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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Advancing Clean Energy Equity

This year’s Financial Innovations Roundtable (June 16-17, 2022) focused on advancing clean energy equity and was co-hosted by the University of New Hampshire's Carsey School of Public Policy and the Federal Reserve Bank of New York. Clean energy technologies are better than ever, with costs continuing to decline. Yet the low-income and under-resourced communities – particularly communities of color, Native communities, and other traditionally marginalized populations – that are disproportionately impacted by climate and severe weather-related events lag in clean energy investments. Community Development Financial Institutions (CDFIs) have a long track record of providing access to capital to low- and moderate-income communities nationwide. Green Banks, established at state and local levels, use innovative financing to attract private capital and incentivize investments in clean and renewable energy. Together, the nation's network of more than 1,300 CDFIs and 21 Green Banks have the financing expertise and deep market understanding and relationships to finance a transition to clean energy. This event explored how Green Banks and CDFIs can funnel creditworthy projects to market and efficiently raise capital for them. Building on the Carsey School White Paper, Clean Energy Project Development for Low-Income Communities: Strengthening the Ecosystem for Delivering Solar Energy and Deep Efficiency Retrofits (Hangen, 2022), the FIR sought to identify options and create opportunities for Green Banks, CDFIs, and impact investors to collaborate in offering a range of products, approaches, and tools to better serve communities and individuals who have thus far been left out of the transition to clean energy. The event had 101 participants from a variety of sectors including CDFIs, Green Banks, mission-driven clean energy organizations, government agencies, banks, and impact investment professionals.

14 SOLAR ENERGY↗
DOE OSTI2020

Spin excitations in the frustrated triangular lattice antiferromagnet NaYbO 2

In this work, we present a neutron scattering-based study of magnetic excitations and magnetic order in NaYbO 2 under the application of an external magnetic field. The crystal electric field-split J = 7=2 multiplet structure is determined, revealing a mixed |m z $\rangle$ ground state doublet and is consistent with a recent report Ding et al. Our measurements further suggest signatures of exchange effects in the crystal field spectrum, manifested by a small splitting in energy of the transition into the first excited doublet. The field-dependence of the low-energy magnetic excitations across the transition from the quantum disordered ground state into the fluctuation driven ordered regime is analyzed. Signs of a first-order phase transition into a noncollinear ordered state are revealed at the upper-field phase boundary of the ordered regime, and higher order magnon scattering, suggestive of strong magnon-magnon interactions, is resolved within the previously reported up-up-down phase. Our results reveal a complex phase diagram of field-induced order and spin excitations within NaYbO 2 and demonstrate the dominant role of quantum fluctuations cross a broad range of fields within its interlayer frustrated triangular lattice.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Employment access assessed using the mobility energy productivity (MEP) metric

Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Resilience framework and metrics for energy master planning of communities

Changes in the nature, intensity, and frequency of climate-related extreme events have imposed a higher risk of failure on energy systems, especially those at the community level. Furthermore, the evolving energy demand patterns and transition towards renewable and localised energy supply can affect energy system resilience. How can an energy system be planned and reconfigured to address these challenges without compromising the system's resilience against chronic stresses and extreme events? Unlike energy system reliability, resilience is neither a common nor an explicit consideration in energy master planning at the community level. In addition, there is no universally agreed-upon method or metrics for measuring or estimating resilience and defining mitigation strategies. This paper introduces a multi-layered energy resilience framework and set of metrics for energy master planning of communities, including the new generation of district energy systems. The potential system disturbances and their short and long-term impacts on various components of the energy system are discussed for commonly expected and extreme events. Three layers of energy resilience are discussed: engineering-designed resilience, operational resilience, and community-societal resilience. A starting set of energy resilience metrics to support engineering design and energy master planning for communities is identified. Implications for future research and practice are noted.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Rare earth element enrichment in coal and coal-adjacent strata of the Uinta Region, Utah and Colorado

This study aims to quantify rare earth element enrichment within coal and coal-adjacent strata in the Uinta Region of central Utah and western Colorado. Rare earth elements are a subset of critical minerals as defined by the U.S. Geological Survey. These elements are used for a wide variety of applications, including renewable energy technology in the transition toward carbon-neutral energy. While rare earth element enrichment has been associated with Appalachian coals, there has been a more limited evaluation of western U.S. coals. Here, samples from six active mines, four idle/historical mines, four mine waste piles, and seven stratigraphically complete cores within the Uinta Region were geochemically evaluated using portable X-ray fluorescence ( n = 3,113) and inductively coupled plasma-mass spectrometry ( n = 145) elemental analytical methods. Results suggest that 24%–45% of stratigraphically coal-adjacent carbonaceous shale and siltstone units show rare earth element enrichment (>200 ppm), as do 100% of sampled igneous material. A small subset (5%–8%) of coal samples display rare earth element enrichment, specifically in cases containing volcanic ash. This study proposes two multi-step depositional and diagenetic models to explain the enrichment process, requiring the emplacement and mobilization of rare earth element source material due to hydrothermal and other external influences. Historical geochemical evaluations of Uinta Region coal and coal-adjacent data are sparse, emphasizing the statistical significance of this research. These results support the utilization of active mines and coal processing waste piles for the future of domestic rare earth element extraction, offering economic and environmental solutions to pressing global demands.

Coe, Haley H.↗
DOE OSTI2020

Machine learning defect properties in Cd-based chalcogenides

Impurity energy levels in the band gap can have serious consequences for a semiconductor's performance as a photovoltaic absorber. Data-driven approaches can help accelerate the prediction of point defect properties in common semiconductors, and thus lead to the identification of potential deep lying impurity states. In this work, we use density functional theory (DFT) to compute defect formation energies and charge transition levels of hundreds of impurities in CdX chalcogenide compounds, where X = Te, Se or S. We apply machine learning techniques on the DFT data and develop on-demand predictive models for the formation energy and relevant transition levels of any impurity atom in any site. The trained ML models are general and accurate enough to predict the properties of any possible point defects in any Cd-based chalcogenide, as we prove by testing on a few selected defects in mixed chalcogen compounds CdTe 0.5 Se 0.5 and CdSe 0.5 S 0.5 . The ML framework used in this work can be extended to any class of semiconductors.

density functional theory↗
DOE OSTI2023

Ten questions concerning reinforcement learning for building energy management

As buildings account for approximately 40% of global energy consumption and associated greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The increased integration of variable energy sources, such as renewables, introduces uncertainties and unprecedented flexibilities, necessitating buildings to adapt their energy demand to enhance grid resiliency. Consequently, buildings must transition from passive energy consumers to active grid assets, providing demand flexibility and energy elasticity while maintaining occupant comfort and health. This fundamental shift demands advanced optimal control methods to manage escalating energy demand and avert power outages. Reinforcement learning (RL) emerges as a promising method to address these challenges. Here, in this paper, we explore ten questions related to the application of RL in buildings, specifically targeting flexible energy management. We consider the growing availability of data, advancements in machine learning algorithms, open-source tools, and the practical deployment aspects associated with software and hardware requirements. Our objective is to deliver a comprehensive introduction to RL, present an overview of existing research and accomplishments, underscore the challenges and opportunities, and propose potential future research directions to expedite the adoption of RL for building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Influence of Surface Defects on WO 3 Photoelectrodes for Catalyzing Chloride Oxidation in Water

Tungsten oxide (WO 3 ) is an n-type semiconductor due to oxygen vacancies (□ O •• in Kroger-Vink notation) or surface protonation as H x WO 3 . It is one of the few acid-stable oxides under large positive bias, which makes WO 3 ideal for interrogating the mechanism of the chloride oxidation reaction (COR). The large, positive valence band edge of ∼3 eV provides the overpotential necessary to carry out the COR, but the reaction competes with the oxygen-evolution reaction in water. The □ O •• defect density can be controlled by the atmosphere under which the material is annealed, so WO 3 films were prepared by a spin-coating method from an ammonium metatungstate precursor annealed at 500 °C under air, flowing O 2 , and flowing argon. Annealing the films in a flowing O 2 atmosphere hinders the formation of □ O ••, and annealing in Ar leads to greater surface W 6+ , likely due to expelling intercalated H + . The saturated photocurrent density (j ph ) is highest in films with the greatest concentration of W 5+ and greatest concentration of oxide defects: (0.66 mA/cm 2 annealed in air, 0.58 mA/cm 2 annealed in Ar, and 0.49 mA/cm 2 annealed in O 2 , reported at 1.5 V vs Ag/AgCl, pH 3 (before the onset of a dark reaction). The defect concentrations are determined by X-ray photoelectron spectroscopy. In all cases the Faradaic efficiency for the COR is near unity. Finally, we demonstrate that W 5d states can be probed by ligand K-edge X-ray absorption near-edge spectroscopy via pre-edge (Cl 1s → W 5d) transitions, lower in energy than the ligand-centered (Cl 1s → 4p) transition. We use this analysis to show the presence of W─Cl covalent bonds on the WO 3 films post-COR, corroborated by DFT calculations. Furthermore, this result stands in contrast to the commonly assumed mechanistic proposal invoking outer-sphere electron transfer to a physisorbed chloride ion.

Cl K-edge↗
DOE OSTI2021

Quantum states of a skyrmion in a two-dimensional antiferromagnet

Quantum states of a skyrmion in a two-dimensional antiferromagnetic lattice are obtained by quantizing the scaling parameter of Belavin-Polyakov model. Skyrmion classical collapse due to violation of the translational invariance of the continuous spin-field model by the lattice is replaced in quantum mechanics by transitions between discrete energy levels of the skyrmion. Here, the rates of transitions due to emission of magnons are computed. Ways of detecting quantization of skyrmion states are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanisms of Low-Level Jet Formation in the U.S. Mid-Atlantic Offshore

Low level jets (LLJs) in the atmosphere exhibit a local windspeed maximum inthe boundary layer and are commonly observed both over land and in coastal environments. Because LLJs present strong positive shear beneath the maximum (or "jet nose") and negative shear above the nose, they pose a challenge to future offshore wind technology through their impacts on turbine performance and wakes. Summertime LLJs in the Great Plains have been attributed to frictional decoupling triggering an inertial oscillation, whilecoastal LLJs in California or the North Sea have additional driving mechanisms such as baroclinic forcing. By comparison, LLJs in the coastal US Mid-Atlantic have received less attention, with conflicting evidence about the mechanism that triggers these high shear events. Motivated by future wind energy development in the region, this work elucidates the atmospheric mechanisms of LLJ formation in the US Mid-Atlantic. Using observational data from two floating LiDAR buoys deployed bythe New York State Energy Research and Development Authority in the NY Bight, we identify four sustained LLJ events whose windspeeds and directions are well predicted by a WRF simulation (Weather Research and Forecasting Model). From analysis of the WRF data, we find that the four case studies provide evidence of concurrent inertial oscillation, reduced vertical mixing, and baroclinicity. In addition, we use simple atmospheric dynamics and a single-column-model to compare the relative contribution of each of these mechanisms to triggering the LLJ. By improving understanding and predictability of coastal mid-Atlantic LLJs, this work reduces uncertaintiesof wind energy deployment in the region, aiding the US's transition toward renewable energy.

atmospheric boundary layers↗
DOE OSTI2020

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Photoluminescence study of solution-deposited Cu 2 BaSnS 4 thin films

To experimentally identify the character of radiative transitions in trigonal Cu 2 BaSnS 4 , we conduct temperature and excitation intensity dependent photoluminescence (PL) measurements in the temperature range of 15–300 K. The low-temperature near band edge PL spectrum is interpreted as the free exciton at 2.11 eV and the bound exciton at 2.08 eV, coupled with associated phonon-assisted transitions. In the low energy region, we assign the dominant defect emission at 1.96 eV to donor–acceptor-pair recombination and the weak broad emission at 1.6 eV to the free-to-bound transition. The activation energies and temperature shift for the radiative transitions are determined and discussed. Above 90 K, the free exciton recombination becomes the dominant radiative transition, with its energy shift mainly governed by the contribution of optical phonons.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Floating photovoltaic power plants: A review of energy yield, reliability, and operation and maintenance

Photovoltaic (PV) systems are essential for the transition to sustainable energy, reducing fossil fuel dependence and mitigating climate change. Although PV requires minimal land area — PV can meet the European Union's energy needs using only 0.26% of its land — space for deployment is often scarce in densely populated regions. Floating photovoltaics (FPV) offer an effective solution to land-use challenges by installing PV systems on floating structures in water bodies. FPV is a growing niche within PV with a cumulative installed capacity reaching 7.7 GW globally by 2023. Almost 90% of the installed FPV capacity is in Asia, with close to 50% of in China alone, while the Netherlands and France are the largest markets outside Asia. FPV shows strong potential to support climate targets, but still faces challenges like regulatory barriers, cost competitiveness compared to ground-based PV (GPV), and uncertainties about environmental impacts and system reliability. FPV systems are currently installed mainly on sheltered inland waters, such as quarry lakes, irrigation ponds and reservoirs. FPV technical standards are still being developed. Guidelines have been published by the World Bank, DNV, and Solar Power Europe, and emerging national standards from South Korea, China, and Singapore address design, components, and safety. The International Electrotechnical Commission (IEC) is working on formal standards for floats, mooring systems, and electrical connectors. However, the published best practices lack quantitative guidance for yield modelling and reliability, which this report aims to address. It provides data-driven insights, models, and parameters essential for accurate energy yield, reliability, and maintenance predictions over FPV systems' lifetimes.

14 SOLAR ENERGY↗
DOE OSTI2021

Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service

Affordable public transit services are crucial for communities since they enable residents to access employment, education, and other services. Unfortunately, transit services that provide wide coverage tend to suffer from relatively low utilization, which results in high fuel usage per passenger per mile, leading to high operating costs and environmental impact. Electric vehicles (EVs) can reduce energy costs and environmental impact, but most public transit agencies have to employ them in combination with conventional, internal-combustion engine vehicles due to the high upfront costs of EVs. To make the best use of such a mixed fleet of vehicles, transit agencies need to optimize route assignments and charging schedules, which presents a challenging problem for large transit networks. We introduce a novel problem formulation to minimize fuel and electricity use by assigning vehicles to transit trips and scheduling them for charging, while serving an existing fixed-route transit schedule. We present an integer program for optimal assignment and scheduling, and we propose polynomial-time heuristic and meta-heuristic algorithms for larger networks. We evaluate our algorithms on the public transit service of Chattanooga, TN using operational data collected from transit vehicles. Our results show that the proposed algorithms are scalable and can reduce energy use and, hence, environmental impact and operational costs. For Chattanooga, the proposed algorithms can save $145,635 in energy costs and 576.7 metric tons of CO 2 emission annually.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Thermodynamics of the Metal Carbonates and Bicarbonates of Mn, Co, Ni, Cu, and Zn Relevant to Mineral Energetics

The gas phase heats of formation of ground-state MCO 3 , M(HCO 3 ) 2 , and M(HCO 3 )(OH), where M = Mn, Co, Ni, Cu, and Zn, have been predicted using the correlated molecular orbital theory at the CCSD(T) level extrapolated to the complete basis set limit using the Feller–Peterson–Dixon (FPD) approach. Cohesive energies of the carbonates were predicted based on the calculated gas phase and experimental solid heats of formation. Coulombic dissociation energies (CDEs) between metal cations and anions show a near-linear correlation with Shannon metal cation atomic radii, yet no correlation is found with the hardness of these cations. The total reaction dissociation energies (TRDEs) of transition metals are higher than their CDEs for the di-bicarbonates, in contrast to those for Mg and Ca based on our prior work. In addition to differences in the energies needed to prepare the transition metal dications, electron donation from the ligands to the 3d orbitals of open-shell transition metal dications from lone pairs of adjacent O atoms also plays a role. No electron donation from the ligands to the fully occupied 3d orbitals of Zn and Cd was found. Decomposition energies for generating MO, CO 2 , and/or H 2 O were calculated. Gas phase metal exchange energies only partially correlate with the electrochemical series for M(s) → M 2+( aq). The FPD heats of formation were used to benchmark a range of density functional theory exchange–correlation functionals, including those commonly used in solid-state mineral calculations. None of the functionals provided chemical accuracy agreement (±1 kcal/mol) with the FPD results. So, the best agreement with the FPD results is predicted for the $\tau$-HCTH functional with an average unsigned error of 8.3 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Trace gas detection with 2-photon, 2-color, cavity ring-down spectroscopy

In one aspect, a method of detecting a trace gas is disclosed. The method includes containing the trace gas in an optical cavity. The method further includes injecting a first laser light from a first laser into the optical cavity causing the trace gas to transition from an energy state lower that a first excited energy state to the first excited energy state, and injecting a second laser light from a second laser into the optical cavity causing the trace gas to transition from the first excited energy state to a second excited energy state. The method includes measuring, by a detector, a first cavity ringdown intensity as a function of time after turning off the second laser with the first laser on, and a second cavity ringdown intensity as a function of time after turning off the second laser with the first laser off.

McCartt, Daniel↗
DOE OSTI2024

Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. To evaluate and quantify outcomes, the research team utilizes the mobility energy productivity (MEP) metric, which is a holistic accessibility measure, to analyze and compare the mobility of various transportation modes in Arlington, Texas. The MEP tool is applied to the ODT system in Arlington, Texas, as well as to five existing transportation modes (driving, transportation network company, transit, biking, and walking). Six ODT scenarios are also analyzed and compared. The analysis is focused on the opportunities that an ODT system presents for transportation disadvantaged communities (DACs) with low rates of car ownership. Although driving received the highest MEP score—a finding typical for a U.S.A. city— the results for the ODT system reveal that it serves those in DACs effectively, helping to achieve an equity design goal. ODT improved the average MEP score across the service area by 83% when considering only accessible, nonprivate vehicle modes (biking, transit, and ODT). For the ODT scenarios, decreasing the wait time by 50% compared with the baseline scenario led to a nearly 160% increase in the MEP score, whereas increasing the ODT travel speed by 21% led to an 80% improvement in the MEP score. As analyzed through the MEP tool, here this paper demonstrates how ODT can enhance mobility, particularly for DACs. The results of an MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems across a service area.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. In order to evaluate and quantify outcomes, we use the Mobility Energy Productivity (MEP) metric, a holistic tool to analyze, quantify, and compare the mobility and accessibility of various transportation modes in a specific area. In this paper, we apply the MEP tool to the ODT system in Arlington, Texas, and compare the results among four existing transportation modes (drive, transportation network company, transit, and bike) and five additional ODT scenarios. We focus our analysis on the opportunities that an ODT system presents such as serving disadvantages communities. While the results in Arlington show the typical U.S. pattern of driving receiving the highest MEP score, the ODT system best serves those in disadvantaged communities, helping with an equity design goal. ODT improved the average MEP score across the service area by 100% when considering only non-private vehicle modes (bike, transit, and ODT). For the ODT scenarios, decreasing the wait time 50% compared to the baseline scenario led to a nearly 160% increase in MEP score, while increasing the ODT travel speed by 21% led to an 80% improvement in MEP score. The decreased wait time scenario had the highest MEP score out of the six ODT scenarios. This paper demonstrates how ODT can enhance mobility, particularly for disadvantaged communities. The results of a MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems in subareas across a service area.

accessibility↗