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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

2D Metal/Graphene and 2D Metal/Graphene/Metal Systems for Electrocatalytic Conversion of CO 2 to Formic Acid

Efficiently transforming CO 2 into renewable energy sources is crucial for decarbonization efforts. Formic acid (HCOOH) holds great promise as a hydrogen storage compound due to its high hydrogen density, non-toxicity, and stability under ambient conditions. However, the electrochemical reduction of CO 2 (CO 2 RR) on conventional carbon black-supported metal catalysts faces challenges such as low stability through dissolution and agglomeration, as well as suffering from high overpotentials and the necessity to overcome the competitive hydrogen evolution reaction (HER). In this study, we modify the physical/chemical properties of metal surfaces by depositing metal monolayers on graphene (M/G) to create highly active and stable electrocatalysts. Strong covalent bonding between graphene and metal is induced by the hybridization of sp and d orbitals, especially the sharp $d_{z^2}$, $d_{yz}$, $d_{xz}$ orbitals of metals near the Fermi level, playing a decisive role. Moreover, charge polarization on graphene in M/G enables the deposition of another thin metallic film, forming metal/graphene/metal (M/G/M) structures. Finally, evaluating overpotentials required for CO 2 reduction to HCOOH, CO, and HER, we find that Pd/G, Pt/G/Ag, and Pt/G/Au exhibit excellent activity and selectivity toward HCOOH production. Our novel 2D hybrid catalyst design methodology may offer insights into enhanced electrochemical reactions through the electronic mixing of metal and other p-block elements.

2D Electrocatalysts↗
DOE OSTI2020

Light‐driven catalysis with engineered enzymes and biomimetic systems

Abstract Efforts to drive catalytic reactions with light, inspired by natural processes like photosynthesis, have a long history and have seen significant recent growth. Successfully engineering systems using biomolecular and bioinspired catalysts to carry out light‐driven chemical reactions capitalizes on advantages offered from the fields of biocatalysis and photocatalysis. In particular, driving reactions under mild conditions and in water, in which enzymes are operative, using sunlight as a renewable energy source yield environmentally friendly systems. Furthermore, using enzymes and bioinspired systems can take advantage of the high efficiency and specificity of biocatalysts. There are many challenges to overcome to fully capitalize on the potential of light‐driven biocatalysis. In this mini‐review, we discuss examples of enzymes and engineered biomolecular catalysts that are activated via electron transfer from a photosensitizer in a photocatalytic system. We place an emphasis on selected forefront chemical reactions of high interest, including CH oxidation, proton reduction, water oxidation, CO 2 reduction, and N 2 reduction.

Edwards, Emily H.↗
DOE OSTI2023

Identifying biomass yield potential of tetra, hexa, and octoploid prairie cordgrass populations grown on marginal lands

As the demand for renewable energy sources with reduced carbon emissions to the atmosphere increases, bioenergy crops remain an attractive alternative to fossil fuels. Another appeal of bioenergy crops is the potential utilization of marginal lands not suitable for food crops. Prairie cordgrass is a perennial warm season polyploid grass species being considered as a bioenergy crop that also exhibits a high tolerance for salinity and flooding. The ploidy level of prairie cordgrass has previously been suggested to correlate with agronomic traits. However, little is known about the agricultural performance of prairie cordgrass on marginal lands and if a correlation of ploidy level to stress tolerance exists. In this experiment, the productivity of tetraploids, hexaploids, and octoploids was investigated when grown on three different marginal sites including waterlogged, saline, and low-nutrient gravelly soils. Here we found that prairie cordgrass populations annually produced dry biomass on a wet marginal site comparable to normal cropland. However, the productivity was remarkedly decreased at both a salt-affected site and a limestone mine reclamation site. We were unable to conclude that different ploidy levels affected the biomass yield of prairie cordgrass grown under abiotic stress. However, there was a differential response of populations to various types of marginal sites. Finally, these results indicate potential genetic resources for developing breeding targets and identifying mechanisms of abiotic stress tolerance. Moreover, we highlight the need to generate diverse ploidy levels of prairie cordgrass in the same genetic backgrounds for future testing.

09 BIOMASS FUELS↗
DOE OSTI2020

A Comparative Review of Metal-Based Charge Carriers in Nonaqueous Flow Batteries

Energy storage is becoming the chief barrier to the utilization of more renewable energy sources on the grid. With independent service operators aiming to acquire gigawatts in the next 10–20 years, there is a large need to develop a suite of new storage technologies. Redox flow batteries (RFB) may be part of the solution if certain key barriers are overcome. This review focuses on a particular kind of RFB based on nonaqueous media that promises to meet the challenge through higher voltages than the organic and aqueous variants. This class of RFB is divided into three groups: molecular, macromolecular, and redox-targeted systems. The growing field of theoretical modeling is also reviewed and discussed.

25 ENERGY STORAGE↗
DOE OSTI2023

Particle Size Optimization of Thermochemical Salt Hydrates for High Energy Density Thermal Storage

Thermal energy storage (TES) solutions offer opportunities to reduce energy consumption, greenhouse gas emissions, and cost. Specifically, they can help reduce the peak load and address the intermittency of renewable energy sources by time shifting the load, which are critical toward zero energy buildings. Thermochemical materials (TCMs) as a class of TES undergo a solid–gas reversible chemical reaction with water vapor to store and release energy with high storage capacities (600 kWh m −3 ) and negligible self‐discharge that makes them uniquely suited as compact, stand‐alone units for daily or seasonal storage. However, TCMs suffer from instabilities at the material (salt particles) and reactor level (packed beds of salt), resulting in poor multi‐cycle efficiency and high‐levelized cost of storage. In this study, a model is developed to predict the pulverization limit or R crit of various salt hydrates during thermal cycling. This is critical as it provides design rules to make mechanically stable TCM composites as well as enables the use of more energy‐efficient manufacturing process (solid‐state mixing) to make the composites. The model is experimentally validated on multiple TCM salt hydrates with different water content, and effect of R crit on hydration and dehydration kinetics is also investigated.

25 ENERGY STORAGE↗
DOE OSTI2021

Exploring filamentous fungi depolymerization of corn stover in the context bioenergy queuing operations

Recalcitrance of lignocellulosic feedstocks to depolymerization is a significant barrier for bioenergy production approaches that require conversion of monomeric carbohydrates to renewable energy sources. This study assesses how low-cost modifications in the feedstock supply chain can be transformed into targeted pretreatments in the context of the entire bioenergy supply chain. The aim of this research is to overcome the physiochemical barriers in corn stover that necessitate increased severity in conversion in terms of chemical loading, temperature, and residence time. Corn stover samples were inoculated with a selective (Ceriporiopsis subvermispora) and non-selective (Phaenarochaete chrysosporium) lignin degrading filamentous fungal strains, then stored aerobically to determine the working envelope for fungal pretreatment to achieve lignin degradation. Dry matter loss and gross chemical makeup of corn stover varied by the length of treatment (2 and 4 weeks) and by the moisture content of the treated corn stover samples (40 and 60%, wet basis). Dry matter loss in P. chrysosporium inoculated biomass was elevated compared to the C. subvermispora inoculated biomass; however, treatment also induced additional chemical composition changes suggestive of depolymerization. Scanning electron microscope images reveal hyphae attached within cell lumen and suggest structural changes within P. chrysosporium treated corn stover after 60% moisture storage. These results highlight that fungal treatment approaches must balance loss of convertible material with the potential for reduction in recalcitrance. Techno-economic assessment (TEA) of fungal pretreatment in a short-term queuing system indicated the viability of this approach compared to conventional queuing operations. The total queuing system cost was estimated at $\$$1.65/tonne of biomass stored. After applying the credit of $\$$1.48/tonne from energy savings in the conversion phase using fungal pretreated biomass, the total system cost was $0.80 lower than traditional biomass queueing approach. While the TEA results suggested that treating biomass with C. subvermispora is the most economically viable storage method in the designed fungal-assisted queuing system, future research should focus on additional fungal depolymerization such as those observed in the P. chrysosporium inoculated biomass.

09 BIOMASS FUELS↗
DOE OSTI2020

Permeation of CO 2 and N 2 through glassy poly(dimethyl phenylene) oxide under steady- and presteady-state conditions

Glassy polymers are often used for gas separations because of their high selectivity. Although the dual-mode permeation model correctly fits their sorption and permeation isotherms, its physical interpretation is disputed, and it does not describe permeation far from steady state, a condition expected when separations involve intermittent renewable energy sources. To develop a more comprehensive permeation model, we combine experiment, molecular dynamics, and multiscale reaction–diffusion modeling to characterize the time-dependent permeation of N 2 and CO 2 through a glassy poly(dimethyl phenylene oxide) membrane, a model system. Simulations of experimental time-dependent permeation data for both gases in the presteady-state and steady-state regimes show that both single- and dual-mode reaction–diffusion models reproduce the experimental observations, and that sorbed gas concentrations lag the external pressure rise. The results point to environment-sensitive diffusion coefficients as a vital characteristic of transport in glassy polymers.

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

Redox‐Functionalized Semiconductor Interfaces for Photoelectrochemical Separations

Redox-mediated electrosorption is a promising platform for selective electrochemical (EC) separations, due to its molecular selectivity, high uptake, and tunability for target ions. However, the electrical energy required is mainly generated by non-renewable energy sources, which limits its sustainability and overall impact to decarbonization. Here, a redox-mediated photoelectrochemical (PEC) separation process using polyvinyl ferrocene functionalized TiO 2 nanorod electrodes is proposed, which integrates direct solar energy as a driver for the selective electrosorption. The photoelectrochemically-driven oxidation and reduction with both homogeneous and heterogeneous ferrocene-systems is investigated to establish the underlying mechanism. The PEC system can separate heavy metal oxyanions at lower voltages or even without electrical energy. At 0.3 V versus SCE, a 124 mg g −1 uptake for Mo is achieved, which is comparable to the performance of EC cells at 0.75 V versus SCE. Thus, PEC systems not only can generate energy for spontaneous redox-separations, but also can reduce electrical energy consumption by 51.4% compared to EC cells for separation processes when coupled with an external electrical energy.

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

Deep Reinforcement Learning Based Smart Water Heater Control for Reducing Electricity Consumption and Carbon Emission

Water heating is the third largest electricity consumer in U.S. households, after space heating and cooling. Thus, water heaters represent a significant potential for reducing electricity consumption and associated CO2 emissions of residential buildings. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity consumption and the CO2 emissions of a heat pump water heater without affecting user comfort. In this approach, a set of RL agents focusing on either electricity saving or emission reduction, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on different hot water usage and Marginal Operating Emissions Rate (MOER) profiles. The testing results showed that the RL agents that focus on electricity saving can save electricity in the range of 12–22% by operating the water heater with maximum heat pump efficiency and minimum electric element utilization. On the other hand, the RL agents that focus on emission reduction reduced emissions in the range of 18–37% by making use of the variable MOER values. These RL agents used the heat pump and/or an element when the MOER values are low due to the availability of renewable energy sources (e.g., solar and wind) and mostly avoided the periods of carbon-intensive periods. Overall, these results showed that the proposed RL approach can help minimize the electricity consumption and the CO2 emissions of a heat pump water heater without having any prior knowledge about the device.

Amasyali, Kadir↗
DOE OSTI2023

The Linkage Between Electro-Chemical Mechanical Instabilities in Battery Materials

Battery chemistry must be diversified to achieve a sustainable energy landscape by effectively utilizing renewable energy sources. Alkali metal-ion, all-solid-state, metal–air batteries, and multivalent batteries offer unique cost, safety, raw material abundance, energy, and power density solutions. However, realizing these “beyond Li-ion batteries” must uncover their working principles and performance & property relationships. In this aspect, mitigating chemo-mechanical instabilities in the structure and surface of the electrodes plays a crucial role in their performance. Unfortunately, the coupling between electrochemical and mechanical interactions is often poorly understood due to a lack of operando characterization. Here, this review article explains the working principles of curvature measurement and digital image correlation for measuring stress and strain generations in battery materials. We provided specific examples of how these operando mechanical measurements shed light on instabilities in alkali metal ion electrodes, solid electrolytes, Li-O 2 batteries, and aqueous Zn-ion batteries. Operando mechanical measurements offer an effective way to map changes in the physical fingerprint of the battery materials, therefore providing crucial information to elucidate instabilities in battery materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Combining shallow-water and analytical wake models for tidal array micro-siting

For tidal-stream energy to become a competitive renewable energy source, clustering multiple turbines into arrays is paramount. Array optimisation is thus critical for achieving maximum power performance and reducing cost of energy. However, ascertaining an optimal array layout is a complex problem, subject to specific site hydrodynamics and multiple inter-disciplinary constraints. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated through applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for arrays with turbines of 3.05 m/s rated speed, demonstrating practical implications whilst considering the temporal variability of the tide. For a 24-turbine array case, micro-siting using this technique delivered an array 15.8% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was evaluated through assessment of the optimised layout within the ocean model that treats turbines through a discrete turbine representation. Used iteratively, this methodology could deliver improved array configurations in a manner that accounts for local hydrodynamic effects.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Thermo-hydro-mechanical analysis of subsurface ice-based thermal energy storage

Ice-based thermal energy storage systems are widely utilized for cooling and managing peak electrical demand globally, offering daily or weekly storage capabilities for both individual homes and larger office buildings. However, scaling these systems for district-level cooling or integrating them with renewable energy sources presents challenges, especially in accommodating larger volumes and addressing seasonal storage requirements in densely populated urban areas. This paper proposes a novel solution by evaluating subsurface ice-based thermal energy storage, in which the underground is subjected to seasonal freeze/thaw cycles. However, these cycles may influence ground behavior, affecting pore pressure and inducing ground movement. To systematically investigate these challenges, we enhance the TOUGH-FLAC simulator by integrating water/ice phase change capabilities and updating the effective stress–strain constitutive relation. Both modifications are validated against analytical solutions or experimental data. Through numerical simulations spanning a decade with ten seasonal freeze/thaw cycles, we evaluate the performance and long-term stability of a generic subsurface ice-based thermal energy storage system, considering factors such as ground permeability, freezing pipe spacing, freeze/thaw damage, and glycol solution temperature. The simulations indicate that ice formation induces pore pressure variations that drive seasonal surface heave and settlement, controlled by ground permeability, pipe spacing, and glycol solution temperature, along with tensile and localized shear deformation around freeze pipes. This highlights the need for accurate ground property characterization and geomechanical analysis for subsurface ice-based thermal energy storage.

Ground freezing↗
DOE OSTI2022

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.

Omenya, Fredrick O.↗
DOE OSTI2021

A forecast-driven decision-making model for long-term operation of a hydro-wind-photovoltaic hybrid system

Hydro-wind-photovoltaic (PV) hybrid system has the potential to increase the integration of renewable energy sources into an existing grid. For the long-term operation of the system, due to the non-storable nature of wind and PV power, it is essentially to decide the optimal long-term carryover storage of cascade reservoirs. However, it remains a challenge due to high uncertainties of long-term forecasts and complicated hydraulic/electrical relationships between cascade reservoirs. Here in this study, a forecast-driven decision-making model is proposed for the hybrid system, which converts the multi-stage long-term operation process into a two-stage operation problem (including current stage and carryover stage) to avoid using longer-horizon forecast information with lower accuracy. First, the carryover stage energy surfaces (CESs) considering the forecast uncertainties of wind, solar and hydro resources are proposed to characterize carryover stage benefit quantitatively. Then a CESs-based forward decision-making optimization model is developed to guide the long-term operation of a hydro-wind-photovoltaic hybrid system. The applications in a hydro-wind-PV hybrid system of Yalong River basin results show that: compared with conventional operation, 1) power generation increases 9.03%; 2) in terms of the carryover storages control, the reservoir impounding and drawdown timing are delayed, and the drawdown depth is increased, which can be used to formulate better reservoir operation rules.

13 HYDRO ENERGY↗
DOE OSTI2022

The value of in-reservoir energy storage for flexible dispatch of geothermal power

Geothermal systems making use of advanced drilling and well stimulation techniques have the potential to provide tens to hundreds of gigawatts of clean electricity generation in the United States by 2050. With near-zero variable costs, geothermal plants have traditionally been envisioned as providing “baseload” power, generating at their maximum rated output at all times. However, as variable renewable energy sources (VREs) see greater deployment in energy markets, baseload power is becoming increasingly less competitive relative to flexible, dispatchable generation and energy storage. Herein we conduct an analysis of the potential for future geothermal plants to provide both of these services, taking advantage of the natural properties of confined, engineered geothermal reservoirs to store energy in the form of accumulated, pressurized geofluid and provide flexible load-following generation. We develop a linear optimization model based on multi-physics reservoir simulations that captures the transient pressure and flow behaviors within a confined, engineered geothermal reservoir. We then optimize the investment decisions and hourly operations of a power plant exploiting such a reservoir against a set of historical and modeled future electricity price series. Further, we find that operational flexibility and in-reservoir energy storage can significantly enhance the value of geothermal plants in markets with high VRE penetration, with energy value improvements of up to 60% relative to conventional baseload plants operating under identical conditions. Across a range of realistic subsurface and operational conditions, our modeling demonstrates that confined, engineered geothermal reservoirs can provide large and effectively free energy storage capacity, with round-trip storage efficiencies comparable to those of leading grid-scale energy storage technologies. Optimized operational strategies indicate that flexible geothermal plants can provide both short- and long-duration energy storage, prioritizing output during periods of high electricity prices. Sensitivity analysis assesses the variation in outcomes across a range of subsurface conditions and cost scenarios.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Investigating capacity credit sensitivity to reliability metrics and computational methodologies

Assigning capacity value to renewable energy sources (RES) is a challenge faced in planning their integration with the grid. The difficulties stem from the natural characteristics of variability and intermittency of wind and solar sources. The capacity credit (CC) analysis evaluates the system’s actual power output compared with a constant capacity generator, i.e., conventional generator and determines an effective capacity to use for planning and operation. Herein this paper presents different factors that could affect the CC of a system. Two methods are proposed to determine the CC, namely equivalent firm capacity (EFC) and effective load carrying capability (ELCC). Since these methods are based on satisfying reliability criteria, daily loss of load expectation (LOLE), hourly loss of load (LOLH), and expected energy not served (EENS) have been employed as indices. To obtain the CC value, both methods apply two techniques: traditional and optimization. Genetic algorithm (GA) is the optimization approach used in this paper. Then, this work compares the two techniques and shows the superior performance of the optimization approach. Two hybrid systems, stand-alone (SA) and grid-connected (GC) modes, are proposed and used as case studies. The hybrid systems consist of photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS). In this work, three different scenarios are used to compare capacity credit: system as a whole, only wind, and no batteries. Finally, sensitivity analysis is carried out to examine the impact of varying the wind speed, solar irradiation, and load. It is demonstrated that the choice of reliability index plays an important role in determining the capacity credit and it is shown that EENS is a more comprehensive and consistent index of reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Evaluating the impact of wildfire smoke on solar photovoltaic production

There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. Finally, this work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow.

14 SOLAR ENERGY↗
DOE OSTI2023

Solar water splitting Pt-nanoparticle photosystem I thylakoid systems: Catalyst identification, location and oligomeric structure

In this study, photosynthetic conversion of light energy into chemical energy occurs in sheet-like membrane-bound compartments called thylakoids and is mediated by large integral membrane protein-pigment complexes called reaction centers (RCs). Oxygenic photosynthesis of higher plants, cyanobacteria and algae requires the symbiotic linking of two RCs, photosystem II (PSII) and photosystem I (PSI), to split water and assimilate carbon dioxide. Worldwide there is a large research investment in developing RC-based hybrids that utilize the highly evolved solar energy conversion capabilities of RCs to power catalytic reactions for solar fuel generation. Of particular interest is the solar-powered production of H 2 , a clean and renewable energy source that can replace carbonbased fossil fuels and help provide for ever-increasing global energy demands. Recently, we developed thylakoid membrane hybrids with abiotic catalysts and demonstrated that photosynthetic Z-scheme electron flow from the light-driven water oxidation at PSII can drive H 2 production from PSI. One of these hybrid systems was created by self-assembling Pt-nanoparticles (PtNPs) with the stromal subunits of PSI that extend beyond the membrane plane in both spinach and cyanobacterial thylakoids. Using PtNPs as site-specific probe molecules, we report the electron microscopic (EM) imaging of oligomeric structure, location and organization of PSI in thylakoid membranes and provide the first direct visualization of photosynthetic Z-scheme solar water-splitting biohybrids for clean H 2 production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗