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At least 397 records · Page 22

Tussock tundra surface temperatures, ambient air and incoming photosynthetically active radiation measured at the NGEE Arctic Council site, 2021 - 2023

This dataset contains temperature measurements carried out along two fiber optics cables/lines (150 m each) laid out along the ground at the Next Generation Ecosystem Experiment (NGEE) Arctic site near Council, Alaska. The lines traverse an heterogeneous part of the tussock tundra site including thermokarst features and lichen dominated sections of the tundra. Measurements were done using a Sensornet Oryx DTS, a Distributed Temperature sensor that was installed in September 2021 and taken down in August 2023. The sensor was powered by solar power with data being collected every 30 minutes at 1 m resolution. In addition to these measurements air temperature and incoming photosynthetically active radiation (PAR) are provided. These measurements are co-located with the NGEE Arctic Council eddy flux and meteorological station (AmeriFlux ID US-NGC). Included are six *.csv files (four data files and two reporting format files) and two *.kml files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Air temperature↗

Molecular Mass Growth Processes to Polycyclic Aromatic Hydrocarbons through Radical–Radical Reactions Exploiting Photoionization Reflectron Time-of-Flight Mass Spectrometry

Polycyclic aromatic hydrocarbons (PAHs) represent critical building blocks in molecular mass growth processes to carbonaceous nanoparticles, referred to as interstellar and circumstellar grains along with soot particles in astrophysical environments and combustion systems, respectively. Recent advancements on elucidating elementary steps to PAHs have utilized reactions of aromatic radicals, resonantly stabilized free radicals, and aliphatic radicals with closed shell hydrocarbons. However, the role of radical–radical reactions (RRRs) leading to PAHs has remained largely unexplored on the molecular level due to preceding experimental challenges in producing sufficiently high number densities of radical reactants for isomer-selective detection of products from bimolecular and termolecular reactions. This Account offers the latest developments in our knowledge on the mechanisms and pathways to PAHs via RRRs probed in a chemical microreactor at temperatures as high as 1600 K. Product preservation in a molecular beam coupled with synchrotron vacuum ultraviolet photoionization reflectron time-of-flight mass spectrometry and photoelectron photoion coincidence spectroscopy enabled isomer-selective detection of PAHs of up to three rings by their photoionization efficiency curves, which were fit with a linear combination of reference curves for identification. Experiments were combined with computational fluid dynamics modeling of the physicochemical processes in the microreactor, as well as high-level electronic structure calculations to reveal the reaction pathways of each system. Six distinct reaction mechanisms were discovered in this work: propargyl addition─benzannulation (PABA), methyl addition─ring expansion (MARE), cyclopentadienyl addition─naphthylization (CPAN), fulvenallenyl addition─cyclization─aromatization (FACA), benzyl addition─aromatization (BAA), and phenyl addition─pentacyclization (PAP). By systematically varying the number of carbon atoms in the radical reactants, molecular mass growth processes involving reactions between radicals with odd numbers of carbon atoms access aromatics carrying one, two, or three six-membered rings, whereas reactions between even- and odd-carbon-numbered radicals produce aromatics combining five- and six-membered rings. Our investigations reveal unconventional cycloadditions on excited state triplet surfaces, additions of radicals to low spin density carbon-centered radicals, spiroaromatic and fulvene-type intermediates, and highly strained bicyclic reaction intermediates, challenging current perceptions of PAH molecular mass growth processes. All of the listed mechanisms, except for FACA, feature endoergic reactions or barriers which lie above the separated reactants and therefore might be central to circumstellar environments of carbon-rich stars and planetary nebulae as their descendants, but they play no role in the gas phase of cold molecular clouds where temperatures as low as 10 K dominate. Altogether, this work provides detailed reaction mechanisms of PAH growth processes, advancing our knowledge of the chemistry of carbonaceous matter in the universe.

Addition reactions↗

Ray-tracing image simulations of transparent objects with complex shape and inhomogeneous refractive index

Optical images of transparent three-dimensional objects can be different from a replica of the object’s cross section in the image plane, due to refraction at the surface or in the body of the object. Simulations of the object’s image are thus needed for the visualization and validation of physical models. We report ray tracing image simulations that achieved high physical fidelity, reproducing optical behaviors and image features not rendered in previous studies. We replicated brightfield microscopy images of drops with complex shapes, and images of pressure and shock waves traveling inside them. For high physical fidelity, the simulations must replicate the spatial and angular distribution of illumination rays, and both the experiment and the simulation must be designed for accurate optical modeling. The simulations are highly sensitive to the properties of the drops and can be used to diagnose and refine fluid dynamics models. The simulated images can also be optimized to extract multiple 3D properties from experimental images. Compared to specialized single-shot 3D imaging methods, this approach has the advantage that it preserves the experimental simplicity, the high resolution, and the visual interpretability characteristic to basic optical imaging. The techniques introduced here are directly applicable to optical microscopy, so they can be used in other fields, such as microfluidics and biology, to expand the type and the accuracy of three-dimensional information that can be extracted from basic optical images.

Cavitation↗

Light-ray wave functions and integrability

Using integrability, we construct (to leading order in perturbation theory) the explicit form of twist-three light-ray operators in planar $\mathcal{N}$ = 4 SYM. This construction allows us to directly compute analytically continued CFT data at complex spin. We derive analytically the “magic” decoupling zeroes previously observed numerically. Using the Baxter equation, we also show that certain Regge trajectories merge together into a single unifying Riemann surface. Perhaps more surprisingly, we find that this unification of Regge trajectories is not unique. If we organize twist-three operators differently into what we call “cousin trajectories” we find infinitely more possible continuations. We speculate about which of these remarkable features of twist-three operators might generalize to other operators, other regimes and other theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Heuristic algorithms for design of integrated monitoring of geologic carbon storage sites

Designs for Risk Evaluation and Management (DREAM) is a tool developed under the National Risk Assessment Partnership (NRAP) to enhance geologic carbon storage safety and efficiency. Using potential leakage scenarios generated externally by the users preferred history-matching approach, DREAM constructs ideal combinations of sensor locations in the right place at the right time to detect as many leaks as possible, detect them as early as possible, and minimize cost. This user-friendly tool, developed in Java, features a window-based GUI for input and a 3D visualization tool for viewing the domain space and optimized monitoring plans. DREAM's latest version accommodates real-world usage by allowing for joint optimization of wellbore point sensor placements and surface geophysics survey geometries, and by using more efficient multi-objective optimization algorithms. We show an example where, these two improvements combined allow us to support containment assurance and go from detecting 80–90 % of the potential CO 2 leakage to +99.7 %, a step-change improvement that can make the deciding difference in whether a site is suitable for geologic carbon storage. Though developed for geologic carbon storage, this tool would be equally applicable in many surface or offshore environmental monitoring projects.

58 GEOSCIENCES↗

Hidden features in the OH-stretching spectra of amino acid decorated air–water interfaces

Chemical reactivity at the air–water interface is governed by the interfacial solvation of reactive species. For instance, during aqueous amino acid-based CO 2 absorption, water reorganizes around the reactive sites and couples dynamically with reaction pathways, facilitating the reaction. In this context, surface-sensitive vibrational sum-frequency generation (vSFG) spectroscopy can probe the OH stretch vibrations of interfacial water and determine the solvation structures around reactants and products, thereby furthering our understanding of the role of interfacial solvation. However, vSFG spectra of the air–water interface in the presence of charged species can be remarkably complex; key species-bound local water structures with distinct orientations may be hidden beneath prominent vSFG peaks arising from water–water hydrogen bonds and remain difficult to resolve. Here, we measure and compute vSFG spectra of the water OH stretch at air–water interfaces decorated with amino acids in their zwitterionic and anionic forms, as well as equimolar mixtures of these forms with bicarbonate. The latter represents post-CO 2 -absorption conditions. We find that computing depth- and frequency-dependent spectral densities—decomposed into contributions from water molecules hydrogen-bonded exclusively to other water molecules, exclusively to amines, exclusively to carboxylates, or shared between these polar/charged groups—is indispensable for accurate interpretation of the vSFG spectra. Key findings include orientational flip-flop in water sub-layers, strong carboxylate-water H-bonding, and water orientational ordering extending into the bulk aqueous phase induced by anionic amino acids. Here, this study provides a computational spectroscopic platform for improved understanding of interfacial solvation relevant to interfacial reactivity.

Air-water interface↗

Templates for Risk Informed Assurance with Curvature Embeddings (TRACE)

We investigate recovery of geometric structure from networks embedded in manifolds with spatially varying curvature, extending the constant-curvature framework of Lubold et al. (2023). Our work supports cascade risk assessment in critical infrastructure through the Templates for Risk-informed Assurance with Curvature Embeddings (TRACE) framework. Simulations on a bi-modal Gaussian surface show that constant-curvature methods yield weighted averages shaped by clique patterns, while hierarchical clustering identifies distinct regimes. Localized estimation, however, reveals boundary contamination in transitional regions. To address heterogeneity, we develop distance metrics for graphs with edge and node features, proving their metric validity, and validate them via deterministic graph generation from canonical tilings. We further propose a diffusion-based anomaly detection approach that treats networks as glued manifolds, using curvature discontinuities to detect structural anomalies. Employing the carré-du-champ operator and scalar curvature, we achieve robust anomaly discrimination, demonstrated on the Singapore Water Treatment (SWaT) dataset with joint network-traffic and sensor features. Integration with TRACE reveals how curvature shapes cascade dynamics: positive curvature impedes, while negative curvature accelerates propagation. This geometric perspective provides interpretable risk metrics and visualization tools for critical infrastructure managers. While full validation remains ongoing, our contributions establish a rigorous foundation for geometric analysis of network resilience and cascade vulnerability.

97 MATHEMATICS AND COMPUTING↗

Environmental Quenching of Low-surface-brightness Galaxies Near Hosts from Large Magellanic Cloud to Milky Way Mass Scales

Low-surface-brightness galaxies (LSBGs) are excellent probes of quenching and other environmental processes near massive galaxies. We study an extensive sample of LSBGs near massive hosts in the local universe that are distributed across a diverse range of environments. The LSBGs with surface-brightness ${\mu }_{\mathrm{eff},{g}}\gt 24.2\,\mathrm{mag}\,{\mathrm{arcsec}}^{-2}$ are drawn from the Dark Energy Survey Year 3 catalog while the hosts with masses $9.0\lt \mathrm{log}({{ \mathcal M }}_{\star }/{M}_{\odot })\lt 11.0$ comparable to the Milky Way and the Large Magellanic Cloud are selected from the z0MGS sample. We study the projected radial density profiles of LSBGs as a function of their color and surface brightness around hosts in both the rich Fornax–Eridanus cluster environment and the low-density field. We detect an overdensity with respect to the background density, out to 2.5 times the virial radius for both hosts in the cluster environment and the isolated field galaxies. When the LSBG sample is split by g − i color or surface brightness μ eff, g , we find the LSBGs closer to their hosts are significantly redder and brighter, like their high-surface-brightness counterparts. The LSBGs form a clear “red sequence” in both the cluster and isolated environments that is visible beyond the virial radius of the hosts. This suggests preprocessing of infalling LSBGs and a quenched backsplash population around both host samples. More so, the relative prominence of the “blue cloud” feature implies that preprocessing is ongoing near the isolated hosts compared to the cluster environment where the LSBGs are already well processed.

79 ASTRONOMY AND ASTROPHYSICS↗

Influence of printing parameters on the mechanical behavior of 3D-printed SS316L parts manufactured using laser hot wire directed energy deposition

Hybrid manufacturing combines the simultaneous benefits of additive manufacturing (complex geometries, part consolidation, and mass customization) with the advantages of subtractive manufacturing (superior surface finish and enhanced dimensional accuracies) by integrating a suite of complementary traditional processes into a base platform of additive manufacturing. The use of hybrid technology has grown in recent years given its capabilities on repairing metallic structures, producing parts with conformal cooling features, and manufacturing functionally graded products. These kinds of capabilities are of great interest to the medical implant, energy, automotive, maritime, and aerospace industry sectors, among many other fields. This work investigated the mechanical properties of stainless steel (SS) 316L as a function of different tool paths strategies using an integrated 5-axis CNC hybrid Mazak system with a laser hot wire deposition system (LHWDS). This study includes the evaluation of different printing parameters and their impact on the quality of the printed bead as well as the incorporation of a structure–property material relationship based on the mechanical performance of the manufactured coupons.

36 MATERIALS SCIENCE↗

More Heavy Precipitation in World Urban Regions Captured Through a Two‐Way Subgrid Land‐Atmosphere Coupling Framework in the NCAR CESM2

Abstract Current global climate models (GCMs), limited to grid‐scale land‐atmosphere coupling, cannot represent subgrid urban‐rural precipitation contrasts. This study develops an innovative two‐way subgrid land‐atmosphere coupling framework in the National Center for Atmospheric Research (NCAR) Community Earth System Model version 2 (CESM2) to explicitly resolve land‐atmosphere interaction over subgrid individual land units. Results show that urban heat island (UHI) leads to the urban rainfall effect (URE), which in turn alleviates overestimated UHI over China in CESM2. The URE manifests as a shift toward more heavy precipitation and less light precipitation in world urban areas than in surrounding rural counterparts. This feature is consistent with available observations. In heavy precipitation situations, the UHI promotes atmospheric instability and enhances atmospheric water vapor holding capacity, resulting in more heavy precipitation in urban areas. Conversely, in light precipitation situations, the UHI and decreased evaporation from urban impermeable surfaces diminish atmospheric relative humidity, suppressing light precipitation.

Geology↗

Anti-distortion bioinspired camera with an inhomogeneous photo-pixel array

The bioinspired camera, comprising a single lens and a curved image sensor—a photodiode array on a curved surface—, was born of flexible electronics. Its economical build lends itself well to space-constrained machine vision applications. The curved sensor, much akin to the retina, helps image focusing, but the curvature also creates a problem of image distortion, which can undermine machine vision tasks such as object recognition. Here we report an anti-distortion single-lens camera, where 4096 silicon photodiodes arrayed on a curved surface in a nonuniform pattern assimilated to the distorting optics are the key to anti-distortion engineering. That is, the photo-pixel distribution pattern itself is warped in the same manner as images are warped, which correctively reverses distortion. Acquired images feature no appreciable distortion across a 120° horizontal view, as confirmed by their neural-network recognition accuracies. This distortion correction via photo-pixel array reconfiguration is a form of in-sensor computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Two-dimensional hydrodynamic flood models are commonly employed for simulating flood extent and inundation depth. However, the influence of urban drainage network (UDN) is frequently overlooked in these models, potentially compromising their accuracy. Furthermore, the expensive computational costs and longer processing times make them challenging for large-scale hydrodynamic simulation. To address these challenges, this paper develops a machine learning (ML)-driven emulator for an open-source flood model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). A TRITON-ML Emulator (TR-Emulator) that utilizes Convolutional Long Short-Term Memory is developed to capture the spatiotemporal features of flood events based on the outputs from TRITON. We further enhance the emulator by integrating UDN parameters (TR-UDN), such as the flow capacity of drainage pipes, pipe size, and pipe length, via an ML stacking technique to improve the water surface elevation (WSE) simulation. Hurricane Harvey 2017 in Houston, TX is used as the case study. We compare WSE results from TRITON, TR-Emulator, TR-UDN, and the United States Geological Survey (USGS) observations to evaluate the performance of these models. The results indicate that the TR-Emulator effectively replicates the WSE simulated by TRITON. Additionally, TR-UDN performs well in capturing WSE patterns and peak flows, aligning more closely with USGS observations, except in areas with milder slopes where conveyance discrepancies are observed. We further test the generalizability of our ML-based models using another smaller event. This paper shows that the TR-Emulator is effective for users and engineers to emulate a 2D hydrodynamic model, and the enhanced version of the TR-Emulator, TR-UDN, can be an efficient tool for predicting WSEs during urban flooding.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Transformation of High-Architectural Nanocrystal Superlattices upon Solvent Molecule Exposure

The cluster-based body-centered-cubic superlattice (cBCC SL) represents one of the most complicated structures among reported nanocrystal assemblies, comprised of 72 truncated tetrahedral quantum dots per unit cell. Our previous report revealed that truncated tetrahedral quantum dots within cBCC SLs possessed highly controlled translational and orientational order owing to an unusual energetic landscape based on the balancing of entropic and enthalpic contributions during the assembly process. However, the cBCC SL’s structural transformability and mechanical properties, uniquely originating from such complicated nanostructures, have yet to be investigated. Herein, we report that cBCC SLs can undergo dynamic transformation to face-centered-cubic SLs in response to post-assembly molecular exposure. We monitored the dynamic transformation process using in situ synchrotron-based small-angle X-ray scattering, revealing a dynamic transformation involving multiple steps underpinned by interactions between incoming molecules and TTQDs’ surface ligands. Furthermore, our mechanistic study demonstrated that the precise configuration of TTQDs’ ligand molecules in cBCC SLs was key to their high structural transformability and unique jelly-like soft mechanical properties. While ligand molecular configurations in nanocrystal SLs are often considered minor features, our findings emphasize their significance in controlling weak van der Waals interactions between nanocrystals within assembled SLs, leading to previously unremarked superstructural transformability and unique mechanical properties. Finally, our findings promote a facile route toward further creation of soft materials, nanorobotics, and out-of-equilibrium assemblies based on nanocrystal building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗

QCD moat regime and its real-time properties

Dense quantum chromodynamics (QCD) matter may exhibit crystalline phases. Their existence is reflected in a moat regime, where mesonic correlations feature spatial modulations. We study the real-time properties of pions at finite temperature and density in QCD in order to elucidate the nature of this regime. We show that the moat regime arises from particle-hole-like fluctuations near the Fermi surface. This gives rise to a characteristic peak in the spectral function of the pion at nonzero spacelike momentum. This peak can be interpreted as a new quasi particle, the moaton. In addition, our framework also allows us to directly test the stability of the homogeneous chiral phase against the formation of an inhomogeneous condensate in QCD. We find that an inhomogeneous instability is highly unlikely for baryon chemical potentials μ B ≤ 630 MeV . Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Recent advances in rational design of defect-engineered photocatalysts toward sustainable NH 3 synthesis as H 2 carrier: From fundamental and development to machine-learning

In this study, we provide a detailed overview of the fundamental mechanisms underpinning photocatalytic N 2 reduction. We also discuss advances in catalyst design for the synthesis of NH 3 . Particular emphasis is placed on the role of surface defect engineering, which includes the creation of surface defects to enhance the performance of semiconducting photocatalysts for efficient N 2 reduction. In addition, the application of a machine learning-based computational modeling approach is discussed as an important driving force for predicting and regulating NH 3 synthesis efficiency based on catalyst features and reaction conditions. Finally, existing challenges and future perspectives for improving the performance of defect-engineered photocatalysts are outlined to contribute to the ongoing discourse on sustainable ammonia generation. This review aims to clarify recent progress in the rational design of defect-containing photocatalysts for the synthesis of NH 3 and encourages innovative approaches to catalyst optimization rather than solely focusing on new materials.

08 HYDROGEN↗

Site-Selective Doping and Oxidation State Control of Copper in Gold Nanorods

We report the synthesis of plasmonic gold–copper nanostructures with tunable copper spatial distribution and oxidation state. Au–Cu alloy shells were deposited in aqueous solution onto colloidal gold nanorods that functioned as seeds, and the resulting shell morphology was found to depend strongly on the nanorod aspect ratio. For relatively fat gold nanorods (16 x 31 nm), Au–Cu growth was preferentially localized near the rod midsections, forming belt-like structures, whereas for skinnier nanorods (9 x 32 nm), Au–Cu growth produced patchy surface coverage around the entire rod. The shell thickness was tuned from 1 to 4 nm; upon air exposure, thicker shells exhibited a higher Cu(I) fraction compared to the initial shell. Incorporation of the Au–Cu shell led to pronounced shifts in the plasmonic features of the gold nanorods. These tunable plasmonic Au–Cu nanorods provide a materials basis for Cu-based plasmonic materials in the context of electrochemical CO₂ reduction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Symmetry breaking of fluorophore binding to a G-quadruplex generates an RNA aptamer with picomolar K D

Fluorogenic RNA aptamer tags with high affinity enable RNA purification and imaging. The G-quadruplex (G4) based Mango (M) series of aptamers were selected to bind a thiazole orange based (TO1-Biotin) ligand. Using a chemical biology and reselection approach, we have produced a MII.2 aptamer–ligand complex with a remarkable set of properties: Its unprecedented K D of 45 pM, formaldehyde resistance (8% v/v), temperature stability and ligand photo-recycling properties are all unusual to find simultaneously within a small RNA tag. Crystal structures demonstrate how MII.2, which differs from MII by a single A23U mutation, and modification of the TO1-Biotin ligand to TO1-6A-Biotin achieves these results. MII binds TO1-Biotin heterogeneously via a G4 surface that is surrounded by a stadium of five adenosines. Breaking this pseudo-rotational symmetry results in a highly cooperative and homogeneous ligand binding pocket: A22 of the G4 stadium stacks on the G4 binding surface while the TO1-6A-Biotin ligand completely fills the remaining three quadrants of the G4 ligand binding face. Similar optimization attempts with MIII.1, which already binds TO1-Biotin in a homogeneous manner, did not produce such marked improvements. We use the novel features of the MII.2 complex to demonstrate a powerful optically-based RNA purification system.

59 BASIC BIOLOGICAL SCIENCES↗