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At least 1,189 records · Page 66

Importance of finite-size corrections for accurate ab initio modeling of carrier capture at semiconductor defects: A case study of substitutional C N in GaN

In ab initio studies of carrier-capture processes in defective semiconductor materials, the single-effective-mode formalism and the static-coupling approximation have become the predominant theoretical approaches for determining carrier-capture coefficients. The single-mode formalism relies on accurate nonequilibrium defect energies obtained from density-functional theory (DFT), where required inputs are a series of configurationally displaced, defect-containing supercells obtained using an interpolative ansatz, and where the DFT outputs are corresponding total energies that have traditionally been postprocessed using a long-established ground-state formulation of finite-size corrections and defect-formation energies. This formulation remains commonly used even though the defects that form a configuration-coordinate (CC) diagram typically exist as structures that are displaced from the ground state. To remedy this inconsistency, Kumagai has recently proposed novel methods for implementing finite-size corrections specifically intended for DFT calculations of the defect energies used to construct CC diagrams and implement the single-mode formalism [Y. Kumagai, Phys. Rev. B 107, L220101 (2023)]. Kumagai's approach builds on the latest finite-size-correction methods introduced to describe vertical charge-state transitions for charge-localizing point defects in semiconductors and insulators [T. Gake et al., Phys. Rev. B 101, 020102 (2020); S. Falletta et al., Phys. Rev. B 102, 041115 (2020)]. The newly identified finite-size artifact treated in these studies is the polarization charge induced on a configurationally frozen defect and its subsequent interaction with a vertical transition in charge state. In this work, we evaluate Kumagai's proposed methodology by applying it in a high-precision DFT study of carrier capture by substitutional C N in GaN, a well-characterized and technologically relevant defect and material. We have rigorously calculated C N defect energies across various supercell sizes for each defect configuration and charge state on the hole-capture CC diagram of C N (𝑞=−1), enabling a direct comparison of the slopes of the defect energies versus inverse cell size with those predicted by Kumagai. The most consequential prediction of Kumagai's method is that these slopes distinctly vary as the square of the linear-interpolation parameter used to construct the nonequilibrium defect configurations. Our results quantitatively support this prediction. Moreover, with these new finite-size corrections and multiple-cell-size DFT calculations in place, we find that the classical energy barrier for hole capture by C N (𝑞=−1) in GaN decreases to 0.092–0.127 eV. This finding confirms the recent ≈ 0.1 eV prediction of Reshchikov based on the weak temperature dependence for hole capture observed in photoluminescence experiments [M. A. Reshchikov, J. Appl. Phys. 129, 121101 (2021)]. These results stand in stark contrast to previously calculated barriers of 0.486 and 0.73 eV, which also used the single-mode formalism but were obtained by instead using ground-state-based finite-size corrections. Our reduced classical barrier for capture increases the temperature-dependent hole-capture coefficient of a C N (𝑞=−1) defect by more than two to four orders of magnitude for temperatures of 100–600 K, compared to the previous 0.486 eV results. While other defects may not be as dramatically affected as here, we suggest that incorporating proper finite-size corrections for the vertical-transition-like states embedded within CC diagrams is an essential, yet previously unrecognized, component of accurate modeling of carrier-capture when using the single-effective-mode formalism.

dielectric properties↗

Defect-Enhanced Polarization Switching in the Improper Ferroelectric LuFeO 3

Results of switching behavior of the improper ferroelectric LuFeO 3 are presented. Here, using a model set of films prepared under controlled chemical and growth-rate conditions, it is shown that defects can reduce the quasi-static switching voltage by up to 40% in qualitative agreement with first-principles calculations. Switching studies show that the coercive field has a stronger frequency dispersion for the improper ferroelectrics compared to a proper ferroelectric such as PbTiO 3 . It is concluded that the primary structural order parameter controls the switching dynamics of such improper ferroelectrics.

36 MATERIALS SCIENCE↗

New Norms or Old Habits: Evaluating Interlinked Trajectories of Online Shopping and Work Commute Post-Pandemic

The COVID-19 pandemic has significantly shifted travel behaviors, with major changes observed in online shopping and travel to work. Despite considerable research into pandemic-induced changes in travel behavior, it remains uncertain whether these new patterns have persisted or reverted to pre-pandemic norms. This study addresses this uncertainty by evaluating whether shifts in online shopping and work travel during the pandemic have become permanently ingrained in individuals' daily routine. Leveraging data from the 2022 National Household Travel Survey, a bivariate ordered probit model is employed to analyze changes in online shopping and work travel - whether they have increased, decreased, or remained stable compared to pre-pandemic levels across different population segments. The analysis finds that the pandemic did not significantly alter online shopping for home delivery and travel to work for the majority of society. However, a substantial portion of respondents reported increased online shopping for home delivery and reduced travel to work compared to pre-pandemic levels, with online shopping trends appearing more permanent. Segment-wise analysis and model results indicate heterogeneity in behavioral shifts with females engaging more in online shopping, while zero-vehicle households are traveling less to work, compared to pre-pandemic levels. Additionally, increase in online shopping frequency is significantly and negatively correlated with decrease in traveling to work. These findings highlight the need for improved digital infrastructure, flexible work policies, and integrated transportation solutions tailored to evolving demographic and socioeconomic needs in the post-pandemic era. Additionally, the study calls for integrating passenger and freight movement in a single framework rather than treating them in silos.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Vibronic Relaxation Pathways in Molecular Spin Qubit Na 9 [Ho(W 5 O 18 ) 2 ]·35H 2 O under Pressure

In order to explore how spectral sparsity and vibronic decoherence pathways can be controlled in a model qubit system with atomic clock transitions, we combined diamond anvil cell techniques with synchrotron-based far infrared spectroscopy and first-principles calculations to reveal the vibrational response of Na 9 [Ho(W 5 O 18 ) 2 ]·35H 2 O under compression. Because the hole in the phonon density of states acts to reduce the overlap between the phonons and f manifold excitations in this system, we postulated that pressure might move the HoO 4 rocking, bending, and asymmetric stretching modes that couple with the M J = ±5, ±2, and ±7 levels out of resonance, reducing their interactions and minimizing decoherence processes, while a potentially beneficial strategy for some molecular qubits, pressure slightly hardens the phonons in Na 9 [Ho(W 5 O 18 ) 2 ]·35H 2 O and systematically fills in the transparency window in the phonon response. The net result is that the vibrational spectrum becomes less sparse and the overlap with the various M J levels of the Ho 3+ ion actually increases. These findings suggest that negative pressure, achieved using chemical means or elongational strain, could further open the transparency window in this rare earth-containing spin qubit system, thus paving the way for the use of device surfaces and interface elongational/compressive strains to better manage decoherence pathways.

36 MATERIALS SCIENCE↗

Component-Level Inverse Design of Transmon Qubits Using Neural Networks

Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer chooses a layout geometry, simulates it, extracts circuit parameters such as capacitances, and refines the geometry. We study the inverse version of this task using a neural-network workflow that maps target Hamiltonian parameters directly to component-level layout parameters, which we subsequently demonstrate on a planar transmon layout. During training, we pair the inverse model with a frozen forward surrogate model and evaluate the loss in Hamiltonian space rather than in layout-parameter space. In validation against a conventional EM solver, 97% of generated designs produce usable geometries, and the inverse-plus-surrogate pipeline reaches mean percent errors of 0.73% for qubit frequency and 1.58% for anharmonicity, comparable to or below the fabrication and simulation-to-measurement uncertainty expected for academic-process transmon devices of this type. A single pipeline query takes ~60 ms on CPU, versus ~2 min for a conventional EM capacitance extraction on the same hardware, a speedup of approximately 2,000x. Batching minimizes the AI model inference overhead, reducing the runtime to 3.1 microseconds per sample on CPU and 2.6 microseconds per sample on GPU at a batch size of 2048, resulting in speedups of 3.9 x 10^7 and 4.6 x 10^7, respectively, relative to a single conventional CPU EM extraction. Our results indicate that component-level inverse design usefully extends and complements conventional EM simulation, including for small datasets on the order of 1,000 samples.

Seidel, Olivia [Fermilab; Texas U., Arlington]↗

Evaluating E3SM Global Storm‐Resolving Model Simulations of Deep Convection: Insights From DP‐SCREAM During TRACER

Global Storm-Resolving Models (GSRMs) are becoming increasingly vital for advancing climate modeling and improving the prediction of extreme weather events. Houston, a coastal region frequently affected by deep convective storms, offers an ideal setting to evaluate the ability of GSRMs to simulate deep convection. This study assesses the performance of the Doubly Periodic Simple Cloud-Resolving E3SM (Energy Exascale Earth System Model) Atmosphere Model (DP-SCREAM) using observations from the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. DP-SCREAM effectively reproduces the diurnal cycles of clouds and precipitation, demonstrating much greater skill than the E3SM single column model. The DP-SCREAM is demonstrated to be applicable to coastal regions, partially due to the forcing data sets already capturing the influence of breezes. DP-SCREAM also replicates biases persistent in the global version of SCREAM: the underrepresentation of boundary layer shallow clouds, a lack of mid-level congestus clouds, and the popcorn convection, characterized by small and disorganized convective cells generating the strongest precipitation. To investigate these issues, two sensitivity experiments were conducted: increasing the mixing length and scaling up the buoyancy flux within the Simplified Higher Order Closure scheme. Increasing the mixing length improved mid-level congestus representation and reduced unrealistic early morning fog occurrence. Enhancing buoyancy flux only marginally improved the bias of underproduced big convective cells. In conclusion, an additional resolution sensitivity test at 0.5 km grid spacing demonstrated that a refined horizontal resolution alone is insufficient to resolve these biases.

54 ENVIRONMENTAL SCIENCES↗

Typological representation of the offshore oceanographic environment along the Alaskan North Slope

Erosion and flooding impacts to Arctic coastal environments are intensifying with nearshore oceanographic conditions acting as a key environmental driver. Robust and comprehensive assessment of the nearshore oceanographic conditions require knowledge of the following boundary conditions: incident wave energy, water level, incident wind energy, ocean temperature and salinity, bathymetry, and shoreline orientation. The number of offshore oceanographic boundary conditions can be large, requiring a significant computational investment to reproduce nearshore conditions. This present study develops location-independent typologies to reduce the number of boundary conditions needed to assess nearshore oceanographic environments in both a Historical (2007–2019) and Future (2020–2040) timespan along the Alaskan North Slope. We used WAVEWATCH III® and Delft3D Flexible Mesh model output from six oceanographic sites located along a constant ~50 m bathymetric line spanning the Chukchi to Beaufort Seas. K-means clustering was applied to the energy-weighted joint-probability distribution of significant wave height (H s ) and peak period (T p ). Distributions of wave and wind direction, wind speed, and water level associated with location-independent centroids were assigned single values to describe a reduced order, typological rendition of offshore oceanographic conditions. Reanalysis data (e.g., ASRv2, ERA5, and GOFS) grounded the historical simulations while projected conditions were obtained from downscaled GFDL-CM3 forced under RCP8.5 conditions. Location-dependence for each site is established through the occurrence joint-probability distribution in the form of unique scaling factors representing the fraction of time that the typology would occupy over a representative year. As anticipated, these typologies show increasingly energetic ocean conditions in the future. They also enable computationally efficient simulation of the nearshore oceanographic environment along the North Slope of Alaska for better characterization of coastal processes (e.g., erosion, flooding, or sediment transport).

54 ENVIRONMENTAL SCIENCES↗

Connected Vehicle-Based Traffic Signal Coordination

This study presents a connected vehicles (CVs)-based traffic signal optimization framework for a coordinated arterial corridor. The signal optimization and coordination problem are first formulated in a centralized scheme as a mixed-integer nonlinear program (MINLP). The optimal phase durations and offsets are solved together by minimizing fuel consumption and travel time considering an individual vehicle’s trajectories. Due to the complexity of the model, we decompose the problem into two levels: an intersection level to optimize phase durations using dynamic programming (DP), and a corridor level to optimize the offsets of all intersections. In order to solve the two-level model, a prediction-based solution technique is developed. The proposed models are tested using traffic simulation under various scenarios. Compared with the traditional actuated signal timing and coordination plan, the signal timing plans generated by solving the MINLP and the two-level model can reasonably improve the signal control performance. When considering varies vehicle types under high demand levels, the proposed two-level model reduced the total system cost by 3.8% comparing to baseline actuated plan. MINLP reduced the system cost by 5.9%. It also suggested that coordination scheme was beneficial to corridors with relatively high demand levels. For intersections with major and minor street, coordination conducted for major street had little impacts on the vehicles at the minor street.

42 ENGINEERING↗

Testing the efficacy of active pressure management as a tool to mitigate induced seismicity

Manipulation of subsurface stresses through fluid injection/extraction may induce seismicity through modulation of overpressure along faults. Globally, most industrial operations do not induce significant earthquakes. However, the possibility of inducing moderate to large earthquakes is recognized as a significant risk for basin-scale carbon dioxide (CO 2 ) storage operations (Niass et al., 2017). One possible method to reduce the occurrence of induced seismicity is to maintain only small (or zero) fluid overpressure changes in the subsurface through extraction of formation brine. For active pressure management (APM), operators may employ different procedures including extraction of various brine volumes and different configurations of injection/extraction well locations. However, the impact each these operational procedures on induced seismicity must be understood in order to develop management strategies. Here, we describe a numerical modeling workflow to evaluate the efficacy of APM techniques, that when applied to a specific site may be used to inform operational management strategies. We couple the multiphase reservoir model, NUFT, with the earthquake simulator, RSQSim and simulate seismicity induced by CO 2 injection into a hypothetical brine saturated reservoir. Reservoir overpressure is modified by co-extraction of brine at various fractions of the injected CO 2 volume from five potential wells. Our goal is to understand how the well-pair configuration and the extracted brine volume impact the total number and the maximum event magnitude. Additionally, the performance of each scenario is also evaluated in terms of the volume of CO 2 that can be stored before an earthquake above a tolerance threshold is induced.

58 GEOSCIENCES↗

Equation-of-motion internally contracted multireference unitary coupled-cluster theory

The accurate computation of excited states remains a challenge in electronic structure theory, especially for systems with a ground state that requires a multireference treatment. In this work, we introduce a novel equation-of-motion (EOM) extension of the internally contracted multireference unitary coupled-cluster framework (ic-MRUCC), termed EOM-ic-MRUCC. EOM-ic-MRUCC follows the transform-then-diagonalize approach, in analogy to its non-unitary counterpart. By employing a projective approach to optimize the ground state, the method retains additive separability and proper scaling with system size. We show that excitation energies are size-intensive if the EOM operator satisfies the “killer” and the projective conditions. Furthermore, we propose to represent changes in the reference state upon electron excitation via projected many-body operators that span the active orbitals and show that the EOM equations formulated in this way are invariant with respect to active orbital rotations. We test the EOM-ic-MRUCC method truncated to single and double excitations by computing the potential energy curves for several excited states of a BeH2 model system, the HF molecule, and water undergoing symmetric dissociation. Across these systems, our method delivers accurate excitation energies and potential energy curves within 5 mE h (∼0.14 eV) from full configuration interaction. Here, we find that truncating the Baker–Campbell–Hausdorff series to fourfold commutators contributes negligible errors (on the order of 10 −5 E h or less), offering a practical route to highly accurate excited-state calculations with reduced computational overhead.

74 ATOMIC AND MOLECULAR PHYSICS↗

Agentic artificial intelligence for multistage physics experiments at a large-scale user facility particle accelerator

We present a language-model-driven agentic artificial intelligence (AI) system to autonomously execute multistage physics experiments on a production synchrotron light source. Implemented at the Advanced Light Source particle accelerator, the system translates natural language user prompts into structured execution plans that combine archive data retrieval, control-system channel resolution, automated script generation, controlled machine interaction, and analysis. In a representative machine physics task, we show that preparation time was reduced by 2 orders of magnitude relative to manual scripting even for a system expert, while operator-standard safety constraints were strictly upheld. Core architectural features, plan-first orchestration, bounded tool access, and dynamic capability selection, enable transparent, auditable execution with fully reproducible artifacts. These results establish a blueprint for the safe integration of agentic AI into accelerator experiments and demanding machine physics studies, as well as routine operations, with direct portability across accelerators worldwide and, more broadly, to other large-scale scientific infrastructures.

Accelerator/storage ring control systems↗

Neutrino charge radius and additional one-loop radiative corrections at ultranear reactor experiments

We scrutinize the potential of upcoming ultranear reactor neutrino experiments to detect radiative corrections in the elastic neutrino-electron scattering channel, focusing on the JUNO-TAO and CLOUD detectors, which employ advanced scintillator detection technologies. Previous reactor experiments have already constrained the electron neutrino charge radius, which is a neutrino property associated with a certain subset of the total radiative corrections, and have achieved limits that are only about an order of magnitude away from the Standard Model prediction. Our study demonstrates that JUNO-TAO and CLOUD could discover the neutrino charge radius in the near future, considering the established treatment of the charge radius. However, we show that it is necessary to go beyond this standard treatment. By including the complete set of one-loop level radiative corrections, we find a partial cancellation with the charge radius effect, reducing the experimental sensitivity to this quantity. Nevertheless, JUNO-TAO and CLOUD still have the potential to achieve a 5 σ discovery but over longer timescales within a reasonable operational time frame. Published by the American Physical Society 2024

Brdar, Vedran (ORCID:0000000170275104)↗

Electromagnetic Transient Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (Distribution Grid Models)

The distribution and transmission grids are observing an increased penetration of power electronics in loads and generations. For example, there is increasing interest in integrating in extreme fast charging (XFC) systems for fast charging of electrical vehicles. As these systems are integrated, developing high-fidelity electromagnetic transient model of XFC systems in distribution grids and evaluating their interactions with the power grid would be of significant interest. This model will be utilized for design of XFC systems, to identify upgrades in distribution and/or transmission grids, for planning purposes by transmission planners or operators or owners, among others. It can also be utilized in operations for improved reliable performance of the grid and/or XFC station. The challenge with simulating these models is the high computational complexity introduced by the large number of states present in the system and the time-step needed to simulate the system. In this paper, advanced simulations algorithms are applied to reduce the computational complexity of simulating large-scale XFC systems. The algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. While the first three algorithms split the matrix that needs to be inverted from a large matrix to much smaller matrices, the final algorithm reduces the computational burden of applying higher-order integration approaches in the complete system. The comparison made in the previous sentence is with respect to use of homogeneous integration approaches used in conventional electromagnetic transient simulators like power systems computer aided design (PSCAD). The approaches mentioned here have resulted in speed-up of 36x in the simulation of a single distribution system with 15 XFCs.

Debnath, Suman↗

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Network reconfiguration has long been employed as a strategic approach to minimize power distribution system losses and effectively regulate voltage levels. Tap-changing voltage regulators are also critical for controlling bus voltages, especially in accommodating the increasing integration of distributed energy resources (DERs) with intermittent outputs. This paper introduces novel methodologies to address the challenges of dynamic reconfiguration and optimal tap setting in unbalanced three-phase distribution systems. We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on Special Ordered Set type 1 (SOS1). To mitigate computational complexity, we propose a physics-informed spatial-temporal graph convolutional network (STGCN) with an integrated link classifier. The proposed approach enables efficient solution generation by fixing specific variables in the MIQCP instance and solving the simplified sub-MIP using an MIP solver. Numerical studies demonstrate the superior prediction accuracy of our STGCN model compared to baseline neural network models, resulting in reduced DER curtailment and voltage deviation with shorter computation time.

dynamic reconfiguration↗

Evaluating uncertainty-based active learning for accelerating the generalization of molecular property prediction

Deep learning models have proven to be a powerful tool for the prediction of molecular properties for applications including drug design and the development of energy storage materials. However, in order to learn accurate and robust structure–property mappings, these models require large amounts of data which can be a challenge to collect given the time and resource-intensive nature of experimental material characterization efforts. Additionally, such models fail to generalize to new types of molecular structures that were not included in the model training data. The acceleration of material development through uncertainty-guided experimental design has the promise to significantly reduce the data requirements and enable faster generalization to new types of materials. To evaluate the potential of such approaches for electrolyte design applications, we perform comprehensive evaluation of existing uncertainty quantification methods on the prediction of two relevant molecular properties - aqueous solubility and redox potential. We develop novel evaluation methods to probe the utility of the uncertainty estimates for both in-domain and out-of-domain data sets. Finally, we leverage selected uncertainty estimation methods for active learning to evaluate their capacity to support experimental design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designing Quaternary and Quinary Refractory-Based High-Entropy Alloys: Statistical Analysis of Their Lattice Distortion, Mechanical, and Thermal Properties

The rapid evolution in materials science has resulted in a significant interest in high-entropy alloys (HEAs) for their unique properties. This study focuses on understanding both quaternary and quinary body-centered cubic (BCC) of 12 refractory-based HEAs, and on analysis of their electronic structures, lattice distortions, mechanical, and thermal properties. A comprehensive assessment is undertaken by means of density functional theory (DFT)-based first principles calculations. It is well known that multiple constituents lead to notable lattice distortions, especially in quinary HEAs. This distortion, in turn, has significant implications on the electronic structure that ultimately affect mechanical and thermal behaviors of these alloys such as ductility, lattice thermal conductivity, and toughness. Our in-depth analysis of their electronic structures revealed the role of valence electron concentration and its correlation with bond order and mechanical properties. Local lattice distortion (LD) was investigated for these 12 HEA models. M1 (WTiVZrHf), M7 (TiZrHfW), and M12 (TiZrHfVNb) have the highest LD whereas the models M3 (MoTaTiV), M5 (WTaCrV), M6 (MoNbTaW), and M9 (NbTaTiV) have the less LD. Furthermore, we investigated the thermal properties focusing on Debye temperature (ΘD), thermal conductivity (κ), Grüneisen parameter (γα), and dominant phonon wavelength (λdom). The NbTaTiV(M9) and TiVNbHf(M10) models have significantly reduced lattice thermal conductivities (κL). This reduction is due to the mass increase and strain fluctuations, which in turn signify lattice distortion. The findings not only provide an understanding of these promising materials but also offer guidance for the design of next-generation HEAs with properties tailored for potential specific applications.

Materials Science↗

MicroRNAs in laser-induced choroidal neovascularization in mice and rats: their expression and potential therapeutic targets

Choroidal neovascularization characterizes wet age-related macular degeneration. Choroidal neovascularization formation involves a primarily angiogenic process that is combined with both inflammation and proteolysis. A primary cause of choroidal neovascularization pathogenesis is alterations in pro- and anti-angiogenic factors derived from the retinal pigment epithelium, with vascular endothelium growth factor being mainly responsible for both clinical and experimental choroidal neovascularization. MicroRNAs (miRNAs) which are short, non-coding, endogenous RNA molecules have a major role in regulating various pathological processes, including inflammation and angiogenesis. A review of recent studies with the mouse laser-induced choroidal neovascularization model has shown alterations in miRNA expression in choroidal neovascularization tissues and could be potential therapeutic targets for wet age-related macular degeneration. Upregulation of miR-505 (days 1 and 3 post-laser), miR-155 (day 14) occurred in retina; miR-342-5p (days 3 and 7), miR-126-3p (day 14) in choroid; miR-23a, miR-24, miR-27a (day 7) in retina/choroid; miR-505 (days 1 and 3) in retinal pigment epithelium/choroid; downregulation of miR-155 (days 1 and 3), miR-29a, miR-29b, miR-29c (day 5), miR-93 (day 14), miR-126 (day 14) occurred in retinal pigment epithelium/choroid. Therapies using miRNA mimics or inhibitors were found to decrease choroidal neovascularization lesions. Choroidal neovascularization development was reduced by overexpression of miR-155, miR-188-5p, miR-(5,B,7), miR-126-3p, miR-342-5p, miR-93, miR-126, miR-195a-3p, miR24, miR-21, miR-31, miR-150, and miR-184, or suppression of miR-505, miR-126-3p, miR155, and miR-23/27. Further studies are warranted to determine miRNA expression in mouse laser-induced choroidal neovascularization models in order to validate and extend the reported findings. Important experimental variables need to be standardized; these include the strain and age of animals, gender, number and position of laser burns to the eye, laser parameters to induce choroidal neovascularization lesions including wavelength, power, spot size, and duration.

therapeutic targets↗

Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic

Biomass burning smoke is advected over the southeastern Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly in both magnitude and sign. NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) had deployments for field campaigns off the west coast of Africa in 3 consecutive years (September 2016, August 2017, and October 2018) with the goal of better characterizing this plume as a function of the monthly evolution by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on the comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models, the simulated plume is too vertically diffuse and has smaller vertical gradients, and in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate underestimates in modeled plume concentrations, leading, in general, to underestimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2017) and September (2016). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and, therefore, in the aerosol direct radiative effect. Model biases in cloud fraction, and, therefore, the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is underestimated in the GEOS model; UM-UKCA simulates cloud optical thickness that is significantly too high. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a subset of five comparison grid boxes. A significant finding is that the observed grid box average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five grid boxes, whereas DARE using the grid-box-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

54 ENVIRONMENTAL SCIENCES↗