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At least 757 records · Page 42

Uncertainties in Simulating Flooding During Hurricane Harvey Using 2D Shallow Water Equations

Abstract Flooding is one of the most impactful weather‐related natural hazards. Numerical models that solve the two dimensional (2D) shallow water equations (SWE) represent the first‐principles approach to simulate all types of spatial flooding, such as pluvial, fluvial, and coastal flooding, and their compound dynamics. High spatial resolution (e.g., () m) is needed in 2D SWE simulations to capture flood dynamics accurately, resulting in formidable computational challenges. Thus, relatively coarser spatial resolutions are used for large‐scale simulations of flooding, which introduce uncertainties in the results. It is unclear how the uncertainty associated with the model resolution compares to the uncertainties in precipitation data sets and assumptions regarding boundary conditions when channelized flows interact with other water bodies. In this study, we compare these three sources of uncertainties in 2D SWE simulations for the 2017 Houston flooding event. Our results show that precipitation uncertainty and mesh resolution have more significant impacts on the simulated streamflow and inundation dynamics than the choice of the downstream boundary condition at the watershed outlet. We point out the viability to confine the uncertainty of coarsening mesh resolution by using the variable resolution mesh (VRM) which refines critical topographic features with far fewer grid cells. Specifically, in simulations with VRM, the simulated inundation depths over the refined region are comparable to that use the finest uniform mesh. This study contributes to understanding the challenges and pathways for applying 2D SWE models to improve the realism of flood simulations over large scales.

54 ENVIRONMENTAL SCIENCES↗

A Hybrid Biophysical‐Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy ( LE ) and sensible heat ( H ) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R 2 = 0.81–0.94) and H (R 2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

evapotranspiration↗

Dark matter from axion strings with adaptive mesh refinement

Abstract Axions are hypothetical particles that may explain the observed dark matter density and the non-observation of a neutron electric dipole moment. An increasing number of axion laboratory searches are underway worldwide, but these efforts are made difficult by the fact that the axion mass is largely unconstrained. If the axion is generated after inflation there is a unique mass that gives rise to the observed dark matter abundance; due to nonlinearities and topological defects known as strings, computing this mass accurately has been a challenge for four decades. Recent works, making use of large static lattice simulations, have led to largely disparate predictions for the axion mass, spanning the range from 25 microelectronvolts to over 500 microelectronvolts. In this work we show that adaptive mesh refinement simulations are better suited for axion cosmology than the previously-used static lattice simulations because only the string cores require high spatial resolution. Using dedicated adaptive mesh refinement simulations we obtain an over three order of magnitude leap in dynamic range and provide evidence that axion strings radiate their energy with a scale-invariant spectrum, to within ~5% precision, leading to a mass prediction in the range (40,180) microelectronvolts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Structural basis for breadth development in the HIV-1 V3-glycan targeting DH270 antibody clonal lineage

Antibody affinity maturation enables adaptive immune responses to a wide range of pathogens. In some individuals broadly neutralizing antibodies develop to recognize rapidly mutating pathogens with extensive sequence diversity. Vaccine design for pathogens such as HIV-1 and influenza has therefore focused on recapitulating the natural affinity maturation process. Here, we determine structures of antibodies in complex with HIV-1 Envelope for all observed members and ancestral states of the broadly neutralizing HIV-1 V3-glycan targeting DH270 antibody clonal B cell lineage. These structures track the development of neutralization breadth from the unmutated common ancestor and define affinity maturation at high spatial resolution. By elucidating contacts mediated by key mutations at different stages of antibody development we identified sites on the epitope-paratope interface that are the focus of affinity optimization. Thus, our results identify bottlenecks on the path to natural affinity maturation and reveal solutions for these that will inform immunogen design aimed at eliciting a broadly neutralizing immune response by vaccination.

60 APPLIED LIFE SCIENCES↗

Non-linear enhancement of ultrafast X-ray diffraction through transient resonances

Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI). State-of-the-art X-ray snapshots lack high spatial resolution because of weak diffraction signal. Bleaching effects from photo-ionization significantly restrain image brightness scaling. We find that non-linear transient ion resonances can overcome this barrier if X-ray laser pulses are shorter than in most experiments. We compared snapshots from individual ≈ 100 nm Xe nanoparticles as a function of pulse duration and incoming X-ray fluence. Our experimental results and Monte Carlo simulations suggest that transient resonances can increase ionic scattering cross sections significantly beyond literature values. This provides a novel avenue towards substantial improvement of the spatial resolution in CDI in combination with sub-femtosecond temporal precision at the nanoscale.

47 OTHER INSTRUMENTATION↗

Strain-associated nanoscale fluctuating lithium transport within single-crystalline LiNi 1/3 Mn 1/3 Co 1/3 O 2 cathode particles

Solid-state lithium diffusion dynamics are critical for the rate capability and longevity of Li-ion batteries. Conventionally, nanoscale lithium diffusion within individual battery particles has been simplified as being primarily driven by concentration gradients, despite the associated processes inducing local lattice expansion, contraction, and strain fields. Using operando scanning transmission soft X-ray microscopy with high spatial resolution and chemical sensitivity to track nanoscale intraparticle lithium transport, and post-cycling Bragg coherent diffraction X-ray imaging to directly reveal three-dimensional intraparticle strain fields, we uncover strain-associated lithium transport dynamics within single-crystalline LiNi 1/3 Mn 1/3 Co 1/3 O 2 (scNMC) particles during cycling. Contrary to the expected thermodynamic solid-solution behavior of scNMC, our observations reveal near-uniform but fluctuating regions of lithium-dense and lithium-dilute areas during cycling. These fluctuations suggest that nanoscale lithium diffusion can proceed counter to concentration gradients. Additionally, we demonstrate that an increased presence of lithium-dilute regions near the surface enhances lithium surface insertion kinetics, emphasizing the importance of controlling surface lithium distribution to improve rate performance. Our study provides insights into nanoscale solid-state ion transport, with potential applications in batteries, solid-state fuel cells, and memristors.

Lee, Danwon [Seoul National Univ. (Korea, Republic↗

Multi-modal characterization of nitrate reduction nano-catalysts with periodic strain distribution

Strain engineering serves as a pivotal strategy to optimize catalytic activity in electrocatalysis. However, the catalyst sizes under industrial conditions are usually large and even beyond nanometer regime. The critical methodological limitations on strain imaging of such catalysts with both large field of view and high spatial resolution obscure the mechanistic understanding of strain-performance correlations. Here, we present an optimized four-dimensional scanning transmission electron microscopy (4D-STEM) method to acquire strain mapping of both bulk and surface across particles up to 500 nm with 0.6 nm spatial resolution and 0.55% precision. We observe the ripple-like periodic strain coupled with elemental fluctuations inside a perovskite-type hydroxide CuCoSn(OH) 6 and find it correlated to electrocatalytic nitrate reduction (NO 3 – RR) absorption energy to achieve the 92.6% Faradaic efficiency and long-term test over 1000 h at membrane electrode assembly (MEA) for ammonia electrosynthesis. This universal framework design offers a practical method that not only develops an advanced measurement combining multi-modal characterization techniques but also reveals the intrinsic structure-property constitutive law of industry-level catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Differential programming enabled functional imaging with Lorentz transmission electron microscopy

Abstract Lorentz transmission electron microscopy is an advanced characterization technique that enables the simultaneous imaging of both the microstructure and functional properties of materials. Information such as magnetization and electric potentials is carried by the phase of the electron wave, and is lost during image acquisition. Various methods have been proposed to retrieve the phase of the electron wavefunction using intensities of the acquired images, most of which work only in the small defocus limit. Imaging at strong defoci not only carries more quantitative phase information, but is essential to the study of weak magnetic and electrostatic fields at the nanoscale. In this work we develop a method based on differentiable programming to solve the inverse problem of phase retrieval. We show that our method maintains a high spatial resolution and robustness against noise even at the upper defocus limit of the microscope. More importantly, our proposed method can go beyond recovering just the phase information. We demonstrate this by retrieving the electron-optical parameters of the contrast transfer function alongside the electron exit wavefunction.

97 MATHEMATICS AND COMPUTING↗

Symmetric carbon tetramers forming spin qubits in hexagonal boron nitride

Abstract Point defect quantum bits in semiconductors have the potential to revolutionize sensing at atomic scales. Currently, vacancy-related defects are at the forefront of high spatial resolution and low-dimensional sensing. On the other hand, it is expected that impurity-related defect structures may give rise to new features that could further advance quantum sensing in low dimensions. Here, we study the symmetric carbon tetramer clusters in hexagonal boron nitride and propose them as spin qubits for sensing. We utilize periodic-DFT and quantum chemistry approaches to reliably and accurately predict the electronic, optical, and spin properties of the studied defect. We show that the nitrogen-centered symmetric carbon tetramer gives rise to spin state-dependent optical signals with strain-sensitive intersystem crossing rates. Furthermore, the weak hyperfine coupling of the defect to their spin environments results in a reduced electron spin resonance linewidth that can enhance sensitivity.

Chemistry↗

Low-symmetry vacancy-related spin qubit in hexagonal boron nitride

Abstract Point defect qubits in semiconductors have demonstrated their outstanding capabilities for high spatial resolution sensing generating broad multidisciplinary interest. Hexagonal boron nitride (hBN) hosting point defect qubits have recently opened up new horizons for quantum sensing by implementing sensing foils. The sensitivity of point defect sensors in hBN is currently limited by the linewidth of the magnetic resonance signal, which is broadened due to strong hyperfine couplings. Here, we report on a vacancy-related spin qubit with an inherently low symmetry configuration, the VB2 center, giving rise to a reduced magnetic resonance linewidth at zero magnetic fields. The VB2 center is also equipped with a classical memory that can be utilized for storing population information. Using scanning transmission electron microscopy imaging, we confirm the existence of the VB2 configuration in free-standing monolayer hBN.

Chemistry↗

Expanded modelling scenarios to understand the role of offshore wind in decarbonizing the United States

An assessment of decarbonization pathways in energy models reveals fundamental limitations in representing factors that are relevant for practical decision-making. Although these modelling limitations are widely acknowledged, their impact on the deployment of individual power generation types is not well understood. As a result, the societal value from such generation types could be vastly misrepresented. Here we explore a wide spectrum of factors that impact offshore wind deployment in the United States using a detailed capacity expansion model. Many factors prescribe a large future role for offshore wind, yet this diverges from what models often show. We extend the typically narrow modelling context through high spatial resolution, several cost and transmission possibilities and various energy-sector policies. Further, we estimate offshore wind to constitute 1-8% (31-256 gigawatts) of total US generation by 2050. This wide range suggests an uncertain but potentially important regional role. Our expansive scenarios demonstrate how to address many limitations of decarbonization modelling.

17 WIND ENERGY↗

Single-defect phonons imaged by electron microscopy

Crystal defects affect the thermal and heat-transport properties of materials by scattering phonons and modifying phonon spectra. To appreciate how imperfections in solids influence thermal conductivity and diffusivity, it is thus essential to understand phonon–defect interactions. Sophisticated theories are available to explore such interactions, but experimental validation is limited because most phonon-detecting spectroscopic methods do not reach the high spatial resolution needed to resolve local vibrational spectra near individual defects. In this paper, we demonstrate that space- and angle-resolved vibrational spectroscopy in a transmission electron microscope makes it possible to map the vibrational spectra of individual crystal defects. We detect a red shift of several millielectronvolts in the energy of acoustic vibration modes near a single stacking fault in cubic silicon carbide, together with substantial changes in their intensity, and find that these changes are confined to within a few nanometres of the stacking fault. These observations illustrate that the capabilities of a state-of-the-art transmission electron microscope open the door to the direct mapping of phonon propagation around defects, which is expected to provide useful guidance for engineering the thermal properties of materials.

42 ENGINEERING↗

Visualizing interaction-driven restructuring of quantum Hall edge states

Many topological phases host gapless boundary modes that can be dramatically modified by electronic interactions. Even for the long-studied edge modes of quantum Hall phases, forming at the boundaries of two-dimensional (2D) electron systems, the nature of such interaction-induced changes has been elusive. Despite advances made using local probes, key experimental challenges persist: the lack of direct information about the internal structure of edge states on microscopic scales, and complications from edge disorder. Here, we use scanning tunneling microscopy (STM) to image pristine electrostatically defined quantum Hall edge states in graphene with high spatial resolution and demonstrate how correlations dictate the structures of edge channels on both magnetic and atomic length scales. For integer quantum Hall states in the zeroth Landau level, we show that interactions renormalize the edge velocity, dictate the spatial profile for copropagating modes, and induce unexpected edge valley polarization that differ from those of the bulk. While some of our findings can be understood by mean-field theory, others show breakdown of this picture, highlighting the roles of edge fluctuations and inter-channel couplings. We also extend our measurements to spatially resolve the edge state of fractional quantum Hall phases and detect spectroscopic signatures of interactions in this chiral Luttinger liquid. Furthermore, our study establishes STM as a promising tool for exploring edge physics of the rapidly expanding 2D topological phases, including newly realized fractional Chern insulators.

Electronic properties and materials↗

Extreme flood return levels in a U.S. mid-Atlantic estuary using 40-year fluvial-coastal model simulations

Using an integrated watershed-coastal modeling framework, we conducted long-term historical simulations (1980-2019) of fluvial and coastal flooding in the Delaware Bay and River, a vulnerable estuarine system in the U.S., at high spatial resolutions. By applying process-based models, we generated physically consistent and spatially detailed estimates of estuarine, riverine, and surge-driven extreme water level compared to previous studies that used field data only. We then evaluated changes in the magnitude of flood events using the 40-year simulations and detrended Floodwater Depth values with stationary extreme value analysis. Our detailed assessment of spatial-varying extreme values revealed how different flood-generation mechanisms can dominate various zones in the estuary. The datasets produced through this work will be valuable for long-term flood hazard mitigation planning in coastal communities in the Delaware Bay and River region. Additionally, this work will serve as a benchmark for other coastal flood hazard modeling communities worldwide, aiding them in systematically modeling long-term and continuous extreme flood events.

Coastal and Riverine Flooding↗

Absolute contrast estimation for soft X-ray photon fluctuation spectroscopy using a variational droplet model

Abstract X-ray photon fluctuation spectroscopy using a two-pulse mode at the Linac Coherent Light Source has great potential for the study of quantum fluctuations in materials as it allows for exploration of low-energy physics. However, the complexity of the data analysis and interpretation still prevent recovering real-time results during an experiment, and can even complicate post-analysis processes. This is particularly true for high-spatial resolution applications using CCDs with small pixels, which can decrease the photon mapping accuracy resulting from the large electron cloud generation at the detector. Droplet algorithms endeavor to restore accurate photon maps, but the results can be altered by their hyper-parameters. We present numerical modeling tools through extensive simulations that mimic previous x-ray photon fluctuation spectroscopy experiments. By modification of a fast droplet algorithm, our results demonstrate how to optimize the precise parameters that lift the intrinsic counting degeneracy impeding accuracy in extracting the speckle contrast. These results allow for an absolute determination of the summed contrast from multi-pulse x-ray speckle diffraction, the modus operandi by which the correlation time for spontaneous fluctuations can be measured.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nanometre-resolved observation of electrochemical microenvironment formation at the nanoparticle–ligand interface

The dynamic response of surface ligands on nanoparticles (NPs) to external stimuli critically determines the functionality of NP–ligand systems. For example, in electrocatalysis the collective dissociation of ligands on NP surfaces can lead to the creation of an NP/ordered-ligand interlayer, a microenvironment that is highly active and selective for CO 2 -to-CO conversion. However, the lack of in situ characterization techniques with high spatial resolution hampers a comprehensive molecular-level understanding of the mechanism of interlayer formation. Here, in this work, we utilize in situ infrared nanospectroscopy and surface-enhanced Raman spectroscopy, unveiling an electrochemical bias-induced consecutive bond cleavage mechanism of surface ligands leading to formation of the NP/ordered-ligand interlayer. This real-time molecular insight could influence the design of confined localized fields in multiple catalytic systems. Moreover, the demonstrated capability of capturing nanometre-resolved, dynamic molecular-scale events holds promise for the advancement of using controlled local molecular behaviour to achieve desired functionalities across multiple research domains in nanoscience.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The GAPS programme at TNG

Neptunes represent one of the main types of exoplanets and have chemical-physical characteristics halfway between rocky and gas giant planets. Therefore, their characterization is important for understanding and constraining both the formation mechanisms and the evolution patterns of planets. We investigate the exoplanet candidate TOI-1422 b, which was discovered by the TESS space telescope around the high proper-motion G2 V star TOI-1422 (V = 10.6 mag), 155 pc away, with the primary goal of confirming its planetary nature and characterising its properties. We monitored TOI-1422 with the HARPS-N spectrograph for 1.5 yr to precisely quantify its radial velocity (RV) variation. We analyse these RV measurements jointly with TESS photometry and check for blended companions through high-spatial resolution images using the AstraLux instrument. We estimate that the parent star has a radius of R$_\star$ = 1.019 -0.013 +0.014 R ⊙ , and a mass of M$_\star$ = 1.019 -0.013 +0.014 M ⊙ . Our analysis confirms the planetary nature of TOI-1422 b and also suggests the presence of a Neptune-mass planet on a more distant orbit, the candidate TOI-1422 c, which is not detected in TESS light curves. The inner planet, TOI-1422 b, orbits on a period of P b = 12.9972 ± 0.0006 days and has an equilibrium temperature of T eq,b = 867 ± 17 K. With a radius of R b = 3.96 -0.11 +0.13 R ⊕ , a mass of M b = 9.0 -2.0 +2.3 M ⊕ and, consequently, a density of ρ b = 0.795 -0.235 +0.290 g cm -3 , it can be considered a warm Neptune-sized planet. Compared to other exoplanets of a similar mass range, TOI-1422 b is among the most inflated, and we expect this planet to have an extensive gaseous envelope that surrounds a core with a mass fraction around 10% – 25% of the total mass of the planet. The outer non-transiting planet candidate, TOI-1422 c, has an orbital period of P c = 29.29 -0.20 +0.21 days, a minimum mass, M c sin i, of 11.1 -2.3 +2.6 M ⊕ , an equilibrium temperature of T eq,c = 661 ± 13 K and, therefore, if confirmed, could be considered as another warm Neptune.

79 ASTRONOMY AND ASTROPHYSICS↗

MUSE adaptive-optics spectroscopy confirms dual active galactic nuclei and strongly lensed systems at sub-arcsec separation

The novel Gaia multi peak (GMP) technique has proven to be able to successfully select dual and lensed active galactic nuclei (AGN) candidates at sub-arcsecond separations. Both populations are important because dual AGN represent one of the central, still largely untested, predictions of ΛCDM cosmology, and compact lensed AGN allow us to probe the central regions of the lensing galaxies. In this work, we present high-spatial-resolution spectroscopy of 12 GMP-selected systems. We used the adaptive-optics assisted integral-field spectrograph MUSE at the VLT to resolve each system and investigate the nature of each component. All targets show the presence of two components confirming the GMP selection. We classify 4 targets as dual AGN, 3 as lensed quasar candidates, and 5 as a chance alignment of a star and an AGN. With separations ranging from 0.30″ to 0.86″, these dual and lensed systems are among the most compact systems discovered to date at z > 0.5. This is the largest sample of distant dual AGN with sub-arcsecond separations ever presented in a single paper.

Scialpi, M. (ORCID:0009000651004986)↗