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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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324 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Challenges and Opportunities in Magnetospheric Space Weather Prediction

Abstract Space Weather is the study of the dynamics of the coupled Solar‐Terrestrial environment, as these dynamics impact technological systems and human activity. This paper reviews a selection of the advances, challenges, and new opportunities for magnetospheric space weather, and while the focus is on specific phenomena, many other aspects of space weather will have similar challenges and needs. As a scientific field with direct applications, the field of space weather is partly driven by imperatives from both policy and operations. We provide an introduction to some of the context in which the field exists and discuss how this might shape future developments and norms within the space weather enterprise. We briefly examine benchmarking, as a policy and operationally driven activity, as it provides immediate societal relevance and an opportunity to stretch scientific understanding. As numerical space weather prediction now becomes routine, and exascale computing is in the near future, we identify challenges relating to computational expense and big data, capturing and accounting for uncertainties, and specification of boundary conditions. Here, as with the observations supporting numerical space weather prediction, the key challenge lies in extending the lead time of predictions. We also discuss the role of data, particularly in regard to model validation and empirical modeling. Due to the growing societal impact of space weather, we also examine the relationships between space weather and its terrestrial counterpart and look at the importance of continuous evaluation, monitoring progress in predictive capability, and communication with researchers, forecasters, and end users.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Indoor and Outdoor Test Results for 'DUSST', a Low-Cost, Low-Maintenance PV Soiling Sensor

Soiling can cause significant losses to photovoltaic systems, and therefore it is often measured for the purposes of predicting long-term energy forecasts or for monitoring real time performance and triggering maintenance events as needed. Currently, the most common soiling monitoring technologies are soiling stations that use the electrical outputs of a regularly cleaned PV device and of a naturally soiled PV device to quantify soiling. As part of a new class of low-cost and low-maintenance soiling stations NREL has previously presented 'DUSST'. DUSST projects a collimated monochromatic light source through a glass surface (exposed similarly to the PV modules that need to be monitored) and on to a light detector to measure the intensity of the transmitted light. As the glass surface naturally soils, the losses are quantified by comparing this soiled reading with a calibrated reading under baseline clean condition. This work presents the ongoing improvement of DUSST and the ongoing indoor and outdoor validation of this new soiling sensor.

14 SOLAR ENERGY↗
DOE OSTI2025

High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future

Electrification and renewables deployment efforts are amplifying the interdependence of the climate and energy systems. Increases in climate model resolution, which is now approaching that of reanalysis datasets and operational weather forecast models, present a unique opportunity to use future climate projections for energy infrastructure planning. In this Perspective, we review recent developments in high-resolution climate modeling, which have been driven by increased computing power and advanced software tools. We then look ahead to discuss how high-resolution climate data can be used to plan for a renewable-dependent future, and envision a unified climate-energy model framework that captures the two-way feedbacks between these interdependent systems.

climate change↗
DOE OSTI2020

Mesoscale Modeling to Characterize Eagle Soaring Habitat

Uncovering drivers of risk is crucial to understanding interactions between wildlife and wind turbines, and identifying options for impact minimization. These drivers tie to co-variates linked to behavior and movement patterns that allow us to estimate locations and periods of risk. For volant species, atmospheric flow can have significant influence on flight patterns. For obligate soaring birds, like golden eagles, updraft velocities can inform where eagles are likely to travel, at what altitude, and where conditions are not likely sufficient to sustain soaring flight. This has been an active area of study in recent years, using relatively coarse atmospheric data generally at the 20km x 20km scale or larger. Leveraging a 20-year dataset from the Weather Research and Forecasting Model (WRF) (https://www.mmm.ucar.edu/weather-research-and-forecasting-model), we are quantifying vertical velocities across the continental United States at a 2km x 2km resolution. Wind resource data sets originally were static maps showing the mean annual wind speed over an area. However, for these data sets to be optimally used for various applications they must be high-resolution time series, seamlessly span large geographic contexts, and account for uncertainty in wind speed. The National Renewable Energy Laboratory is producing public available datasets that meet these criteria and will be bias corrected to yield the most accurate wind resource data. This effort is an augment to the current WIND Toolkit which houses a high resolution data set. In the new iteration of the WIND Toolkit, a 20-year dataset will be used to improve the accuracy and estimate uncertainty using ensemble and machine-learning techniques. The resulting product will be the most accurate dataset of its size and at a 2km x 2km spatial and 5-minute temporal resolution. Through this work, a mesoscale vertical velocity layer will be produced by calculating the likelihood of orographic updraft and thermal updraft conditions across the continental United States. Specifically, we will use WRF model output combined with digital elevation maps to predict updrafts and then determine if vertical velocities are sufficient to support Golden Eagle soaring and gliding. Ultimately this data layer will be made available as a GIS layer in the Wind Prospector (maps.nrel.gov/wind-prospector/) tool or a similar framework. Data that will be incorporated include wind speed, direction temperature, relative humidity, barometric pressure, air density, precipitation rate, solar radiation, atmospheric stability, skin temperature, and upward heat flux. These products will advance research on interactions between volant species and wind energy by providing open access to highly resolved data with uncertainty quantification not previously available at this scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A Model for Evaluating the Configuration and Dispatch of PV Plus Battery Power Plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

Detection of supernova magnitude fluctuations induced by large-scale structure

The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magnitude fluctuations of type Ia supernova from the Pantheon+ compilation across redshifts z < 0.1. We find a detection of the cross-correlation signal between galaxies and type Ia supernova magnitudes. Fitting the normalised growth rate of structure f sigma_8 to the auto- and cross-correlation function measurements we find f sigma_8 = 0.384 +0.094 -0.157, which is consistent with the Planck LambdaCDM model prediction, and indicates that the supernova magnitude fluctuations are induced by peculiar velocities. Using a large ensemble of N-body simulations, we validate our methodology, calibrate the covariance of the measurements, and demonstrate that our results are insensitive to supernova selection effects. We highlight the potential of this methodology for measuring the growth rate of structure, and forecast that the next generation of type Ia supernova surveys will improve f sigma_8 constraints by a further order of magnitude.

Nguyen, A. [Swinburne U., Ctr. Astrophys. Supercom↗
DOE OSTI2024

Planning Roadmap for DER Integration in India: Industry Best Practices and Resource Guide

Ensuring safe, reliable, cost-effective DER integration at scale requires holistic planning, broad stakeholder engagement, and should address key development areas such as standards adoption, equipment testing and certification, interoperability and cybersecurity, interconnection procedures, and advanced forecasting and DER management. Each of these areas currently represent significant challenges for utilities, regulators, OEMs, developers, and even consumers worldwide. India has already seen significant growth of DERs and has announced targets for substantial growth yet to come, with the potential for DERs to make up a non-negligible portion of the country's overall generation capacity. As such, it is of critical importance that Indian stakeholders consider the potential impacts of wide-spread adoption of DERs and take preemptive action related to the five development areas listed here, among others. India should consider strategies including the adoption of key DER standards related to interconnection, testing, and cybersecurity; enabling effective and secure communication channels for DER interoperability; testing and certifying DER equipment in accredited testing laboratories; building robust, streamlined interconnection procedures; and revamping legacy system planning structures to incorporate DERs in a holistic planning framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Intermediate-mass Early-type Disk Galaxies in the Virgo Cluster. II. Near-Infrared Spectra and Evidence for Differences in Evolution

We discuss near-infrared (NIR) slit spectra of six early-type disk galaxies in the Virgo Cluster that were examined previously at visible/red wavelengths. Despite having similar intrinsic luminosities, colors, and morphologies, the NIR spectrophotometric properties of these galaxies indicate that they are not a homogeneous ensemble differing only in terms of luminosity-weighted age and metallicity. While the depth of the CO(2,0) band is consistent with the centers of these galaxies having solar or slightly sub-solar luminosity-weighted metallicities, galaxy-to-galaxy variations in the depth of the Na i 2.21 μm doublet are found, with Na i2.21 μm lines in three galaxies (NGC 4491, NGC 4584, and NGC 4620) that are deeper than those predicted for a solar chemical mixture and a solar-neighborhood mass function. In contrast, the Ca i2.26 μm triplet shows good galaxy-to-galaxy agreement but tends to be deeper than the model prediction. Considering the depth of the NaD lines, the deep Na i2.21 μm lines are tentatively attributed to a bottom-heavy mass function. This is counter to observed trends between mass function slope and velocity dispersion, and so the possibility of a super-solar [Na/Fe] is also discussed. Two of the three galaxies with deep Na i 2.21 μm (NGC 4584 and NGC 4620) have Sérsic exponents that are consistent with a classical bulge. As for NGC 4491, its central NIR spectrum contains prominent emission lines. The relative strengths of Brγ and H{sub 2}S(1), the presence of [Fe ii] emission, and the mid-infrared spectral-energy distribution are all consistent with intense recent star formation near the center of that galaxy. The NIR spectrum of NGC 4584 is devoid of line emission in the NIR, suggesting that star formation does not power the emission detected at visible wavelengths from that galaxy. Wavelengths that contain the Ballick–Ramsey C{sub 2} band at 1.76 μm are matched by moderately metal-poor E-MILES model spectra with an age of 2 Gyr. The radial age trends in these galaxies are in the opposite sense to those in late-type disk galaxies, and it is concluded that they have evolved in a cluster environment for at least several Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys

In this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029.We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth.The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 < z < 3.5 range.We find that fixing a target density budget of 1,100 deg$^{-2}$, the Random Forest approach gives a density of z > 2 targets of 873 deg$^{-2}$, and a density of 493 deg$^{-2}$ of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg$^{2}$. We predict uncertainties on Alcock-Paczynski parameters α$_{⊥}$ and α$_{∥}$ to be 0.7% and 1% for 2.6 < z < 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ$_{fNL}$ ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ$_{fNL}$ ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Stabilizing the Power System in 2035 and Beyond: Evolving from Grid-Following to Grid-Forming Distributed Inverter Controllers (Final Technical Report)

Under existing grid operations, large synchronous generators provide sufficient rotational inertia to form a rigid backbone for the bulk power system. With photovoltaics (PV) forecasted to provide more than 600 GW of generation by 2050 under the U.S. Department of Energy’s SunShot Initiative objectives, however, it is clear that power electronic inverters will play a dominant role in future systems, and low-inertia stability must be ensured to maintain system reliability. Today, the risks to system stability can be observed on geographically small islands, such as Hawaii, which contain a relatively large amount of installed PV. These risks stem from a fundamental shortcoming of contemporary control strategies—existing inverter controllers cannot guarantee grid stability. Given that future power systems driven by sustainable resources will be characterized by low inertia, locations such as Hawaii provide a glimpse into the obstacles facing future power systems. Considering these challenges, the aim of this project was to develop and demonstrate distributed inverter controllers that enable the reliable control of low-inertia power systems with hundreds of gigawatts of integrated PV.

14 SOLAR ENERGY↗
DOE OSTI2022

Modeling Needs to Support the Reconstruction Strategy of Ukraine

Ukraine has been facing difficult times. Russia started a full-scale invasion on February 24, 2022, and has caused huge human and infrastructure losses. As a result of the invasion, more than 8 million people left their homes. The Russian army has targeted Ukrainian energy sources, destroying or damaging over 50% of thermal power generation capacity (coal and gas), 30% of solar generation, and 90% of wind generation. The Russians are also threatening Ukrainian energy security, as they currently control the Zaporizhzhia nuclear power plant – Europe’s largest. In addition, Russia has destroyed 121,000 buildings, including 5,300 multistory buildings - more buildings than Ukraine built during the past five years. The occupiers destroyed or damaged 343 district heat boiler stations (destroyed 12 / damaged 331) and 8 CHPs (destroyed 4/ damaged 4). There is no doubt that Ukraine will be able to protect its sovereignty and restore its territorial integrity; however, this will be a long process. The Government of Ukraine needs to simultaneously focus on many issues, from waging war to the restoration of electricity, water, and heat supply in the territories close to the front line. In addition to these time-sensitive issues, the government also needs to plan a long term multi-sector strategy for the reconstruction of Ukraine’s economy. Ukraine initiated a broad-based political process for recovery at the International Ukraine Recovery Conference (URC 2022) in Lugano, Switzerland. Prior to URC 2022, Ukraine applied for EU membership on February 28 and was granted the status of candidate country by the European Council on June 23, 2022. More than 40 nations are fully committed to supporting Ukraine throughout its path from early to long-term recovery. In addition, these countries link a successful recovery to Ukraine’s European future (URC, 2022a). The reconstruction process will be long. The government also recognizes that it is not enough to build energy infrastructure back – it should be built back better. The government is committed to building a more sustainable and cleaner energy sector. Energy modeling can provide important insights into paths to decarbonize Ukraine’s economy while rebuilding it after the war. Pacific Northwest National Laboratory (PNNL) and the Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine (IEF) work on modeling decarbonization scenarios in the energy sector of Ukraine. The teams focus on the heat sector, which includes district heat, autonomous and individual heating, and energy consumption by final energy consumption sectors, including buildings. Since the teams use world-class integrated assessment models, other sectors will be analyzed as well. The purpose of the document is to describe the needs of key Ukrainian ministries in modeling the reconstruction process. The scope of this document is limited to modeling energy consumption by the power and heat sectors, final energy consumption by buildings, and GHG emissions from these two sectors. The rest of this policy memo is organized as follows. After this introduction, Chapter 2 discusses key provisions of the reconstruction strategy with a focus on energy, buildings, heat supply, environment, and European integration aspirations. Section 3 provides an overview of recent developments and key decisions of the Government of Ukraine in the area of energy efficiency and decarbonization. Finally, Section 4 provides key suggestions on how PNNL and IEF can help the Government of Ukraine in developing strategic documents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests

Abstract Dry deposition is the second largest tropospheric ozone (O 3 ) sink and occurs through stomatal and nonstomatal pathways. Current O 3 uptake predictions are limited by the simplistic big‐leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O 3 fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface‐atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi‐Layer Canopy CHemistry and Exchange Model, MLC‐CHEM) to the GEOS‐Chem CTM and use this new framework to simulate O 3 fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC‐CHEM runs to test current knowledge of O 3 deposition and its drivers. We show that GEOS‐Chem overpredicts observed O 3 fluxes across all four studies by up to 2×, whereas the resolved‐canopy models capture observed diel profiles of O 3 deposition and in‐canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O 3 flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O 3 deposition on average; (b) in‐canopy chemistry makes only a small contribution to total O 3 fluxes; and (c) the CTM big‐leaf treatment overestimates O 3 ‐driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O 3 predictions.

Vermeuel, Michael P. [Department of Soil, Water, a↗
DOE OSTI2026

Unified Modeling Architecture for Load Management in Extreme Heat: The New York City Case

Integration of renewable resources to meet growing energy demand is becoming a global priority under decarbonization mandates. This study contributes to ongoing efforts on this key subject by assessing the feasibility of using coastal-urban renewable energy resources, namely, offshore wind and rooftop photovoltaic systems, to meet electricity demand of New York City during the intense recent heat wave period of June 2025. A unified modeling framework, based on the urbanized weather research and forecasting model, is used to simulate climate, renewable resources, and energy demand variables. Findings show significant energy load mismatch of approximately 1150 GWh over the month, between the demand and the combined renewable generation outcome. Three storage integration scenarios are analyzed to mitigate the deficits, reducing said deficits by a minimum of approximately 9% over the duration of the month. This study provides a transferable modeling framework tool for evaluating renewable integration in dense urban environments that can be used by grid operators to support grid resilience during extreme heat events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Polarization fraction of Planck Galactic cold clumps and forecasts for the Simons Observatory

ABSTRACT We measure the mean-squared polarization fraction of a sample of 6282 Galactic cold clumps at 353 GHz, consisting of Planck Galactic cold clump (PGCC) catalogue category 1 objects [flux densities measured with signal-to-noise ratio (S/N) > 4]. At 353 GHz, we find the mean-squared polarization fraction, which we define as the mean-squared polarization divided by the mean-squared intensity, to be (4.79 ± 0.44) × 10−4 equation to an $11\, \sigma$ detection of polarization. We test if the polarization fraction depends on the clumps’ physical properties, including flux density, luminosity, Galactic latitude, and physical distance. We see a trend towards increasing polarization fraction with increasing Galactic latitude, but find no evidence that polarization depends on the other tested properties. The Simons Observatory, with angular resolution of order 1 arcmin and noise levels between 22 and $54\, \mu$K−arcmin at high frequencies, will substantially enhance our ability to determine the magnetic field structure in Galactic cold clumps. At $\ge 5\, \sigma$ significance, we predict the Simons Observatory will detect at least ∼12 000 cold clumps in intensity and ∼430 cold clumps in polarization. This number of polarization detections would represent a two orders of magnitude increase over the current Planck results. We also release software that can be used to mask these Galactic cold clumps in other analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Outcomes of the DOE Workshop on Atmospheric Challenges for the Wind Energy Industry

The U.S. Department of Energy-funded Mesoscale-to-Microscale Coupling (MMC) project team planned and conducted a virtual Workshop on Atmospheric Challenges for the Wind Energy Industry on October 19 and 20, 2020. The goal of the workshop was to forge a dialog with the community, including industry representatives, on how modeling tools are currently being used, the present active atmospheric modeling research in support of wind energy, and required advancements in capabilities and technology to continue to advance wind energy deployment. The workshop was planned in collaboration with an industry advisory panel that included representatives from wind power plant developers, turbine manufacturers, and companies that provide resource assessment and forecasting services. The format of the workshop included panels from government research sponsors, visionaries from industry, and mixed panels of researchers discussing research status and needs. A shared keynote presentation from the Technical University of Denmark experts anchored the second day of the workshop. An emphasis was placed on understanding the research needs in the offshore environment. In addition, breakout opportunities were provided each day. On the first day, the breakout discussions addressed predesigned questions configured to elicit participants’ thoughts on needed research directions. The second-day breakouts treated three important technical topics through a combination of presentations and group conversations. Each workshop participant chose their breakout preference from among downscaling details, modeling for turbines, and using artificial intelligence for atmospheric modeling. The discussions were robust and productive. The outcomes of the workshop include archiving a series of recommendations from industry and the research community on research directions required to further advance wind energy deployment. Discussions confirmed the need for high-fidelity modeling but that there are specific areas of applicability and other areas where the time and cost of computation is prohibitive. In those cases, the high-fidelity models can inform low-order models that are more practical for real-time or widely deployed applications. Industry must consider the financial cost of performing more expensive modeling approaches, but industry engineers and researchers are using these approaches where there appears to be a return on investment. An emerging type of low-order model is based on machine learning (ML). Participants confirmed that there are many atmospheric phenomena that need to be modeled better, including low-level jets, cold air outbreaks, land-sea induced circulations, diurnal variability, thin stable boundary layers, dynamic changes such as from frontal passage, interaction of wakes and blockage, and more. For the offshore environment, there is wide agreement that some level of ocean-wave-atmospheric coupling is necessary to capture variations in rotor-level winds needed to plan and operate offshore wind plants. Another recurring recommendation is that more observations are needed, particularly for the offshore environment. Those observations should consider the needs for model improvement, both for physically based models and for ML models. Observations must capture atmospheric profiles of variables that are important to understanding and modeling atmospheric and oceanic phenomena that impact boundary layer winds. Models must be validated with data and the uncertainty quantified, particularly those that are sensitive to initial and boundary conditions. Finally, a repeated request was to consider the holistic needs of hybrid plants of wind, solar, and storage resources because those types of plants are likely to be the wave of the future. In addition, industry wishes to understand impacts of the resource under a changing climate for long-term planning.

17 WIND ENERGY↗
DOE OSTI2020

Revisiting MOA 2013-BLG-220L: A Solar-type Star with a Cold Super-Jupiter Companion

We present the analysis of high-resolution images of MOA-2013-BLG-220, taken with the Keck adaptive optics system six years after the initial observation, identifying the lens as a solar-type star hosting a super-Jupiter-mass planet. The masses of planets and host stars discovered by microlensing are often not determined from light-curve data, while the star–planet mass ratio and projected separation in units of Einstein ring radius are well measured. High-resolution follow-up observations after the lensing event is complete can resolve the source and lens. This allows direct measurements of flux, and the amplitude and direction of proper motion, giving strong constraints on the system parameters. Due to the high relative proper motion, μ{sub rel,Geo}=12.62±0.11 mas yr{sup −1}, the source and lens were resolved in 2019, with a separation of 77.1 ± 0.5 mas. Thus, we constrain the lens flux to K{sub Keck,lens}=17.92±0.02. By combining constraints from the model and Keck flux, we find the lens mass to be M{sub L}=0.88±0.05 M{sub ⊙} at D{sub L}=6.72±0.59 kpc. With a mass ratio of q=(3.00±0.03)×10{sup −3} the planet’s mass is determined to be M{sub P}=2.74±0.17 M{sub J} at a separation of r{sub ⊥}=3.03±0.27 au. The lens mass is much higher than the prediction made by Bayesian analysis that assumes all stars have an equal probability to host a planet of the measured mass ratio, and suggests that planets with mass ratios of a few times 10{sup −3} are more common orbiting massive stars. This demonstrates the importance of high-resolution follow-up observations for testing theories like these.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Enhancing lifetime, forecasting, and economic benefits of photovoltaic technologies undergoing UV-induced degradation with optical filtering

Ultraviolet-induced degradation (UV-ID) of various PV cell types was analyzed under optical UV filters with different cutoff wavelengths. Cell types studied included interdigitated back contact (IBC), passivated emitter and rear totally diffused (PERT), and heterojunction technology (HJT) based on crystalline Si (c-Si), and metal halide perovskite (MHP) cells. Analyzing degradation rates in two distinct regimes proved beneficial for all cell types. We used empirical linearizing functions ln(t) for c-Si technologies and 2 √t for MHP samples where t is time. These were applied to extrapolate UV-induced degradation over the lifetime of PV modules under various levels of optical UV filtering and used to predict the relative economic benefits for PV power plants. Degradation rates for all technologies were generally faster under the long pass optical filters having shorter cutoff wavelengths transmitting more UV irradiation and at elevated temperatures when testing MHP samples in the range between 60 °C and 90 °C.

14 SOLAR ENERGY↗
DOE OSTI2025

Elucidating Processes Controlling Arctic Atmospheric Aerosol Sources, Aging, and Mixing States (Final Report)

Atmospheric aerosols play critical roles in the Earth’s energy budget, directly by scattering or absorbing solar and terrestrial radiation and indirectly by serving as seeds (nuclei) for cloud droplet and ice crystal formation and by depositing on snow and ice surface, thereby changing the surface albedo. These effects are dependent on aerosol particle size and chemical composition and impact the hydrological cycle as well. This project provided single-particle size and chemical composition measurements across the entire annual cycle in the high Arctic and in the Alaskan Arctic during fall – winter, addressing the most significant gaps in Arctic aerosol observational data. These needs were based on recent rapid sea ice loss across the entire Arctic, as well as the major annual delays in sea ice freeze-up during fall in the Chukchi Sea and increased wintertime sea ice fracturing in the Beaufort Sea, both off the North Slope of Alaska. Two DOE Atmospheric Radiation Measurement (ARM) field campaigns were conducted for atmospheric aerosol sampling. The Aerosols during the Polar Utqiagvik Night (APUN – ‘snow on ground’ in Iñupiaq) ARM field campaign at Utqagivik, Alaska was conducted from Oct. 28 – Dec. 22, 2018. Aerosol sizing instrumentation and a single-particle mass spectrometer were successfully deployed for size-resolved number concentration measurements and measurements of individual particle size and chemical composition, respectively. These results show the influence of locally-produced sea spray aerosol, with high cloud-forming potential, due to delayed sea ice freeze-up in the fall. During the 2019‐2020 international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, daily atmospheric aerosol particles were collected aboard the German icebreaker Polarstern in the Central Arctic from Nov. 2019 – Oct. 2020. Sea salt aerosol and marine organics were observed year-round during MOSAiC with varying morphologies and sources. These findings are important because most Arctic models do not include a sea spray aerosol source, despite this source increasing with declining sea ice extent. In addition to collecting new samples and data, this project also conducted further analysis of previously collected single-particle chemical composition measurements within the North Slope of Alaska oil fields and at Utqiaġvik, AK, during Aug. – Sep. 2015 and 2016 field campaigns. This work resulted in the discovery of chemical reactions of oil field combustion emissions occurring within fog droplets across the North Slope of Alaska and forming secondary aerosol, showing the impact of Arctic oil field emissions beyond black carbon aerosol and greenhouse gases. In addition, the distribution of chemical species across the aerosol population within the oil fields was quantified, using these data and a previously development framework. We also presented the first ambient evidence of the collision of two atmospheric particles resulting in formation of an organic-coated ammonium sulfate particle of marine origin, which has implications for cloud formation with declining sea ice extent. Overall, this project has elucidated connections between seawater biogeochemistry, resource extraction activities, atmospheric composition, clouds, and the energy budget of the Arctic region. The results of this project are expected to improve weather and sea ice forecasting for security and development in the Arctic and beyond.

54 ENVIRONMENTAL SCIENCES↗