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At least 217 records · Page 12

Lagrangian Characterization of Surface Transport From the Equatorial Atlantic to the Caribbean Sea Using Climatological Lagrangian Coherent Structures and Self‐Organizing Maps

Abstract This study presents an assessment of the transport of suspended material by surface ocean currents, which have a critical role in determining the connectivity and distribution of living and non‐living material. Lagrangian experiments reveal pathways from the Equatorial Atlantic to 10 strategic regions within the Caribbean Sea, determined by considering the space‐time variability of climatological Lagrangian Coherent Structures, which act as recurrent attracting pathways and transport barriers. Due to windage or Stokes drift, wind forcing is a significant factor in determining the spatial locations where particles cluster and the time needed to reach the Caribbean from the Equatorial Atlantic. Pathways shift westward within the Caribbean and take less time to arrive with increasing wind influence. Depending on the wind effect, the particles show higher confluence in different areas of the Caribbean. A case study is presented for the Mexican Caribbean nearshore area, isolated from ocean‐current trajectories. Here, wind weakens the transport barrier responsible for this isolation and causes particle confluence toward that region. Spatial patterns of the Eulerian velocity identified through Self‐Organizing Maps, with time dependence given by their best matching units, can reproduce the characteristic Lagrangian patterns of surface current climate variability. Our study demonstrates the application of tools from dynamical systems and unsupervised neural networks to understand Lagrangian patterns and identify the processes that drive them. These findings improve our understanding of transport mechanisms of suspended material by surface ocean currents in the Western Atlantic and the Caribbean Sea, which is essential for managing and conserving marine ecosystems.

Allende‐Arandía, Ma. Eugenia↗

Tethered balloon measurements reveal enhanced aerosol occurrence aloft interacting with Arctic low-level clouds

Low-level clouds in the Arctic affect the surface energy budget and vertical transport of heat and moisture. The limited availability of cloud-droplet-forming aerosol particles strongly impacts cloud properties and lifetime. Vertical particle distributions are required to study aerosol–cloud interaction over sea ice comprehensively. This article presents vertically resolved measurements of aerosol particle number concentrations and sizes using tethered balloons. The data were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the summer of 2020. Thirty-four profiles of aerosol particle number concentration were observed in 2 particle size ranges: 12–150 nm (N 12−150 ) and above 150 nm (N >150 ). Concurrent balloon-borne meteorological measurements provided context for the continuous profiles through the cloudy atmospheric boundary layer. Radiosoundings, cloud remote sensing data, and 5-day back trajectories supplemented the analysis. The majority of aerosol profiles showed more particles above the lowest temperature inversion, on average, double the number concentration compared to below. Increased N 12−150 up to 3,000 cm −3 were observed in the free troposphere above low-level clouds related to secondary particle formation. Long-range transport of pollution increased N >150 to 310 cm −3 in a warm, moist air mass. Droplet activation inside clouds caused reductions of N >150 by up to 100%, while the decrease in N 12−150 was less than 50%. When low-level clouds were thermodynamically coupled with the surface, profiles showed 5 times higher values of N 12−150 in the free troposphere than below the cloud-capping temperature inversion. Enhanced N 12−150 and N >150 interacting with clouds were advected above the lowest inversion from beyond the sea ice edge when clouds were decoupled from the surface. Vertically discontinuous aerosol profiles below decoupled clouds suggest that particles emitted at the surface are not transported to clouds in these conditions. It is concluded that the cloud-surface coupling state and free tropospheric particle abundance are crucial when assessing the aerosol budget for Arctic low-level clouds over sea ice.

54 ENVIRONMENTAL SCIENCES↗

Selective capture and recovery of uranium oxide colloids from aqueous soil suspensions using high gradient magnetic filtration

High Gradient Magnetic Filtration (HGMF) is a promising method for the selective capture and recovery of uranium oxide from surface soils. To date, however, magnetic filtration of uranium oxide has only been demonstrated at a proof-of-principle scale using relatively small filters (<5 cm 3 ) at low flowrates (<60 mL/min). Here, to explore the efficacy of magnetic filtration of uranium oxide at a larger scale, a newly designed HGMF apparatus that is more than an order of magnitude larger than our earlier filters (106 cm 3 ) was designed, fabricated, and tested at relatively high flowrates. Filtration experiments were performed using aqueous uranium oxide particle suspensions with Arizona Road Dust (ARD) as a soil simulant. At a flowrate of 125 mL/min, the apparatus’ uranium capture rate was exceptionally high (96 %), but selectivity was poor due to the high rate of capture for diamagnetic soil constituents (e.g., 77 % for silicon). All particles were captured at a lower rate when the flowrate was increased to 250 mL/min, but uranium selectivity was significantly increased due to the more substantial reduction in diamagnetic particle capture (i.e., capture rate of 77 % and 15 % for uranium and silicon, respectively). When backwashing the apparatus at the same flowrates used during filtration experiments, the rate of uranium recovery tended to be fairly low. Nevertheless, higher flowrates (1 L/min) and sonication were both shown to be highly effective methods of increasing uranium recovery. Magnetic field simulations were also performed to investigate potential optimizations to the design of the apparatus. These simulations showed that the intensity of the applied magnetic field could be increased by increasing the thickness of the steel magnetic housing. Additionally, stochastic trajectory simulations were performed to investigate the potential mechanisms of particle capture.

HGMF↗

Measurement report: A comparative analysis of an intensive incursion of fluorescing African dust particles over Puerto Rico and another over Spain

Measurements during episodes of African dust, made with two wideband integrated bioaerosol spectrometers (WIBSs), one on the northeastern coast of Puerto Rico and the other in the city of León, Spain, show unmistakable, bioaerosol-like fluorescing aerosol particles (FAPs) that can be associated with these dust episodes. The Puerto Rico event occurred during a major incursion of African dust during June 2020. The León event occurred in the late winter and spring of 2022, when widespread, elevated layers of dust inundated the Iberian Peninsula. Satellite and back-trajectory analyses confirm that dust from northern Africa was the source of the particles during both events. The WIBSs measure the size of individual particles in the range from 0.5 to 30 µm, derive a shape factor, and classify seven types of fluorescence from the FAPs. In general, it is not possible to directly determine the specific biological identity from fluorescence signatures; however, measurements of these types of bioaerosols in laboratory studies allow us to compare ambient fluorescence patterns with whole microbial cells measured under controlled conditions. Here we introduce some new metrics that offer a more quantitative approach for comparing FAP characteristics derived from particles measured under different environmental conditions. The analysis highlights the similarities and differences at the two locations and reveals differences that can be attributed to the age and history of the dust plumes, e.g., the amount of time that the air masses were in the mixed layer and the frequency of precipitation along the air mass trajectory.

54 ENVIRONMENTAL SCIENCES↗

Impact of dry intrusion events on the composition and mixing state of particles during the winter Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA)

Abstract. Long-range transport of continental emissions has a far-reaching influence over remote regions, resulting in substantial change in the size, morphology, and composition of the local aerosol population and cloud condensation nuclei (CCN) budget. Here, we investigate the physicochemical properties of atmospheric particles collected on board a research aircraft flown over the Azores during the winter 2018 Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) campaign. Particles were collected within the marine boundary layer (MBL) and free troposphere (FT) after long-range atmospheric transport episodes facilitated by dry intrusion (DI) events. Chemical and physical properties of individual particles were investigated using complementary capabilities of computer-controlled scanning electron microscopy and X-ray spectromicroscopy to probe particle external and internal mixing state characteristics. Furthermore, real-time measurements of aerosol size distribution, cloud condensation nuclei (CCN) concentration, and back-trajectory calculations were utilized to help bring into context the findings from offline spectromicroscopy analysis. While carbonaceous particles were found to be the dominant particle type in the region, changes in the percent contribution of organics across the particle population (i.e., external mixing) shifted from 68 % to 43 % in the MBL and from 92 % to 46 % in FT samples during DI events. This change in carbonaceous contribution is counterbalanced by the increase in inorganics from 32 % to 57 % in the MBL and 8 % to 55 % in FT. The quantification of the organic volume fraction (OVF) of individual particles derived from X-ray spectromicroscopy, which relates to the multi-component internal composition of individual particles, showed a factor of 2.06 ± 0.16 and 1.11 ± 0.04 increase in the MBL and FT, respectively, among DI samples. We show that supplying particle OVF into the κ-Köhler equation can be used as a good approximation of field-measured in situ CCN concentrations. We also report changes in the κ values in the MBL from κMBL, non-DI=0.48 to κMBL, DI=0.41, while changes in the FT result in κFT, non-DI=0.36 to κFT, DI=0.33, which is consistent with enhancements in OVF followed by the DI episodes. Our observations suggest that entrainment of particles from long-range continental sources alters the mixing state population and CCN properties of aerosol in the region. The work presented here provides field observation data that can inform atmospheric models that simulate sources and particle composition in the eastern North Atlantic.

54 ENVIRONMENTAL SCIENCES↗

Room-temperature fabrication of garnet-type solid-electrolyte: Optimizing particle size for high ionic conductivity

Dense and uniform Li 6.25 Al 0.25 La 3 Zr 2 O 12 (Al-doped LLZO) solid-electrolyte film of ~24 µm thickness is successfully fabricated by room temperature aerosol deposition (AD) method. The process optimization study revealed that careful control of particle size and morphology is one of critical determinants in the development of a compact AD membrane. Notably, our method facilitated an impressive ionic conductivity of approximately 10 –5 S cm –1 , bypassing the necessity for post-annealing processes, a milestone in itself. However, it is hypothesized that the attained conductivity is somewhat restrained by factors such as smaller grain size and potential surface degradation due to moisture exposure during fabrication, indicating avenues for further research. Looking forward, detailed investigations into the film's microstructure and its impact on transport properties will be a focal point, alongside potential enhancements through post-annealing and particle coating strategies. Finally, this research hints at a promising trajectory for the development of high-efficiency solid-state battery technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Substrate-Mediated Evaporation and Stochastic Evolution of Supported Au Nanoparticles

Here, we use in situ transmission electron microscopy with automated tracking to study supported gold nanoparticles (NPs) during high-temperature vacuum annealing. The average mass loss per NP is governed by a flat, nearly size-independent substrate-mediated evaporation profile. On top of this mean shrinkage, individual NPs show significant fluctuations in apparent growth or shrinkage, and NP volume follows a random-walk-like trajectory. To rationalize both the ensemble-mean behavior and the particle-resolved variability, we develop a self-consistent theory that couples substrate-mediated evaporation to collective 2D Ostwald-type mass exchange through a shared adatom field, described in terms of a renormalized screening length and background concentration. In the experimentally relevant regime, the theory predicts an approximately size-independent mean shrinkage rate and clarifies how net mass loss suppresses classical coarsening. Superimposed on this deterministic drift, we quantify stochastic volume trajectories and capture their fluctuation spectrum with a minimal Langevin description consistent with intermittent adatom attachment and detachment events. In addition, we characterize the lateral diffusive motion of NPs, which is responsible for their coalescence. Altogether, our results highlight that stochasticity is intrinsic at the nanoscale and that predicting the evolution of supported NPs at early and intermediate times requires a unified framework combining substrate-mediated evaporation, collective mass exchange, and stochastic fluctuations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Particle transport-driven flow dynamics and heat transfer modulation in solar photovoltaic modules: Implications on soiling

Wind-swept debris and excessive heating reduce solar photovoltaic efficiency and accelerate panel degradation. For many solar plants in open environments, particle deposition is well-understood to exacerbate efficiency losses by blocking useable light and insulating panel surfaces. However, little is known about particle behavior in multi-panel systems, where complex wakes dominate and alter trajectories. This study examines debris-laden flow within a scaled array of two model solar panels, observing convective cooling and focusing on turbulent inter-panel flow dynamics. Convection is compared between the first and second panels (P 1 and P 2 ) and for a single inflow velocity at four particle concentrations (Φ v ), including a neutrally buoyant particle (i.e. tracer) case and three water droplet cases. Tracers and Φ v > 0 concentrations show increased convective heat transfer for P 2 compared to P 1 , while inertial particle presence and increased concentration reduces this improvement from +170% to +90%. Particle image velocimetry surrounding P 2 reveals dampened inter-panel wake features for particle-laden flow compared to the tracer case, where diminished mean flow and mean kinetic energy breakdown are observed for the particles due to their inertia. Together, the reduction in comparative convection and dampened wake effects accompanying inertial particle concentration motivates further studies on coupled array physics in debris-filled flow.

14 SOLAR ENERGY↗

A Lagrangian Study of Interfaces at the Edges of Cumulus Clouds

Abstract Interfaces at the edge of an idealized, nonprecipitating, warm cloud are studied using direct numerical simulation (DNS) complemented with a Lagrangian particle tracking routine. Once a shell has formed, four zones can be distinguished: the cloud core, visible shell, invisible shell, and the environment. The union of the visible and invisible regions is the shell commonly referred to in literature. The boundary between the invisible shell and the environment is the turbulent–nonturbulent interface (TNTI), which is typically not considered in cloud studies. Three million particles were seeded homogeneously across the domain and properties were recorded along individual trajectories. The results demonstrate that the traditional cloud boundary (separating cloudy and noncloudy regions using thresholds applied on liquid condensate or updraft velocity) are some distance away from the TNTI. Furthermore, there is no dynamic difference between the traditional liquid-condensate boundary and the region extending to the TNTI. However, particles crossing the TNTI exhibit a sharp jump in enstrophy and a smooth increase in buoyancy. The traditional cloud boundary coincides with the location of minimum buoyancy in the shell. The shell premixes the entraining and detraining air and analysis reveals a highly skewed picture of entrainment and detrainment at the traditional cloud boundary. A preferential entrainment of particles with velocity and specific humidity higher than the mean values in the shell is observed. Large-eddy simulation of a more realistic setup detects an interface with similar properties using the same thresholds as in the DNS, indicating that the DNS results extrapolate beyond their idealized conditions.

54 ENVIRONMENTAL SCIENCES↗

Notes on Asay Foil Analysis

As is the norm for momentum diagnostic analyses (i.e., both piezopin and Asay foil measurements), we begin by assuming all particles are created instantaneously at the moment of shock breakout; that all particles move collinearly through a perfect vacuum from source to sensor with a long mean free path to scattering (i.e., so that particle velocities and areal masses do not change in flight); and that the particles collide perfectly inelastically with the sensor. We also assume the foil supports have a negligible effect on the trajectory, as has been demonstrated experimentally, and the foil is sufficiently thin that corrections for thick-plate effects (e.g., time delays between particle impacts on the collecting side and velocity changes on the probe side) can be disregarded. We seek an exact analytic treatment of an ideal system that perfectly embodies these characteristics.

36 MATERIALS SCIENCE↗

Search for heavy, long-lived, charged particles with large ionisation energy loss in $pp$ collisions at $ \sqrt{s} $ = 13 TeV using the ATLAS experiment and the full Run 2 dataset

This paper presents a search for hypothetical massive, charged, long-lived particles with the ATLAS detector at the LHC using an integrated luminosity of 139 fb –1 of proton–proton collisions at √s =13 TeV. These particles are expected to move significantly slower than the speed of light and should be identifiable by their high transverse momenta and anomalously large specific ionisation losses, dE/dx. Trajectories reconstructed solely by the inner tracking system and a dE/dx measurement in the pixel detector layers provide sensitivity to particles with lifetimes down to O(1) ns with a mass, measured using the Bethe–Bloch relation, ranging from 100 GeV to 3 TeV. Interpretations for pair-production of R-hadrons, charginos and staus in scenarios of supersymmetry compatible with these particles being long-lived are presented, with mass limits extending considerably beyond those from previous searches in broad ranges of lifetime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Online multi-objective particle accelerator optimization of the AWAKE electron beam line for simultaneous emittance and orbit control

Multi-objective optimization is important for particle accelerators where various competing objectives must be satisfied routinely such as, for example, transverse emittance vs bunch length. We develop and demonstrate an online multi-time scale multi-objective optimization algorithm that performs real time feedback on particle accelerators. We demonstrate the ability to simultaneously minimize the emittance and maintain a reference trajectory of a beam in the electron beamline in CERN’s Advanced Proton Driven Plasma Wakefield Acceleration Experiment.

43 PARTICLE ACCELERATORS↗

Deep learning for characterizing the self-assembly of three-dimensional colloidal systems

Creating a systematic framework to characterize the structural states of colloidal self-assembly systems is crucial for unraveling the fundamental understanding of these systems’ stochastic and non-linear behavior. The most accurate characterization methods create high-dimensional neighborhood graphs that may not provide useful information about structures unless these are well-defined reference crystalline structures. Dimensionality reduction methods are thus required to translate the neighborhood graphs into a low-dimensional space that can be easily interpreted and used to characterize non-reference structures. We investigate a framework for colloidal system state characterization that employs deep learning methods to reduce the dimensionality of neighborhood graphs. The framework next uses agglomerative hierarchical clustering techniques to partition the low-dimensional space and assign physically meaningful classifications to the resulting partitions. In this work, we first demonstrate the proposed colloidal self-assembly state characterization framework on a three-dimensional in silico system of 500 multi-flavored colloids that self-assemble under isothermal conditions. We next investigate the generalizability of the characterization framework by applying the framework to several independent self-assembly trajectories, including a three-dimensional in silico system of 2052 colloidal particles that undergo evaporation-induced self-assembly.

36 MATERIALS SCIENCE↗

CryoTRANS: predicting high-resolution maps of rare conformations from self-supervised trajectories in cryo-EM

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.

47 OTHER INSTRUMENTATION↗

Modeling rarefied gas chemistry with QuiPS, a novel quasi-particle method

The goal of this work is to build up the capability of quasi-particle simulation (QuiPS), a novel flow solver, such that it can adequately model the rarefied portion of an atmospheric reentry trajectory. Direct simulation Monte Carlo (DSMC) is the conventional solver for such conditions, but struggles to resolve transient flows, trace species, and high-level internal energy states due to stochastic noise. Quasi-particle simulation (QuiPS) is a novel Boltzmann solver that describes a system with a discretized, truncated velocity distribution function. The resulting fixed-velocity, variable weight quasi-particles enable smooth variation of macroscopic properties. The distribution function description enables the use of a variance-reduced collision model, greatly minimizing expense near equilibrium. This work presents the addition of a neutral air chemistry model to QuiPS and some demonstrative 0D simulations. The explicit representation of internal distributions in QuiPS reveals some of the flaws in existing physics models. Overall, variance reduction, a key feature of QuiPS, can greatly reduce expense of multi-dimensional calculations, but is only cheaper when the gas composition is near chemical equilibrium.

42 ENGINEERING↗

3D ion gyro-orbit heat load predictions for NSTX-U

Abstract High power tokamaks operate with divertor heat loads capable of destroying the plasma facing components (PFCs). High fidelity heat load predictions are necessary to ascertain the PFC state for design and during operation. Typical heat flux calculations are 2D, time invariant, and assume that power flows directly along the magnetic field lines (the optical approximation). These assumptions neglect the complex 3D geometries employed to protect the PFCs, the time varying nature of the plasma and PFC thermal state, and the helical trajectories of ions with finite Larmor radii (the gyro-orbit approximation). An integrated software framework, the heat flux engineering analysis toolkit (HEAT), was developed to generate time varying optical heat loads applied to real engineering computer aided design (CAD) (Looby et al 2022 Fusion Sci. Technol. 78 10–27). Recently, an ion-gyro orbit module has been added to HEAT. This module calculates the helical trajectories of ions as they gyrate about the magnetic field lines using kinetic theory macro-particles to accelerate the calculation. First, the new gyro-orbit module will be presented. Next, a comparison to existing research is performed. Finally, an analysis of the gyro-orbit heat loads for NSTX-U is presented for diverted discharges using the engineering CAD models utilized for PFC fabrication. Including these gyro-orbit effects can enhance the PFC performance by ‘smearing’ out the magnetic shadows associated with the castellated fish-scaled geometry. Simultaneously, the helical trajectories can degrade performance when they load narrow regions on edges and corners with high heat fluxes. Analysis of the trade-offs between these competing effects is included, and regions for further investigation are identified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Chemical Insights into the Molecular Composition of Organic Aerosols in the Urban Region of Houston, Texas

Molecular functional groups, such as organosulfates (CHOS) and organonitrates (CHNO) are important tracers for field observations of secondary organic aerosols (SOA). While CHOS and CHNO are prevalent in the atmosphere, there is a lack of knowledge regarding daily and day- and night-time variations in these species in the urban atmosphere. Meteorological factors such as wind speed/direction, relative humidity (RH), and temperature can influence the formation of CHOS/CHNO. To investigate these trends, we utilized multimodal chemical imaging and advanced high resolution mass spectrometry techniques to acquire particle speciation and molecular formulas (MFs) associated with day and night sampling periods. Back trajectory analyses revealed the oceanic influence of southern wind airmasses in later June sampling periods with organic fractions <10%. Conversely, northern winds in early June sampling periods contributed to the episodic emergence of extremely low volatile organics (ELVOCs) and organic factions up to 41%. The observed unique MFs to June 3 (223 MFs) and to June 4 (144 MFs) were largely found to be of biogenic rather than anthropogenic origin. Finally, our findings reveal episodic prevalence and temporal distribution of SOA constituents across the urban region of Houston, Texas.

54 ENVIRONMENTAL SCIENCES↗