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At least 595 records · Page 33

Structural Tolerance Factor Approach to Defect-Resistant I 2 -II-IV-X 4 Semiconductor Design

Recent work on quaternary semiconductors Cu 2 BaSn(S,Se) 4 and Ag 2 BaSnSe 4 for photovoltaic and thermoelectric applications, respectively, has shown the promise of exploring the broader family of defect-resistant I 2 -II-IV-X 4 materials (where I, II, and IV refer to the formal oxidation state of the metal cations and X is a chalcogen anion) with tetrahedrally coordinated I/IV cations and larger II cations (i.e., Sr, Ba, Pb, and Eu) for optoelectronic and energy-related applications. Chemical dissimilarity among the II and I/IV atoms represents an important design motivation because it presents a barrier to antisite formation, which otherwise may act as electronically harmful defects. We herein show how all 31 experimentally reported I 2 -II-IV-X 4 examples (with large II cations and tetrahedrally coordinated smaller I/IV cations), which form within five crystal structure types, are structurally linked. Based on these structural similarities, we derive a set of tolerance factors that serve as descriptors for phase stability within this family. Despite common usage in the well-studied perovskite system, Shannon ionic radii are found to be insufficient for predicting metal–chalcogen bond lengths, pointing to the need for experimentally derived correction factors as part of an empirically driven learning approach to structure prediction. Here, we use the tolerance factors as a predictive tool and demonstrate that four new I 2 -II-IV-X 4 compounds, Ag 2 BaSiS 4 , Ag 2 PbSiS 4 , Cu 2 PbGeS 4 , and Cu 2 SrSiS 4 , can be synthesized in correctly predicted phases. One of these compounds, Ag 2 PbSiS 4 , shows potentially promising optoelectronic properties for photovoltaic applications.

36 MATERIALS SCIENCE↗

AI Improves the Accuracy, Reliability, and Economic Value of Continental‐Scale Flood Predictions

Accurate flood early warnings are critical to minimize damage and loss of life. Current large‐scale operational forecasting systems, however, have limited accuracy, description of uncertainty, and computational efficiency. While Artificial intelligence (AI) can address these limitations in principle, the accuracy and reliability of AI forecasts have thus far proven insufficient. Here we present a novel hybrid framework that integrates AI‐based machinery termed Errorcastnet (ECN) with the National Water Model (NWM) to showcase the potential of ensemble AI flood forecasts over the contiguous U.S. ECN boosts prediction accuracy four‐ to six‐fold across lead times of 1–10 days, while providing uncertainty quantification. It also outperforms Google's state‐of‐the‐art global AI model. ECN‐based forecasts offer superior economic value (up to four‐fold) for decision‐making as compared to those from NWM alone. ECN performs well in varied ecoregions, physiography, and land management conditions. The framework is computationally efficient, enabling national‐scale ensemble forecasts in minutes.

artificial intelligence↗

Short‐Term Hourly Weather Forecasting Using PredRNN With Image Preprocessing

Global weather forecast models are vital tools with numerous applications, including public safety, agriculture, and transportation. Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown the potential to enhance weather forecasting accuracy and speed. In this study, we developed a short-term hourly weather forecast framework with a wavelet transform function for data preprocessing and a spatiotemporal DL model, PredRNN, for predicting five surface atmospheric variables, including wind speed and direction, mean sea level pressure (MSLP), temperature, and precipitation. The framework demonstrated promising results. It produces global forecasts at 0.25° (∼25 km) with a 1-day lead time RMSE of 1.8 m/s for wind components, 180 Pa for MSLP, and 1.8 K for temperature. Although our model does not surpass state-of-the-art AI weather forecast models across all metrics, it outperforms these models in precipitation forecasting and wind prediction at short lead times and achieves comparable accuracy for MSLP. Its native hourly forecasting capability, together with training on widely accessible GPU hardware, contributes meaningfully to the advancement of accessible DL weather forecasting methods. Our work highlights the importance of integrating temporal components and data transformation techniques to improve the predictability and accuracy of weather forecasts.

Tran, Hoang [Pacific Northwest National Laboratory↗

Detectable ship tracks account for just 5% of aerosol indirect forcing from ship emissions

Ship emissions are a major source of aerosols over oceans, affecting both air quality and energy balance of the climate. However, estimates of their climate forcing diverge between studies relying on visible ship-tracks and those based on models. Here we show that forcing due to visible ship-tracks accounts for just 5% of the total forcing over the southeast Atlantic shipping-lane. Most forcing from ship emissions comes from aerosols that do not form detectable ship-tracks. They are only tips of the iceberg. We make three forcing calculations, one bottom-up based on visible ship-tracks, one top-down based on spatial relationships, and a hybrid approach that combines top-down or model estimated cloud droplet number concentration changes and cloud adjustments. Although the forcing based on machine learning detected ship tracks is an order of magnitude greater than prior results using manually detected ship-tracks, it remains only 5% of that inferred by top-down or cloud adjustment based methods for pre-2020 shipping. The top-down and the combined cloud adjustments methods show similar forcing for the post-2020 reduction in ships’ sulfur emission, although the methods have important regional differences in cloud adjustments that need further investigation. Our results reconcile a long-standing discrepancy in the literature and have important implications for aerosol indirect forcing and marine cloud brightening.

Yuan, Tianle [NASA Goddard Space Flight Center (GS↗

Review of pulsed power-driven high energy density physics research on Z at Sandia

Pulsed power accelerators compress electrical energy in space and time to provide versatile experimental platforms for high energy density and inertial confinement fusion science. The 80-TW “Z” pulsed power facility at Sandia National Laboratories is the largest pulsed power device in the world today. Z discharges up to 22 MJ of energy stored in its capacitor banks into a current pulse that rises in 100 ns and peaks at a current as high as 30 MA in low-inductance cylindrical targets. Considerable progress has been made over the past 15 years in the use of pulsed power as a precision scientific tool. This paper reviews developments at Sandia in inertial confinement fusion, dynamic materials science, x-ray radiation science, and pulsed power engineering, with an emphasis on progress since a previous review of research on Z in Physics of Plasmas in 2005.

Sinars, D. B. (ORCID:0000000155473532)↗

High-resolution analysis of clay minerals and amorphous materials in martian analog environments

Mudrocks and mud-sized sediments (i.e., silt to clay) dominate the surface of Earth and Mars. These fine-grained sediments preserve a rich history of sedimentary processes from source to sink and shed light on ancient climates. However, both the physical and chemical nature of these materials make them difficult to fully characterize with traditional laboratory techniques. Here, we explore a cross-disciplinary and high-resolution approach using synchrotron radiation for X-ray diffraction, pair distribution function analysis, and submicrometer-scale X-ray fluorescence, combined with transmission electron microscopy, to better understand the nanostructure and composition of mud-sized sediments from a glacio-fluvial watershed in southwest Iceland. Our results demonstrate that sediments in the cold and wet climate of Iceland are more altered than previously thought, as evidenced by the identification of kaolinite and mixed-layer kaolinite-smectite. Additionally, sediments are enriched in amorphous materials and nanocrystalline phases, as determined from grain morphologies and compositions consistent with allophane, hisingerite, ferrihydrite, and halloysite. These alteration products are present as intimate mixtures that vary across depositional sites, demonstrating the dynamic nature of the secondary assemblage from source to sink. This work has implications for Mars, where, for example, basalt-sourced sedimentary rocks from Gale crater are abundant in clay minerals and amorphous materials. Finally, this work underpins the importance of using high-resolution techniques, a coordinated methodology, and developing innovative approaches for future planetary sample return missions (e.g., Mars sample return).

36 MATERIALS SCIENCE↗

Advanced Manufacturing of Thermal Protection System Tiles for Space Plane Atmospheric Reentry

Thermal protection systems (TPS) constitute a major material, engineering, and manufacturing challenge for space access. Atmospheric re-entry generates very high heats and requires advanced materials to withstand such conditions. Combining the required materials and integrating them into the vehicle is a major engineering undertaking that often must use creative designs to accommodate the selected materials and systems. Likewise, the manufacture of TPS is costly and challenging; it requires a combination of materials in a range of complex and unique shapes with specialized process conditions. Compounding these challenges, for harsh re-entry profiles or on high heat flux regions of the vehicle, even state of the art TPS is effectively single use and thereby creating a strong economic incentive to improve the TPS materials, integration, and manufacture. This work focuses on the use of ceramic modifications to TPS materials thereby allowing multi flight capability.

36 MATERIALS SCIENCE↗

Modeling and Characterization of Surface Discharges in Insulating Material for Spacers: Electrode Shape, Discharge Mode, and Revision of the Creepage Concept

In the design of MV AC and DC spacers, the predominant factors are surface and interface conditions. Design is generally carried out on specifications and standards which are based on long-term experience and lab testing. However, the diffusion of power electronics with a trend to increase electric field, switching frequency, and rise time to achieve higher power density calls for an innovative, global approach to optimized insulation system design. A new methodology, based on field simulation, discharge modeling, and partial discharge inception measurements, called the three-leg approach, can form the basis to optimize insulation design for any type of supply voltage waveform. This paper focuses on the influence of the type of electrode on the inception and phenomenology of surface discharges and, as a consequence, on the interpretation of the results used for application of the three-leg approach. It is demonstrated that a typical electrode system used for insulating material testing can generate both gas and surface discharges at the triple point, when the electrodes have a smooth profile that is used to avoid corona or flashover. Hence, testing partial discharge may not provide a straightforward indication of the surface discharge inception and, thus, be partially misleading for insulation design. Another takeover is that such analysis must benefit from PD testing tools endowed with analytics able to provide automatic identification of the type of defect generating PD, i.e., internal, surface, and corona, since design and remedy actions can be taken, and adequate insulating materials developed, only knowing the type of source generating PD. Hence, testing partial discharge may not provide a straightforward indication of surface discharge inception and, thus, be partially misleading for insulation design. In addition to the importance of the three-leg approach to favor reliable and optimized design of insulation systems, there is a clear need to have a PD testing tool endowed with analytics. It should preferably be able to provide automatic identification of the type of defect generating PD, i.e., internal, surface, and corona.

36 MATERIALS SCIENCE↗

Evaluation of cloud height, optical thickness, and phase retrievals from the CHROMA algorithm applied to Sentinel-3 OLCI data

We previously developed the Cloud Height Retrieval from O 2 Molecular Absorption (CHROMA) algorithm for the Ocean Color Instrument (OCI) on the new NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Here, we apply CHROMA to observations from the Ocean Land Colour Instrument (OLCI) to guide expectations for PACE, as it will take some time to obtain large-scale validation data for OCI. We use cloud top height (CTH), phase, and (for liquid clouds) cloud optical thickness (COT) data from the ground-based Atmospheric Radiation Measurement (ARM) network to evaluate the OLCI retrievals. We found that OLCI and Moderate Resolution Imaging Spectroradiometer (MODIS) CTH compare similarly well to the ARM reference. OLCI has a tendency to underestimate CTH as CTH increases, and algorithm assumptions about cloud geometric thickness may contribute to this. ARM COT from multifilter shadowband radiometers (MFRSR) and Sun photometers are well-correlated with one another, albeit with a roughly 30 % offset on average; OLCI and MODIS COT agree more closely with the MFRSR data. OLCI retrieval uncertainty estimates show skill at telling low-uncertainty cases from high-uncertainty ones, although CTH uncertainties are underestimated. Additionally, we compare the OLCI data to satellite retrievals based on thermal infrared measurements from MODIS and Sea and Land Surface Temperature Radiometer (SLSTR) data. Differences are broadly consistent with physical expectations based on the A-band vs. thermal techniques, although one key challenge in such aggregated comparisons is different cloud masking sensitivities and algorithm failure rates meaning additional sampling differences are introduced. We conclude by discussing the transition to and possible enhancements for PACE OCI.

Sayer, Andrew M. [Univ. of Maryland Baltimore Coun↗

SITCOMTN-128: Unrecognized Blends in LSSTComCam Data Preview 1 ECDFS

Unrecognized blends are a class of blended objects where two (or more) objects are so close on the sky that they are mistakenly identified as a single object. These objects can cause a variety of issues for science and simple validation. We can identify such objects by using higher resolution imaging from a space based telescope that will not be affected by ground based seeing and then label detected objects as isolated, recognized blends, or unrecognized blends. We find that for objects with 23 < i < 24.5, 18% of objects are unrecognized blends.

79 ASTRONOMY AND ASTROPHYSICS↗

Non-Equilibrium Actinide Radiation Chemistry and the Nuclear Fuel Cycle

Actinides are inherently unstable elements that frequently coexist with other radioisotopes, generating intense ionizing radiation fields that drive the formation of non equilibrium oxidation states. These transient species exert a profound mechanistic influence on the radiation response of actinide containing systems due to their unique redox chemistry. Despite their importance, they remain poorly understood, yet such insight is essential for advancing actinide science and accurately predicting radiation driven behavior. Actinide separations—critical for nuclear energy technologies, strategic deterrence, space exploration, and nuclear medicine—depend on precise control of actinide oxidation states to recover targeted elements from complex matrices such as used nuclear fuel. However, during these processes, actinides, their coordination complexes, and the separation media are all exposed to intense, multicomponent (alpha, beta, gamma, etc.) radiation fields that can alter process efficiency, selectivity, and chemical stability. Understanding, controlling, and mitigating radiation induced reactions is therefore key to innovating and optimizing next generation separation technologies. This seminar will provide an overview of the nuclear fuel cycle and non equilibrium actinide radiation chemistry in the context of recovering actinides from used nuclear fuel, with a particular emphasis on direct dissolution–based reprocessing strategies. We will explore time resolved electron pulse radiolysis and alpha and gamma dose accumulation studies, integrated with multiscale computational modeling, to elucidate the molecular level roles of radiation driven, non equilibrium actinide species in process performance and in the radiolytic stability of organic ligands used for actinide recovery. These insights offer new pathways for designing advanced separation methods and next generation solvent systems, with broad implications for the future of the nuclear fuel cycle.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Effect of Active Lengthening and Shortening on Small-Angle X-ray Reflections in Skinned Skeletal Muscle Fibres

Our purpose was to use small-angle X-ray diffraction to investigate the structural changes within sarcomeres at steady-state isometric contraction following active lengthening and shortening, compared to purely isometric contractions performed at the same final lengths. We examined force, stiffness, and the 1,0 and 1,1 equatorial and M3 and M6 meridional reflections in skinned rabbit psoas bundles, at steady-state isometric contraction following active lengthening to a sarcomere length of 3.0 µm (15.4% initial bundle length at 7.7% bundle length/s), and active shortening to a sarcomere length of 2.6 µm (15.4% bundle length at 7.7% bundle length/s), and during purely isometric reference contractions at the corresponding sarcomere lengths. Compared to the reference contraction, the isometric contraction after active lengthening was associated with an increase in force (i.e., residual force enhancement) and M3 spacing, no change in stiffness and the intensity ratio I 1,1 /I 1,0 , and decreased lattice spacing and M3 intensity. Compared to the reference contraction, the isometric contraction after active shortening resulted in decreased force, stiffness, I 1,1 /I 1,0 , M3 and M6 spacings, and M3 intensity. This suggests that residual force enhancement is achieved without an increase in the proportion of attached cross-bridges, and that force depression is accompanied by a decrease in the proportion of attached cross-bridges. Furthermore, the steady-state isometric contraction following active lengthening and shortening is accompanied by an increase in cross-bridge dispersion and/or a change in the cross-bridge conformation compared to the reference contractions.

59 BASIC BIOLOGICAL SCIENCES↗

Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time

The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗

Radar Studies of Convective Dynamics (CONVECT) Field Campaign Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s third ARM Mobile Facility (AMF3)-Bankhead National Forest (BNF) field deployment site and surrounding region offer a significant advantage for convective cloud studies. The higher mid-tropospheric humidity promotes frequent clouds, and when coupled with seasonal variability in convective environments, promotes isolated convection and severe thunderstorms, organized convection in the summertime, and strongly sheared convection during transitional seasons. The CONVECT field experiment was designed to provide unique, high-spatiotemporal-resolution microphysical and dynamical observations of severe weather events. The CONVECT scientific objectives align well with the AMF3-BNF site science plan.

54 ENVIRONMENTAL SCIENCES↗

Determining best practices for using genetic algorithms in molecular discovery

Genetic algorithms (GAs) are a powerful tool to search large chemical spaces for inverse molecular design. However, GAs have multiple hyperparameters that have not been thoroughly investigated for chemical space searches. In this tutorial, we examine the general effects of a number of hyperparameters, such as population size, elitism rate, selection method, mutation rate, and convergence criteria, on key GA performance metrics. Here, we show that using a self-termination method with a minimum Spearman’s rank correlation coefficient of 0.8 between generations maintained for 50 consecutive generations along with a population size of 32, a 50% elitism rate, three-way tournament selection, and a 40% mutation rate provides the best balance of finding the overall champion, maintaining good coverage of elite targets, and improving relative speedup for general use in molecular design GAs.

36 MATERIALS SCIENCE↗

Cooling rate and dendrite spacing control in direct metal deposition printed Cu-Fe alloys

Over the last several decades, additive manufacturing (AM) has been primarily used for rapid prototyping or to create novel geometries that would be difficult or impossible to create by normal manufacturing methods. More recently, research has been focused on expanding the list of materials that can be made through additive manufacturing, opening a greater range of material properties for this manufacturing method. Due to the unusual conditions during AM, including the high cooling rates and voxel by voxel method of production, AM parts often have anisotropic material microstructures and properties. In this investigation, the laser power, composition, and nozzle head speed during direct metal deposition of copper-iron alloys was varied to understand how the grain structure within the printed parts could be changed and controlled. The resulting dendrite spacing was measured and compared to calculated cooling rates from Gaussian beams on flat plates under similar material and laser properties, which resulted in a cooling rate to dendrite spacing relationship following an inverse square root, as is found in other dendritic systems [Young and Kerkwood, Metall. Trans. A 6, 197–205 (1975)]. Thus, it is demonstrated that in the Cu-Fe system, dendrite spacing can be controlled through manipulation of printing parameters.

36 MATERIALS SCIENCE↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗