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At least 145 records · Page 8

Understanding the Effects of Inhomogeneities at the Back Interface of CdTe‐Based Solar Cells Using 2D Modeling

One-dimensional modeling cannot capture lateral inhomogeneities in CdTe-based devices. Here, we use 2D modeling to investigate the role of varying energetics at the back interface. We consider improvements in the back interface layer (BIL) through either reducing back surface recombination velocity (BSRV) or decreasing the downward band bending near the back interface. We show that when the BSRV is reduced, but strong downward band bending remains, there is no change in the device performance until the BSRV of 90% of the back interface is improved by the BIL. On the other hand, any coverage with a BIL that improves band bending results in device improvements. We use band bending, back interface recombination current densities, and voltage dependent current flow through the device to understand these improvements. The modeling shows that lateral flow of carriers greatly affects device performance, which is not captured in parallel diode modeling, and demonstrates improved understanding with 2D modeling.

2D modelling↗

ON THE EFFECTIVENESS OF LLMS IN UNIT TEST GENERATION FOR STRUCTURED TEXT PROGRAMS

The reliability of industrial automation systems heavily depends on the correctness of Programmable Logic Controller (PLC) programs, which are often written in Structured Text (ST). While Large Language Models (LLMs) have shown promise in automating test generation for mainstream programming languages, their effectiveness for the syntactically strict ST language remains underexplored. This thesis presents a systematic empirical evaluation of three state-of-the-art LLMs—GPT-4o, Gemini 2.5 Pro, and Claude Sonnet 4.5—for generating ST unit tests. We examine three prompting strategies: Natural Language (NL), Code Language (CL), and Chain-of-Thought (CoT), across a curated set of 11 ST function blocks. The quality of the generated tests is assessed using Compilation Success Rate (CSR), Statement Coverage (SC), and Branch Coverage (BC). In the zero-shot setting, Claude Sonnet 4.5 achieves the highest CSR, while Gemini 2.5 Pro consistently delivers the best statement and branch coverage, particularly under CL prompts. By incorporating a one-shot CL prompt, all models exhibit substantial improvements—most notably GPT-4o, whose CSR increases from 45.45% to 90.91%, with substantial gains in both SC and BC. To further contextualize these findings, we compare GPT-4o’s one-shot results with PLCAutoTester, a state-ofthe- art ST unit test generation tool, on an additional benchmark dataset. While LLMgenerated tests approach competitive coverage levels, PLCAutoTester maintains significantly higher and more stable coverage across programs. This study provides the first comprehensive benchmark of modern LLMs for ST unit testing, highlighting their strengths, limitations, and improvements through one-shot prompting, and positioning their performance relative to specialized automated testing tools in industrial automation.

42 ENGINEERING↗

Impact of Particle Size on the Vapor-Phase Oxidative Coupling of Methanol and Dimethylamine over Palladium–Gold Nanoparticles

Oxidative coupling of methanol and dimethylamine in the presence of O 2 in the vapor phase over dilute Pd in Au bimetallic catalysts occurs via the dissociation of O 2 on Pd and selective oxidation of methanol on Au. Here, we synthesize a series of silica-supported PdAu alloy nanoparticle catalysts of varied Pd:Au ratios with ~5 nm particle diameter and show that these catalysts have increased selectivity to dimethylformamide across all Pd:Au ratios (~95%), distinct from observations over larger PdAu nanoparticles (~15–25 nm diameter) of similar Pd:Au ratios. Small monometallic Pd particles are more selective than large monometallic Pd particles, and small Au nanoparticles are reactive and selective for oxidative coupling (while large Au nanoparticles are inactive). Rates per surface metal atom were similar over PdAu nanoparticles of all sizes and increased monotonically with increasing Pd content for the small nanoparticles. Further, apparent reaction kinetics demonstrate distinct apparent methanol reaction order and apparent activation energy relative to those reported over larger nanoparticles of similar Pd:Au ratios. Unlike larger PdAu nanoparticles, the rate of dimethylformamide formation is not promoted by cofed water over small PdAu nanoparticles. The results of the kinetic studies are used to propose a series of elementary steps, derive a plausible rate expression, and regress rate and equilibrium constants. These results suggest high coverages of surface methoxy species and low coverages of adsorbates derived from dimethylamine. Taken together, these results demonstrate the sensitivity of the rates, selectivities, and kinetics of oxidative coupling reactions to the size of bimetallic nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Landau–Zener Transition Enhanced Quantum Sensing in Spin Defects of Hexagonal Boron Nitride

Negatively charged boron vacancies (V $^{–}_{B}$ ) in hexagonal boron nitride (hBN) comprise a promising quantum sensing platform, optically addressable at room temperature and transferable onto samples. However, broad hyperfine-split spin transitions of the ensemble pose challenges for quantum sensing with conventional resonant excitation due to limited spectral coverage. While V $^{–}_{B}$ in isotopically enriched hBN using 10 B and 15 N isotopes (h 10 B 15 N) exhibits sharper spectral features, significant inhomogeneous broadening persists. We show that, implemented via frequency modulation on an FPGA, a frequency-ramped microwave pulse achieves around 4-fold greater |0⟩→|−1⟩ spin-state population transfer and thus contrast than resonant microwave excitation and thus 16-fold shorter measurement time for spin relaxation-based quantum sensing. Quantum dynamics simulations reveal that an effective two-state Landau–Zener model captures the complex relationship between population inversion and pulse length with relaxations incorporated. Our approach is robust and valuable for quantum relaxometry with spin defects in hBN, especially in noisy environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗

Sieving Hydrogen Isotopes via Machine Learning Assisted Chemical Vapor Deposition (CVD) of High‐Quality Monolayer Hexagonal Boron Nitride (h‐BN) on Iron Foils

Atomically thin two-dimensional (2D) ceramics, such as monolayer hexagonal boron nitride (h-BN), present potential for disruptive advances in separations. However, sub-atomic scale separation of hydrogen isotopes (H + /D + ) require near pristine 2D material membranes, and scalable synthesis of such high-quality h-BN comparable to mechanically exfoliated crystals remains a significant challenge. Here, we report a scalable Fe-catalyzed chemical vapor deposition (CVD) process for bottom-up synthesis of large-area, high-quality monolayer h-BN films, overcoming key limitations of conventional ammonia-based routes. By leveraging mechanistic insights and higher CVD temperatures, we suppress multilayer formation and achieve uniform monolayer h-BN coverage on commercially available Fe foils. Machine learning enables systematic exploration of the complex, multi-dimensional CVD parameter space (growth time, temperature, precursor temperature, multilayer faction, coverage), providing data-driven approaches to visualize and identify process regimes facilitating predominantly monolayer h-BN growth with minimal secondary nuclei/ad-layers. The optimized Fe-catalyzed CVD h-BN membranes show high-quality as observed by proton/deuteron (H + /D + ) selectivity ≈8.45, approaching the highest quality benchmark of mechanically exfoliated h-BN (H + /D + selectivity ≈10) as well as significantly outperforming Cu-catalyzed CVD h-BN membranes (H + /D + selectivity ≈3.62, control selectivity ≈1.7). Our work provides a scalable cost-effective route for high-quality monolayer h-BN synthesis for sub-atomic scale separations (H + /D + ) and demonstrates the broader potential of machine learning-guided optimization of CVD for advancing synthesis of 2D materials.

36 MATERIALS SCIENCE↗

Activation of propane on Ag–PdO(101) model surfaces

Oxidation of alkanes remains a central challenge in catalysis due to the high activation barriers of C–H bonds and the thermodynamic favorability of complete oxidation. Palladium oxide (PdO), particularly its (101) facet, is known for its high reactivity in alkane oxidation, which is attributed to its coordinatively unsaturated palladium (Pd) and O atoms. In this study, we investigate the effect of silver (Ag) incorporation on the oxidation behavior of propane over PdO(101) using temperature-programmed reaction spectroscopy (TPRS) under controlled conditions. While pristine PdO(101) exhibits complete oxidation of propane with CO₂ and H₂O desorption at high temperatures (approximately 475 K), Ag incorporation induces a new CO₂ desorption peak at significantly lower temperatures (approximately 330 K). This shift is attributed to the formation of new active sites at the Ag–PdO(101) interface. Quantitative analysis reveals that low-temperature activity correlates with Ag coverage, while overall CO₂ production decreases, suggesting a redistribution of reactivity rather than an increase in active surface area. Activation energy estimations using the Redhead method confirm that C–H bond activation becomes more facile at the interface, with a 46 kJ/mol reduction compared to pristine PdO(101). These findings demonstrate that incorporating a less reactive metal such as Ag into PdO surfaces not only modifies the reaction energetics but also enables the design of bimetallic catalysts with improved selectivity for partial oxidation reactions.

Chemistry↗

ULTRA-effective labeling of tandem repeats in genomic sequence

In the age of long read sequencing, genomics researchers now have access to accurate repetitive DNA sequence (including satellites) that, due to the limitations of short read-sequencing, could previously be observed only as unmappable fragments. Tools that annotate repetitive sequence are now more important than ever, so that we can better understand newly uncovered repetitive sequences, and also so that we can mitigate errors in bioinformatic software caused by those repetitive sequences. To that end, we introduce the 1.0 release of our tool for identifying and annotating locally repetitive sequence, ULTRA Locates Tandemly Repetitive Areas (ULTRA). ULTRA is fast enough to use as part of an efficient annotation pipeline, produces state-of-the-art reliable coverage of repetitive regions containing many mutations, and provides interpretable statistics and labels for repetitive regions.

59 BASIC BIOLOGICAL SCIENCES↗

Heteroepitaxial control of thickness, strain, and domain architecture in few-layer ferroelectric tin monochalcogenides

Thin-film epitaxy and epitaxial strain have been widely exploited to tune domain configurations, switching behavior, and ferroic properties in conventional three-dimensional ferroelectric thin films; however, its application to controlling the properties of two-dimensional (2D) ferroelectrics has remained largely unexplored. Here, using SnX (X = Se, S) as a model system, we demonstrate heteroepitaxial control of thickness, strain state, and domain architecture in few-layer ferroelectric SnX via growth on monolayer MoS2 van der Waals (vdW) templates. Compared with conventional growth, MoS2-templated heteroepitaxy promotes epitaxial alignment, yielding ultrathin SnSe films with improved crystalline quality, full areal coverage, and enlarged lateral dimensions. Strong interfacial epitaxial coupling induces pronounced in-plane strain and stabilizes a hierarchical ferroelastic domain architecture, in which long-range 90° stripe domains are further subdivided into nanoscale rotational variants, as revealed by scanning transmission electron microscopy and synchrotron X-ray microscopy. Piezoresponse force microscopy and second-harmonic polarimetry confirm robust in-plane polarization, while ferroelectricity in SnSe is established through polarization-electric field hysteresis and nonvolatile ferroelectric resistive switching with on/off ratios approaching 1000. A nonvolatile, switchable ferroelectric diode effect further evidences direct coupling between polarization and charge transport. Notably, ferroelectric switchability exhibits a strong thickness dependence and is preserved only below ∼10 layers. This vdW heteroepitaxial strategy is further extended to ferroelectric SnS. The seamless heteroepitaxial integration of 2D ferroelectrics with CMOS-compatible, wafer-scale MoS2 templates provides a general and scalable route for strain-enabled structural and ferroelectric engineering in emerging memory and low-power optoelectronic applications.

Wang, Yueyin↗

Enhanced nucleation mechanism in ruthenium atomic layer deposition: Exploring surface termination and precursor ligand effects with RuCpEt(CO)2

Miniaturization of microelectronic devices necessitates atomic precision in manufacturing techniques, particularly in the deposition of thin films. Atomic layer deposition (ALD) is recognized for its precision in controlling film thickness and composition on intricate three-dimensional structures. This study focuses on the ALD nucleation and growth mechanisms of ruthenium (Ru), a metal that has significant future implications for microelectronics. Despite its advantages, the deposition of a high surface-free energy material like Ru on a low surface-free energy material such as an oxide often faces challenges of large nucleation delays and non-uniform growth. To address these challenges, we explored the effectiveness of organometallic surface pretreatments using trimethylaluminum (TMA) or diethylzinc (DEZ) to enhance Ru film nucleation and growth. Our study employed a less-studied Ru precursor, cyclopentadienylethyl(dicarbonyl)ruthenium [RuCpEt(CO)2], which demonstrated promising results in terms of reduced nucleation delay and increased film continuity. Ru ALD was performed on silicon substrates with native oxide, using RuCpEt(CO)2 and O2 as coreactants. Our findings reveal that surface pretreatment significantly improves nucleation density and film thickness within the initial 60 ALD cycles, achieving up to a 3.2-fold increase in Ru surface coverage compared to nonpretreated substrates. Supported by density functional theory calculations, we propose that the enhanced nucleation observed with RuCpEt(CO)2 compared to previously-studied Ru(Cp)2 is due to two key mechanisms: the facilitated removal of CO ligands during deposition, which enhances the reactivity of the precursor, and a hydrogen-abstraction reaction involving the ethyl ligand of RuCpEt(CO)2 and the metal-alkyl groups on the surface. This study not only advances our understanding of Ru ALD processes but also highlights the significant impact of precursor chemistry and surface treatments in optimizing ALD for advanced microelectronic applications.

Materials Science↗

Variation in Cation Adsorption Mechanism Controlled by Chemical and Structural Heterogeneities at the Quartz (101)–Water Interface

Mineral–water interfacial reactions are central to chemical processes that control the fate of nutrients and contaminants in natural environments. Mineral surfaces commonly have complex structures and compositions whose impact on interfacial reactivity is poorly understood. Here, in this work, we investigated the effects of surface heterogeneities on Rb + sorption at the quartz (101)–10 mM RbCl solution interface at pH 9.8 using in situ high-resolution X-ray reflectivity. Two surface locales (i.e., Spots A and B) having distinct interfacial structures were chosen: Spot A was characterized by its low defect density (≤20% topmost Si vacancies) and Rb + adsorption occurred predominantly as an inner-sphere complex. In comparison, Spot B had a higher defect density (~50% vacancies) and was covered with poorly crystalline SiO 2 . A substantially larger Rb + uptake (i.e., 7-times higher coverage) was observed on this defective surface where Rb + incorporated in the vacancy sites (confirmed by density functional tight binding-based molecular dynamics simulations) or adsorbed directly on the disordered film. These results provide a direct quantification of how surface heterogeneity influences the geochemical behavior of mineral–water interfaces, in particular highlighting the important role of chemical and structural defects on the sorbate speciation and coverage at silicate mineral surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New developments and verification of fusion blanket simulation capabilities in the MOOSE framework

Multiphysics modeling capabilities have a crucial role to play in the accelerated deployment of fusion energy. To that end, we developed new multiphysics fusion blanket simulation capabilities in the Multiphysics Object-Oriented Simulation Environment (MOOSE). Firstly, we expanded on the existing capabilities of the previously published work, by coupling 3D tritium transport modeling capabilities using the Tritium Migration Analysis Program, version 8 (TMAP8) to an existing tool including thermal hydraulics, fully three-dimensional (3D) heat transfer, and loosely coupled neutronics analysis. Secondly, we performed a thorough verification of the new capabilities and increased testing code coverage to meet MOOSE’s software quality standards. The MOOSE framework follows a strict software quality assurance plan to be Nuclear Quality Assurance, Level 1 compliant. The new multiphysics fusion blanket simulation capabilities are now held to the same standard. Thirdly, to demonstrate MOOSE’s new fusion blanket modeling capabilities, we performed a fully integrated, multiphysics simulation of a 3D solid ceramic breeder blanket design. This proof-of-concept simulation provides the temperature and tritium distribution across the blanket. In conclusion, the combined efforts towards software quality and the development of multiphysics coupling capabilities provide an effective and reliable framework for modeling solid ceramic fusion blankets using MOOSE.

modeling and simulation↗

Spatially resolved polarization swings in the supermassive binary black hole candidate OJ 287 with first Event Horizon Telescope observations

We present the first Event Horizon Telescope 1.3 mm observations of the supermassive binary black hole candidate OJ 287. The observations achieved an unprecedented angular resolution of 18 μas and reveal significant structural and polarization variability over just five days, marking the shortest timescale on which such changes have been directly imaged in this source. The inner jet exhibits a twisted ridgeline structure, with features displaying apparent superluminal motions up to about 22 c. The linear polarization maps reveal three main polarized features whose electric-vector position angles (EVPAs) change substantially over the time span of our observations, including a component with a radial polarization consistent with being produced by a recollimation shock. Most notably, we directly resolved two innermost jet components whose EVPAs rotate in opposite directions. The faster component, moving at 2.4 ± 0.9 μas/day (17.4 ± 6.5 c), exhibits counterclockwise EVPA swings of roughly 3.7° per day, while the slower component, with a proper motion of 1.4 ± 0.3 μas/day (10.2 ± 2.2 c), rotates clockwise at approximately 2.5° per day. Previous studies inferred helical magnetic fields in AGN jets from time-resolved or integrated polarization variability but lacked the angular resolution to directly image this effect. Our results provide spatially resolved evidence that a helical magnetic field threads the jet’s collimation and acceleration zone, ruling out models based on the superposition of unresolved components. Our analysis suggests that propagating shocks interact with a Kelvin–Helmholtz plasma instability, illuminating different phases of the helical magnetic field and producing the observed polarization spatial and temporal variability. Moreover, our model naturally accounts for the more rapid polarization rotation observed in the faster moving component. Our model predicts even more rapid swings in polarization, which could be tested with future observations featuring a more densely sampled time coverage.

OJ 287↗

Improving Miscibility of Polymer Donor and Polymer Acceptor by Reducing Chain Entanglement for Realizing 18.64 % Efficiency All Polymer Solar Cells

All-polymer solar cells have experienced rapid development in recent years by the emergence of polymerized small molecular acceptors (PSMAs). However, the strong chain entanglements of polymer donors (P D s) and polymer acceptors (P A s) decrease the miscibility of the resulting polymer mixtures, making it challenging to optimize the blend morphology. Herein, we designed three P A s, namely PBTPICm-BDD, PBTPICγ-BDD and PBTPICF-BDD, by smartly using a BDD unit as the polymerized unit to copolymerize with different Y-typed non-fullerene small molecular acceptors (NF-SMAs), thus achieving a certain degree of distortion and giving the polymer system enough internal space to reduce the entanglements of the polymer chains. Such effects increase the chances of the P D being interspersed into the acceptor material, which improve the solubility between the P D and P A . The PBTPICγ-BDD and PBTPICF-BDD displayed better miscibility with PBQx-TCl, leading to a well optimized morphology. As a result, high power conversion efficiencies (PCEs) of 17.50 % and 17.17 % were achieved for PBQx-TCl : PBTPICγ-BDD and PBQx-TCl : PBTPICF-BDD devices, respectively. In conclusion, with the addition of PYFT-o as the third component into PBQx-TCl : PBTPICγ-BDD blend to further extend the absorption spectral coverage and finely tune microstructures of the blend morphology, a remarkable PCE of 18.64 % was realized finally.

36 MATERIALS SCIENCE↗

Supernova pointing capabilities of DUNE

The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on 40 Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called “brems flipping,” as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE’s burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Supernova pointing capabilities of DUNE

The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on Ar 40 and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called “brems flipping,” as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE’s burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Private, public, and bottled drinking water: Shared contaminant-mixture exposures and effects challenge

Background: Humans are primary drivers of environmental–contaminant exposures worldwide, including in drinking-water (DW). In the United States, point-of-use DW (POU–DW) is supplied via private tapwater (TW), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly–intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision–making. Objectives: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU–DW contaminant–mixture exposures and corresponding potential human–health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical–health–benchmark–weighted and bioactivity–weighted effects predictions across previous studies by this research group. Discussion: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supplies. Differences in contaminant or contaminant–class exposures, with important implications for DW–quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring. Conclusion: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW–supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low–level inorganic–/organic–contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased public engagement in source-water protection and drinking–water treatment is necessary to reduce risks associated with long-term DW–contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.

54 ENVIRONMENTAL SCIENCES↗

Measurement report: Vertically resolved atmospheric properties observed over the Southern Great Plains with the ArcticShark uncrewed aerial system

Abstract. This study presents the unique capability of the Department of Energy (DOE) ArcticShark – a mid-size fixed-wing uncrewed aerial system (UAS) – for measuring vertically resolved atmospheric properties over the Southern Great Plains (SGP) of the United States. Focusing on atmospheric states, such as ambient temperature, wind, and aerosol properties, we overview measurements from 32 research flights (∼ 97 flight hours) in 2023. The August operations, aided by a visual observer on a chase plane, allowed for extensive UAS coverage, surpassing typical UAS operation envelopes. Our data from March, June, and August 2023 reveal distinctive seasonal patterns within the atmospheric column through unique chemical composition measurements. In situ measurements combined with remote sensing retrievals and radiosonde measurements provided valuable insights into their consistency and complementarity. Furthermore, we demonstrate the capabilities of the ArcticShark through several case studies, including the analyses of correlations between UAS-derived atmospheric profiles and conventional radiosonde measurements, as well as the derivation of vertically resolved profiles of aerosol chemical, optical, and microphysical properties. These case studies highlight the versatility of the ArcticShark UAS as a powerful tool for comprehensive atmospheric research, effectively bridging data gaps and enhancing our understanding of vertical atmospheric structures in the region.

54 ENVIRONMENTAL SCIENCES↗