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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Tailoring-Orientated Deposition of Li 2 S for Extreme Fast-Charging Lithium–Sulfur Batteries

Precipitation/dissolution of insulating Li 2 S has long been recognized as the rate-determining step in lithium-sulfur (Li-S) batteries, which dramatically undermines sulfur utilization at elevated charging rates. Herein, we present an orientated Li 2 S deposition strategy to achieve extreme fast charging (XFC, ≤15 min) through synergistic control of porosity, electronic conductivity, and anchoring sites of electrode substrate. Via magnesiothermic reduction of a zeolitic imidazolate framework, a nitrogen-doped and hierarchical porous carbon with highly graphitic phase was developed. This design effectively reduces interfacial resistance and ensures efficient sequestration of polysulfides during deposition, leading to (110)-preferred growth of Li 2 S nanocrystalline between (002)-dominated graphitic layers. Our approach directs an alternative Li 2 S deposition pathway to the commonly reported lateral growth and 3D thickening growth mode, ameliorating the electrode passivation. Therefore, a Li-S cell capable of charging/discharging at 5C (12 min) while maintaining excellent cycling stability (82% capacity retention) for 1000 cycles is demonstrated. In conclusion, even under high S loading (8.3 mg cm -2 ) and low electrolyte/sulfur ratio (3.8 mL mg -1 ), the sulfur cathode still delivers a high areal capacity of >7 mAh cm -2 for 80 cycles.

25 ENERGY STORAGE↗
DOE OSTI2024

Evaluation of Autonomous Vehicle Sensing and Compute Load on a Chassis Dynamometer

The sensing and compute load auxiliary energy consumption in autonomous vehicles may be significant due to the large number of sensors and the high compute load from sensor processing and route planning. To understand this issue, this study investigates the top-down energy usage of an electric 2015 Kia Soul fully instrumented with state sensors and a state-specific computer for path planning and sensor processing. A chassis dynamometer was then used to evaluate the cases of (1) no sensors or computation, (2) only sensors operating, and (3) sensors plus compute load. The vehicle was operated autonomously on the dynamometer using a PolySync drive-kit with drive-by-wire longitudinal control. The DynoJet model 224xLC was used to adapt the eddy current dynamometer's road load parameters to comply with an Environmental Protection Agency drive schedule and to evaluate performance against the Argonne National Laboratory Digital Dynamometer Dataset. On the UDDS-HWFET combined driving cycle, the stock battery's range was reduced by 5.6% for sensors alone and 12.2% for sensors and compute load. These results show that the added sensing and compute auxiliary load from automated and autonomous systems is significant and that research efforts need to be spent investigating new energy efficient systems.

Brown, Nicholas E.↗
DOE OSTI2022

Platinum nanoparticle compression: Combining in situ TEM and atomistic modeling

The mechanical behavior of nanoparticles governs their performance and stability in many applications. However, the small sizes of technologically relevant nanoparticles, with diameters in the range of 10 nm or less, significantly complicate experimental examination. These small nanoparticles are difficult to manipulate onto commercial test platforms and deform at loads that are below the typical noise floor of the testing instruments. Here, we synthesized small platinum nanoparticles directly onto a mechanical tester and used a modified nanomanipulator to enhance load resolution to the nanonewton scale. We demonstrated the in situ compression of an 11.5-nm platinum nanoparticle with simultaneous high-resolution measurements of load and particle morphology. Molecular dynamics simulations were performed on similarly sized particles to achieve complementary measurements of load and morphology, along with atomic resolution of dislocations. The experimental and simulation results revealed comparable values for the critical resolved shear stress for failure, 1.28 and 1.15 GPa, respectively. Altogether, this investigation demonstrated the promise of, and some initial results from, the combination of atomistic simulations and in situ experiments with an unprecedented combination of high spatial resolution and high load resolution to understand the behavior of metal nanoparticles under compression.

42 ENGINEERING↗
DOE OSTI2020

Designed Iron Single Atom Catalysts for Highly Efficient Oxygen Reduction Reaction in Alkaline and Acid Media

Abstract Single atom catalysts (SACs) have attracted much attentions due to their advantages of high catalysis efficiency and excellent selectivity. However, for industrial applications, synthesis of SACs in large and practical quantities is very important. The challenge is to develop synthesis methods with controllability and scalability. Herein, a well‐characterized and scalable method is demonstrated to synthesize atomically dispersed iron atoms coordinated with nitrogen on graphene, SAFe @ NG, with high atomic loading (≈4.6 wt%) through a one‐pot pyrolysis process. The method is scalable for the fabrication of Fe SACs with high quantities. The Fe–N–G catalyst exhibits high intrinsic oxygen reduction reaction (ORR) performance, reaching half potential of 0.876 and 0.702 V in alkaline and acidic solutions, respectively, with excellent microstructure stability. Furthermore, the density functional theory (DFT) simulation confirms that the Fe atoms in coordination with four nitrogen atoms, FeN4, in graphene is the active center for the 4‐electron ORR process. This work demonstrates an efficient design pathway for single atom catalysts as highly active and stable electrocatalysts for high‐performance ORR applications.

Zhao, Shiyong↗
DOE OSTI2020

Phase distribution in Fischer-Tropsch mimicked slurry bubble column via computed tomography

This study aims to investigate the phases distribution and hydrodynamics in an air-Therminol LT-glass beads slurry bubble column reactor in bubbly and churn-turbulent flow regimes by implementing a gamma-ray computed tomography. It is found that gas holdup increases with increasing superficial gas velocity and operating pressure while increasing solids loading has an opposite effect on gas holdup measurements. It is noticed that the pressure effect is more significant at high solids loading and the solids loading is relatively more substantial at lower pressure. Solids loading has the most significant a stronger effect on the solids holdup profile than on the gas holdup profile. Current results were compared with the Sedimentation-Dispersion Model (SDM) predictions. Overall, the findings of this study advance the knowledge of the true behavior of phases distribution in FT mimicked slurry bubble columns which are pertinent in designing such reactors.

42 ENGINEERING↗
DOE OSTI2024

Molecular Engineering Enabled Stable Deep Eutectic Amide-Based Electrolyte for High-Temperature Lithium–Metal Batteries

The development of advanced lithium-metal batteries (LMBs), such as high-temperature LMBs and high-energy-density LMBs, has critical requirements for electrolytes. However, conventional electrolytes suffer from thermal instability and insufficient electrolyte/Li interfacial compatibility, severely limiting their utilization in high-temperature LMBs. Herein, we design a high-temperature N-methylacetamide (NMAc)-based deep eutectic electrolyte (DEE) by molecular engineering on a solvation structure via a sacrificial additive of vinyl ethylene carbonate (VEC). Specifically, VEC interacts with the Li prior to NMAc, facilitating the formation of a solid electrolyte interphase to inhibit the reaction between Li and NMAc. The stable VEC-DEE effectively suppresses the growth of lithium dendrites and ensures the battery a cycling stability of 550 cycles at 80 °C. Additionally, we also demonstrate the application of VEC-DEE in high-energy-density LMBs with a high mass loading of 2.5 mAh/cm 2 . In conclusion, this research opens a new avenue for the rational design of advanced high-temperature electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2024

Exploring Grid-Interactive Efficient Building Strategies for Laboratories Through Energy Modeling

Laboratories are often overlooked in demand flexibility research due to constraints on their operations as mission critical facilities, despite the major role they play in an organization's emissions. Laboratories consume 3-4 times more energy than a typical office building and are commonly the largest energy users on any campus. Consequently, most laboratories in the United States are significant contributors to their organization's carbon footprint if their energy needs are met through the combustion of fossil fuels. As part of the initiative to decarbonize laboratories, this report documents an analysis on specifically grid-interactive efficient building (GEB) opportunities for reducing energy costs and emissions associated with laboratory operations. The goal of this initiative was to provide a case study and guidance on how to use OpenStudio and REopt as modeling tools for GEB technologies and strategies in laboratory environments across different climate zones in the United States. The analysis found that efficiency-based GEB strategies had the most significant impact on laboratory operations, while load-shedding and load-shifting GEB strategies produced smaller results. The culmination of these approaches applied across all five climate zones generated on average: 1) 28% energy cost savings and 30% greenhouse gas (GHG) emissions reductions, and 2) 4% enhanced energy cost savings under a time-of-use (TOU) pricing schedule compared to traditional pricing schemes. Grid-interactive efficiency building measures were found to produce the greatest energy savings in both electricity and natural gas, particularly in regions with high electrical loads, such as warm climates for cooling. Laboratories that had high levels of natural gas consumption, meanwhile, experienced the greatest emission reductions. The report concludes with an analysis on the opportunities for flexible loads in lab spaces and how small-scale measures in addition to opaque pricing structures for peak demand could become barriers to demand flexibility planning. The report also explores how electrifying laboratory buildings with heat pumps could reduce energy costs and GHG emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Ducted Fuel Injection Provides Consistently Lower Soot Emissions in Sweep to Full-Load Conditions

Earlier studies have proven how ducted fuel injection (DFI) substantially reduces soot for low- and mid-load conditions in heavy-duty engines, without significant adverse effects on other emissions. Nevertheless, no comprehensive DFI study exists showing soot reductions at high- and full-load conditions. This study investigated DFI in a single-cylinder, 1.7-L, optical engine from low- to full-load conditions with a low-net-carbon fuel consisting of 80% renewable diesel and 20% biodiesel. Over the tested load range, DFI reduced engine-out soot by 38.1–63.1% compared to conventional diesel combustion (CDC). This soot reduction occurred without significant detrimental effects on other emission types. Thus, DFI reduced the severity of the soot–NO x tradeoff at all tested conditions. While DFI delivered considerable soot reductions in thepresent study, previous DFI studies at low- and mid-load conditions delivered larger soot reductions (>90%) compared to CDC operation at the same conditions. Therefore, the DFI configuration used here has been deemed nonoptimal (in terms of parameters such as the injector-spray and piston geometries), and several improvements are recommended for future studies with high-load DFI. Further, these improvements include employing better spray-duct alignment, a deeper piston bowl with a smaller injector umbrella angle, and a fuel injector that opens and closes faster. The study also suggests future research to make DFI ready for commercialization, such as metal-engine tests to ensure desirable DFI performance over an engine’s complete speed/load map. Overall, this study supports the continued development and commercialization of DFI to meet upcoming emissions regulations for heavy-duty vehicles. Specifically, multicylinder engine experiments and CFD simulations should be utilized to optimize the performance and clarify the full potential of DFI.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Electrical Load Forecasting Over Multihop Smart Metering Networks With Federated Learning

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) record household energy data. Traditional machine learning (ML) methods are often employed for load forecasting, but require data sharing, which raises data privacy concerns. Federated learning (FL) can address this issue by running distributed ML models at local SMs without data exchange. However, current FL-based approaches struggle to achieve efficient load forecasting due to imbalanced data distribution across heterogeneous SMs. Here, this article presents a novel personalized FL (PFL) method for high-quality load forecasting in metering networks. A meta-learning-based strategy is developed to address data heterogeneity at local SMs in the collaborative training of local load forecasting models. Moreover, to minimize the load forecasting delays in our PFL model, we study a new latency optimization problem based on optimal resource allocation at SMs. A theoretical convergence analysis is also conducted to provide insights into FL design for federated load forecasting. Extensive simulations from real-world datasets show that our method outperforms existing approaches regarding better load forecasting and reduced operational latency costs.

Rahman, Ratun [Univ. of Alabama, Huntsville, AL (U↗
DOE OSTI2026

Melter Tests to Define LAW Halide Concentrations, Phase 2

The present work represents the second of two phases to address the formation of secondary sulfate phases while processing high waste loading LAW formulations with elevated halide, chromium, and phosphate feed concentrations over a wide range of LAW waste types, including those with high potassium concentrations. The Test Plan for the present work outlines a series of tests designed to assess the formation of secondary phases over a range of sulfur and halide concentrations for two LAW streams and associated glass formulations as well as crucible testing to identify additives that have the potential to suppress the formation of secondary phases for wastes with high chlorine contents. The combined results from both phases of testing and from previous tests with these LAW waste streams will be used as inputs to future work to develop concentration limits for these components in the LAW glass property composition models and to support the modification and updating of the current WTP LAW glass formulation algorithm.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Impact of Stabilizing Cations on Lithium Intercalation in Tunneled Manganese Oxide Cathodes

Stabilizing cations such as K + , Ba 2+ , and Ag + are known to provide charge neutrality and enhance structural stability in low-cost tunneled manganese dioxide (MnO 2 ) cathodes for Li ion batteries. However, a fundamental understanding of the role of these cations in the electrochemical performance of tunneled MnO 2 cathodes remains unclear, especially at low stabilizing cation concentrations. Here, we employ density functional theory (DFT + U) calculations to reveal the impact of stabilizing potassium cation (K + ) concentration on the structural stability, electronic properties, and kinetics of lithium transport in 2 x 2 tunneled manganese oxide (α-K y Mn 8 O 16 , at y = 0, 1, and 2) battery cathodes during lithium intercalation. Specifically, we provide insights into the effect of K + ions on several critical factors governing the electrochemical storage performance of tunneled MnO2 cathodes, including (a) energetically favorable Li+ host sites, (ii) Li + and electron transport capabilities, (iii) optimal intercalation pathways, crystal distortion, microstructural stability, and tunneled-to-layer phase transformation as a function of lithium content, and (iv) cell output voltage profile. Interestingly, we find that low K + concentrations (y ≤ 1) yield partially cation-deficient tunnels in the MnO 2 cathode. Such unique tunnel structures in the cathode enable (a) low kinetic barriers for Li transport, (b) excellent thermodynamic stability of the tunneled structure even at a high Li + loading (up to ~ 0.625 Li/Mn), and (c) good electronic conductivity facilitated by Jahn-Teller distortions; all of which are critical for achieving high capacity batteries with enhanced rate capability. Additionally, these results provide perspectives to design low-cost transition metal oxide cathodes for high-performance Li-ion batteries with excellent cycle life.

25 ENERGY STORAGE↗
DOE OSTI2025

Optimization of catholyte for halide-based all-solid-state batteries

Halide solid electrolytes gain significant attention due to their high ionic conductivity, low processing temperature, dry air compatibility, and high-voltage stability. However, low cathode active material (CAM) loading in the composite cathode constrains the realization of high energy density for halide-based all-solid-state batteries. In this study, three halide materials, raw Li 3 YBrCl 5 (LYBC-R, <30μm), milled LYBC (LYBC-M, <5 μm) and freeze-dried Li 3 InCl 6 (LIC, <500 nm), were used as catholytes, combined with LYBC-M as the electrolyte and LiIn alloy as the anode. The CAM:catholyte ratio was investigated as well as stack pressure and operating temperature. Our study demonstrates that particle size of the catholyte plays an important role only for high CAM loading or high C-rate cycling. At moderate CAM loading (65 and 70wt% LiNi 0.83 Mn 0.06 Co 0.11 O 2 ) and 0.1 C-rate, all the three catholytes perform well, providing initial discharge capacities >177 mAh/g. At high CAM loading (85wt%) and 0.1 C-rate, a cathode with the nano-scale LIC catholyte provides discharge capacity of 175 mAh/g, while the larger particle size catholytes suffer significantly reduced capacity. Both LYBC and LIC catholytes provided capacity retention >80% after 200 cycles at 0.5C. These results imply that cathode particle size is critically important for performance at high CAM loading. Furthermore, both electrolyte and cathode were tape cast to scale up size and prepare realistic layer thicknesses. A small amount of binder was used in both layers, to balance the electrochemical performance and mechanical properties. Further, the discharge capacity of a tape cell was 152mA h/g at 0.1C with a capacity retention of 81.8% after 20 cycles at 0.5C. The results demonstrate the excellent performance of LYBC as an electrolyte, and provide guidance for halide-based cathode design.

25 ENERGY STORAGE↗
DOE OSTI2022

The Effect of Inverter Loading Ratio on Energy Estimate Bias: Preprint

Subhourly effects, particularly variability in solar irradiance, can lead to underestimation of inverter clipping losses and overestimation of energy in hourly photovoltaic system performance models, particularly for systems with high inverter loading ratios. Direct simulation of this error can be complicated by factors such as the representation of spatial and temporal variability in hourly weather data and transient system conditions. In this work we take an alternative approach using real system power measurements to show that energy predictions from typical industry models suffer from a bias that increases with inverter loading ratio. We also show that this loading ratio-dependent bias is strongly correlated with an empirical subhourly inverter clipping bias derived from real power plant data. Finally, we show that this bias is not necessarily specific to any one model or weather dataset by recreating similar biases with alternatives of each.

clipping↗
DOE OSTI2023

Solar‐Driven CO 2 Conversion via Optimized Photothermal Catalysis in a Lotus Pod Structure

Abstract Photothermal CO 2 reduction is one of the most promising routes to efficiently utilize solar energy for fuel production at high rates. However, this reaction is currently limited by underdeveloped catalysts with low photothermal conversion efficiency, insufficient exposure of active sites, low active material loading, and high material cost. Herein, we report a potassium‐modified carbon‐supported cobalt (K + −Co−C) catalyst mimicking the structure of a lotus pod that addresses these challenges. As a result of the designed lotus‐pod structure which features an efficient photothermal C substrate with hierarchical pores, an intimate Co/C interface with covalent bonding, and exposed Co catalytic sites with optimized CO binding strength, the K + −Co−C catalyst shows a record‐high photothermal CO 2 hydrogenation rate of 758 mmol g cat −1 h −1 (2871 mmol g Co −1 h −1 ) with a 99.8 % selectivity for CO, three orders of magnitude higher than typical photochemical CO 2 reduction reactions. We further demonstrate with this catalyst effective CO 2 conversion under natural sunlight one hour before sunset during the winter season, putting forward an important step towards practical solar fuel production.

Wang, Hongmin↗
DOE OSTI2023

Solar–Driven CO 2 Conversion via Optimized Photothermal Catalysis in a Lotus Pod Structure

Photothermal CO 2 reduction is one of the most promising routes to efficiently utilize solar energy for fuel production at high rates. However, this reaction is currently limited by underdeveloped catalysts with low photothermal conversion efficiency, insufficient exposure of active sites, low active material loading, and high material cost. Herein, we report a potassium-modified carbon-supported cobalt (K + –Co–C) catalyst mimicking the structure of a lotus pod that addresses these challenges. As a result of the designed lotus-pod structure which features an efficient photothermal C substrate with hierarchical pores, an intimate Co/C interface with covalent bonding, and exposed Co catalytic sites with optimized CO binding strength, the K + –Co–C catalyst shows a record-high photothermal CO 2 hydrogenation rate of 758 mmol gcat –1 h –1 (2871 mmol gCo –1 h –1 ) with a 99.8 % selectivity for CO, three orders of magnitude higher than typical photochemical CO 2 reduction reactions. Here, we further demonstrate with this catalyst effective CO 2 conversion under natural sunlight one hour before sunset during the winter season, putting forward an important step towards practical solar fuel production.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Opportunities and challenges for flow-through hydrothermal pretreatment in advanced biorefineries

Hydrothermal pretreatment (HTP) using only water offers great potential to reduce the overall cost of the bioconversion process. However, traditional HTP performed in a batch has limitations in removing lignin and often needs to be performed under severe conditions to achieve reasonable pretreatment effects. Additionally, lignin left in the pretreated residue at these conditions is also highly condensed, thus possessing an even more adverse impact on the hydrolysis process, which requires high enzyme loadings. To address these technical challenges, HTP performed in a flow-through configuration was developed to simultaneously achieve near-complete hemicellulose recovery, high lignin removal and high sugar release. Despite facing challenges such as potentially large water usage, flow-through HTP still represents one of the most cost-effective and eco-friendly pretreatment methods. This review mainly covers the latest cutting-edge innovations of flow-through HTP along with structural and compositional changes of cellulose, hemicellulose, and lignin before and after pretreatment.

09 BIOMASS FUELS↗
DOE OSTI2020

Understanding the Charging Flexibility of Shared Automated Electric Vehicle Fleets

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL. In each of these four cities, SAEV simulations are performed using local projected electricity prices from the Regional Energy Deployment System (ReEDS) for a handful of supply side scenarios. A coordinated charging model is introduced that seeks to reduce fleet charging costs in response to time-varying electricity prices and increasing shares of personal trip demand served (between 1% and 25% of all metro trips served by the SAEV fleet). Simulation results are presented across various scenarios assuming fleetwide coordination to minimize charging energy costs while constrained by offering adequate mobility service to fleet customers. The results indicate that the SAEV charging load is highly flexible; energy costs were shown to reduce between 13% and 46% across a wide range of simulated scenarios. In addition, these savings were realized without detrimentally impacting the fleet’s ability to service trips.

autonomous vehicle↗
DOE OSTI2020

Subseasonal Variability of Elevated Dust Concentrations Over South Florida

Dust mass concentrations have been measured daily at Miami, Florida, in the summer months, and biweekly throughout the remaining months, since 1974. The 43-year record of dust mass concentrations indicate large daily, seasonal, and interannual variations, with most of the dust arriving within 5–8 episodes each summer. On average, dust arrives to Miami, Florida, 10 days after emission from North Africa, with measured concentrations depending on characteristics of the lower free-tropospheric winds due to the vast travel distance. Daily dust mass concentrations from July and August, the months that contribute the most to the annual mean, are used to characterize the synoptic conditions most favorable for dust transport. Two key regions are linked with the highest daily dust mass concentrations above Miami: (i) easterly winds, averaged over 850–500 mb, over the Tropical West Atlantic [15–25°N, 45–80°W], and (ii) southerly winds, similarly averaged, over the Florida Peninsula [20–30°N,75–80°W]. Winds within these two regions are enhanced when the North Atlantic subtropical high is displaced south and zonally elongated, relocating the western edge over Florida. A dust-transport-efficiency index, based on the maximum potential for dust to arrive above Miami with limited loss to deposition or mixing, identifies high-dust loading cases on the subseasonal scale. Monthly dust-transport-efficiency values agree well with the monthly dust trends over the 43-year time span. While seasonal dust loadings have been decreasing over Florida in the past decade, the transport efficiency has been increasing, possibly due to trends in the North Atlantic subtropical high.

54 ENVIRONMENTAL SCIENCES↗