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At least 163 records · Page 9

ED-cPSD: Fast Phase-Size Distribution via Sequential Erosion-Dilation

The Erosion-Dilation continuous Phase-Size Distribution, ED-cPSD, is an application for calculating continuous pore and particle-size distribution from digital reconstructions and/or image-based structural data. It is based on the erosion-dilation continuous phase-size distribution method. A continuous size distribution is a measure of the probability density of finding a particle or pore of a certain size. These distributions are of interest in any field of study involving porous media, including but not limited to electrochemistry, petroleum engineering, geology, and food science. The algorithm behind the software provides a computationally efficient way to calculate phase-size distributions for large domains. For a 3D battery electrode reconstruction with 1.3 x 10 8 voxels, the particle size distribution is derived in under 2 min on a desktop, while also retaining flexibility and computational efficiency for HPC-scale multi-threading. The software can handle structures with over 10 9 voxels. The algorithm is roughly 280 times faster than a previous version on the same task.

Characterization↗

Characterizing how size distribution and concentration affect echogenicity of ultrasound contrast agents

Here, we investigated the effects of UCA gas bubble size distribution and concentration on the generated ultrasound echogenicity signal. Gas bubble size characterization using Coulter Counter and cryogenic-SEM revealed the hollow structure and rare presence of microbubbles >10 µm in a commercial UCA product, Lumason™. Volume-weighed size and concentration were observed to be more sensitive to changes in UCA bubble stability than number-weighted size and concentration. Size distribution measurements showed that the force (e.g., shaking/agitation energy) used to redisperse the sample did not affect the size distribution, concentration, or echogenicity of the UCA sample. The ultrasound backscattering coefficient (BSC) of size fractionated and serial diluted microbubbles showed that the echogenicity signal correlates most with UCA bubble concentration, especially volume-weighted concentration. Findings from this study may be used to support demonstrating the equivalence of a generic UCA product to the reference listed drug.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO

Abstract Streambed grain sizes control river hydro‐biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo‐driven, artificial intelligence (AI)‐enabled, and theory‐based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground‐truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log‐normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy‐Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.

58 GEOSCIENCES↗

Data Report: UT-GOM2-1 Sediment Grain Size Measurements at Site GC 955, Holes H002 and H005

Sediment grain size measurement in marine sediments provides a record of the stratigraphic variation in grain size and thus energy regime at the time of deposition. In addition to the grain size distribution, the degree of sediment sorting can also be calculated, and together they both influence primary sediment porosity and permeability. Here we present sediment grain size results from laser diffraction particle size analysis of samples from pressure cores collected during the 2017 UT GOM2-1 Expedition. We measured both bulk sediment and organic carbon-free sediment fractions for 46 samples and organic carbon-free sediment for 5 samples at Site GC 955, Holes H002 and H005. Differences between the bulk sediment and organic carbon-free fractions reflect the relative amount and size fraction of the organic carbon. The sample results presented here represent the grain size variation of the host lithology across the Green Canyon (GC) 955 gas hydrate reservoir.

03 NATURAL GAS↗

Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose

Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.

09 BIOMASS FUELS↗

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22–20 μm) and micro-eukaryotes (20–200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

Spatial Mapping of Riverbed Grain-Size Distribution Using Machine Learning

Recent alluvial sediments in riverbeds play a significant role in controlling hydrologic exchange flows (HEFs) in river systems. The alluvial layer is usually associated with strong heterogeneity in physical properties (e.g., permeability and hydraulic conductivity), which affects local HEFs and therefore biogeochemical processes. The spatial distribution of these physical properties needs to be determined to inform the numerical models used to reveal the realistic hydro-biogeochemical behaviors. Such information can be obtained based on the intrinsic link between sediment grain-size distribution and hydraulic properties where sediment texture information is available. However, grain-size measurements are usually spatially sparse and do not have adequate coverage and resolution, particularly for a relatively large domain such as the Hanford Reach of the Columbia River. In this paper, we adopted machine learning (ML) approaches for categorizing and mapping the spatial distributions of riverbed substrate grain size and filling in missing areas of substrate data using the ML models along the reach. Such ML models for substrate size mapping were trained at 13,372 locations using measured substrate sizes along with observed and simulated attributes, including bathymetric attributes (e.g., elevation, slope, and aspect ratio) from LIDAR and bathymetric surveys, and hydrodynamic properties (e.g., water depth, velocity, shear stress, and their statistical moments). An ensemble bagging-based ML technique, Random Forest, was adopted to identify the most influential factors as predictors to develop the predictive models with over-fitting issues addressed. The models were evaluated with respect to each individual substrate size class and the lumped group, and then used to generate the final substrate size maps covering all the grid cells in the numerical modeling domain.

54 ENVIRONMENTAL SCIENCES↗

How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null-hypothesis that simulating the presence of a large mass fraction of phyllosilicates in dust aerosols in the size range 2 m, in comparison to a simple model assumption where this is neglected, does not yield a significant effect on the magnitude and geographical distribution of the predicted IFN number. Results from sensitivity experiments are presented as well.

Dust↗

On the Interplay between Size and Disorder in Suppressing Intercalation-Induced Phase Transitions in Pseudocapacitive Nanostructured MoS 2

Pseudocapacitors are an emerging class of energy storage materials that offer an attractive compromise between the energy density of batteries and power density of electric double-layer capacitors. Decreasing particle size and increasing surface area of battery materials is a common approach for introducing pseudocapacitive behavior and increasing power density. However, in many cases, as the crystal size is reduced, lattice disorder of unknown extent is also introduced, making it difficult to characterize the relative contribution of size and disorder to fast-charging performance. Here, in this work, a series of nanostructured MoS 2 materials are synthesized with different crystallite sizes and degrees of crystallinity to decouple the effects of size and disorder on charge/discharge kinetics. The extent and type of disorder in each material is quantified by total X-ray scattering experiments and pair distribution function analyses. Electrochemical characterization, including galvanostatic rate capability, cyclic voltammetry, and various kinetic analyses, are used to demonstrate that both decreasing particle size and introducing lattice disorder are effective strategies for increasing charge storage kinetics, and that the effects are additive. Finally, operando X-ray diffraction measurements show that both size and disorder can be used suppress first-order Li + intercalation-induced phase transitions, a key feature for enabling pseudocapacitive charge storage.

36 MATERIALS SCIENCE↗

Interlaminar improvement of carbon fiber/epoxy composites via fluorine‐containing high‐epoxy‐value sizing agent

Abstract To improve the interfacial bonding effect of carbon fibers (CFs) and epoxy resins, we prepared a fluorine‐containing high‐epoxy‐value sizing agent (named TS) in this article. It is an emulsion with a more uniform particle size distribution and higher stability better than a commercial Takemoto sizing agent. In addition, sulfonic acid groups can improve the hydrophilicity of the TS, and the presence of epoxy groups enhances the wettability between CFs and the matrix. The properties of the sizing agents were examined by Fourier transform infrared spectroscopy, dynamic light scattering, and thermogravimetric analysis. The sized CFs were evaluated by scanning electron microscopy, x‐ray photoelectron spectroscopy, monofilament tensile test, and dynamic contact angle. Afterward, CF/epoxy composites were prepared, and their fracture morphology and interlaminar shear strength (ILSS) were examined. Results indicated that the TS sizing significantly increased the content of activated carbon on the surface of the CFs and improved the bonding effect between the fiber and the matrix. After TS was sized, the ILSS increased from 49.64 to 58.74 MPa, 18.34% higher than unsized CF/epoxy composites, showing the prominent interfacial reinforcement better than commercial Takemoto.

Qiu, Zhijie↗

Grain size dependencies of intergranular solute segregation in nanocrystalline materials

Grain boundary segregation is of increasing importance for stabilizing nanocrystalline alloys, and while segregation is typically modeled as a scale-independent phenomenon, at the finest nanocrystalline grain sizes there are several sources of grain size dependence. Here we provide quantitative detail on two grain size dependencies not previously elaborated, both of which arise from the spectrality of intergranular segregation sites. The first of these arises because a change in grain size affects which portions of the segregation spectrum are occupied by the solutes, with no change in the shape or nature of the spectrum itself. The second of these arises from the presence of higher-order grain junctions, which have unique segregation behaviors and an increasing relative presence at finer grain sizes. This paper uses molecular statics to quantify these size dependencies in detail for the case of an Al(Mg) binary alloy. Together, these two effects combined have a significant effect on the effective McLean segregation energy of more than 6 kJ/mol (from approximately -18.5 kJ/mol at 5 nm to -12.5 kJ/mol at more than 40 nm), with the majority of grain size dependence arising from the spectrality of segregation sites.

36 MATERIALS SCIENCE↗

Atomistic simulations of nanoindentation on nanoglasses: Effects of grain size and gradient microstructure on the mechanical properties

The use of nanoglass (NG) microstructures has been shown as an effective strategy to improve the ductility of rather brittle metallic glass alloys. To evaluate the effects of grain size and gradient design on the mechanical properties of NGs, we perform molecular dynamics simulations of nanoindentation on Cu 64 Zr 36 NGs. We consider samples with uniform 3 and 7 nm grain sizes as well as gradient microstructures with gradient grain sizes varying from 3 to 7 nm. Here, the results show that the deformation mechanism in NGs with small grain sizes is dominated by the activation and evolution of multiple shear transformation zones. Increasing grain sizes enhances the elastic modulus and hardness at the cost of reduced abrasion resistance. Though the average grain size at the indentation surface plays a crucial role in the deformation behavior of gradient NG models, their strain localization and plastic deformation states are affected by the grain sizes far from the indenter. Desired combinations of mechanical properties can be realized by different NG microstructure designs.

36 MATERIALS SCIENCE↗

Pt Particle Size Affects Both the Charge Separation and Water Reduction Efficiencies of CdS–Pt Nanorod Photocatalysts for Light Driven H 2 Generation

Decreasing the metal catalyst size into nanoclusters or even single atom is an emerging direction of developing more efficient and cost-effective photocatalytic systems. Because the catalyst particle size affects both the catalyst activity and light driven charge separation efficiency, their effects on the overall photocatalytic efficiency are still poorly understood. Herein, using a well-defined semiconductor–metal heterostructure with Pt nanoparticle catalysts selectively grown on the apexes of CdS nanorods (NRs), we study the effect of the Pt catalyst size on light driven H 2 generation quantum efficiency (QE H 2 ). With the increase of the Pt catalyst size from 0.7 ± 0.3 to 3.0 ± 0.8 nm, the QEH 2 of CdS–Pt increases from 0.5 ± 0.2% to 38.3 ± 5.1%, by nearly 2 orders of magnitude. Transient absorption spectroscopy measurement reveals that the electron transfer rate from the CdS NR to the Pt tip increases with the Pt diameter following a scaling law of d 5.6 , giving rise to the increase of electron transfer efficiency at larger Pt sizes. Additionally, the observed trend can be understood by a simplified kinetic model that assumes the overall efficiency is the product of the quantum efficiencies of charge separation (including hole transfer, electron transfer, and hole scavenging) and water reduction steps, and for CdS–Pt NRs, the quantum efficiencies of electron transfer and water reduction steps increase with the Pt sizes. Our findings suggest the importance of improving the quantum efficiencies of both charge separation and catalysis in designing efficient semiconductor–metal hybrid photocatalysts, especially in the regime of small metal particle sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Asteroids seen by JWST-MIRI: Radiometric size, distance, and orbit constraints

Infrared measurements of asteroids are crucial for the determination of physical and thermal properties of individual objects, and for understanding the small-body populations in the solar system as a whole. However, standard radiometric methods can only be applied if the orbit of an object is known, hence its position at the time of the observation. With JWST-MIRI observations the situation will change and many unknown, often very small, solar system objects will be detected. Later orbit determinations are difficult due to the faintness of the objects and the lack of dedicated follow-up concepts. We present MIRI observations of the outer-belt asteroid (10920) 1998 BC1 and an unknown object, detected in all nine MIRI bands in close apparent proximity to (10920). We developed a new method called STM-ORBIT to interpret the multi-band measurements without knowing the object’s true location. The power of the new technique is that it determines the most-likely heliocentric and observer-centric distance and phase angle ranges, allowing us to make a radiometric size estimate. The application to the MIRI fluxes of (10920) was used to validate the method. It leads to a confirmation of the known radiometric size-albedo solution, and puts constraints on the asteroid’s location and orbit in agreement with its true orbit. To back up the validation of the method, we obtained additional ground-based light curve observations of (10920), combined with Gaia data, which indicate a very elongated object (a/b ≥ 1.5), with a spin-pole at (λ, β) ecl = (178°, +81°), with an estimated error of about 20°, and a rotation period of 4.861191 ± 0.000015 h. A thermophysical study of all available JWST-MIRI and WISE measurements leads to a size of 14.5–16.5 km (diameter of an equal-volume sphere), a geometric albedo pV between 0.05 and 0.10, and a thermal inertia in the range 9–35 (best value 15) J m -2 s -0.5 K -1 . For the newly discovered MIRI object, the STM-ORBIT method revealed a size of 100–230 m. The new asteroid must be on a low-inclination orbit (0.7° < i < 2.0°) and it was located in the inner main-belt region during JWST observations. A beaming parameter η larger than 1.0 would push the size even below 100 meters, a main-belt regime that has escaped IR detections so far. This kind of MIRI observations can therefore contribute to formation and evolution studies via classical size-frequency studies, which are currently limited to objects larger than about one kilometer in size. We estimate that MIRI frames with pointings close to the ecliptic and short integration times of only a few seconds will always include a few asteroids; most of them will be unknown objects.

79 ASTRONOMY AND ASTROPHYSICS↗

Two rest-frame wavelength measurements of galaxy sizes at z < 1: the evolutionary effects of emerging bulges and quenched newcomers

We analyse the size evolution of 16 000 star-forming galaxies (SFGs) and 5000 quiescent galaxies (QGs) with mass M * > 10 9.5 M ⊙ at 0.1 < z < 0.9 from the COSMOS field using deep CLAUDS + HSC imaging in two rest-frame wavelengths, 3000 Å (UV light) and 5000 Å (visible light). With half-light radius (R e ) as proxy for size, SFGs at characteristic mass M 0 = 5 × 10 10 M ⊙ grow by 20 per cent (30 per cent) in UV (visible) light since z ~ 1 and the strength of their size evolution increases with stellar mass. After accounting for mass growth due to star formation, we estimate that SFGs grow by 75 per cent in all stellar mass bins and in both rest-frame wavelengths. Redder SFGs are more massive, smaller and more concentrated than bluer SFGs and the fraction of red SFGs increases with time. These results point to the emergence of bulges as the dominant mechanism for the average size growth of SFGs. We find two threshold values for the stellar mass density within central 1 kpc (Σ 1 ): all SFGs with log Σ 1 ≳ 9 are red and only QGs have log Σ 1 ≳ 9.7. The size of M * = M 0 QGs grows by 50 per cent (110 per cent) in the UV (visible) light. Up to $\sim 20~{{\rm per\,cent}}$ of this increase in size of massive QGs is due to newcomers (recently quenched galaxies). However, newcomers cannot explain the observed pace in the size growth of QGs; that trend has to be dominated by processes affecting individual galaxies, such as minor mergers and accretion.

79 ASTRONOMY AND ASTROPHYSICS↗

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗

Experimental Report: Multi-Instrument Comparison of AAF Size Distribution Instruments

Aerosols are particles suspended in the atmosphere, ranging in size from nanometers to micrometers. Their size distribution affects key atmospheric processes, including nucleation, coagulation, scavenging, activation, and radiative properties (Seinfeld and Pandis 2016). Aerosol size distribution is a critical parameter in atmospheric science, influencing processes such as cloud formation and radiative forcing. Accurate representation of aerosol size distributions is essential for understanding their impact on climate, air quality, and human health. However, aerosol size and composition vary significantly across time and space due to meteorological conditions and natural or anthropogenic sources. (Wu and Boor 2021). Various instruments are used to measure aerosol size distributions, each with distinct principles, advantages, and limitations. This report begins with an in-depth overview of aerosol size-distribution comparison studies, focusing on the passive cavity aerosol spectrometer probe (PCASP), portable optical particle spectrometer (POPS), ultra-high-sensitivity aerosol spectrometer (UHSAS), aerodynamic particle sizer (APS), and scanning mobility particle sizer (SMPS). All of these instruments are used by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), which commissioned this comparison and report. The report evaluates the strengths and weaknesses of these instruments, highlights their applications, and discusses efforts to merge data from multiple instruments for comprehensive analysis.

54 ENVIRONMENTAL SCIENCES↗

Early Results from GLASS-JWST. V: The First Rest-frame Optical Size–Luminosity Relation of Galaxies at z > 7

We present the first rest-frame optical size–luminosity relation of galaxies at z > 7, using the NIRCam imaging data obtained by the GLASS James Webb Space Telescope Early Release Science (GLASS-JWST-ERS) program, providing the deepest extragalactic data of the ERS campaign. Our sample consists of 19 photometrically selected bright galaxies with m F444W ≤ 27.8 at 7 < z < 9 and m F444W < 28.2 at z ~ 9–15. We measure the size of the galaxies in five bands, from rest-frame optical (~4800 Å) to the UV (~1600 Å) based on the Sérsic model, and analyse the size–luminosity relation as a function of wavelength. Remarkably, the data quality of the NIRCam imaging is sufficient to probe the half-light radius r e down to ~100 pc at z > 7. Given the limited sample size and magnitude range, we first fix the slope to that observed for larger samples in rest-frame UV using Hubble Space Telescope samples. The median size r 0 at the reference luminosity M = –21 decreases slightly from rest-frame optical (600 ± 80 pc) to UV (450 ± 130 pc). We then refit the size–luminosity relation allowing the slope to vary. The slope is consistent with β ~ 0.2 for all bands except F150W, where we find a marginally steeper slope of β = 0.53 ± 0.15. The steep UV slope is mainly driven by the smallest and faintest galaxies. If confirmed by larger samples, it implies that the UV size–luminosity relation breaks toward the faint end, as suggested by lensing studies.

79 ASTRONOMY AND ASTROPHYSICS↗