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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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Corn stover‐derived porous carbon for asymmetric supercapacitors
In this investigation, hydrothermal liquefaction‐derived hydrochar from pulverized corn stover (avg. particle size 1.12 mm and ash content 6.75 wt%) is chemically activated with aqueous KOH in the presence of Pluronic F127 surfactant and thermally treated further up to 800°C to generate porous carbon (POC) with higher specific surface area and porosity. POC obtained under different processing conditions is thoroughly characterized by Brunauer‐Emmett‐Teller surface area analyzer, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, and transmission electron microscopy. Metallic impurity present in POC is characterized by inductively coupled plasma mass spectrometry. Higher specific surface area POC is observed with the use of the surfactant during the activation process. Fully characterized POC is used with (Mn, Ti)‐mixed oxide electrode to fabricate asymmetric supercapacitor (ASC). Specific capacitance of ASC is measured by cyclic voltammetry (CV) technique using Gamry G‐300 potentiostat/galvanostat/ZRA. CV plots are obtained with different voltage scan rates whereas galvanostatic charge‐discharge plots are studied by varying the current density. Renewable corn stover‐derived POC prepared using Pluronic F127/KOH activation method is found to be highly suitable as an electrode material because of higher capacitance and electrochemical stability over 100 charging‐discharging cycles.
Sodium-ion Battery
Room temperature rechargeable sodium-ion batteries (NIBs) are one of the most promising candidates for large-scale energy storage and load leveling of renewable energy sources due to the abundance, low cost of Na resources, and their relatively high energy density. NIBs are primarily based on intercalation chemistry and are similar to Lithium-ion batteries (LIB). The rich knowledge gained in LIBs for the past 4 decades have accelerated the discovery and development of high energy density NIBs cathode and anode materials. The use of sustainable Na, Al current collector, and Mn and Fe based cathode materials is expected to stabilize the cost and demand for Li, Co, Ni and Cu.
Sorbent Regeneration via Radiofrequency-Assisted Dielectric Heating for Direct Air Capture of CO 2
Direct air capture (DAC) of CO 2 is a negative emission technology that utilizes sorbents requiring a regeneration step for repeated ab(/d)sorption–desorption cycles. Here we report an unconventional approach to desorb captured CO 2 from a porous sorbent using radiofrequency (RF) irradiation for dielectric heating and targeted energy transfer, thus enabling modularity and promoting renewable energy input. Regeneration of composites of functional ionic liquid and metal–organic framework with high CO 2 capacity and enhanced transport is demonstrated under conditions relevant to DAC. RF-assisted dielectric heating at the megahertz frequency range shows effective absorption of electromagnetic energy and consequently rapid release of the captured CO 2 .
Exploring Sources of Surface Bias in HRRR Using New York State Mesonet
In recent years, there has been increasing demand for applications of short-term forecasting of renewable energy potential and assessments of the likelihood of extreme weather events using the High-Resolution Rapid Refresh (HRRR) model. Examining the biases in the newest version of HRRR is necessary to promote further model development. Using data from one of the most comprehensive and dense monitoring networks, New York State Mesonet (NYSM), we evaluate the HRRR version 3 meteorological fields for an entire year. In this work, the land-atmosphere-cloud coupling system is evaluated as an integrated whole. We investigate the physical processes influencing the soil hydrological balance and the thermodynamic interactions, from surface fluxes up to the level of boundary layer convection from both temporal (seasonal and diurnal) and spatial perspectives. Results show that the model 2 m temperature and humidity biases are seasonally dependent, with warm and dry bias present during the warm season, and an extreme nocturnal cold bias in winter. The summer warm bias includes both a land-surface-induced bias and a cloud-induced bias. Inaccurate representation of energy partition and soil hydrological process across different land use types as well as a hydrological bias in describing spring snowmelt are identified as the main source of the land-surface-induced bias. A feedback loop linking cloud presence, flux changes, and temperature contributes to the cloud-induced bias. The positive solar radiation bias increases from clear sky to overcast sky conditions. The most significant bias occurs during overcast and thick cloud conditions associated with frontal passage and thunderstorms.
A Barrier-Certificated Reinforcement Learning Approach for Enhancing Power System Transient Stability
Increasing integration of renewable resources brings more flexibility and poses new challenges to modern power systems, leading to highly nonlinear and complex dynamics. Here, this paper aims to provide a general solution framework to traditional control problems, such as frequency control and voltage control, which attempt to maintain the stability of either synchronous generators-governed or inverter-governed systems when subjected to a disturbance and simultaneously guarantee operational constraints, providing a complete complement to existing works on control design. Building on reinforcement learning (RL) and control barrier functions, the framework includes two subsystems, i.e., a model-free controller and a barrier-certification system, which discover RL-based control actions and sequentially filter them using a barrier certificate to satisfy operational constraints. Calculating a barrier function is generally challenging for a complex power system. This is addressed by representing the barrier function using neural networks (NNs) and data-based approaches. An adaptive method is introduced to certify the neural barrier function that perseveres barrier conditions, which is more compatible with online implementation. The proposed framework synthesizes a stabilizing controller that satisfies predefined safety regions. The effectiveness of the proposed framework is demonstrated via several comparative case studies.
Using Machine Learning Tools to Predict Compressor Stall
Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.
Microstructure Scale Lithium-Ion Battery Modeling: Part III. When and Where Lithium Plating Occurs and its Correlation with the Electrode Microstructure
Li-ion battery performance and degradation are closely related to the cell’s underlying electrode microstructure. Electrode microstructures are typically characterized with volume-averaged properties that neglect the impact of local heterogeneities. However, local heterogeneities create hot spots that can trigger degradation onset. Herein, a microstructure scale electrochemical model is used to investigate the impact of microstructure heterogeneity on lithium plating. The model predicts lithium plating is not uniform, even when considering a relatively small portion of the electrode (a cross-sectional area of 154×144 µm 2 ), preferring to plate on larger particles as compared to smaller particles. While local heterogeneities control where plating occurs, the model predicts that volume-averaged properties control when plating occurs. Additionally, the model predicts that the active material specific surface area has a linear relationship with the plating onset. However, the linear relationship between increased active material surface area and delayed plating response appears to be sensitive to the microstructure feature used to increase the active interface area. Here, a comparative case-study is explored where the specific surface area is increased by either reducing the active material particle diameter, adding open-porosity cracks, or increasing the active material surface roughness. The model predicts that increasing the specific surface area by reducing the active material particle diameter is the most effective strategy for delaying lithium plating. At 6C, reducing particle size is shown to be 3 and 20 times more effective than, respectively, adding open-porosity cracks and increasing surface roughness. A dual-layer electrode architecture combining gradations both for average properties and uniformities is eventually proposed to improve homogeneous material utilization and reduce degradation at high charge rates.
Scaling Energy Efficient Retrofits for Small Commercial Apartment Buildings
With support from the U.S. Department of Energy’s (DOE) Building Technologies Office (BTO), the International Center for Appropriate and Sustainable Technology (ICAST) recently completed a three-year cooperative agreement to scale energy efficiency retrofits (EER) on small multifamily (MF) buildings. ICAST EER strategies ranged from low-hanging “direct install” of measures such as LED lighting, low-flow showerheads and aerators, and smart thermostats to major strategies such as HVAC replacement with high-efficiency boilers or heat pumps. As feasible, some projects also included the addition of renewable energy sources such as photo voltaic (PV) solar. When ICAST began the BTO project, it operated in two states and oversaw EER at approximately 80 MF buildings per year. With assistance from BTO, ICAST has grown significantly and now has staff in six states with MF EER projects in another seven, and performed EER on 956 MF buildings. ). ICAST was able to successfully execute this project by 1) Improving viability and efficiency of its processes, 2) Launching two new services and 3) Creating an affiliate program. For the most part, ICAST focused on a specific type of MF property: naturally occurring affordable housing (NOAH), because it is a significantly underserved market within the hard-to-serve MF market. NOAHs are typically smaller properties (5 to 64 units), owned by small organizations or individual investors looking for positive cash flow. ICAST believes the NOAH market can be successfully served with a one-stop-shop approach that makes it easy, hassle-free, and cost-effective for owners to acquire green upgrades for their property(ies). With the assistance of BTO funding, ICAST successfully used the cited EER methods and strategies to scale-up its OSS approach to service a greater number of MF housing and expand into new geographies. Additionally, support from BTO helped ICAST create self-sustaining programs which will not need to rely on on-going funding.
Sensors with Intelligent Measurement Platform and Low-cost Equipment (SIMPLE) for Monitoring and Control of Medium Voltage Distribution Systems with High Penetration of Intermittent Distributed Energy Resources
The primary focus of the SIMPLE project was to develop, commission, test and introduce intelligent voltage and current sensor platform with enhanced characteristics (accuracy, bandwidth and harmonic range) and high measurement granularity for medium voltage distribution system monitoring, protection and control. The enhancements incorporated existing (commercially available) sensors and made them suitable for applications such as voltage regulation, frequency support, fault detection and location, distribution system state estimation, power quality measurements and electrical distribution network topology processing. The development of the intelligent sensor platform was driven by the need for high-fidelity monitoring and control of medium voltage distribution feeder to enable higher penetration of renewable resources and microgrid operation.
New Approaches to Low-Cost Scalable Doping of Interdigitated back Contact Silicon Solar Cells (Final Report)
The goal of this project was to develop novel approaches to patterning of dopants in the rear fingers of interdigitated back contact (IBC) Si solar cells to reduce the cost of manufacturing this high-efficiency-potential cell architecture. The work throughout this project can be divided into four categories: (a) development of dopant patterning technique using laser scribed Si contacts masks that are mechanically aligned with ~10 μm resolution to the underlying Si substrate; (b) measuring dopant spreading profiles in the isolation region between n- and p-type dopant fingers during plasma-enhanced chemical vapor deposition (PECVD) of doped hydrogenated amorphous silicon (a-Si:H) via shadow masks, and dopant desorption and re-adsorption during high-temperature annealing; (c) understanding the role of dopant compensation on the shunt resistance in contaminated isolation regions through analysis of defect-enhanced compensation; and (d) simulation and fabrication of passivated two-sided grid and back-contact solar cells to demonstrate the use of direct dopant patterning in cell fabrication. For the passivated two-sided grid solar cells, masked deposition was used to demonstrate an improvement in the blue response of the cell by creating a shallow front emitter. During development of the masked PECVD patterning process, we measured 3-D dopant profiles using secondary ion mass spectrometry. After deposition, in the masked region, the phosphorus dopant tail was >100 µm at concentrations >10 19 cm -3 while the boron dopant tail was shorter. During high-temperature crystallization of doped a-Si:H films to polycrystalline Si (poly-Si), phosphorus atoms spread by desorbing from the poly-Si surface and re-adsorbing onto intrinsic poly-Si on adjacent wafers that were separated by several millimeters. These contamination mechanisms resulted in a decrease in resistivity from ~10 5 Ω·cm for intrinsic poly-Si to ~10 -1 Ω·cm for contaminated poly-Si. Mitigation strategies for each contamination mechanism were developed to maintain a resistivity of ~10 5 Ω·cm between doped fingers. During fabrication of the 209 cells created during this project, it was found that despite contamination of the IBC gap through the abovementioned mechanisms, high shunt resistances and FF ~75% were still reached. Investigation into this led to the discovery of defect-enhanced compensation which exists within highly defective poly-Si when net doping concentrations reach the value of defect density (~10 18 cm -3 for many poly-Si films). Simulations guided us in the fabrication of IBCs and the cells fabricated were able to meet the year-end goals for BP 2 and 3 of 15% and 17% IBC cell efficiency, as well as the BP 4 goal of a 1% absolute increase in efficiency for PERC-like devices. However, the most efficient cell created during this project of 18.6% fell short of the 21% final project target. While the champion device fell short in V oc and J sc , many devices fabricated were able to reach the necessary goals of ~40 mA/cm 2 , ~700 mV, and ~75% FF required for a 21% device. The results generated from this project were disseminated through 11 conference presentations and proceedings. Presentations included oral talks at 2019 IEEE PVSC, 2019 MRS Fall Meeting, 2020 PVSEC-30 and 2021 IEEE PVSC, as well as poster presentations at 2020 IEEE PVSC and 2021 SiPV. The project resulted in 2 peer reviewed publications – one published in IEEE Journal of Photovoltaics and one in ACS Applied Energy Materials. The information gained in this project will aid in development of improved processes for fabrication of high-efficiency solar cells and other areas of the semiconductor device industry as well. The IBC cells will also pave the way for higher efficiency tandem devices. Through further manufacturing of high-efficiency solar cells, more of the world’s energy demands can be met through renewable sources, helping to stave off the worst effects that may come about from global climate change.
Editorial: Advanced water splitting technologies development: Best practices and protocols
As the level of deployment and utilization of renewable energy sources, including wind and solar, continues to rise, large-scale, long-term energy storage technologies that could accommodate weekly and seasonal energy fluctuations will play a significant role in the overall deployment of renewable energies in the future. Harnessing and storing renewable energy resources via electrochemical, photoelectrochemical, or thermochemical processes by converting renewable energy into sustainable (energy storage) fuels have the potential to meet the long-term, terawatt scale energy storage challenge. Renewable hydrogen production is the cornerstone for sustainable fuel production and deep decarbonization of multiple sectors in our society. Cost-competitive clean hydrogen provides value to applications, such as 1) in the transportation sector for fuel cell vehicles, 2) in the electric grid sector for system stability and load balancing, and 3) in the industrial sector with metal refineries, cement production, and biomass upgrading (carbon-free fertilizer production). In addition, coupling clean renewable hydrogen with the carbon and nitrogen cycles enables known and well-established thermal-chemical processes to generate renewable hydrocarbon fuels and ammonia. The Advanced Water Splitting Technologies (AWST): low temperature electrolysis (LTE), high temperature electrolysis (HTE), photoelectrochemical (PEC) and solar thermo-chemical hydrogen (STCH) provide four unique and parallel approaches to produce low cost, low greenhouse gas (GHG) emission hydrogen at scale (Figure 1). Cost competitive clean hydrogen production using these four technologies is a current high priority focus for governments and industry. In June of 2022, the U.S. Department of Energy (DOE) launched the first in a series of Earthshot Initiatives. The Hydrogen Shot, “1 1 1” aims to reduce the cost of clean hydrogen by more than 80% to one dollar per one kilogram in 1 decade ($\$$1/kg H 2 ). The European Green Deal and the International Energy Agency (IEA) have implemented a strong focus on green hydrogen production for a clean and secure energy future.
Solar thermal parabolic dish energy applications
Vu-graphs are presented that show that applications are a viable distributed renewable power generation option. Quality energy can be produced in the form of electricity and high temperature heat. Modular systems are described that can be distributed to new or existing plants and that are mass producible with the associated economies of production.
The Caltech-NRAO Stripe 82 Survey (CNSS) Paper. I. The Pilot Radio Transient Survey in 50 Deg.(exp. 2)
We have commenced a multiyear program, the Caltech-NRAO Stripe 82 Survey (CNSS), to search for radio transients with the Jansky VLA in the Sloan Digital Sky Survey Stripe 82 region. The CNSS will deliver five epochs over the entire approx. 270 deg.(exp. 2) of Stripe 82, an eventual deep combined map with an rms noise of approx. 40 proper motion epoch y and catalogs at a frequency of 3 GHz, and having a spatial resolution of 3 inches. This first paper presents the results from an initial pilot survey of a 50 deg.(exp. 2) region of Stripe 82, involving four epochs spanning logarithmic timescales between 1 week and 1.5 yr, with the combined map having a median rms noise of 35 proper motion epoch y. This pilot survey enabled the development of the hardware and software for rapid data processing, as well as transient detection and follow-up, necessary for the full 270 deg.(exp. 2) survey. Data editing, calibration, imaging, source extraction, cataloging, and transient identification were completed in a semi-automated fashion within 6 hr of completion of each epoch of observations, using dedicated computational hardware at the NRAO in Socorro and custom-developed data reduction and transient detection pipelines. Classification of variable and transient sources relied heavily on the wealth of multiwavelength legacy survey data in the Stripe 82 region, supplemented by repeated mapping of the region by the Palomar Transient Factory. A total of 3.9(+0.5%/-0.9%) of the few thousand detected point sources werefound to vary by greater than 30%, consistent with similar studies at 1.4 and 5 GHz. Multiwavelength photometric data and light curves suggest that the variability is mostly due to shock-induced flaring in the jets of active galactic nuclei (AGNs). Although this was only a pilot survey, we detected two bona fide transients, associated with an RS CVn binary and a dKe star. Comparison with existing legacy survey data (FIRST, VLA-Stripe 82) revealed additional highly variable and transient sources on timescales between 5 and 20 yr, largely associated with renewed AGN activity. The rates of such AGNs possibly imply episodes of enhanced accretion and jet activity occurring once every approx. 40,000 yr in these galaxies. We compile the revised radio transient rates and make recommendations for future transient surveys and joint radio-optical experiments.
WBS 2.1.5.401 - Model Validation and Site Characterization for Early Deployment MHK Sites and Establishment of Wave Classification Scheme
The "Resource Characterization" project delivers the data and tools needed to engineer robust marine renewable energy devices and projects. The project measures resource details at commercially promising sites, runs high resolution models of promising sites and regions, and develops classification schemes that streamline device engineering, project development, and increase investor confidence.
Open Source High Fidelity Modeling Of A Type-5 Wind Turbine Drivetrain
The purpose of this code is to provide a high-fidelity model of Type-5 wind turbine drivetrain for grid integration and transient stability studies. The increasing integration of renewable energy resources in evolving bulk power system (BPS) is impacting the system’s inertia. Type-5 wind turbine generation has the potential to behave like a traditional synchronous generator and can help mitigate the aforementioned impact. A hydraulic torque converter (TC) and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine unit. A generic and high-fidelity model of a Type-5 wind turbine drivetrain is not openly and widely available for grid integration and transient stability studies. This hinders appropriate assessment of Type-5 wind power plant's contribution to the BPS resilience. This work develops and validates a TC model based on those generally used in automobile's transmission system.
Low Intensity Low Temperature (LILT) Measurements and Coefficients on New Photovoltaic Structures
Past NASA missions to Mars, Jupiter and the outer planets were powered by radioisotope thermal generators (RTGs). Although these devices proved to be reliable, their high cost and highly toxic radioactive heat source has made them far less desirable for future planetary missions. This has resulted in a renewed search for alternate energy sources, some of them being photovoltaics (PV) and thermophotovoltaics (TPV). Both of these alternate energy sources convert light/thermal energy directly into electricity. In order to create a viable PV data base for planetary mission planners and cell designers, we have compiled low intensity low temperature (LILT) I-V data on single junction and multi-junction high efficiency solar cells. The cells tested here represent the latest photovoltaic technology. Using this LILT data to calculate Short Circuit Current (I(sub sc)), Open Circuit Voltage (V(sub os)), and Fill Factor (FF) as a function of temperature and intensity, an accurate prediction of cell performance under the AM0 spectrum can be determined. When combined with QUantum efficiency at Low Temperature (QULT) data, one can further enhance the data by adding spectral variations to the measurements. This paper presents an overview of LILT measurements and is only intended to be used as a guideline for material selection and performance predictions. As single junction and multi-junction cell technologies emerge, new test data must be collected. Cell materials included are Si, GaAs/Ge, GaInP/GaAs/GaAs, InP, InGaAs/InP, InP/InGaAs/InP, and GaInP. Temperatures range down to as low as -180 C and intensities range from 1 sun down to 0.02 suns. The coefficients presented in this paper represent experimental results and are intended to provide the user with approximate numbers.
Low Intensity Low Temperature (LILT) measurements and coefficients on new photovoltaic structures
Past NASA missions to Mars, Jupiter, and the outer planets were powered by radioisotope thermal generators (RTG's). Although these devices proved to be reliable, their high cost and highly toxic radioactive heat source has made them far less desirable for future planetary missions. This has resulted in a renewed search for alternate energy sources, some of them being photovoltaic (PV) and thermophotovoltaic (TPV). Both of these alternate energy sources convert light/thermal energy directly into electricity. In order to create a viable PV and TPV data base for planetary mission planners and cell designers, we have compiled low temperature low intensity (LILT) I-V data on single junction and multi-junction high efficiency solar cells. The cells tested here represent the latest photovoltaic technology. Using this LILT data to calculate dI(sub SC)/dT, dV(sub OC)/dT, dFF/dT, and also as a function of intensity, an accurate prediction of cell performance under the AMO spectrum can be determined. When combined with QUantum efficiency at Low Temperature (QULT) data, one can further enhance the data by adding spectral variations to the measurements. This paper presents an overview of LILT measurements and is only intended to be used as a guideline for material selection and performance predictions. As single junction and multi-junction cell technologies emerge, new test data must be collected. Cell materials included are Si, GaAs/Ge, GainP/GaAs/Ge, InP, InGaAs/InP, InP/InGaAs/InP, and GainP. Temperatures range as low as -175 C and intensities range from 1 sun to .02 suns.