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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 955 records · Page 53

Conversion of food waste to renewable energy: A techno-economic and environmental assessment

Increasing quantities of food waste have become a concern due to high disposal costs in landfills and high greenhouse gas emissions. With this increase in food waste generation, there is also an increasing demand for renewable natural gas to supplement traditional fossil fuel combustion and offset the impacts of climate change. Collecting food waste from landfills and turning it into renewable natural gas using anaerobic digestion could be a win-win option for both food waste disposal and renewable energy production. While some literature exists on the energy potential, economic feasibility, and environmental benefit of food waste disposal via anaerobic digestion, no existing study simultaneously evaluates the energy, economic and environmental effect of food waste to renewable energy via anaerobic digestion, especially on a plant and city scale. Further, this study is focused on the techno-economic and environmental assessment of food waste to energy via anaerobic digestion in order to fill this gap. Four anaerobic digestion pathways are considered in this study: flare, pipeline natural gas, combined heat and power, and combined cycle for efficient power generation. Using a city of 1M people the results show that renewable natural gas from food waste could supply the natural gas usage for 1.9% of residential use, 2.7% of commercial use, 1.1% of industrial use, 167.5% of the compressed natural gas vehicle fleet, 0.7% of electric power generation, or 2.5% of industrial high-temperature heating processes. All pathways except pipeline natural gas will have a positive net present value in the baseline scenario, and the pipeline natural gas pathway will become economically viable with a net present value of 31 USD/t of food waste with renewable energy credits. Lastly, all of the pathways achieve negative greenhouse gas emissions, which indicates that anaerobic digestion is a more environmentally friendly method for the handling of food waste than landfills.

03 NATURAL GAS↗

System Modeling of the HTTR and Economic Dispatch Model of the Secondary System

High Temperature Gas-cooled Reactors (HTGRs) can be used for the generation of electricity and their process heat can be used to improve the efficiency of chemical processes such as hydrogen production. The JAEA-operated High-Temperature engineering Test Reactor (HTTR-GT/H2) is exploring using the reactor for electricity and hydrogen production. A RELAP5-3D model of the HTTR-GT/H2 secondary system has been developed using design information. The various components and heat exchangers in the secondary system were modeled and results were compared to the design conditions. The results for the sole-power generation mode were shown to fit the design conditions very well. The largest temperature difference was on the order of 7 K, and the largest pressure difference was on the order of 0.05 MPa. The results for the hydrogen cogeneration mode did not match the design conditions nearly as well. The largest temperature difference was about 39 K and the largest pressure difference was about 0.27 MPa at the compressor outlet. The larger differences for the hydrogen cogeneration mode are attributed to the various complex components and the flow being split in the secondary loop. A transient reduction in heat removal capability of the secondary system was investigated. Reactor temperatures are anticipated to rise as a result. The core reactivity response due to this increase in temperature is investigated and is expected to add negative reactivity to the reactor. An economic dispatch model was developed for a nuclear-driven iodine-sulfur cycle system to determine hydrogen sale prices that would make such a system profitable. The study focuses on the development of the economic model and the role that input data plays on final calculated values. It was found that the input electricity prices, whether using historical data or a host of synthetic time histories, produce significantly different breakeven hydrogen sale prices. As such, great care should be used in these economic dispatch analyses to select reasonable input assumptions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Remote Sensing of Electric Fields Observed Within Winter Precipitation During the 2020 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) Field Campaign

Aircraft electric fields from NASA's Lightning Instrument Package (LIP) were coupled with other airborne and ground-based, and in situ measurements to understand electrification in winter clouds that did not produce lightning. The measurements were made during seven research flights by a NASA ER-2 during the 2020 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Observed total electric field magnitudes were as high as 80 V m -1 and variability in the electric field was observed along the flight path of the ER-2, indicating horizontal and/or vertical inhomogeneity in the cloud's electrical structure. X-band airborne radar data indicated 20-dBZ echo tops above 5 km in regions where electrification exceeded 10 V m -1 . In these regions, 85-GHz brightness temperatures (TB) from an airborne radiometer were lower than 265 K, with the lowest T B (~210 K) associated with ice scattering collocated with the strongest electric fields. In situ microphysical measurements from the NASA P-3 aircraft on February 7 indicated that regions near strong electric field contained supercooled water, rimed ice hydrometeors, ice water p- content as high as 1 g m -3 , liquid water content as high as 0.15 g m -3 , and supersaturation as high as 3.5%. Furthermore, these observations support the role of mixed phase microphysics in the generation of electric fields in clouds. In three case studies, ground based S-band polarimetric radar observed depolarization streaks in differential reflectivity near areas where the strongest electrification was observed. This observation reinforces the utility of depolarization streaks to identify areas of electrification prior to lightning occurrence.

54 ENVIRONMENTAL SCIENCES↗

Detection and imaging of electric fields, using polarized neutrons

A method and corresponding apparatus are provided for measuring neutron spin precession in an electric field with high sensitivity suitable for practical applications in non-destructive testing, imaging, and the like. Production of a neutron beam with a polarization vector P is followed by transmitting the spin-polarized neutron beam through a sample region in which there is a target generating an electric field, polarization-analyzing the transmitted neutron beam with an analyzing direction orthogonal to P, detecting an intensity of the polarization-analyzed neutron beam; and mapping the detected neutron-beam intensity to a field-strength value for the target electric field.

Jau, Yuan-Yu↗

Built-in electric field control of magnetic coupling in van der Waals semiconductors

Electrical control of magnetism in a two-dimensional (2D) semiconductor is of great interest for emerging nanoscale low-dissipation spintronic devices. Here, we propose a general approach of tuning magnetic coupling and anisotropy of a van der Waals (vdW) 2D magnetic semiconductor via a built-in electric field generated by the adsorption of superatomic ions. Using first-principles calculations, we predict a significant enhancement of ferromagnetic coupling and a great change of magnetic anisotropy in 2D semiconductors when they are sandwiched between superatomic cations and anions. The magnetic coupling is directly affected by the built-in electric field, which lifts the energy levels of mediated ligands' orbitals and enhances the superexchange interactions. Finally, these findings will be of interest for ionic gating controlled ferromagnets and magnetoelectronics based on vdW 2D semiconductors.

2-dimensional systems↗

Carrier density oscillation in the photoexcited semiconductor

Abstract The perturbation of a semiconductor from the thermodynamic equilibrium often leads to the display of non-linear dynamics and formation of spatiotemporal patterns due to the spontaneous generation of competing processes. Here, we use scanning ultrafast electron microscopy to show that the transport of hot carriers in the strongly excited semiconductor slows down by turning into an oscillatory process; this is evidenced by the expansions and contractions in the second moment of the distribution. We attribute such a response to the electric field generated by the spatial separation of photo-excited electrons and holes under intrinsic and photo-induced fields; we then introduce a transport model that mimics the experimental observation. Our finding provides a direct imaging evidence for the electrostatic oscillation of hot carriers in the highly excited semiconductor and offers new insights into their dynamics in space and time.

Physics↗

eGridGPT: Trustworthy AI in the Control Room

This report outlines the synergy between human decision making and generative artificial intelligence (GenAI), where GenAI supports power system operators by analyzing procedures, suggesting actions, simulating scenarios with physics-based digital twins, and recommending optimal decisions. This report is the first research effort to apply large language models (LLMs), a type of GenAI, in the power grid control room. The authors describe the Electric Grid Generative Pretrained Transformer (eGridGPT), an LLM that virtually assists system operators. Developed with cybersecurity and regulatory requirements in mind, eGridGPT represents an opportunity to responsibly evolve control room technologies to meet the needs of a rapidly changing grid. As an innovative concept, eGridGPT seeks to spearhead productive discussions about the advanced technologies in the control room of the future amid the transition to clean energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Room-Temperature Eutectic Synthesis for Upcycling of Cathode Materials

Ni-rich LiNixMnyCo1−x−yO2 (NMC) materials have been adopted in a range of applications, including electric vehicles. The recycled NMC material from a spent cell would be much more valuable if it could be upgraded to a Ni-rich, more energy-dense version of the material. This work demonstrates a simple, inexpensive, and facile method to upcycle LiNi1/3Mn1/3Co1/3O2 (NMC111, 160 mAh∙g−1), a cathode used in early generations of electric vehicle batteries, to LiNi0.8Mn0.1Co0.1O2 (NMC811, 190 mAh∙g−1), a more energy-dense cathode material. In this study, a preliminary investigation into a room-temperature eutectic synthesis of NMC811 is performed using NMC111, LiOH, and nickel nitrate as precursors. The synthesized material showed the desired crystal structure and stoichiometry, though the cycle life and Li diffusion coefficient need improvement when compared to commercially available NMC811. This study demonstrates an interesting proof of concept of the room-temperature eutectic synthesis process for LIB cathodes and could be improved by tuning the synthesis conditions.

lithium-ion battery↗

Can Wholesale Electricity Markets Achieve Resource Adequacy and High Clean Energy Generation Targets in the Presence of Self-Interested Actors?

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗

Passive deconfinement of runaway electrons using an in-vessel helical coil

A helical coil designed to passively generate non-axisymmetric fields during a plasma disruption is shown (via electromagnetic analysis, linear MHD modeling, and relativistic drift orbit tracing) to be effective at deconfining runaway electrons (REs) on a time scale significantly faster than the plasma current quench. Magnetic equilibria from DIII-D RE-producing scenarios are used to calculate the toroidal electric field generated during the current quench phase of a disruption, which in turn drives current in the proposed n = 1 in-vessel helical coil, without the need for any external power supplies or disruption detection or prediction techniques. Simulations of the plasma evolution using the TokSys GS Evolve code predict the inductive coupling of coil currents up to 12% of the pre-disruption plasma current into the helical coil. The coil geometry is parametrically varied to maximize both the non-resonant and resonant components of the 3D magnetic perturbation, resulting in δB/B ≈ 10 –2 and a vacuumisland overlapwidth of up to 0.7ψ N . The REORBIT module of the MARS-F code is used to model the full non-axisymmetric magnetic field and trace RE drift orbits to determine the effect on RE deconfinement, with up to 70% of the RE orbits lost after 0.2 ms. A two-stage evolution of the RE orbit loss fraction is observed to be caused by resonant trapping between multiple magnetic island chains. Finally, electromagnetic and thermal stresses on the coil are calculated to be within operational limits for installation in DIII-D, and scale favorably to a reactor-size device. Furthermore, these findings motivate future experimental study of the helical coil concept in DIII-D or other tokamaks.

3D coil↗

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and inperson interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

marine renewable energy, powering the blue economy↗

Vector Electrometry in a Wide-Gap-Semiconductor Device Using a Spin-Ensemble Quantum Sensor

Nitrogen-vacancy (N-V) centers in diamond work as a quantum electrometer. Using an ensemble state of N-V centers, we propose vector electrometry and demonstrate measurements in a diamond electronic device. A transverse electric field applied to the N-V axis under a high voltage is measured, while applying a transverse magnetic field. The response of the energy-level shift against the electric field is significantly enhanced compared with that against an axial magnetic field. Repeating the measurement of the transverse electric field for multiple N-V axes, our team obtains the components of the electric field generated in the device.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Benefits and risks of lead halide perovskite photovoltaics

Photovoltaics (PV) do not emit anything during operation, but, over their life-cycle, emissions are generated from the use of fossil-fuels in the extraction and production of materials and in the manufacturing and installation of PV components and systems. Nonetheless, these emissions are always very small compared to those from conventional combustion-based generators of electricity. The case for CO2 emissions has been well documented; over their lifetime, they range from 10 g CO2-eq / kWh for CdTe PV system installed in high-irradiation (2300 kWh/(m2-yr) locations to 80 g CO2-eq / kWh for Chinese single-crystalline silicon PV systems installed in low-irradiation (1000 kWh/(m2-yr) locations,1 compared to ~1000 g CO2-eq/kWh for electricity from coal. However, in the case of the rapidly emerging lead halide perovskite PV (LHP-PV) technology, concerns are raised regarding the potential of emissions of lead from the life-cycles of LHP-PV, including at their end of life. This warranted an evaluation of lead emissions from PV and comparisons with emissions in other power generation life-cycles.

Perovskites, PV, Lead, Risks↗

Probing Plasmonic Near-Fields in Oxide-Modified Aluminum Nanocubes Using Photon-Induced Near-Field Electron Microscopy

Plasmonic nanoparticles generate strong electric fields near their surface upon photoexcitation, enabling applications in sensing, spectroscopy, and photocatalysis. Electron microscopy techniques – such as cathodoluminescence and electron energy loss spectroscopy – have been leveraged to produce nanoscale maps of localized surface plasmon (LSP) modes. More recently, photon-induced near-field electron microscopy (PINEM) has emerged as a powerful technique for imaging evanescent near-fields generated by ultrafast laser excitation. In this work, we employ PINEM within an ultrafast electron microscope, complemented by numerical calculations to investigate how optical polarization, surface modification, and light intensity affect the evanescent fields associated with LSPs on oxide-modified aluminum nanocubes. Polarization control of the incident light field enables spatial mapping of the nanocube’s LSPs at the single particle level. Systematic variation of the oxide layer thickness reveals that increased coating thickness correlates with a stronger PINEM signal and a greater energy gain of probing electrons. Additionally, higher light intensities at fixed polarization and oxide coating further amplify the PINEM signal. These findings demonstrate the utility of PINEM as a high-resolution technique for optical near-field imaging and spectroscopy of single plasmonic nanoparticles. The ability to probe single particle behavior offers new opportunities for advancing the design and characterization of nanophotonic and plasmonic materials.

PINEM↗

A computational pipeline to generate a synthetic dataset of metal ion sorption to oxides for AI/ML exploration

The charged mineral/electrolyte interfaces are ubiquitous in the surface and subsurface–including the surroundings of the geological disposal sites for radioactive waste. Therefore, understanding how ions interact with charged surfaces is critically important for predicting radionuclide mobility in the case of waste leakage. At present, the Surface Complexation Models (SCMs) are the most successful thermodynamic frameworks to describe ion retention by mineral surfaces. SCMs are interfacial speciation models that account for the effect of the electric field generated by charged surfaces on sorption equilibria. These models have been successfully used to analyze and interpret a broad range of experimental observations including potentiometric and electrokinetic titrations or spectroscopy. Unfortunately, many of the current procedures to solve and fit SCM to experimental data are not optimal, which leads to a non-transferable or non-unique description of interfacial electrostatics and consequently of the strength and extent of ion retention by mineral surfaces. Recent developments in Artificial Intelligence (AI) offer a new avenue to replace SCM solvers and fitting algorithms with trained AI surrogates. Unfortunately, there is a lack of a standardized dataset covering a wide range of SCM parameter values available for AI exploration and training–a gap filled by this study. Here, we described the computational pipeline to generate synthetic SCM data and discussed approaches to transform this dataset into AI-learnable input. First, we used this pipeline to generate a synthetic dataset of electrostatic properties for a broad range of the prototypical oxide/electrolyte interfaces. The next step is to extend this dataset to include complex radionuclide sorption and complexation, and finally, to provide trained AI architectures able to infer SCMs parameter values rapidly from experimental data. Here, we illustrated the AI-surrogate development using the ensemble learning algorithms, such as Random Forest and Gradient Boosting. These surrogate models allow a rapid prediction of the SCM model parameters, do not rely on an initial guess, and guarantee convergence in all cases.

Li, Chunhui↗

Volcanic electrification: recent advances and future perspectives

Abstract The electrification of volcanic plumes has been described intermittently since at least the time of Pliny the Younger and the 79 AD eruption of Vesuvius. Although sometimes disregarded in the past as secondary effects, recent work suggests that the electrical properties of volcanic plumes reveal intrinsic and otherwise inaccessible parameters of explosive eruptions. An increasing number of volcanic lightning studies across the last decade have shown that electrification is ubiquitous in volcanic plumes. Technological advances in engineering and numerical modelling, paired with close observation of recent eruptions and dedicated laboratory studies (shock-tube and current impulse experiments), show that charge generation and electrical activity are related to the physical, chemical, and dynamic processes underpinning the eruption itself. Refining our understanding of volcanic plume electrification will continue advancing the fundamental understanding of eruptive processes to improve volcano monitoring. Realizing this goal, however, requires an interdisciplinary approach at the intersection of volcanology, atmospheric science, atmospheric electricity, and engineering. Our paper summarizes the rapid and steady progress achieved in recent volcanic lightning research and provides a vision for future developments in this growing field.

58 GEOSCIENCES↗

Design and Performance of lithium-Ion Batteries for Achieving Electric Vehicle Takeoff, Flight, and Landing

Today, the burgeoning drive towards global urbanization with over half the earth’s population living in cities, has created major challenges with regards to intracity and intercity transit and mobility. This problem is compounded due to the fact that almost always urbanization and increase in standard of living drives individual automobile ownerships. Over 95% of automobiles are presently powered by some form of fossil fuel and as an unintended consequence, urban centers have also been centers for peak greenhouse gas emissions, a major contributor to global climate change. A revolutionary solution to this conundrum is flight capable electric automobiles or electric aerial vehicles that can tackle both urban mobility and climate change challenges. For such advanced electric platforms, energy storage and delivery component is the vital component towards achieving takeoff, flight, cruise, and landing. The requirements and duty cycle demands on the energy storage system is drastically different when compared to the performance metrics required for terrestrial electric vehicles. As the widely deployed lithium ion-based battery systems are often the primary go-to energy storage choice in electric vehicle related applications, it is imperative that performance metrics and specifications for such batteries towards areal electric vehicles need to be established. In this nascent field, there exists ample opportunities for battery material innovations, understanding degradation mechanism, battery design, development and deployment of battery control and management systems. Thus, this chapter comprehensively discusses battery requirements and identifies battery material chemistries suitable for handling aerial electric automobile duty cycles. The chapter also discusses the battery cell-level metrics pertaining to electrochemical, chemical, mechanical, and structural parameters. Furthermore, specific models for battery degradation, state of health (SOH), capacity and models for full cell performance and degradation are also discussed here. Finally, the chapter also discusses battery safety and future directions of batteries that would power these next generation urban electric aircrafts.

Amin, Ruhul↗