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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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At least 145 records · Page 8

Nuclear recoil response of liquid xenon and its impact on solar 8B neutrino and dark matter searches

Knowledge of the ionization and scintillation responses of liquid xenon (LXe) to nuclear recoils is crucial for LXe-based dark matter experiments. Current calibrations carry large uncertainties in the low-energy region below ∼3 keV nr where signals from dark matter particles of <10 GeV/c 2 masses are expected. The coherent elastic neutrino-nucleus scattering (CE ν NS) by solar 8 B neutrinos also results in a continuum of nuclear recoil events below 3.0 keV nr (99% of events), which further complicates low-mass dark matter searches in LXe experiments. In this paper, we describe a method to quantify the uncertainties of low-energy LXe responses using published calibration data, followed by case studies to evaluate the impact of yield uncertainties on 8 B searches and low-mass dark matter sensitivity in a typical ton-scale LXe experiment. We conclude that naively omitting yield uncertainties leads to overly optimistic limits by factor ∼2 for a 6 GeV WIMP mass. Future nuclear recoil light yield calibrations could allow experiments to recover this sensitivity and also improve the accuracy of solar 8 B flux measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Role of the social factors in success of solar photovoltaic reuse and recycle programmes

By 2050, the cumulative mass of end-of-life photovoltaic (PV) modules may reach 80 Mt globally. The impacts could be mitigated by module recycling, repair and reuse; however, previous studies of PV circularity omit the consideration of critical social factors. Here we used an agent-based model to integrate social aspects with techno-economic factors, which provides a more realistic assessment of the circularity potential for previously studied interventions that assesses additional interventions that cannot be analysed using techno-economic analysis alone. We also performed a global sensitivity analysis using a machine-learning metamodel. We show that to exclude social factors underestimates the effect of lower recycling prices on PV material circularity, which highlights the relevance of considering social factors in future studies. Interventions aimed at changing customer attitudes about used PV boost the reuse of modules, although used modules can only satisfy one-third of the US demand during 2020–2050, which suggests that reuse should be complemented by recycling.

14 SOLAR ENERGY↗

Life-cycle environmental impacts of single-junction and tandem perovskite PVs: a critical review and future perspectives

For new technologies, such as perovskite solar cells (PSC), life cycle analysis (LCA) offers a fundamental framework for examining potential environmental, energy and health impacts and mitigation options before large-scale commercialization and for guiding improvements in development and production that further reduce their environmental footprint. However, credible LCA studies require actual process-based material, energy and emissions data, which may not exist before the technologies are commercially produced. Thus, the perovskite LCA literature is based on linear extrapolations of laboratory data. In this paper we critically reviewed the PSC LCA literature, explain the reasoning for a wide divergence of results, and determined which data apply to scalable industrial production, materials and processes. Our investigation probed into the formulation of each layer of a PSC device, and its potential for industrial scale fabrication. We found that electricity use is the main contributor to reported LCA results, explaining the large difference, ranging from 7.78 kWh to 1,460 kWh/m –2 , among various studies. Subsequently, we identified and discuss methodological errors in some of these estimates. In terms of life-cycle toxicity most of the reviewed LCA studies do not attribute any major overall toxicity impact to the presence of lead in the PSC devices. We also reviewed and critiqued studies describing “worst-case” scenarios of accidental release of lead into the environment, and, in spite of statements in those studies, we found them to be inconclusive. Lastly, we discussed end-of-life (EoL) management options for resource recovery and for minimizing environmental impacts.

14 SOLAR ENERGY↗

Scenarios for Future Energy Systems

Energy systems in the U.S. and globally have continuously changed and expanded over the past 200 years, from animal and biomass based energy to electricity and petroleum for heat, light, transportation, and industries of all kinds. The most recent two decades have experienced a significant increase in the use of natural gas, solar, and wind energy, as well as energy efficiency, due to both technology breakthroughs and public policy. With history as a guide, we can expect on-going transformation of our energy system in future decades, including increased electrification and advanced energy technologies, ideally helping meet societal goals of reducing pollution, improving quality of human life, and preserving ecosystems. Scenario modeling is an important tool for planning energy system transformations toward specific goals - such as net-zero greenhouse gas emissions, 100% renewable energy, or energy security - particularly when there are multiple options, conflicting objectives, and significant unknowns about a path forward. This presentation will review the history of energy transitions and the future policy and societal objectives on energy. Then it will summarize multiple scenario studies of future energy systems, with a focus on "100% studies" and the challenges to meeting those objectives. It will also outline of a few of the technologies being researched now that could advance the ongoing energy transition.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY,↗

The kinematic properties of Milky Way stellar halo populations

ABSTRACT In the Gaia era, stellar kinematics are extensively used to study Galactic halo stellar populations, to search for halo structures, and to characterize the interface between the halo and hot disc populations. We use distribution function-based models of modern data sets with 6D phase space data to qualitatively describe a variety of kinematic spaces commonly used in the study of the Galactic halo. Furthermore, we quantitatively assess how well each kinematic space can separate radially anisotropic from isotropic halo populations. We find that scaled action space (the ‘action diamond’) is superior to other commonly used kinematic spaces at this task. We present a new, easy to implement selection criterion for members of the radially anisotropic Gaia–Enceladus merger remnant. Assuming a 1:1 ratio of Gaia–Enceladus stars to more isotropic halo, we find our selection achieves a sample purity of 86 per cent in our models with respect to contamination from the more isotropic halo. We compare this criterion to literature criteria, finding that it produces the highest purity in the resulting samples, at the expense of a modest reduction in completeness. We also show that selection biases that underlie nearly all contemporary spectroscopic data sets can noticeably impact the E−Lz distribution of samples in a manner that may be confused for real substructure. We conclude by providing recommendations for how authors should use stellar kinematics in the future to study the Galactic stellar halo.

79 ASTRONOMY AND ASTROPHYSICS↗

A Review and Perspective on Cathodoluminescence Analysis of Halide Perovskites

Halide perovskite solar cells have achieved a certified efficiency of 25.2%, surpassing CdTe and CuInGaSe 2 , which have long been regarded as the most-efficient thin-film photovoltaic materials. As this exciting class of materials continues to mature, researchers will require characterization techniques capable of exposing the interplay among structure, chemistry, and optoelectronic properties to inform processing strategies and increase both device efficiencies and long-term stability. Cathodoluminescence microscopy is an ideal technique to provide such information due to the high spatial resolution and robust optical information acquired. Here, the current body of work related to cathodoluminescence analysis of halide perovskite materials for optoelectronic applications is surveyed. This review demonstrates how cathodoluminescence can monitor degradation due to environmental stressors, phase segregation resulting from material processing, and other halide perovskite-centric material issues. A persistent concern associated with e-beam-based analysis of halide perovskites is what effect the electron beam has on the material properties being probed. Addressing this, a detailed discussion is provided on the origin of the cathodoluminescence signal and a review of studies focused on revealing changes in the properties of halide perovskites resulting from e-beam excitation. Finally, a perspective on future opportunities to expand the role of cathodoluminescence analysis for halide perovskites is provided.

14 SOLAR ENERGY↗

Improved reproducibility of metal halide perovskite solar cells via automated gas quenching

Achieving reproducible perovskite solar cell fabrication is crucial for making it a scalable technology. We demonstrate an automated gas quenching system to improve perovskite solar cell reproducibility at the lab-scale. We use in situ photoluminescence to monitor the perovskite film formation as a function of the atmosphere in the glove box and find that antisolvent quenching is more sensitive to lingering precursor solvents than the gas quenching method. We observe a better reproducibility with gas quenching than with antisolvent quenching because it maintains a more consistent atmosphere in the glove box. The automated gas quenching process leads to high performing devices that are reproducible both batch to batch and researcher to researcher. The insights into gas quenching film formation as a function of solvent atmosphere and quench velocity will help inform future studies on large scale fabrication systems.

14 SOLAR ENERGY↗

Toward Metal-free Photocatalysis: Photochemical Regeneration of Organic Hydride Donors Using Phenazine-Based Photosensitizers

Earth-abundant chromophores and catalysts are important molecular building blocks for artificial photosynthesis applications. Our team previously reported that metal-free hydride donors, such as biomimetic benzoimidazole-based motifs, can reduce CO 2 selectively to the formate ion and that they can be electrochemically regenerated using the proton-coupled mechanism. To enable direct utilization of solar energy, we report here the photochemical regeneration of a benzoimidazole-based hydride donor using a phenazine-based metal-free chromophore. The photochemical regeneration was investigated under different experimental conditions involving varying sacrificial donors, proton donors, solvents, and component concentrations. The best hydride regeneration yield of 50% was obtained with phenol as a proton source and thiophenolate as a sacrificial electron donor. The mechanism of photochemical regeneration was studied using steady-state and time-resolved UV/Vis spectroscopies. Based on the results of these studies, we hypothesize that the initial photoinduced electron transfer from photoexcited phenazine chromophores involves the benzoimidazole cation and that this process is likely coupled with proton transfer to generate protonated benzoimidazole-based radical cation. The second photoinduced electron transfer is hypothesized to generate the hydride form. Furthermore, our findings provide the requisite information for the future development of reductive photocatalysts for solar energy and light-harvesting applications utilizing earth-abundant metal-free materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving Prediction of Surface Solar Irradiance Variability by Integrating Observed Cloud Characteristics and Machine Learning

A 5-year, 1-minute resolution observational dataset of clouds and solar radiation was produced that includes two metrics of the variability in surface solar irradiance due to cloud type and fractional sky cover. Multiple regression models were trained to fit observations of surface solar irradiance variability from those two cloud property predictors. We found that ensemble tree-based methods, Random Forest and Gradient Boosting Machine, have the least overfitting issues and showed the best performance with an R2 of 0.42. While the observational data trained in this study was only from one site, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, initial comparisons of the seasonality of the statistics suggest that these results are relatively weather regime independent; the generality of such a finding across sites will be tested in future work. The observational data and developed machine learning model are being used to create a numerical weather prediction model parameterization to enable day-ahead solar variability prediction in a computationally efficient way. This is a first step towards creating a new paradigm of predicting day-ahead variability with the potential to provide a new tool to improve grid operation, planning, and resilience.

Riihimaki, Laura↗

Predicting cutoff L-shells of solar protons using the GPPSn particle dataset

Solar energetic protons (SEPs) arriving at the Earth trigger severe radiation storms in the near-Earth space, directly impacting space missions operating at various altitudes. Therefore, monitoring SEP events and predicting the penetration depths of solar protons are critical for aerospace sectors. Building on previous efforts, here we demonstrate the feasibility of using proton measurements from the Global Prompt Proton Sensor network (GPPSn), enabled by Los Alamos National Laboratory developed combined X-ray dosimeters aboard GPS satellites, to characterize and predict the penetration of solar protons into the geomagnetic field. The inclined medium-Earth-orbits (MEOs) of the global GPS constellation offer a unique advantage of allowing simultaneous measurements of penetrating solar protons inside both open- and closed-field line regions. Therefore, the L-profiles of ∼10s–100 MeV solar protons and their associated cutoff L-shells can be determined from the GPPSn dataset, using predefined threshold proton flux values rather than traditional flux ratios. After examining a list of SEP event intervals across solar cycles 23, 24 and 25—including the 2024 Mother’s Day superstorm, we showcase how the latest GPPSn proton dataset (release v1.10), reprocessed and calibrated, can not only be used to monitor solar proton distributions inside the dynamic geomagnetic field for individual events, but also to derive a new empirical model linking cutoff L-shells with several key space weather parameters. This newly developed SEPCL-MEO model demonstrates high predictive performance; for example, predictions for > 30 MeV solar protons yield a correlation coefficient of 0.85 and performance efficiency of 0.67 when validated against GPPSn observations. Results from this pilot study underscores the scientific and operational value of the GPPSn dataset, and this dataset—when paired with machine-learning techniques—can play a critical role in observing and predicting the effects of future incoming SEP events, including extreme ones.

58 GEOSCIENCES↗

Opportunities for green hydrogen production with land-based wind in the United States

Hydrogen (H 2 ) is an efficient energy carrier and storage mechanism that can supply both stationary and transport energy demand. Rapidly declining renewable energy generation costs; technology innovations in wind, solar, battery storage, and electrolysis; and a global push for more sustainable and secure energy have driven increased interest in green H 2 production. In this study, we develop an H 2 scenario analysis tool to assist in rapid, high-resolution insights into future, green H 2 pathways to achieve policy goals and market competitiveness. Using this tool, we estimate H 2 production and costs for U.S., off-grid scenarios given varying policy and cost scenarios from 2025–2035. Results indicate that achieving economically competitive green H 2 production (below $\$$2/kg) is possible in 2030 with no policy incentives (one site achieves this target), while increasing policy support to include wind and green H 2 production tax credits enables widespread economic viability sooner, with sub-$\$$2/kg LCOH targets achieved by 2025 and 51.7% of sites achieving this target by 2035. Maximizing policy support through prevailing wage and apprenticeship credit multipliers enable widespread economic viability, including sub-$\$$2/kg of green H 2 by 2025 and even negative pricing by 2035. Regions with lowest LCOH values correspond to high wind resource areas and capacity factors. Achieving decarbonization goals with green H 2 depends on technology cost reductions and policy support, with a maximum average LCOH reduction of $\$$23.10 between no and maximum policy support scenarios, and a maximum average LCOH reduction of $\$$25.86 between current, conservative technology costs and 2035 projected technology cost assumptions.

08 HYDROGEN↗

Improving Energy Efficiency and Self-Sufficiency on the Pechanga Indian Reservation

This project will study the feasibility and identify the preferred options necessary to allow the Pechanga Tribal Utility, now renamed Pechanga Western Electric (“PWE”) to carefully and thoughtfully expand from providing electrical service to the Tribe’s commercial enterprises and government center loads to also providing electrical service to the Tribe’s over 300 residential loads and potential future non-tribal commercial loads on the reservation. As well as, explore an option under which PWE will acquire solar and battery storage systems for the residential community.

14 SOLAR ENERGY↗

Data‐driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Summary Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well‐studied major crops. Using 727 maize ( Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre‐ and postanthesis maximum temperature, mid‐season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well‐studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Kusmec, Aaron↗

Impact of galactic cosmic ray simulation on nutritional content of foods

Foods packaged for future deep-space exploration missions may be prepositioned ahead of astronaut arrival, and will be exposed to galactic cosmic rays (GCRs) and solar radiation in deep space at higher levels and different spectrums than those found in low-Earth orbit (LEO). In this study, we have evaluated the impact of a GCR simulation (approximately 0.5 and 5 Gy doses) at the NASA Space Radiation Laboratory (NSRL) on two retort thermostabilized food products that are good sources of radiation labile nutrients (thiamin, vitamin E, or unsaturated fats). No trends or nutritional differences were found between the radiation-treated samples and the control immediately after treatment or one-year after treatment. Small changes in a few nutrients were measured following one-year of storage. Further studies are needed to confirm these results, as the foods in this study were heterogeneous, and this may have masked meaningful changes due to pouch-to-pouch variations.

59 BASIC BIOLOGICAL SCIENCES↗

Snowmass 2021 Scintillating Bubble Chambers: Liquid-noble Bubble Chambers for Dark Matter and CE$\nu$NS Detection

The Scintillating Bubble Chamber (SBC) Collaboration is developing liquid-noble bubble chambers for the quasi-background-free detection of low-mass (GeV-scale) dark matter and coherent scattering (CE$\nu$NS) of low-energy (MeV-scale) neutrinos. The first physics-scale demonstrator of this technique, a 10-kg liquid argon bubble chamber dubbed SBC-LAr10, is now being commissioned at Fermilab. This device will calibrate the background discrimination power and sensitivity of superheated argon to nuclear recoils at energies down to 100 eV. A second functionally-identical detector with a focus on radiopure construction is being built for SBC's first dark matter search at SNOLAB. The projected spin-independent sensitivity of this search is approximately $10^{-43}$ cm$^2$ at 1 GeV$/c^2$ dark matter particle mass. The scalability and background discrimination power of the liquid-noble bubble chamber make this technique a compelling candidate for future dark matter searches to the solar neutrino fog at 1 GeV$/c^2$ particle mass (requiring a $\sim$ton-year exposure with non-neutrino backgrounds sub-dominant to the solar CE$\nu$NS signal) and for high-statistics CE$\nu$NS studies at nuclear reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Navigating the Use of Direct Current in Residential Settings: Merits and Obstacles

This review paper provides an in-depth analysis of the role of Direct Current (DC) power systems in residential settings, focusing on their safety, efficiency, and environmental advantages. It recognizes the significant contribution of the residential sector to global carbon dioxide emissions and explores how DC power systems can help mitigate these effects. The paper traces the historical evolution of DC power, its resurgence with renewable energy technologies, and the advancements in power electronics that facilitate its integration. Emphasizing the efficiency and safety benefits, especially in low-voltage applications, the paper highlights the seamless integration of DC systems with inherently DC-generating renewable sources like solar PV and wind. The review discusses the critical role of converter technologies in the transition to DC power and examines the compatibility of DC systems with energy storage solutions, underscoring their potential for enhanced energy management. It also addresses the environmental impacts of adopting DC power, aligning with global carbon reduction efforts. The paper analyzes regional case studies, exploring practical applications and outcomes, and addresses challenges such as the need for standardization. It concludes with recommendations for stakeholders and future research directions, emphasizing the economic, technological, and environmental aspects of DC power systems. Overall, the paper presents DC power as a viable and sustainable option for residential energy conservation, contingent upon ongoing technological progress, supportive policies, and standardization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

PV Hosting Capacity Estimation: Experiences with Scalable Framework

Hosting capacity is an indication of the amount of solar photovoltaics (PV) that can be hosted in a distribution system without additional changes to infrastructure or oper-ations. This paper presents a framework for estimating the PV hosting capacity at scale. First, we analyze computational, modeling and other key challenges of performing relevant, large-scale simulations, provided along with the experiences and lessons learned. Then, we develop two open-source Python-based software tools to conduct repeatable distribution analyses: the Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations and the Job Automation and Deployment Engine (JADE) for parallelizing jobs on high-performance computing clusters. A case study of hosting capacity estimation for the SMART-DS San Francisco (SFO) 2000+ synthetic feeders, is used to demonstrate the capability of the developed DISCO+JADE framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, which can help them better plan for the overall upgrade costs to integrate more PV in the future. The experiences are shared to aid the tool users and researchers to conduct relevant studies and research.

distributed energy resources↗