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At least 415 records · Page 23

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Why Do Oceanic Nonlinearities Contribute Only Weakly to Extreme El Niño Events?

Abstract Extreme El Niño events have outsized global impacts and control the El Niño Southern Oscillation (ENSO) warm/cold phases asymmetries. Yet, a consensus regarding the relative contributions of atmospheric and oceanic nonlinearities to their genesis remains elusive. Here, we isolate the contribution of oceanic nonlinearities by conducting paired experiments forced with opposite wind stress anomalies in an oceanic general circulation model, which realistically simulates extreme El Niño events and oceanic nonlinearities thought to contribute to ENSO skewness (Tropical Instability Waves (TIWs), Nonlinear Dynamical Heating (NDH)). Our findings indicate a weak contribution of oceanic nonlinearities to extreme El Niño events in the eastern Pacific, owing to compensatory effects between lateral (NDH and TIWs) and vertical processes. These results hold across different vertical mixing schemes and modifications of the upper‐ocean heat budget mixed layer criterion. Our study reinforces previous research underscoring the pivotal role of atmospheric nonlinearities in shaping extreme El Niño events.

Geology↗

DGPS measurements of solifluction and hillslopes creep at the Teller 47 field site from 2017-2022, Seward Peninsula, AK

DGPS measurements of benchmarks locations were collected during the 2017, 2018, 2019, 2021 and 2022 summers at the NGEE Arctic Teller-47 solifluction site on the Seward Peninsula, Alaska. Benchmarks were installed in 2017 on several solifluction lobes and hillslope locations and re surveyed in 2018 and 2019 with a Trimble R10 DGPS instrument. In 2018, coincident with a UAS-based laser altimetry collection campaign, more ground control targets were installed and subsequently remeasured in 2019. Additional ground control targets were installed in 2021. Points were corrected using NOAA’s Online Positioning User Software (OPUS) and Trimble Business Center (TBC) software. An update to this dataset was made in July 2024, adding new data from 2021 and 2022. The dataset now contains ten total *.csv files: five are data files plus one file-level metadata and five data dictionaries, two *.jpg, four shape file folders, two *.kml, one archive folder of raw data, and one *.pdf. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Clouds Versus Carbon: Predicting Vegetation Roughness by Maximizing Productivity

Surface roughness is one of the dominant vegetation properties that affects land surface exchange of energy, water, carbon, and momentum with the overlying atmosphere. We hypothesize that the canopy structure of terrestrial vegetation adapts optimally to climate by maximizing productivity, leading to an optimum surface roughness. An optimum should exist because increasing values of surface roughness cause increased surface exchange, leading to increased supply of carbon dioxide for photosynthesis. At the same time, increased roughness enhances evapotranspiration and cloud cover, thereby reducing the supply of photosynthetically active radiation. We demonstrate the optimum through sensitivity simulations using a coupled dynamic vegetation-climate model for present day conditions, in which we vary the value of surface roughness for vegetated surfaces. We find that the maximum in productivity occurs at a roughness length of 2 meters, a value commonly used to describe the roughness of today's forested surfaces. The sensitivity simulations also illustrate the strong climatic impacts of vegetation roughness on the energy and water balances over land: with increasing vegetation roughness, solar radiation is reduced by up to 20 W/sq m in the global land mean, causing shifts in the energy partitioning and leading to general cooling of the surface by 1.5 K. We conclude that the roughness of vegetated surfaces can be understood as a reflection of optimum adaptation, and it is associated with substantial changes in the surface energy and water balances over land. The role of the cloud feedback in shaping the optimum underlines the importance of an integrated perspective that views vegetation and its adaptive nature as an integrated component of the Earth system.

Olsen, Lola M.↗

Photogrammetric and Global Positioning System Measurements of Active Pahoehoe Lava Lobe Emplacement on Kilauea, Hawaii

Basalt is the most common rock type on the surface of terrestrial bodies throughout the solar system and -- by total volume and areal coverage -- pahoehoe flows are the most abundant form of basaltic lava in subaerial and submarine environments on Earth. A detailed understanding of pahoehoe emplacement processes is necessary for developing accurate models of flow field development, assessing hazards associated with active lava flows, and interpreting the significance of lava flow morphology on Earth and other planetary bodies. Here, we examine the active emplacement of pahoehoe lobes along the margins of the Hook Flow from Pu'u 'O'o on Kilauea, Hawaii. Topographic data were acquired between 21 and 23 February 2006 using stereo-imaging and differential global positing system (DGPS) measurements. During this time, the average discharge rate for the Hook Flow was 0.01-0.05 cubic m/s. Using stereogrammetric point clouds and interpolated digital terrain models (DTMs), active flow fronts were digitized at 1 minute intervals. These areal spreading maps show that the lava lobe grew by a series of breakouts tha t broadly fit into two categories: narrow (0.2-0.6 m-wide) toes that grew preferentially down-slope, and broad (1.4-3.5 m-wide) breakouts that formed along the sides of the lobe, nearly perpendicular to the down-flow axis. These lobes inflated to half of their final thickness within approx 5 minutes, with a rate of inflation that generally deceased with time. Through a combination of down-slope and cross-slope breakouts, lobes developed a parabolic cross-sectional shape within tens of minutes. We also observed that while the average local discharge rate for the lobe was generally constant at 0.0064 +/- 0.0019 cubic m/s, there was a 2 to 6 fold increase in the areal coverage rate every 4.1 +/- 0.6 minutes. We attribute this periodicity to the time required for the dynamic pressurization of the liquid core of the lava lobe to exceed the cooling-induced strength of the lobe margins. Using DGPS-derived DTMs of the topography before and after pahoehoe lobe emplacement, we observed that the lava typically concentrated within existing topographic lows, with the lobe reaching a maximum thickness of approx 1.2 m above the lowest points of the initial topography and above reverse-facing slopes. Lobe margins were typically controlled by high-standing topography, with the zone directly adjacent to the final flow margin having average relief that is approx 4 cm higher than the lava-inundated region. This suggests that irregularities approx 25% of the height of the smallest breakout elements (i.e., toes) can exert a strong control on the paths of low-discharge pahoehoe lobes, with stagnated toes forming confining margins that allow interior portions of flow to topographically invert the landscape by inflation.

Hamilton, Christopher W.↗

Yellowstone Ecological Forecasting: Assessing Change in Aspen Extent in Northern Yellowstone National Park

The removal and reintroduction of the gray wolf (Canis lupus) in Yellowstone National Park have played an important role in shaping the ecological composition of this distinct landscape, and it is a textbook example of multi-trophic dynamics. With particular importance to conservation science, the inter-trophic cascades between wolves and species such as the elk (Cervus canadensis) and the quaking aspen (Populus tremuloides) have been extensively studied. In conjunction with the National Park Service, Yellowstone National Park, Utah State University, and the University of Wisconsin–Stevens Point, this project utilized satellite remote sensing to investigate the long-term trends in aspen extent. Through random forest modeling and phenological approaches, Sentinel-2 Multispectral Instrument (MSI; years 2017–2019) and Landsat 5 Thematic Mapper (TM; years 1987–2011) datasets were used to derive an Enhanced Vegetation Index (EVI), a Normalized Difference Vegetation Index (NDVI), Tasseled Cap Indices (Brightness, Greenness, Wetness), and RGB true color composites. The International Space System Global Ecosystem Dynamics Investigation (ISS GEDI) was used to analyze canopy height. Results were consolidated into maps and time-series that provide an in-depth and intricate depiction of aspen stand extent. The end products will assist the National Park Service in its management practices and inform wildlife restoration and rewilding decisions within and beyond the contexts of Yellowstone National Park.

Kyle Steen↗

Forest carbon sequestration on the west coast, USA: Role of species, productivity, and stockability

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, “normal” stands without accounting for the substantial proportion of forests that don’t meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types.

Chisholm, Paul J. (ORCID:0000000238784707)↗

First Principles Modeling of Cluster-Based Solid Electrolytes (Final Technical Report)

Given the trend of global warming and the urgent need to transition from fossil fuels to green energy, lithium-ion batteries continue to be an integral part of our lives. Design, development, and understanding of novel solid-state electrolyte materials play the key role for achieving next-generation all-solid-state batteries with high energy and great safety. The current modeling schemes to develop advanced solid electrolytes are focusing on materials in which the building blocks are individual atoms. Our theoretical approach is a paradigm shift in solid-state electrolyte design. Instead of atoms, we focus on clusters as the building blocks and model these solid electrolytes and their interfaces with electrodes, especially Li-metal anode, for their successful implementation in solid-state batteries. The advantage of using the cluster ions to replace elemental ions is that the size, composition, and shape of the former can be tailored to achieve higher ionic conductivity at room temperature, electrochemical stability, and charge transfer across solid-solid interfaces than conventional materials. Specifically, the project includes: (1) Developing cluster-based solid electrolytes, where the halogen components are replaced by cluster ions that mimic the chemistry of halogens but are characterized by additional degrees of freedom, including the size, shape, composition, and motional dynamics under excitation. (2) Providing a fundamental understanding of the ion conduction mechanism in the developed cluster-based solid electrolytes; (3) Modeling the interfacial properties (i.e., structural, chemical, and transport properties) between the cluster-based solid electrolytes and electrodes at the atomic level. For the cluster-based solid electrolytes incompatible with the Li-metal anode or cathode materials, potential candidates for interfacial coatings are identified and studied. (4) Providing a theoretical framework towards optimizing critical parameters of the solid-state electrolytes that guides experimentalists to attain desired cathode-electrode interface for cluster-based solid-state electrolytes.

25 ENERGY STORAGE↗

Potential virus-mediated nitrogen cycling in oxygen-depleted oceanic waters

Viruses play an important role in the ecology and biogeochemistry of marine ecosystems. Beyond mortality and gene transfer, viruses can reprogram microbial metabolism during infection by expressing auxiliary metabolic genes (AMGs) involved in photosynthesis, central carbon metabolism, and nutrient cycling. While previous studies have focused on AMG diversity in the sunlit and dark ocean, less is known about the role of viruses in shaping metabolic networks along redox gradients associated with marine oxygen minimum zones (OMZs). Here, we analyzed relatively quantitative viral metagenomic datasets that profiled the oxygen gradient across Eastern Tropical South Pacific (ETSP) OMZ waters, assessing whether OMZ viruses might impact nitrogen (N) cycling via AMGs. Identified viral genomes encoded six N-cycle AMGs associated with denitrification, nitrification, assimilatory nitrate reduction, and nitrite transport. The majority of these AMGs (80%) were identified in T4-like Myoviridae phages, predicted to infect Cyanobacteria and Proteobacteria, or in unclassified archaeal viruses predicted to infect Thaumarchaeota. Four AMGs were exclusive to anoxic waters and had distributions that paralleled homologous microbial genes. Together, these findings suggest viruses modulate N-cycling processes within the ETSP OMZ and may contribute to nitrogen loss throughout the global oceans thus providing a baseline for their inclusion in the ecosystem and geochemical models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sources, Sinks, and Transatlantic Transport of North African Dust Aerosol: A Multimodel Analysis and Comparison With Remote Sensing Data

This study evaluates model-simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the Aerosol Comparison between Observations and Models phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-viewing Wide Field-of-view Sensor, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based Aerosol Robotic Network Sun photometer measurements, and dust vertical distributions/centroid height from Cloud Aerosol Lidar with Orthogonal Polarization and Atmospheric Infrared Sounder satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects; however, the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model-simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best known dust environment, and stresses the need for observable quantities to constrain the model processes.

Africa↗

A new model for Mars atmospheric dust based upon analysis of ultraviolet through infrared observations from Mariner 9, Viking, and Phobos

We propose key modifications to the Toon et al. (1977) model of the particle size distribution and composition of Mars atmospheric dust, based on a variety of spacecraft and wavelength observations of the dust. A much broader (r(sub eff)variance-0.8 micron), smaller particle size (r(sub mode)-0.02 microns) distribution coupled with a "palagonite-like" composition is argued to fit the complete ultraviolet-to-30-micron absorption properties of the dust better than the montmorillonite-basalt r(sub eff)variance= 0.4 micron, r(sub mode)= 0.40 micron dust model of Toon et al. Mariner 9 (infrared interferometer spectrometer) IRIS spectra of high atmospheric dust opacities during the 1971 - 1972 Mars global dust storm are analyzed in terms of the Toon et al. dust model, and a Hawaiian palagonite sample with two different size distribution models incorporating smaller dust particle sizes. Viking Infrared Thermal Mapper (IRTM) emission-phase-function (EPF) observations at 9 microns are analyzed to retrieve 9-micron dust opacities coincident with solar band dust opacities obtained from the same EPF sequences. These EPF dust opacities provide an independent measurement of the visible/9-microns extinction opacity ratio (> or equal to 2) for Mars atmospheric dust, which is consistent with a previous measurement by Martin (1986). Model values for the visible/9-microns opacity ratio and the ultraviolet and visible single-scattering albedos are calculated for the palagonite model with the smaller particle size distributions and compared to the same properties for the Toon et al. model of dust. The montmorillonite model of the dust is found to fit the detailed shape of the dust 9-micron absorption well. However, it predicts structured, deep absorptions at 20 microns which are not observed and requires a separate ultraviolet-visible absorbing component to match the observed behavior of the dust in this wavelength region. The modeled palagonite does not match the 8- to 9-micron absorption presented by the dust in the IRIS spectra, probably due to its low SiO2 content (31%). However, it does provide consistent levels of ultraviolet/visible absorption, 9- to 12-micron absorption, and a lack of structured absorption at 20 microns. The ratios of dust extinction opacities at visible, 9 microns, and 30 microns are strongly affected by the dust particle size distribution. The Toon et al. dust size distribution (r(sub mode)= 0.40, r(sub eff)variance= 0.4 microns, r(sub cw mu)= 2.7 microns) predicts the correct ratio of the 9- to 30-micron opacity, but underpredicts the visible/9-micron opacity ratio considerably (1 versus > or equal to 2). A similar particle distribution width with smaller particle sizes (r(sub mode)= 0.17, r(sub eff)variance= 0.4 microns, r(sub cw mu)=1.2 microns) will fit the observed visible/9-micron opacity ratio, but overpredicts the observed 9-micron/30-micron opacity ratio. A smaller and much broader particle size distribution (r(sub mode)= 0.02, r(sub eff)variance= 0.8 microns, r(sub cw mu)= 1.8 microns) can fit both dust opacity ratios. Overall, the nanocrystalline structure of palagonite coupled with a smaller, broader distribution of dust particle sizes provides a more consistent fit than the Toon et al. model of the dust to the IRIS spectra, the observed visible/9-micron dust opacity ratio, the Phobos occultation measurements of dust particle sizes, and the weakness of surface near IR absorptions expected for clay minerals.

Clancy, R. T.↗

DEM Solutions Develops Answers to Modeling Lunar Dust and Regolith

With the proposed return to the Moon, scientists like NASA-KSC's Dr. Calle are concerned for a number of reasons. We will be staying longer on the planet's surface, future missions may include dust-raising activities, such as excavation and handling of lunar soil and rock, and we will be sending robotic instruments to do much of the work for us. Understanding more about the chemical and physical properties of lunar dust, how dust particles interact with each other and with equipment surfaces and the role of static electricity build-up on dust particles in the low-humidity lunar environment is imperative to the development of technologies for removing and preventing dust accumulation, and successfully handling lunar regolith. Dr. Calle is currently working on the problems of the electrostatic phenomena of granular and bulk materials as they apply to planetary surfaces, particularly to those of Mars and the Moon, and is heavily involved in developing instrumentation for future planetary missions. With this end in view, the NASA Kennedy Space Center's Innovative Partnerships Program Office partnered with OEM Solutions, Inc. OEM Solutions is a global leader in particle dynamics simulation software, providing custom solutions for use in tackling tough design and process problems related to bulk solids handling. Customers in industries such as pharmaceutical, chemical, mineral, and materials processing as well as oil and gas production, agricultural and construction, and geo-technical engineering use OEM Solutions' EDEM(TradeMark) software to improve the design and operation of their equipment while reducing development costs, time-to-market and operational risk. EDEM is the world's first general-purpose computer-aided engineering (CAE) tool to use state-of-the-art discrete element modeling technology for the simulation and analysis of particle handling and manufacturing operations. With EDEM you'can quickly and easily create a parameterized model of your granular solids system. Computer-aided design (CAD) models of real particles can be imported to obtain an accurate representation of their shape. EDEM(TradeMark) uses particle-scale behavior models to simulate bulk solids behavior. In addition to particle size and shape, the models can account for physical properties of particles along with interaction between particles and with equipment surfaces and surrounding media, as needed to define the physics of a particular process.

Dunn, Carol Anne↗

Detecting Small-Scale Topographic Changes and Relict Geomorphic Features on Barrier Islands Using SAR

The shapes and elevations of barrier islands may change dramatically over a short period of time during a storm. Coastal scientists and engineers, however, are currently unable to measure these changes occurring over an entire barrier island at once. This three-year project, which is funded by NASA and jointly conducted by the Bureau of Economic Geology and the Center for Space Research at The University of Texas at Austin, is designed to overcome this problem by developing the use of interferometry from airborne synthetic aperture radar (AIRSAR) to measure coastal topography and to detect storm-induced changes in topography. Surrogate measures of topography observed in multiband, fully polarimetric AIRSAR (This type of data are now referred to as POLSAR data.) are also being investigated. Digital elevation models (DEM) of Galveston Island and Bolivar Peninsula, Texas obtained with Topographic SAR (TOPSAR) are compared with measurements by Global Positioning System (GPS) ground surveys and electronic total station surveys. In addition to topographic mapping, this project is evaluating the use of POLSAR to detect old features such as storm scarps, storm channels, former tidal inlets, and beach ridges that have been obscured by vegetation, erosion, deposition, and artificial filling. We have also expanded the work from the original proposal to include the mapping of coastal wetland vegetation and depositional environments. Methods developed during this project will provide coastal geologists with an unprecedented tool for monitoring and understanding barrier island systems. This understanding will improve overall coastal management policies and will help reduce the effects of natural and man-induced coastal hazards. This report summarizes our accomplishments during the second year of the study. Also included is a discussion of our planned activities for year 3 and a revised budget.

Gibeaut, James C.↗

Skyrme–Hartree–Fock–Bogoliubov mass models on a 3D mesh: IIb. Fission properties of BSkG2

Large-scale models of nuclear structure are currently the only way to provide consistent datasets for the many properties of thousands of exotic nuclei that are required by nucleosynthesis simulations. In [W. Ryssens et al., Eur. Phys. J. A 58, 246 (2022)], we recently presented the new BSkG2 model based on an energy density functional of the Skyrme type. Relying on a flexible three-dimensional coordinate representation of the nucleus, the model takes into account both triaxial deformation and time-reversal symmetry breaking. BSkG2 achieves a state-of-the-art global description of nuclear ground state (g.s.) properties and reproduces in particular the known masses with a root-mean-square (rms) deviation of 678 keV. Moving beyond g.s. properties, the model also reproduces all empirical values for the primary and secondary barriers as well as isomer excitation energies of actinide nuclei with rms deviations below 500 keV, i.e. with unprecedented accuracy. Here we discuss in detail the extension of our framework to the calculation of the fission barriers of 45 actinide nuclei, including odd-mass and odd-odd systems. We focus in particular on the impact of symmetry breaking which is key to the accuracy of the model: we allow systematically for axial, reflection and time-reversal symmetry breaking. The effect of the latter on the fission properties of odd-mass and odd-odd nuclei is small, but we find that allowing for shapes with triaxial or octupole deformation, as well as shapes with both, is crucial to achieving this accuracy. Here, the numerical accuracy of our coordinate space approach, the variety of nuclear configurations explored and the simultaneous successful description of fission properties and known masses makes BSkG2 the tool of choice for the large-scale study of nuclear structure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impacts of turbine and plant upsizing on the levelized cost of energy for offshore wind

Turbine and plant upsizing are major trends in offshore wind deployment, although the quantitative impact on project costs has not been well-characterized. The uncertain value of continued wind turbine and project growth limits the ability of the supply chain to prepare for future technology trends, leading to challenges in the realization of larger projects. This analysis explores the levelized cost of energy impacts of turbine ratings between 6 and 20 MW and plant capacities between 250 and 2,500 MW for fixed-bottom offshore wind using techno-economic cost models for foundation, electrical, installation, and operation and maintenance costs, along with annual energy production. We consider a nominal set of technology assumptions for all scenarios to isolate economies of size and scale without additional benefits from decreasing turbine capital costs, quantity discounts for larger projects, or optimized technology solutions. These results indicate that using a 20-MW wind turbine in a 2,500-MW power plant array can reduce the levelized cost of energy by over 23% relative to the global average turbine and plant size installed in 2019; primarily because of reductions in the balance-of-system and operation and maintenance costs. We also identify improved installation vessels, optimized export systems, and novel operation and maintenance strategies as additional cost reduction opportunities. These results suggest that upsizing represents a significant cost reduction opportunity for offshore wind energy and will continue to be a main factor in shaping the future of the sector.

17 WIND ENERGY↗

Ion velocity distributions in the vicinity of the current sheet in Earth's distant magnetotail

Observations of the three-dimensional velocity distributions of positive ions and electrons have been recently gained for the first time in Earth's distant magnetotail with the Galileo and Geotail spacecraft. For this brief discussion of these exciting results the focus is on the overall character of the ion velocity distributions during substorm activity. The ion velocity distributions within and near the magnetotail current sheet are not accurately described as convecting, isotropic Maxwellians. The observed velocity distributions are characterized by at least two robust types. The first type is similar to the 'lima bean'-shaped velocity distributions that are expected from the nonadiabatic acceleration of ions which execute Speiser-type trajectories in the current sheet. The second distribution is associated with the presence of cold ion beams that presumably also arise from the acceleration of plasma mantle ions in the electric and weak magnetic fields in the current sheet. The ion velocity distributions in a magnetic field structure that is similar to that for plasmoids are also examined. Again the velocity distributions are not Maxwellian but are indicative of nonadiabatic acceleration. An example of the pressure tensor within the plasmoid-like event is also presented because it is anticipated that the off-diagonal elements are important in a description of magnetotail dynamics. Thus our concept of magnetotail dynamics must advance from the present assumption of co-moving electron and ion Maxwellian distributions into reformulations in terms of global kinematical models and nonadiabatic particle motion.

Frank, L. A.↗

Postglacial migration shaped the genomic diversity and global distribution of the wild ancestor of lager-brewing hybrids

The wild, cold-adapted parent of hybrid lager-brewing yeasts, Saccharomyces eubayanus, has a complex and understudied natural history. The exploration of this diversity can be used both to develop new brewing applications and to enlighten our understanding of the dynamics of yeast evolution in the wild. Here, we integrate whole genome sequence and phenotypic data of 200 S. eubayanus strains, the largest collection known to date. S. eubayanus has a multilayered population structure, consisting of two major populations that are further structured into six subpopulations. Four of these subpopulations are found exclusively in the Patagonian region of South America; one is found predominantly in Patagonia and sparsely in Oceania and North America; and one is specific to the Holarctic ecozone. Plant host associations differed between subpopulations and between S. eubayanus and its sister species, Saccharomyces uvarum. S. eubayanus is most abundant and genetically diverse in northern Patagonia, where some locations harbor more genetic diversity than is found outside of South America, suggesting that northern Patagonia east of the Andes was a glacial refugium for this species. All but one subpopulation shows isolation-by-distance, and gene flow between subpopulations is low. However, there are strong signals of ancient and recent outcrossing, including two admixed lineages, one that is sympatric with and one that is mostly isolated from its parental populations. Using our extensive biogeographical data, we build a robust model that predicts all known and a handful of additional regions of the globe that are climatically suitable for S. eubayanus, including Europe where host accessibility and competitive exclusion by other Saccharomyces species may explain its continued elusiveness. We conclude that this industrially relevant species has rich natural diversity with many factors contributing to its complex distribution and natural history.

59 BASIC BIOLOGICAL SCIENCES↗

FFT-based solver for higher-order and multi-phase-field fracture models applied to strongly anisotropic brittle materials

This paper presents the application of a fast Fourier transform (FFT) based method to solve two phase field models designed to simulate crack growth of strongly anisotropic materials in the brittle regime. By leveraging the ability of the FFT-based solver to generate solutions with higher-order and global continuities, we design two simple algorithms to capture the complex fracture patterns (e.g. sawtooth, and curved crack growth) common in materials with strongly anisotropic surface energy via the multi-phase-field and high-order phase-field frameworks. A staggered operator-split solver is used where both the balance of linear momentum and the phase field governing equations are formulated in the periodic domain. The unit phase field of the initial failure region is prescribed by the penalty method to alleviate the sharp material contrast between the initial failure region and the base material. The discrete frequency vectors are generalized to estimate the second and fourth order gradients such that the Gibbs effect near shape interfaces or jump conditions can be suppressed. Furthermore, a preconditioner is adopted to improve the convergence rate of the iterative linear solver. Three numerical experiments are used to systematically compare the performance of the FFT-based method in the multi-phase-field and high-order phase-field frameworks.

42 ENGINEERING↗