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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

OSIRIS-REx constraints on local dark matter and cosmic neutrino profiles

We derive purely gravitational constraints on dark matter and cosmic neutrino profiles in the solar system using asteroid (101955) Bennu. We focus on Bennu because of its extensive tracking data and high-fidelity trajectory modeling resulting from the OSIRIS-REx mission. We find that the local density of dark matter is bound by $ρ_{DM}$ ≲ 3.3 × 10 -15 kg/m 3 ≃ 6 × 10 6 $\bar{ρ_{DM}}$, in the vicinity of ~ 1.1 au (where $\bar{ρ_{DM}}$ ≃ 0.3 GeV/cm 3 ). We show that high-precision tracking data of solar system objects can constrain cosmic neutrino overdensities relative to the Standard Model prediction n̅ν, at the level of η ≡ nν/n̅ν ≲ 1.7 × 10 11 (0.1 eV/m ν ) (Saturn), comparable to the existing bounds from KATRIN and other previous laboratory experiments (with m ν the neutrino mass). These local bounds have interesting implications for existing and future direct-detection experiments. Our constraints apply to all dark matter candidates but are particularly meaningful for scenarios including solar halos, stellar basins, and axion miniclusters, which predict overdensities in the solar system. Furthermore, introducing a DM-SM long-range fifth force with a strength tilde alphaDtimes stronger than gravity, Bennu can set a constraint on ρDM ≲ $\bar{ρ_{DM}}$(6 × 10 6 /$_{\tilde{αD}}$). These constraints can be improved in the future as the accuracy of tracking data improves, observational arcs increase, and more missions visit asteroids.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Resolving electron and hole transport properties in semiconductor materials by constant light-induced magneto transport

The knowledge of minority and majority charge carrier properties enables controlling the performance of solar cells, transistors, detectors, sensors, and LEDs. Here, we developed the constant light induced magneto transport method which resolves electron and hole mobility, lifetime, diffusion coefficient and length, and quasi-Fermi level splitting. We demonstrate the implication of the constant light induced magneto transport for silicon and metal halide perovskite films. We resolve the transport properties of electrons and holes predicting the material’s effectiveness for solar cell application without making the full device. The accessibility of fourteen material parameters paves the way for in-depth exploration of causal mechanisms limiting the efficiency and functionality of material structures. To demonstrate broad applicability, we further characterized twelve materials with drift mobilities spanning from 10 –3 to 10 3 cm 2 V –1 s –1 and lifetimes varying between 10 –9 and 10 –3 seconds. The universality of our method its potential to advance optoelectronic devices in various technological fields.

14 SOLAR ENERGY↗
DOE OSTI2022

Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters

The industrial sector consumes about one-third of global energy, making them a frequent target for energy use reduction. Variation in energy usage is observed with weather conditions, as space conditioning needs to change seasonally, and with production, energy-using equipment is directly tied to production rate. Previous models were based on engineering analyses of equipment and relied on site-specific details. Others consisted of single-variable regressors that did not capture all contributions to energy consumption. Further, new modeling techniques could be applied to rectify these weaknesses. Applying data from 45 different manufacturing plants obtained from industrial energy audits, a supervised machine-learning model is developed to create a general predictor for industrial building energy consumption. The model uses features of air enthalpy, solar radiation, and wind speed to predict weather-dependency; motor, steam, and compressed air system parameters to capture support equipment contributions; and operating schedule, production rate, number of employees, and floor area to determine production-dependency. Results showed that a model that used a linear regressor over a transformed feature space could outperform a support vector machine and utilize features more representative of physical systems. Using informed parameters to build a reliable predictor will more accurately characterize a manufacturing facility's energy savings opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

The Rise of US Photovoltaics: An Exploration of Land Use Density Trends in Large‐Scale Solar Facility Attributes, 2012–2021

An energy transition is underway in the United States; renewable energy generation is now on par with coal and nuclear generation. The number of large-scale solar photovoltaic facilities increased approximately tenfold between 2012 and 2021, with an associated 25-fold increase in cumulative installed capacity. With ambitious decarbonization and renewable energy deployment goals at both the federal and state levels, deployments of large-scale solar photovoltaic facilities will continue apace. This growth is likely to be complex with ripples of impacts felt throughout different aspects of society, and thus accurate solar land use metrics allowing more accurate predictions are of value to policymakers, planners, and other stakeholders in the future photovoltaic build-out. In this paper, we leverage data from the newly released US Large-Scale Solar Photovoltaic Database to examine recent trends in large-scale solar photovoltaic land use. We analyze the relationships between solar array capacity density (W/acre) and a range of facility attributes to better understand the future land requirements of solar capacity expansion over the coming years. Installed capacity was the single strongest determinant of solar array area. However, we found substantial variation in capacity density across facility attributes, including mount type, latitude, urbanicity, time, and prior land use.

14 SOLAR ENERGY↗
DOE OSTI2020

Modeling Time to Failure in Potential-Induced Degradation of Silicon Solar Modules based on Quantitative Sodium Kinetics

We present a physics-based simulation environment for the prediction of potential-induced-degradation (PID) failure time in silicon solar modules. Our model is based on experimental sodium migration kinetics obtained from our recently developed trap-corrected bias-stress-temperature method and from secondary ion mass spectrometry measurements. Furthermore, we model sodium migration to stacking faults and subsequent formation of conductive pathways through the p-n junction, which causes a decrease of the shunt resistance and loss of efficiency.

42 ENGINEERING↗
DOE OSTI2021

Comprehensive energy balance analysis of photon-enhanced thermionic power generation considering concentrated solar absorption distribution

The present article reports a comprehensive energy balance analysis of a photon-enhanced thermionic emission (PETE) device when it is used for concentrated solar power (CSP) generation. To this end, we consider a realistic PETE device composed of a boron-doped silicon emitter on glass and a phosphorus-doped diamond collector on tungsten separated by the interelectrode vacuum gap. Here, depth-dependent spectral solar absorption and its photovoltaic and photothermal energy conversion processes are rigorously calculated to predict the PETE power output and energy conversion efficiency. Our calculation predicts that when optimized, the power output of the considered PETE device can reach 1.6 W/cm 2 with the energy conversion efficiency of ~ 18% for 100× solar concentration, which is substantially lower than those predicted in previous works under ideal conditions. In addition, the photon-enhancement ratio is lower than 10 and decreases with the increasing solar concentration due to the photothermal heating of the emitter assembly, suggesting that PETE should be more suitable for lowto- medium CSP below ~ 100× concentration. These observations signify the importance of a rigorous energy balance analysis based on spectral and spatial solar absorption distribution for the accurate prediction of PETE power generation.

14 SOLAR ENERGY↗
DOE OSTI2021

Understanding Solar Photovoltaic System Performance: An Assessment of 75 Federal Photovoltaic Systems

This report presents a performance analysis of 75 photovoltaic systems based on PV system production data collected as part of a FEMP Federal PV Performance Assessment project combined with co-incident insolation, and ambient temperature to analyze how actual performance compares with a performance model. FEMP collaborated with 17 Federal agencies and sub-agencies to collect the information required to analyze the performance of each system. The systems represent a total capacity of 30,714 kW and range in size from 1 kW to 4,043 kW, with an average size of 410 kW, and were installed between 2011 and 2020. The data is analyzed for Key Performance Indicators, Availability, Performance Ratio and Energy Ratio by comparing the measured production data to model production data. The System Advisor Model (SAM) combines a description of the system (such as inverter capacity, de-rating for temperature, balance-of-system efficiency) with environmental parameters (coincident solar and temperature data) to calculate predicted performance. The performance metrics are calculated by lining up the measured production data with the model estimate on an hour-by-hour, day-by-day, or month-by-month basis (depending on the interval resolution of the production data). A report with system description, photo of the system, special assumptions made for the site, graph of measured production and model production, table of key performance indicators, and links to O&M resources that might improve performance was produced and delivered to site and agency staff with a short on-line briefing.

14 SOLAR ENERGY↗
DOE OSTI2023

Investigating Various Failure Models on Commercial Silicon Carbide

Structures and components made from ceramic materials are often brittle and can fail by the unstable growth of existing flaws such as voids and cracks. There have been several failure criteria developed for ceramics, in the past and they are broadly categorized based on their dependency on crack geometry. The present work implements eight failure criteria using an open-source software package – srlife, which predicts the lifetime or failure probability of concentrated solar power (CSP) structural components. The present work also checks the viability of building a ceramic CSP receiver, by analyzing the reliability predictions from srlife for a SiC ceramic. The reliability predictions for a biaxial loading problem indicated the Shetty Mixed-Mode criterion gives the most conservative predictions. Whereas, in case of the CSP receiver, the predictions show that the co-planar strain energy criterion gives the most conservative predictions as it is agnostic towards the type of stress, and therefore, is not recommended to be used designing ceramic receivers.

Chaugule, Pawan (ORCID:0000000275706572)↗
DOE OSTI2024

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗
DOE OSTI2026

An Updated Picture of Presolar History from Short-lived Radioactive Isotopes and Inferences on the Birth of the Sun

We examine the origin of the short-lived radionuclides (SLRs; defined as having half-lives between 0.1 and 100 Ma) present in the early solar system (ESS) by investigating how predictions of their abundances in the interstellar medium (ISM) from steady-state equilibrium relate to their ESS values. For this, we take into account the non-negligible time t iso elapsed between the isolation of the presolar molecular cloud and the formation of the ESS, during which the SLRs decayed freely. We also consider the alternative scenario in which the presolar molecular cloud remained partially mixed with the ISM, with a mixing timescale t mix . We find that the ESS abundances of 107 Pd and 182 Hf produced by slow neutron captures (s-process) and of 53 Mn and 60 Fe produced by explosive nucleosynthesis can be consistently explained within these scenarios. Their required tiso is 9–12 Ma and their required tmix is 11–14 Ma (with one potential exception of t mix = 38 Ma), depending on galactic uncertainties, such as the galactic star formation history and efficiency and the star-to-gas mass ratio. Another s -process SLR, 205 Pb, has a more uncertain ESS value and falls within only some of these time values. The same applies to the SLRs produced by the p -process ( 92 Nb and 146 Sm), depending on the latter’s half-life. In agreement with previous studies, we find that the ESS abundances of the rapid neutron-capture isotopes ( 129 I, 244 Pu, and 247 Cm) and of the most short-lived radionuclides ( 26 Al, 36 Cl, and 41 Ca) cannot be explained by assuming steady-state equilibrium in the ISM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

Xie, Yu↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

DNI↗
DOE OSTI2021

Toward predictive permeabilities: Experimental measurements and multiscale simulation of methanol transport in Nafion

A polymer membrane's permeability to solutes determines its suitability for various applications: a permeability value is essential for predicting performance in diverse contexts. Using aqueous methanol permeation through Nafion as an example, we describe a methodology for determining membrane permeability that accounts for boundary layer effects and the possibility of swelling. For the materials and apparatus used herein, analysis of a permeance measurement and computational fluid dynamics simulations show that the mass transfer boundary layer is on the order of ones to tens of microns. Additionally, the data are used to develop and validate a multiscale model describing solute permeation through a hydrated membrane as a series of physical mechanistic steps: reversible adsorption from solution at the membrane interface, diffusion driven by a concentration gradient within the membrane, and reversible desorption into solution at the opposite membrane interface. The validated model is used to predict methanol transport across a solar-driven CO 2 reduction device and to assess the impact of polymer changes on the measured value. The approach of combining experimental data, computational fluid dynamics, and the mechanistic multiscale model is expected to provide more accurate analysis of membrane permeation data in cases with polymer swelling or unusual device geometries, among others.

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

The Observed and Projected Changes of Global Monsoons: Current Status and Future Perspectives

The global monsoon system, encompassing the Asian-Australian, African, and American monsoons, sustains two-thirds of the world’s population by regulating water resources and agriculture. Monsoon anomalies pose severe risks, including floods and droughts. Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms. Observational data reveal a 20th-century shift: increased rainfall pre-1950s, followed by aridification and partial recovery post-1980s, driven by both internal variability (e.g., Atlantic Multidecadal Oscillation) and external forcings (greenhouse gases, aerosols), while ENSO drives interannual variability through ocean-atmosphere interactions. Future projections under greenhouse forcing suggest long-term monsoon intensification, though regional disparities and model uncertainties persist. Models indicate robust trends but struggle to quantify extremes, where thermodynamic effects (warming-induced moisture rise) uniformly boost heavy rainfall, while dynamical shifts (circulation changes) create spatial heterogeneity. Volcanic eruptions and proposed solar radiation modification (SRM) further complicate predictions: tropical eruptions suppress monsoons, whereas high-latitude events alter cross-equatorial flows, highlighting unresolved feedbacks. The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons. Critical challenges remain. Model biases and sparse 20th-century observational data hinder accurate attribution. The interplay between natural variability and anthropogenic forcings, along with nonlinear extreme precipitation risks under warming, demands deeper mechanistic insights. Additionally, SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation. Addressing these gaps necessitates enhanced observational networks, refined climate models, and interdisciplinary efforts to disentangle multiscale drivers, ultimately improving resilience strategies for monsoon-dependent regions.

climate extreme events↗
DOE OSTI2026

Measurement of the Alfvén Wave Parametric Decay Instability Growth Rate

Alfvén waves, a fundamental mode of magnetized plasmas, are ubiquitous in space and laboratory plasmas. The nonlinear behavior of these modes is thought to play a key role in important problems in space plasma, such as the heating of the solar corona and solar wind turbulence. In particular, theoretical predictions show that these Alfvén waves may be unstable to various parametric instabilities, but space observations of these processes are limited. We demonstrate the first measurement of the Alfvén wave parametric decay instability (PDI) growth rate. Experiments are conducted on the Large Plasma Device at UCLA in which a high amplitude 𝛿⁢𝐵/𝐵 0 ∼ 0.7% pump Alfvén wave is launched from one end of the device and a smaller seed Alfvén wave is launched from the other side. When the frequency of the seed wave is chosen to match the backward wave expected from PDI, damping of the seed wave is reduced. We compare this reduction in damping to the theoretically expected PDI growth rate while accounting for acoustic mode damping. Results show agreement between measurements and theoretical predictions. As a result, this not only provides critical validation for PDI theories and simulations that could help interpret future space observations but also suggests a new way of studying similar nonlinear wave phenomena.

Alfvén waves↗
DOE OSTI2020

Evaluating the Potential for Tidal Phase Diversity to Produce Smoother Power Profiles

Although tidal energy conversion technologies are not yet commercially available or cost-competitive with other renewable energy technologies like wind turbines and solar panels, tides are a highly predictable resource. Tidal energy’s predictability indicates that the resource could introduce less volatility into balancing the electric grid when compared to other renewables, a fundamentally desirable attribute for the electric system. More specifically, tidal energy resources are unique in that they have the potential to produce relatively smoother power profiles over time through aggregation. In order to generate smooth power profiles from tidal resources, sufficient complexity within the timing of tides is necessary within electrical proximity. This study evaluates the concept of aggregating diverse tides for the purpose of reducing periods of no and low energy production and creating smoother power profiles in regions around Alaska and Washington by calculating cross-correlations of tidal current velocity time series. Ultimately, study results show limited potential to exploit the resources for this purpose and describe the institutional mechanisms necessary to realize the benefits in practice.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Model, Design, and Control for Power Conversion in Wave Energy Converter System

Wave energy, if all been harvested along the U.S. coastline, can power around 65% of the energy consumption in U.S.. Comparing to other renewable energy sources like solar or wind, ocean wave can provide up to 90% of steady uptime. With the high energy density (2-3 kW/m 2 ), it can produce more energy with the same amount of installation area comparing to the energy density of wind turbine (0.6 kW/m 2 ) and solar panel(0.2 kW/m 2 ). The predictability of wave provides advantages like planning installation, power dispatching, and maintenance activities. Although with all these advantages, wave energy converter system is still in the research stage due to its high system cost per electricity production. One of the challenges that need to be solved is the irregularity from the wave motion that leads to high instantaneous peak power into the wave energy converter, which usually reaches up to 10 - 20 times of the average power. The high peak power will not only bring high mechanical/electrical stress but also result in an overrating design of the components in the system. Another obstacle that prevents the wave energy system from moving forward is the high testing cost from the validations in wave-energy-test sites or tank-test sites. A high-fidelity multi-disciplinary system model, including hydrodynamics, mechanical dynamics, electromagnetics, and power electronics, is needed to predict the behavior of the system and reduce the cost of design validation.

16 TIDAL AND WAVE POWER↗