of the fibers due to the presence of lignin. Surface analysis of fiber feedstocks, via streaming potential measurements and dynamic light scattering (DLS), confirmed a significant change in the feedstock hydrophobicity before and after hybridization. While mild additions of CNF (1 wt.% on the macroscale fiber) do not impact the composite melt viscosity, the viscosity is found to increase at higher CNF loadings (5 wt.% on the macroscale fiber), indicating its utility as a rheology modifier. Lastly, use of these materials as novel feedstocks for medium-scale additive manufacturing in high-fidelity part production was demonstrated.

bio-based↗

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

To minimize the eutrophication pressure along the Gulf of Mexico or reduce the size of the hypoxic zone in the Gulf of Mexico, it is important to understand the underlying temporal and spatial variations and correlations in excess nutrient loads, which are strongly associated with the formation of hypoxia. This study’s objective was to reveal and visualize structures in high-dimensional datasets of nutrient yield distributions throughout the Mississippi/Atchafalaya River Basin (MARB). For this purpose, the annual mean nutrient concentrations were collected from thirty-three US Geological Survey (USGS) water stations scattered in the upper and lower MARB from 1996 to 2020. Eight surface water quality indicators were selected to make comparisons among water stations along the MARB over the past two decades. Principal component analysis (PCA) was used to comprehensively evaluate the nutrient yields across thirty-three USGS monitoring stations and identify the major contributing nutrient loads. The results showed that all samples could be analyzed using two main components, which accounted for 81.6% of the total variance. The PCA results showed that yields of orthophosphate (OP), silica (SI), nitrate–nitrites (NO 3 -NO 2 ), and total suspended sediment (TSS) are major contributors to nutrient yields. It also showed that land-planted crops, density of population, domestic and industrial discharges, and precipitation are fundamental causes of excess nutrient loads in MARB. These factors are of great significance for the excess nutrient load management and pollution control of the Mississippi River. It was found that the average nutrient yields were stable within the sub-MARB area, but the large nitrogen yields in the upper MARB and the large phosphorus yields in the lower MARB were of great concern. t-distributed stochastic neighbor embedding (t-SNE) revealed interesting nonlinear and local structures in nutrient yield distributions. Clustering analysis (CA) showed the detailed development of similarities in the nutrient yield distribution. Moreover, PCA, t-SNE, and CA showed consistent clustering results. This study demonstrated that the integration of dimension reduction techniques, PCA, and t-SNE with CA techniques in machine learning are effective tools for the visualization of the structures of the correlations in high-dimensional datasets of nutrient yields and provide a comprehensive understanding of the correlations in the distributions of nutrient loads across the MARB.

54 ENVIRONMENTAL SCIENCES↗

The Anatomy of an Unusual Edge-on Protoplanetary Disk. I. Dust Settling in a Cold Disk

As the earliest stage of planet formation, massive, optically thick, and gas-rich protoplanetary disks provide key insights into the physics of star and planet formation. When viewed edge-on, high-resolution images offer a unique opportunity to study both the radial and vertical structures of these disks and relate this to vertical settling, radial drift, grain growth, and changes in the midplane temperatures. In this work, we present multi-epoch Hubble Space Telescope and Keck scattered light images, and an Atacama Large Millimeter/submillimeter Array 1.3 mm continuum map for the remarkably flat edge-on protoplanetary disk SSTC2DJ163131.2–242627, a young solar-type star in ρ Ophiuchus. We model the 0.8 μm and 1.3 mm images in separate Markov Chain Monte Carlo (MCMC) runs to investigate the geometry and dust properties of the disk using the MCFOST radiative transfer code. In scattered light, we are sensitive to the smaller dust grains in the surface layers of the disk, while the submillimeter dust continuum observations probe larger grains closer to the disk midplane. An MCMC run combining both data sets using a covariance-based log-likelihood estimation was marginally successful, implying insufficient complexity in our disk model. The disk is well characterized by a flared disk model with an exponentially tapered outer edge viewed nearly edge-on, though some degree of dust settling is required to reproduce the vertically thin profile and lack of apparent flaring. A colder than expected disk midplane, evidence for dust settling, and residual radial substructures all point to a more complex radial density profile to be probed with future, higher-resolution observations.

47 OTHER INSTRUMENTATION↗

Simulated effect of edge plasma density parameters on lower hybrid wave scattering in EAST

The incorporation of lower hybrid (LH) wave spectrum broadening in the poloidal wavenumber (⁠k θ ) space at the last close field surface (LCFS) is reported to lead to better agreement of the modeled LH wave current profile with the experimental results [Baek et al., Nucl. Fusion 61, 106034 (2021)]. To further understand its underlying mechanism and find the possible influence factors, effects of wave scattering caused by drift-wave type density fluctuation on the probability distribution of the LH wave polar refractive index (⁠N θ ) at the LCFS are studied under density parameters in the scrape-off-layer. According to a scattering model [P. T. Bonoli and E. Ott, Phys Fluids 25(2), 359–375 (1982)], scattering probability and scattering angle distribution are two main factors that determine the degree of spectral broadening. Studies presented here show that the total scattering probability increases first and then decreases as the wave propagates toward a smaller normalized radius of poloidal magnetic flux (⁠ρ⁠). The degree of spectral broadening is found to depend on the density and density fluctuation together by changing the intensity and a proportion of the geometrical optics approximation term and the E×B drift term in the scattering model. Additionally, the fluctuation correlation length can significantly modify the probability distribution of N θ at the LCFS, which is found to significantly change the LH wave current profile.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗