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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 163 records · Page 9

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗

Modeling plasma-induced surface charge effects on CO 2 activation by single atom catalysts supported on reducible and irreducible metal oxides

Abstract The accumulation of negative surface charge on catalytic surfaces in the presence of low-temperature plasma (LTP) could influence catalytic performance. However, it is difficult to disentangle the role of surface charging and other LTP catalytic effects in experiment. Herein, we use density functional theory (DFT) modeling to understand the effect of plasma-induced surface charging on CO 2 activation by atomically dispersed single atom (SA) catalysts on both reducible and irreducible metal oxide supports. We model CO 2 adsorption strength and CO 2 dissociation barriers for Co 1 , Ni 1 , Cu 1 , Rh 1 , Pd 1 , and Ag 1 SAs on both reducible and irreducible supports, namely, CeO 2 (100), TiO 2 (101), and γ -Al 2 O 3 (110), to elucidate trends. We find that accumulated surface charge on the SA increases the CO 2 adsorption strength and decreases the CO 2 dissociation barrier for all studied SA/support combinations. For both charged and uncharged (neutral) systems, SAs on the reducible CeO 2 (100) support generally adsorb CO 2 more weakly compared to when on irreducible supports like γ -Al 2 O 3 (110). SAs on γ -Al 2 O 3 (110) typically have larger barriers for CO 2 dissociation for both charged and uncharged systems compared to TiO 2 (101) and CeO 2 (100). The magnitude of surface charging effects on CO 2 binding energies and dissociation barriers depends sensitively on both the SA and the support. In some cases, the CO 2 activation trends qualitatively change between neutral and charged systems for a fixed SA across different supports. This DFT modeling study demonstrates that surface charging should be considered in strong electric fields because it can have a large effect on molecule adsorption and bond-breaking on catalytic surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Physics-Based Model to Represent Membrane-Electrode Assemblies of Solid-Oxide Fuel Cells Based on Gadolinium-Doped Ceria

This paper reports a physics-based model that predicts membrane-electrode assembly (MEA) performance of solid-oxide fuel cells (SOFCs) with Ce 0.9 Gd 0.1 O 2− δ (GDC10) electrolyte membranes. The paper derives self-consistent thermodynamic and transport properties for GDC1o mobile charged defects (oxide vacancies and reduced-ceria small polarons) by fitting published measurements of oxygen non-stoichiometry and conductivity over ranges of temperature and O 2 partial pressures. The button-cell model is applied to evaluate how mixed ionic-electronic conductivity influences the performance of an SOFC MEA with a GDC10 electrolyte sandwiched between a porous, composite Ni-GDC10 anode and a porous, composite cathode of Sm 0.5 Sr 0.5 CoO 3− δ (i.e., SSC) and GDC10. SSC properties are also derived by fitting published conductivity and oxygen non-stoichiometry measurements. Mixed conductivity of GDC10 and competing charge transfer reactions at both electrodes reduce open circuit voltages due to leakage current and buildup of defect concentrations at electrode-electrolyte interfaces. To fit polarization data, the button-cell model includes heterogeneous reaction rates for defect incorporation on the GDC10 surface along with Butler–Volmer expressions derived for competing charge transfer reaction rates from rigorous analyses assuming rate-limiting, elementary charge transfer reactions for each electrode. The calibrated MEA model can support rigorous SOFC modeling with GDC10 electrolytes over the range of conditions within a fully operating cell.

Electrochemistry↗

High-speed mapping of surface charge dynamics using sparse scanning Kelvin probe force microscopy

Unraveling local dynamic charge processes is vital for progress in diverse fields, from microelectronics to energy storage. This relies on the ability to map charge carrier motion across multiple length- and timescales and understanding how these processes interact with the inherent material heterogeneities. Towards addressing this challenge, we introduce high-speed sparse scanning Kelvin probe force microscopy, which combines sparse scanning and image reconstruction. This approach is shown to enable sub-second imaging (>3 frames per second) of nanoscale charge dynamics, representing several orders of magnitude improvement over traditional Kelvin probe force microscopy imaging rates. Bridging this improved spatiotemporal resolution with macroscale device measurements, we successfully visualize electrochemically mediated diffusion of mobile surface ions on a LaAlO 3 /SrTiO 3 planar device. Such processes are known to impact band-alignment and charge-transfer dynamics at these heterointerfaces. Furthermore, we monitor the diffusion of oxygen vacancies at the single grain level in polycrystalline TiO 2 . Through temperature-dependent measurements, we identify a charge diffusion activation energy of 0.18 eV, in good agreement with previously reported values and confirmed by DFT calculations. Together, these findings highlight the effectiveness and versatility of our method in understanding ionic charge carrier motion in microelectronics or nanoscale material systems.

25 ENERGY STORAGE↗

How Does Water Dissociation Work in Bipolar Membranes?

Bipolar membranes (BPMs) create counteracting spatial gradients of pH and electrostatic potential in electrochemical systems, enabling applications in pH regulation, electrocatalysis, and separations. At the polarized junction of a BPM the water dissociation (WD, 2H2O ⇌ H3O+ + OH-) reaction can be driven, but it remains poorly understood. In this Perspective, we integrate molecular insights from bulk-water autoionization and the associated field effects with continuum descriptions of BPM electrostatics and experimental WD kinetic analyses to describe possible mechanisms of voltage-driven WD. Pristine BPM junctions highlight both the limits of primarily electric-field-driven WD and the practical challenges of junction stability at extreme reverse bias. Introducing heterogeneous catalyst layers, commonly metal oxides and graphene oxides, accelerates WD by orders of magnitude through hypothesized coupled effects in which surface acid-base functionality and high-density hydroxyl sites mediate proton-transfer steps, and catalyst mobile electronic/ionic charges redistribute the junction electric potential drop to shape the local electric fields and reactive microenvironments. Kinetic analyses suggest two regimes of heterogeneous WD mechanism, including field-driven ordering of interfacial water and a Second-Wien-Effect dissociation-barrier lowering. We conclude by defining the key unknown variables (local pH, electrostatic potential, catalyst charge state and relationships among mechanisms) and outlining experimental and multiscale modeling strategies needed for predictive WD catalysis and for controlling related ion-transfer reactions.

Wu, Yifan↗

Single Nanoflake Photoelectrochemistry Reveals Intrananoflake Doping Heterogeneity That Explains Ensemble-Level Photoelectrochemical Behavior

Transition metal dichalcogenide (TMD) nanoflake thin films are attractive electrode materials for photoelectrochemical (PEC) solar energy conversion and sensing applications, but their photocurrent quantum yields are generally lower than those of bulk TMD electrodes. The poor PEC performance has been primarily attributed to enhanced charge carrier recombination at exposed defect and edge sites introduced by the exfoliation process. Here, a single nanoflake PEC approach reveals how an alternative effect, doping heterogeneity, limits ensemble-level PEC performance. Photocurrent mapping and local photocurrent–potential (i–E) measurements of MoS 2 nanoflakes exfoliated from naturally occurring bulk crystals revealed the presence of n- and p-type domains within the same nanoflake. Interestingly, the n- and p-type domains in the natural MoS 2 nanoflakes were equally efficient for iodide oxidation and tri-iodide reduction (IQE values exceed 80%). At the single domain-level, the natural MoS 2 nanoflakes were nearly as efficient as nanoflakes exfoliated from synthetic n-type MoS 2 crystals. Single domain-level i–E measurements explain why natural MoS 2 nanoflakes exhibit an n-type to p-type photocurrent switching effect in ensemble-level measurements: the n- and p-type diode currents from individual domains oppose each other upon illuminating the entire nanoflake, resulting in zero photocurrent at the switching potential. Furthermore, the doping heterogeneity effect is likely due to nonideal stoichiometry, where p-type domains are S-rich according to XPS measurements. Although this doping heterogeneity effect limits photoanode or photocathode performance, these findings open the possibility to synthesize efficient TMD nanoflake photocatalysts with well-defined lateral p- and n-type domains for enhanced charge separation.

14 SOLAR ENERGY↗

Low-Rate Cycling Regeneration Sustains NMC811–Graphite Battery Performance through Extreme Ultrafast Charging

Urban air mobility (UAM) systems, such as electric vertical takeoff and landing (eVTOL) aircraft, require batteries capable of extreme ultrafast charging to support high-frequency operations. Here, in this work, we evaluate the electrochemical stability of NMC811–graphite full cells using a complex mixed-modal protocol designed to simulate the aggressive turnaround demands of UAM missions. We demonstrate that incorporating a periodic low-rate (0.3C) “regeneration” cycle enables cells to maintain 96% capacity retention over 900 cycles, despite repeated exposure to ultrafast pulses. To validate the efficacy of this regeneration mechanism, we performed simplified control experiments comparing continuous 10C charging against a 10C–0.3C interleaved protocol. Advanced characterization reveals that while mechanical particle fracture is pervasive at these rates, the regeneration cycles decelerate the electrochemical degradation by resolving spatially heterogeneous Ni oxidation states and relaxing lithium-ion concentration gradients. These findings provide a vital mechanistic framework for battery operation, proving that restorative charging can effectively delay and mitigate failure in demanding UAM applications.

batteries↗

Electrostatic Asymmetry of Wurtzite Nanocrystals and Resulting Photocatalytic Properties

Efficient light absorption and high energy of charge carriers of zinc cadmium sulfide (ZCS) make this semiconductor attractive for many photocatalytic reactions. Despite marked successes in shape-controlled synthesis of ZCS central to their photocatalytic performance, recombination of charge carriers as they migrate through the nanoscale particles results in losses of excitation energy, markedly reducing the photocatalytic activity of ZCS and other heterogeneous photocatalysts. Here, in this study, we show that the electrostatic asymmetry of nanostructures, previously discovered for nearly spherical nanoparticles, also manifests in wurtzite ZCS with planar geometry. The electrostatic asymmetry assists charge separation and substantially increases the yield of photocatalytic reactions in monocrystalline ZCS. The synthesized ZCS nanorods and nanoplates with identical chemical composition were found to have markedly different photocatalytic activity for evolution of hydrogen in water. Despite much smaller specific surface areas, the ~500 nm wide nanoplates displayed a hydrogen evolution rate 12 times higher than the ~35 nm long nanorods, also outperforming other ZCS photocatalysts. Experimental and computational data indicate that the homo- and heterojunction-free ZCS nanoplates with continuous wurtzite lattice behave essentially as nanoscale dipoles with intrinsic dipole moment as high as 48.39 D per unit cell. Electric-field-directed migration of charge carriers stimulates their localization on opposite parts of the nanoplates. Direct imaging of the intraparticle electrical field using off-axis electron holography confirmed their electrostatic asymmetry. Polarization-enhanced charge separation provides a new pathway to efficient and stable photocatalysts for sustainable energy technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BEAST DB: Grand-Canonical Database of Electrocatalyst Properties

We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogeneous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze the electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain a granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage.

database↗

Effects of composition and pressure on electronic states of iron in bridgmanite

Electronic states of iron in the lower mantle's dominant mineral, (Mg,Fe,Al)(Fe,Al,Si)O 3 bridgmanite, control physical properties of the mantle including density, elasticity, and electrical and thermal conductivity. However, the determination of electronic states of iron has been controversial, in part due to different interpretations of Mössbauer spectroscopy results used to identify spin state, valence state, and site occupancy of iron. We applied energy-domain Mössbauer spectroscopy to a set of four bridgmanite samples spanning a wide range of compositions: 10–50% Fe/total cations, 0–25% Al/total cations, 12–100% Fe 3+ /total Fe. Measurements performed in the diamond-anvil cell at pressures up to 76 GPa below and above the high to low spin transition in Fe 3+ provide a Mössbauer reference library for bridgmanite and demonstrate the effects of pressure and composition on electronic states of iron. Results indicate that although the spin transition in Fe 3+ in the bridgmanite B-site occurs as predicted, it does not strongly affect the observed quadrupole splitting of 1.4 mm/s, and only decreases center shift for this site to 0 mm/s at ~70 GPa. Thus center shift can easily distinguish Fe 3+ from Fe 2+ at high pressure, which exhibits two distinct Mössbauer sites with center shift ~1 mm/s and quadrupole splitting 2.4–3.1 and 3.9 mm/s at ~70 GPa. Correct quantification of Fe 3+ /total Fe in bridgmanite is required to constrain the effects of composition and redox states in experimental measurements of seismic properties of bridgmanite. Furthermore, in Fe-rich, mixed-valence bridgmanite at deep-mantle-relevant pressures, up to ~20% of the Fe may be a Fe 2.5+ charge transfer component, which should enhance electrical and thermal conductivity in Fe-rich heterogeneities at the base of Earth's mantle.

58 GEOSCIENCES↗

Microstructure Scale Lithium-Ion Battery Modeling, Part IV: The Representativity of Microstructure Parameters and Electrochemical Response

Lithium-ion battery electrochemical models require an accurate description of the electrodes microstructures to be predictive, that can be achieved through nanoscale imaging. Such observations are however limited by their field of view (FOV), as they provide only a subset of the whole electrode volume that does not necessarily represent the whole electrode microstructure heterogeneity, and therefore can bias the analysis. A representativity analysis has been performed on the microstructure parameters and, in a novel way, on the full cell electrochemical response to evaluate the predictions representativeness, and thus relevance, of a microstructure scale electrochemical model. The microstructure parameter deviation propagations to the electrochemical response have been quantified for different charge rates. This defines a threshold for the microstructure parameters FOV for a desired maximum deviation of the electrochemical response. Electrochemical model shows cell representative section areas are increasing with C-rate, due to higher in-plane heterogeneities, indicating larger FOVs are required specifically for fast charge modeling. Representativity analysis determines a cell FOV of 144.4 × 154.4 μm 2 is large enough to establish a convergence on the representative section areas for low-intermediate C-rate (≤2.5 C), therefore positively concludes on the model representativeness for these rates, but is not large enough to conclude for higher rates.

25 ENERGY STORAGE↗

Advanced diagnostics to evaluate heterogeneity in lithium-ion battery modules

Battery packs for electric and stationary applications experience varied operating conditions, including abuse—e.g., fast charging, overcharging, thermal, vibration, shock, etc.—throughout their lifetimes. Innovative diagnostic tools and algorithms that go beyond single cells and deal with modules and packs are essential for early detection of off-normal issues. High-resolution tools with known detection limits are key to developing appropriate mitigation strategies. With the advent of rapid impedance spectroscopy that can generate a broadband impedance spectrum in ~10 sec, the case for impedance-based diagnostics that can be readily aligned with other methods, such as incremental capacity or dQ.dV -1 , has become promising. This study used the aforementioned diagnostic methods to identify realistic in-vehicle battery abnormalities (e.g., localized self-discharge and non-uniform aging), in series (up to 10S) and parallel (4P) strings, using 16 Ah graphite/NMC cells. The impedance-based diagnostic is found to be sensitive to the string size and state. Depending on the type of abnormality, detection frequency varied. The dQ.dV -1 method showed the potential to detect long-term aging-related heterogeneity in modules. In general, both the impedance and dQ.dV -1 methods were able to detect series strings’ abnormalities, but struggled to find those issues within parallel modules.

25 ENERGY STORAGE↗