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At least 1,693 records · Page 94

Influence of Surface Aerosol Injection on Stratocumulus‐to‐Cumulus Transition: Cloud‐Surface Coupling and Background Aerosol Concentrations

The influence of surface aerosol injection on the stratocumulus‐to‐cumulus transition (SCT) is explored using large‐eddy simulations. We examine how cloud‐surface coupling (or the strength of the marine boundary layer (MBL) stratification that limits vertical turbulent mixing and convection) impacts the vertical transport of aerosols, and how injected aerosols influence cloud properties and associated cloud radiative effects during the SCT. By injecting aerosols at different stages of the SCT, noting that cloud is more decoupled from the surface over time due to entrainment warming, we find that cloud‐surface coupling significantly affects aerosol vertical transport. However, injection timing (before drizzle if any) does not notably affect the SCT and the efficiency of marine cloud brightening, because aerosol number concentrations due to injections at different times rapidly converge before the transition onset. By varying the background aerosol concentration, we find that injected aerosols can significantly extend the persistence of stratocumulus decks by suppressing precipitation in clean environments but have little impact on stratocumulus breakup with higher background aerosol concentrations due to saturated aerosol effects. In clean MBLs, the SCT‐delay‐induced increase in cloud fraction dominates the overall cooling effects in response to aerosols, followed by Twomey effects. These cooling effects are slightly offset by decreased liquid water path (LWP) due to entrainment drying. In polluted MBLs, the Twomey effect is more dominant, followed by cloud fraction adjustments, and these coolings are also partly offset by LWP adjustments. All the simulations are made in relatively small domains in which injected aerosols are homogenized over a short time scale.

Zhang, Haipeng [Univ. of Maryland, College Park, M↗

Imaging grain microstructure in a model ceramic energy material with optically generated coherent acoustic phonons

Characterization of microstructure, chemistry and function of advanced energy materials remains a challenge for instrumentation science with tremendous opportunity for new discoveries. This active area of research is starting to make considerable strides with examples ranging from methodologies that employ bright X-rays, electron microscopy and optical spectroscopy. However, further development of instruments, capable of multimodal measurements, is necessary to fully reveal complex microstructure evolution in realistic environments and dynamical systems that are far from equilibrium. In this regard, laser-based instruments have a unique advantage as multiple measurement methodologies are easily combined into a single instrument using standard optics. A new pump-probe method that uses optically generated acoustic phonons is expanding standard optical characterization by providing depth resolved information. Here we report on a noteworthy extension of this pump-probe method to image grain microstructure in ceria. Rich information regarding the orientation of individual crystallites is obtained by monitoring acoustic phonon velocities and noting how the polarization of the probe beam influences the detected signal amplitude. When paired with other optical microscopies, this methodology will provide new perspectives for optical characterization of ceramic materials.

36 MATERIALS SCIENCE↗

Reply to: “Extracting Kondo temperature of strongly-correlated systems from the inverse local magnetic susceptibility”

In his comment1, Katanin reanalyzes our LDA + DMFT results for the temperature-dependent static local spin susceptibility of Sr 2 RuO 4 and V 2 O 3 fitting them to a Curie–Weiss (CW) form, χ(T) ≃ a/(T + θ). Invoking Wilson’s analysis of the impurity susceptibility of the spin-½ one-channel Kondo model (1CKM) in the wide-band limit, he extracts spin Kondo temperatures using T K = θ/√2, obtaining T K = 350 K and 100 K for Sr 2 RuO 4 and V 2 O 3 , respectively. Noting that these are significantly smaller than the scales $T$$^{onset}_{sp}$ = 2300 K and 1000 K reported in ref. 2, he argues that our $T$$^{onset}_{sp}$ scales “do not characterize the screening process”.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Broadly cross-reactive human antibodies that inhibit genogroup I and II noroviruses

The rational development of norovirus vaccine candidates requires a deep understanding of the antigenic diversity and mechanisms of neutralization of the virus. Here, we isolate and characterize a panel of broadly cross-reactive naturally occurring human monoclonal IgMs, IgAs and IgGs reactive with human norovirus (HuNoV) genogroup I or II (GI or GII). We note three binding patterns and identify monoclonal antibodies (mAbs) that neutralize at least one GI or GII HuNoV strain when using a histo-blood group antigen (HBGA) blocking assay. The HBGA blocking assay and a virus neutralization assay using human intestinal enteroids reveal that the GII-specific mAb NORO-320, mediates HBGA blocking and neutralization of multiple GII genotypes. The Fab form of NORO-320 neutralizes GII.4 infection more potently than the mAb, however, does not block HBGA binding. The crystal structure of NORO-320 Fab in complex with GII.4 P-domain shows that the antibody recognizes a highly conserved region in the P-domain distant from the HBGA binding site. Dynamic light scattering analysis of GII.4 virus-like particles with mAb NORO-320 shows severe aggregation, suggesting neutralization is by steric hindrance caused by multivalent cross-linking. Aggregation was not observed with the Fab form of NORO-320, suggesting that this clone also has additional inhibitory features.

59 BASIC BIOLOGICAL SCIENCES↗

Manipulating the oxygen reduction reaction pathway on Pt-coordinated motifs

Electrochemical oxygen reduction could proceed via either 4e - -pathway toward maximum chemical-to-electric energy conversion or 2e - -pathway toward onsite H 2 O 2 production. Bulk Pt catalysts are known as the best monometallic materials catalyzing O 2 -to-H 2 O conversion, however, controversies on the reduction product selectivity are noted for atomic dispersed Pt catalysts. Here, we prepare a series of carbon supported Pt single atom catalyst with varied neighboring dopants and Pt site densities to investigate the local coordination environment effect on branching oxygen reduction pathway. Manipulation of 2e - or 4e - reduction pathways is demonstrated through modification of the Pt coordination environment from Pt-C to Pt-N-C and Pt-S-C, giving rise to a controlled H 2 O 2 selectivity from 23.3% to 81.4% and a turnover frequency ratio of H 2 O 2 /H 2 O from 0.30 to 2.67 at 0.4 V versus reversible hydrogen electrode. Energetic analysis suggests both 2e - and 4e - pathways share a common intermediate of *OOH, Pt-C motif favors its dissociative reduction while Pt-S and Pt-N motifs prefer its direct protonation into H 2 O 2 . By taking the Pt-N-C catalyst as a stereotype, we further demonstrate that the maximum H 2 O 2 selectivity can be manipulated from 70 to 20% with increasing Pt site density, providing hints for regulating the stepwise oxygen reduction in different application scenarios.

36 MATERIALS SCIENCE↗

Triangular lattice quantum dimer model with variable dimer density

Abstract Quantum dimer models are known to host topological quantum spin liquid phases, and it has recently become possible to simulate such models with Rydberg atoms trapped in arrays of optical tweezers. Here, we present large-scale quantum Monte Carlo simulation results on an extension of the triangular lattice quantum dimer model with terms in the Hamiltonian annihilating and creating single dimers. We find distinct odd and even $${{\mathbb{Z}}}_{2}$$ Z 2 spin liquids, along with several phases with no topological order: a staggered crystal, a nematic phase, and a trivial symmetric phase with no obvious broken symmetry. We also present dynamic spectra of the phases, and note implications for experiments on Rydberg atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Characterization of SARS-CoV-2 Omicron BA.2.75 clinical isolates

The prevalence of the Omicron subvariant BA.2.75 rapidly increased in India and Nepal during the summer of 2022, and spread globally. However, the virological features of BA.2.75 are largely unknown. Here, we evaluated the replicative ability and pathogenicity of BA.2.75 clinical isolates in Syrian hamsters. Although we found no substantial differences in weight change among hamsters infected with BA.2, BA.5, or BA.2.75, the replicative ability of BA.2.75 in the lungs is higher than that of BA.2 and BA.5. Of note, BA.2.75 causes focal viral pneumonia in hamsters, characterized by patchy inflammation interspersed in alveolar regions, which is not observed in BA.5-infected hamsters. Moreover, in competition assays, BA.2.75 replicates better than BA.5 in the lungs of hamsters. These results suggest that BA.2.75 can cause more severe respiratory disease than BA.5 and BA.2 in a hamster model and should be closely monitored.

59 BASIC BIOLOGICAL SCIENCES↗

Competing itinerant and local spin interactions in kagome metal FeGe

The combination of a geometrically frustrated lattice, and similar energy scales between degrees of freedom endows two-dimensional Kagome metals with a rich array of quantum phases and renders them ideal for studying strong electron correlations and band topology. The Kagome metal, FeGe is a noted example of this, exhibiting A-type collinear antiferromagnetic (AFM) order at T N ≈ 400 K, then establishes a charge density wave (CDW) phase coupled with AFM ordered moment below T CDW ≈ 110 K, and finally forms a c-axis double cone AFM structure around T Canting ≈ 60 K. Here we use neutron scattering to demonstrate the presence of gapless incommensurate spin excitations associated with the double cone AFM structure of FeGe at temperatures well above T Canting and T CDW that merge into gapped commensurate spin waves from the A-type AFM order. Commensurate spin waves follow the Bose factor and fit the Heisenberg Hamiltonian, while the incommensurate spin excitations, emerging below T N where AFM order is commensurate, start to deviate from the Bose factor around T CDW , and peaks at T Canting . This is consistent with a critical scattering of a second order magnetic phase transition with decreasing temperature. By comparing these results with density functional theory calculations, we conclude that the incommensurate magnetic structure arises from the nested Fermi surfaces of itinerant electrons and the formation of a spin density wave order.

36 MATERIALS SCIENCE↗

Benchmarking graph neural networks for materials chemistry

Graph neural networks (GNNs) have received intense interest as a rapidly expanding class of machine learning models remarkably well-suited for materials applications. To date, a number of successful GNNs have been proposed and demonstrated for systems ranging from crystal stability to electronic property prediction and to surface chemistry and heterogeneous catalysis. However, a consistent benchmark of these models remains lacking, hindering the development and consistent evaluation of new models in the materials field. Here, we present a workflow and testing platform, MatDeepLearn, for quickly and reproducibly assessing and comparing GNNs and other machine learning models. We use this platform to optimize and evaluate a selection of top performing GNNs on several representative datasets in computational materials chemistry. From our investigations we note the importance of hyperparameter selection and find roughly similar performances for the top models once optimized. We identify several strengths in GNNs over conventional models in cases with compositionally diverse datasets and in its overall flexibility with respect to inputs, due to learned rather than defined representations. Meanwhile several weaknesses of GNNs are also observed including high data requirements, and suggestions for further improvement for applications in materials chemistry are discussed.

36 MATERIALS SCIENCE↗

Growth of concomitant laser-driven collisionless and resistive electron filamentation instabilities over large spatiotemporal scales

Collective processes in plasmas often induce microinstabilities that play an important role in many space or laboratory plasma environments. Particularly of note is the Weibel-type current filamentation instability, which is believed to drive the creation of collisionless shocks in weakly magnetized astrophysical plasmas. In this paper, this instability class is studied through interactions of ultraintense and short laser pulses with solid foils, leading to localized generation of megaelectronvolt electrons. Proton radiographic measurements of both low- and high-resistivity targets show two distinct, superimposed electromagnetic field patterns arising from the interpenetration of the megaelectronvolt electrons and the background plasma. Particle-in-cell simulations and theoretical estimates suggest that the collisionless Weibel instability building up in the dilute expanding plasmas formed at the target surfaces causes the observed azimuthally symmetric electromagnetic filaments. For a sufficiently high resistivity of the target foil, an additional resistive instability is triggered in the bulk target, giving rise to radially elongated filaments. The data reveal the growth of both filamentation instabilities over large temporal (tens of picoseconds) and spatial (hundreds of micrometres) scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transforming US agriculture for carbon removal with enhanced weathering

Abstract Enhanced weathering (EW) with agriculture uses crushed silicate rocks to drive carbon dioxide removal (CDR) 1,2 . If widely adopted on farmlands, it could help achieve net-zero emissions by 2050 2–4 . Here we show, with a detailed US state-specific carbon cycle analysis constrained by resource provision, that EW deployed on agricultural land could sequester 0.16–0.30 GtCO 2 yr −1 by 2050, rising to 0.25–0.49 GtCO 2 yr −1 by 2070. Geochemical assessment of rivers and oceans suggests effective transport of dissolved products from EW from soils, offering CDR on intergenerational timescales. Our analysis further indicates that EW may temporarily help lower ground-level ozone and concentrations of secondary aerosols in agricultural regions. Geospatially mapped CDR costs show heterogeneity across the USA, reflecting a combination of cropland distance from basalt source regions, timing of EW deployment and evolving CDR rates. CDR costs are highest in the first two decades before declining to about US$100–150 tCO 2 −1 by 2050, including for states that contribute most to total national CDR. Although EW cannot be a substitute for emission reductions, our assessment strengthens the case for EW as an overlooked practical innovation for helping the USA meet net-zero 2050 goals 5,6 . Public awareness of EW and equity impacts of EW deployment across the USA require further exploration 7,8 and we note that mobilizing an EW industry at the necessary scale could take decades.

Science & Technology - Other Topics↗

Spin squeezing in an ensemble of nitrogen–vacancy centres in diamond

Spin-squeezed states provide a seminal example of how the structure of quantum mechanical correlations can be controlled to produce metrologically useful entanglement. These squeezed states have been demonstrated in a wide variety of quantum systems ranging from atoms in optical cavities to trapped ion crystals. By contrast, despite their numerous advantages as practical sensors, spin ensembles in solid-state materials have yet to be controlled with sufficient precision to generate targeted entanglement such as spin squeezing. Here we report the experimental demonstration of spin squeezing in a solid-state spin system. Our experiments are performed on a strongly interacting ensemble of nitrogen–vacancy colour centres in diamond at room temperature, and squeezing (−0.50 ± 0.13 dB) below the noise of uncorrelated spins is generated by the native magnetic dipole–dipole interaction between nitrogen–vacancy centres. To generate and detect squeezing in a solid-state spin system, we overcome several challenges. First, we develop an approach, using interaction-enabled noise spectroscopy, to characterize the quantum projection noise in our system without directly resolving the spin probability distribution. Second, noting that the random positioning of spin defects severely limits the generation of spin squeezing, we implement a pair of strategies aimed at isolating the dynamics of a relatively ordered sub-ensemble of nitrogen–vacancy centres. Furthermore, our results open the door to entanglement-enhanced metrology using macroscopic ensembles of optically active spins in solids.

Atomic and molecular physics↗

The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Many current gridded surface meteorological datasets are inadequate for quantifying near surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981-2018 over the CONUS. Daily maximum, minimum, and mean values for a variety of temperature estimates, humidity, and surface energy budget terms, among others, are included. This High-resolution Urban Meteorology for Impacts Dataset (HUMID) will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology.

54 ENVIRONMENTAL SCIENCES↗

Low-temperature (< 200 °C) degradation of electronic nicotine delivery system liquids generates toxic aldehydes

Electronic cigarette usage has spiked in popularity over recent years. The enhanced prevalence has consequently resulted in new health concerns associated with the use of these devices. Degradation of the liquids used in vaping have been identified as a concern due to the presence of toxic compounds such as aldehydes in the aerosols. Typically, such thermochemical conversions are reported to occur between 300 and 400 °C. Herein, the low-temperature thermal degradation of propylene glycol and glycerol constituents of e-cigarette vapors are explored for the first time by natural abundance 13 C NMR and 1 H NMR, enabling in situ detection of intact molecules from decomposition. The results demonstrate that the degradation of electronic nicotine delivery system (ENDS) liquids is strongly reliant upon the oxygen availability, both in the presence and absence of a material surface. When oxygen is available, propylene glycol and glycerol readily decompose at temperatures between 133 and 175 °C over an extended time period. Among the generated chemical species, formic and acrylic acids are observed which can negatively affect the kidneys and lungs of those who inhale the toxin during ENDS vapor inhalation. Further, the formation of hemi- and formal acetals is noted from both glycerol and propylene glycol, signifying the generation of both formaldehyde and acetaldehyde, highly toxic compounds, which, as a biocide, can lead to numerous health ailments. The results also reveal a retardation in decomposition rate when material surfaces are prevalent with no directly observed unique surface spectator or intermediate species as well as potentially slower conversions in mixtures of the two components. The generation of toxic species in ENDS liquids at low temperatures highlights the dangers of low-temperature ENDS use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction

Abstract Developing prediction models for emerging infectious diseases from relatively small numbers of cases is a critical need for improving pandemic preparedness. Using COVID-19 as an exemplar, we propose a transfer learning methodology for developing predictive models from multi-modal electronic healthcare records by leveraging information from more prevalent diseases with shared clinical characteristics. Our novel hierarchical, multi-modal model ( $${\textsc {TransMED}}$$ T R A N S MED ) integrates baseline risk factors from the natural language processing of clinical notes at admission, time-series measurements of biomarkers obtained from laboratory tests, and discrete diagnostic, procedure and drug codes. We demonstrate the alignment of $${\textsc {TransMED}}$$ T R A N S MED ’s predictions with well-established clinical knowledge about COVID-19 through univariate and multivariate risk factor driven sub-cohort analysis. $${\textsc {TransMED}}$$ T R A N S MED ’s superior performance over state-of-the-art methods shows that leveraging patient data across modalities and transferring prior knowledge from similar disorders is critical for accurate prediction of patient outcomes, and this approach may serve as an important tool in the early response to future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of precipitation across the contiguous United States, Alaska, and Puerto Rico in multi-decadal convection-permitting simulations

Abstract This study is an early effort to generate a multi-decadal convection-permitting regional climate dataset that covers nearly the entire North American continent. We assessed a 20 year dynamically downscaled regional climate simulation at a 4 km spatial resolution with explicit convection across the contiguous United States (CONUS), Alaska, and Puerto Rico. Specifically, we evaluated the model’s performance in representing mean, 95th percentile, and extreme precipitation across regions. Our findings indicate that when compared with ERA5 reanalysis, the forcing data, convection-permitting simulation improves representations of seasonal, 95th percentile, and extreme precipitation over a large portion of the CONUS, Alaska, and Puerto Rico, particularly in areas where precipitation is heaviest. The simulation adds value over its forcing data (ERA5) in up to 53% of all grid cells in the CONUS, 68.8% in Alaska, and 84.0% in Puerto Rico. It is important to note that, however, despite improvements, model errors in Puerto Rico remain large. Similar improvements are observed in extreme indices, including consecutive dry days, maximum 5 days precipitation, and extreme precipitation. Analysis of the diurnal cycle of mean hourly precipitation suggests that representations of convective processes—including onset, dissipation, suppression, downstream propagation, and local circulation—improved overall.

54 ENVIRONMENTAL SCIENCES↗

Ferroelectric capacitors and field-effect transistors as in-memory computing elements for machine learning workloads

Abstract This study discusses the feasibility of Ferroelectric Capacitors (FeCaps) and Ferroelectric Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate machine learning (ML) workloads. We conducted an exploration of device fabrication and proposed system-algorithm co-design to boost performance. A novel FeCap device, incorporating an interfacial layer (IL) and$$\text {Hf}_{0.5}\text {Zr}_{0.5}\text {O}_2$$ Hf 0.5 Zr 0.5 O 2 (HZO), ensures a reduction in operating voltage and enhances HZO scaling while being compatible with CMOS circuits. The IL also enriches ferroelectricity and retention properties. When integrated into crossbar arrays, FeCaps and FeFETs demonstrate their effectiveness as IMC components, eliminating sneak paths and enabling selector-less operation, leading to notable improvements in energy efficiency and area utilization. However, it is worth noting that limited capacitance ratios in FeCaps introduced errors in multiply-and-accumulate (MAC) computations. The proposed co-design approach helps in mitigating these errors and achieves high accuracy in classifying the CIFAR-10 dataset, elevating it from a baseline of 10% to 81.7%. FeFETs in crossbars, with a higher on-off ratio, outperform FeCaps, and our proposed charge-based sensing scheme achieved at least an order of magnitude reduction in power consumption, compared to prevalent current-based methods.

Science & Technology - Other Topics↗

Radiation-induced alteration of apatite on the surface of Mars: first in situ observations with SuperCam Raman onboard Perseverance

Abstract Planetary exploration relies considerably on mineral characterization to advance our understanding of the solar system, the planets and their evolution. Thus, we must understand past and present processes that can alter materials exposed on the surface, affecting space mission data. Here, we analyze the first dataset monitoring the evolution of a known mineral target in situ on the Martian surface, brought there as a SuperCam calibration target onboard the Perseverance rover. We used Raman spectroscopy to monitor the crystalline state of a synthetic apatite sample over the first 950 Martian days (sols) of the Mars2020 mission. We note significant variations in the Raman spectra acquired on this target, specifically a decrease in the relative contribution of the Raman signal to the total signal. These observations are consistent with the results of a UV-irradiation test performed in the laboratory under conditions mimicking ambient Martian conditions. We conclude that the observed evolution reflects an alteration of the material, specifically the creation of electronic defects, due to its exposure to the Martian environment and, in particular, UV irradiation. This ongoing process of alteration of the Martian surface needs to be taken into account for mineralogical space mission data analysis.

Science & Technology - Other Topics↗