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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Estimating Interplanetary Magnetic Field Conditions at Mercury's Orbit From MESSENGER Magnetosheath Observations Using a Feedforward Neural Network

Abstract Mercury's small magnetosphere is embedded in the dynamic and intense solar wind environment characteristic of the inner heliosphere. Both the magnitude and orientation of the interplanetary magnetic field (IMF) significantly influence the solar wind‐magnetospheric interaction at Mercury, driving phenomena such as magnetic reconnection. The MErcury Surface, Space Environment, Geochemistry and Ranging (MESSENGER) spacecraft provided in‐situ magnetic field measurements of the solar wind, the magnetosheath, and the magnetosphere along each orbit. However, it is a challenge to directly assess the IMF's impact on Mercury's plasma environment due to the temporal separation between observations within the solar wind and the magnetosphere, especially in the absence of an upstream monitor. Here, we present a feedforward neural network (FNN) trained on a subset of magnetosheath observations to estimate the strength and orientation of the IMF upstream of the bow shock. Utilizing magnetosheath magnetic field, cylindrical spatial coordinates, and heliocentric distance measurements, the FNN predicts upstream IMF conditions with an score of 0.70 and mean averaged error of 5.3 nT, thereby greatly decreasing the temporal separation between IMF estimates and magnetospheric measurements throughout the MESSENGER mission. This approach yields IMF estimates for all magnetosheath data measured by MESSENGER, providing a useful tool for future investigations of the IMF impact on Mercury's magnetosphere. This method will be integrable with the dual‐spacecraft BepiColombo magnetosheath measurements, providing useful estimates of upstream IMF conditions particularly during the extended periods in which neither spacecraft sample the solar wind. Our results demonstrate the utility of machine learning techniques on advancing space science research.

Bowers, Charles F.↗
DOE OSTI2022

Stability-limiting heterointerfaces of perovskite photovoltaics

Optoelectronic devices consist of heterointerfaces formed between dissimilar semiconducting materials. The relative energy level alignment between contacting semiconductors determinately affects the heterointerface charge injection and extraction dynamics. For perovskite solar cells (PSCs), the heterointerface between the top perovskite surface and a charge-transporting material (CTM) is often treated for defect passivation to improve PSC stability and performance. However, such surface treatments could also affect the heterointerface energetics. Here we show that surface treatments may induce a negative work function shift (i.e. more n-type), which activates halide migration to aggravate PSC instability. Therefore, despite the beneficial effects of surface passivation, this detrimental side effect limits the maximum stability improvement attainable for PSCs treated in these ways. Furthermore, this trade-off between the beneficial and detrimental effects should guide further work on improving PSC stability via surface treatments.

14 SOLAR ENERGY↗
DOE OSTI2025

Effect of the space weather conditions on the Earth magnetosphere soft X-ray emissivity

The aim of the study is to model and characterize the soft X-ray emissivity on the Earth magnetosphere for different space weather conditions (SWC), providing information to interpret the soft X-ray measurements of the Solar wind Magnetosphere Ionosphere Link Explorer space mission. The MHD code pluto in spherical coordinates is used to perform parametric studies with respect to the solar wind (SW) dynamic pressure (considering density and velocity effects independently) as well as the IMF intensity and orientation, predicting the soft X-ray emissivity for different SWC. The integrated soft X-ray emissivity inside the magnetosheath is calculated as a proxy of the soft X-ray emission dependencies with the SWC independently of the satellite orbit and camera line of sight. The analysis indicates fluctuations of the interplanetary magnetic field (IMF) orientation and magnitude may significantly affect the measured soft X-ray emission although changes in the SW dynamic pressure should be the main source of variability. The southward IMF orientation leads to the configuration with the largest soft X-ray emissivity and northward to the lowest. Strongly distorted magnetospheres explored in configurations showing SW and IMF parameters comparable to the impact of interplanetary coronal mass ejections may show a decrease of the soft X-ray emissivity as the IMF magnitude increases, explained by the strong magnetosphere compression and constriction of the magnetosheath region where the soft X-ray emissivity maximum is located. The simulations also indicate large excursions of the soft X-ray emissivity maximum inside the magnetosheath as the IMF magnitude and SW dynamic pressure fluctuate particularly for radial and ecliptic IMF orientations.

Earth↗
DOE OSTI2020

Black hole perturbations and quasinormal modes in hybrid metric-Palatini gravity

The rapid advancement of gravitational wave astronomy in recent years has paved the way for the burgeoning development of black hole spectroscopy, which enhances the possibility of testing black holes by their quasinormal modes (QNMs). In this paper, the axial gravitational perturbations and the QNM frequencies of black holes in the hybrid metric-Palatini gravity (HMPG) are investigated. Additionally, the HMPG theory is characterized by a dynamical scalar degree of freedom and is able to explain the late-time accelerating expansion of the universe without introducing any ad hoc screening mechanism to preserve the dynamics at the Solar System scale. We obtain the master equation governing the axial gravitational perturbations of the HMPG black holes and calculate the QNM frequencies. Moreover, in the scrutiny of the black holes and their QNMs, we take into account the constraints on the model parameters based on the post-Newtonian analysis, and show how the QNM frequencies of the HMPG black holes would be altered in the observationally consistent range of parameter space.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Data-Driven Model for Photovoltaic Generation: Comparison with Physical Models Using a Microgrid in Puerto Rico

Photovoltaic (PV) generation is a critical component of microgrids, but its accurate modeling is challenging due to the complex and dynamic interactions between solar irradiance, temperature, and PV system installation. This paper develops a multilayer perceptron (MLP) model that inputs solar irradiance and temperature to estimate the PV generation, and it compares the proposed data-driven model’s performance to two well-known physical models: the single-diode model and the inverter model. The results demonstrate that all the models can reach high levels of accuracy. However, the MLP model outperforms the physical models on average by 4.5 to 6.6 percent in R squared scores and 220 to 290 Watts in RMSE scores, and it does not require physical system parameters. Moreover, the data-driven model can overcome the limitations of the lack of real-time PV generation data.

R pesante colón, Marcos↗
DOE OSTI2026

SIRENOpt.jl

SAND2026-22945O SIRENOpt.jl is a Julia software package for prototype hybrid power, storage, and platform dynamics. It integrates solar, wind, wave, hydrokinetic, diesel, generator, converter, battery, hydrogen, desalination, mooring, and floating-platform model interfaces in an automatic-differentiation-friendly simulation framework. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Michelen Strofer, Carlos [Sandia National Lab. (SN↗
DOE OSTI2020

Characterizing the Small-Scale Dynamical, Ice Microphysical, and Residual Aerosol Properties of Mid-Latitude Cold Clouds: A Pilot Study (Final Report)

Our understanding of cirrus clouds has been advancing rapidly due to improvements in measurements made inside clouds, computer cloud models, and laboratory experimentation. This advancement in knowledge has made it clear that cirrus are complicated systems where the intricate interactions among dynamic air motions, solar and terrestrial radiation, ice crystal growth, and water and air chemistry can substantially influence cirrus structure and evolution. Measurements made inside clouds have shown that cirrus crystals are often complex with shapes that are often unclassifiable, especially at small sizes. Laboratory measurements have revealed that the ice crystal surface is complex, even at small sizes. Recent laboratory and satellite studies show that this surface complexity modifies the radiative properties of cirrus clouds in important ways. Moreover, observations and computer cloud modeling work show that the larger and smaller scale properties of cirrus are sensitive to the interplay between small-scale air motions and the aerosol articles upon which cirrus ice crystals form. Taken together, these studies indicate that accurately accounting for the radiative properties of cirrus clouds requires knowing the air motions and aerosol properties that influence the number concentration and crystal size, along with an understanding of the surface properties of vapor grown ice. Although this prior work has been illuminating, there have been few studies that provide detailed shape and surface complexity measurements for the small ice crystals that often compose cirrus clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Unlocking the Sun's Secrets: Laboratory Insights into the Sun's Outer Atmosphere

The Sun’s corona, its outermost and hottest atmospheric layer, emits brightly in the extreme ultraviolet (EUV) and X-rays. This emission comes from atoms that have been highly ionized by the high temperature, forming a plasma of atomic ions and free electrons. By studying this light, scientists learn about the complex and dynamic drivers of solar activity. Many past, current, and future solar observatories focus on measuring EUV spectra from the Fe IX ion, as this ion provides powerful diagnostics for solar physics. Using Fe IX spectra, solar physicists can measure the plasma temperature, density, elemental abundances, and flow velocities in the corona. However, atomic data uncertainties concerning spectral line identification and plasma density diagnostics are a major problem for the accurate interpretation of these spectra.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Advancing Mass Timber Buildings: Novel Methods Improve Thermal Assessment and Material Use

For nearly a century, thermal demand calculations for buildings have relied on simplified models developed to match the technical constraints of their era. The first standards, introduced in Germany and Austria in 1929, established climate zones and material conductivity coefficients that, with only incremental updates, still underpin many current assessments. Yet, methods such as Hot box testing, originally designed for lightweight insulation, continue to be applied for mass timber buildings, overlooking thermodynamic characteristics confer real-world advantages. Recent research at Oak Ridge National Laboratory incorporates updated methodologies, aligned with ASHRAE Standard 55 (ASHRAE, 2023) accounting for factors such as thermal inertia, inner surface temperatures, emissivity, solar gains, and dynamic outdoor conditions. These factors better reflect observed heating and cooling loads and highlight opportunities for efficient use of materials in mass timber construction. This work provides a framework for designing comfortable, resilient, and resource-efficient buildings while aligning with performance expectations in energy codes.

Pickett, Robert [International Mass Timber Allianc↗
DOE OSTI2021

Behind the Meter Solar+Storage: Market data and trends [Slides]

As the distributed solar market evolves toward more dynamic forms of deployment, interest in paired solar-plus-storage applications continues to gain steam, but details on the current state of the market are relatively sparse. To fill that void, Berkeley Lab has released an in-depth analysis of this budding market segment. This report draws on the Lab’s Tracking the Sun dataset to characterize trends in deployment, system sizing and equipment selection, installer-market development, and system pricing. The report also provides indicative analyses of the financial and resilience value that host customers in several key markets presently receive by pairing storage with solar.

14 SOLAR ENERGY↗
DOE OSTI2023

Modeling and Control of Solar PVs for Large Grid Disturbances and Weak Grids

The purpose of this project is to understand dynamic phenomena by designing dynamic models of utility-sale solar photovoltaic (PV) power plants and their interactions with grids; and construct effective coordination strategies for stability enhancement for solar PVs to respond to rapidly changing grid conditions.

14 SOLAR ENERGY↗
DOE OSTI2022

Increased panel height enhances cooling for photovoltaic solar farms

We report solar photovoltaic (PV) systems suffer substantial efficiency loss due to environmental and internal heating. However, increasing the canopy height of these systems promotes surface heat transfer and boosts production. This work represents the first wind tunnel experiments to explore this concept in terms of array flow behavior and relative convective heat transfer, comparing model solar arrays of varied height arrangements - a nominal height, extended height, and a staggered height configuration. Analyses of surface thermocouple data show average Nusselt number (Nu) to increase with array elevation, where panel convection at double height improved up to 1.88 times that of the nominal case. This behavior is an effect of sub-array entrainment of high velocity flow and panel interactions as evidenced through flow statistics and mean kinetic energy budgets on particle image velocimetry (PIV) data. The staggered height arrangement encourages faster sub-panel flow than in the nominal array. Despite sub-array blockage due to the lower panel interaction, heat shedding at panel surfaces promotes improvements on over 1.3 times that of the nominal height case.

14 SOLAR ENERGY↗
DOE OSTI2023

Origin of high optical contrast in zinc-zinc oxide electrodeposits for dynamic windows

The control of solar light and heat emission through windows is an important strategy for increasing the energy efficiency of buildings. Reversible Zn electrodeposition has recently emerged as a promising method for constructing electronically tintable robust dynamic windows. In Zn electrodeposits formed from dimethyl sulfoxide (DMSO) electrolytes during device tinting, we observe extraordinary absorption that is in excess of what is predicted by the Beer-Lambert law for a uniform Zn thin film. Here, the charge required to electroplate these films is abnormally low, significantly less than previously reported dynamic windows based on reversible metal electrodeposition, which facilitates the construction of large-area devices that switch uniformly. Finite-difference time-domain (FDTD) simulations are used to investigate the origin of this enhanced absorption, which arises from plasmonic effects among the Zn nanoparticles and ZnO dendrites in the film. The dielectric ZnO dendrites promote absorption via slit-like Zn-dielectric-Zn structures that from hybrid surface plasmon resonance at metal walls. Through these investigations, we provide design principles to construct low-charge and high-contrast metal and metal oxide-based dynamic windows.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Dynamic Effects and Hydrogen Bonding in Mixed-Halide Perovskite Solar Cell Absorbers

The organic component (methylammonium) of CH 3 NH 3 PbI 3- x Cl x -based perovskites shows electronic hybridization with the inorganic framework via H-bonding between N and I sites. Femtosecond dynamics induced by core excitation are shown to strongly influence the measured X-ray emission spectra and the resonant inelastic soft X-ray scattering of the organic components. The N K core excitation leads to a greatly increased N-H bond length that modifies and strengthens the interaction with the inorganic framework compared to that in the ground state. The study indicates that excited-state dynamics must be accounted for in spectroscopic studies of this perovskite solar cell material, and the organic-inorganic hybridization interaction suggests new avenues for probing the electronic structure of this class of materials. Furthermore, it is incidentally shown that beam damage to the methylamine component can be avoided by moving the sample under the soft X-ray beam to minimize exposure and that this procedure is necessary to prevent the creation of experimental artifacts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multioutput Convolutional Neural Network for Improved Parameter Extraction in Time-Resolved Electrostatic Force Microscopy Data

Time-resolved scanning probe microscopy methods, like time-resolved electrostatic force microscopy (trEFM), enable imaging of dynamic processes ranging from ion motion in batteries to electronic dynamics in microstructured thin film semiconductors for solar cells. Reconstructing the underlying physical dynamics from these techniques can be challenging due to the interplay of cantilever physics with the actual transient kinetics of interest in the resulting signal. Previously, quantitative trEFM used empirical calibration of the cantilever or feed-forward neural networks trained on simulated data to extract the physical dynamics of interest. Both these approaches are limited by interpreting the underlying signal as a single exponential function, which serves as an approximation but does not adequately reflect many realistic systems. Here, we present a multi-branched, multi-output convolutional neural network (CNN) that uses the trEFM signal in addition to the physical cantilever parameters as input. The trained CNN accurately extracts parameters describing both single-exponential and bi-exponential underlying functions, and more accurately reconstructs real experimental data in the presence of noise. This article demonstrates an application of physics-informed machine learning to complex signal processing tasks, enabling more efficient and accurate analysis of trEFM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Simulating a solar parabolic trough collector plant used for industrial process heat using an optimized operating scheme that utilizes flexible heat integration

This study focuses on the modeling and simulation of a novel design and operation of a solar industrial process heat (SIPH) plant that uses a parabolic trough collector system for generating process heat. The SIPH plant incorporates flexible heat integration (FHI) by having two options for heat sinks as well as a flexible collection temperature for the heat transfer fluid. Leveraging the degrees of freedom created by FHI allows an optimized operating scheme to be created which maximizes the solar heat delivered to the industrial processes. Yearly results for a 27 MW-t plant located in Salt Lake City, UT are simulated for a base case and a case utilizing optimized FHI. For the main process temperature case presented, FHI increases the total solar share by 13.0% and reduces the levelized cost of heat of the SIPH plant by 10.4% relative to the base case. Furthermore, three case study days are presented which highlight how FHI maximizes solar share, specifically during mornings, afternoons, and days with intermittent solar conditions. An environmental analysis is also performed showing that the SIPH plant can reduce harmful emissions by 15.4% for the base case and 17.4% for the FHI case compared to a plant that only utilizes a natural gas furnace for process heat. Overall, the work thoroughly explores an effective operating scheme for a SIPH plant, helping to make it more economical and environmentally beneficial.

14 SOLAR ENERGY↗
DOE OSTI2020

Dynamic optimization and economic evaluation of flexible heat integration in a hybrid concentrated solar power plant

Hybridization of concentrated solar power (CSP) plants provides flexibility in operation that can drastically improve the solar-to-electric (STE) efficiency and levelized cost of electricity (LCOE) relative to standalone CSP plants. Flexible heat integration (FHI) is a novel concept where the collection and integration of CSP within a power plant is modified relative to the amount of solar energy available. FHI improves the thermal efficiency of a hybrid solar tower steam Rankine cycle power plant but leads to increased pumping needs due to continuously elevated molten salt flow rates through the collection system, which can negatively impact STE efficiency. The present work is carried out to maximize the STE efficiency of a hybrid CSP plant utilizing FHI by employing a dynamic optimization framework where a genetic algorithm optimizes the operation of the plant over a given solar irradiance profile. The study concerns a plant hypothetically located in Salt Lake City, Utah. Here, the optimization results confirm the accuracy of a predictive heuristic where the preferred operation of the plant can be estimated relative to local peaks in the incident power generated by the heliostat collection field. The optimized FHI operation demonstrates a yearly STE efficiency of 13.8%, whereas the equivalent base-level hybrid and solar-only plants exhibit solar efficiencies of 13.4% and 11.2%, respectively. Economic analysis shows that FHI reduces yearly natural gas costs, leading to a $\$0.5$/MWh reduction in LCOE relative to the base-level hybrid configuration. Overall, the results show that hybrid FHI schemes exhibit economic benefits along with observed thermodynamic improvements.

14 SOLAR ENERGY↗
DOE OSTI2026

Rotation‐Controlled Diurnal Evolution of Uranus' Asymmetric Bow Shock at Equinox

Uranus possesses the most extreme magnetic and rotational geometry in the solar system, resulting in a uniquely dynamic and asymmetric interaction between its magnetosphere and the solar wind. Here we investigate the diurnal evolution of the Uranian bow shock (BS) at equinox using global multifluid magnetohydrodynamic simulations constrained by Voyager 2 observations. The BS structure and variability are quantified using the stand‐off distance, terminator distance, flaring parameter, and BS parameter, enabling a systematic assessment of its global asymmetry over one planetary rotation. Our results show that the BS exhibits pronounced diurnal asymmetry that is primarily controlled by planetary rotation. Even under steady upstream solar wind conditions, the BS undergoes periodic expansion and contraction, reflecting rotation‐driven reconfiguration of the planetary magnetospheric topology. This diurnal modulation represents a remarkably large asymmetry in planetary BS geometry within the solar system. These results establish planetary rotation as the intrinsic primary driver of Uranus' BS dynamics at equinox and provide essential constraints for the design and formulation of future space missions to the ice giants. These findings also offer a unique framework for understanding shock physics in the abundant population of ice‐giant exoplanets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗