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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Understanding the Oxygen Evolution Reaction Mechanism on CoO x using Operando Ambient-Pressure X-ray Photoelectron Spectroscopy

Photoelectrochemical water splitting is a promising approach for renewable production of hydrogen from solar energy and requires interfacing advanced water-splitting catalysts with semiconductors. Understanding the mechanism of function of such electrocatalysts at the atomic scale and under realistic working conditions is a challenging, yet important, task for advancing efficient and stable function. This is particularly true for the case of oxygen evolution catalysts and, here, we study a highly active Co 3 O 4 /Co(OH) 2 biphasic electrocatalyst on Si by means of operando ambient-pressure X-ray photoelectron spectroscopy performed at the solid/liquid electrified interface. Spectral simulation and multiplet fitting reveal that the catalyst undergoes chemical-structural transformations as a function of the applied anodic potential, with complete conversion of the Co(OH) 2 and partial conversion of the spinel Co 3 O 4 phases to CoO(OH) under precatalytic electrochemical conditions. Furthermore, we observe new spectral features in both Co 2p and O 1s core-level regions to emerge under oxygen evolution reaction conditions on CoO(OH). The operando photoelectron spectra support assignment of these newly observed features to highly active Co 4+ centers under catalytic conditions. Comparison of these results to those from a pure phase spinel Co 3 O 4 catalyst supports this interpretation and reveals that the presence of Co(OH) 2 enhances catalytic activity by promoting transformations to CoO(OH). The direct investigation of electrified interfaces presented in this work can be extended to different materials under realistic catalytic conditions, thereby providing a powerful tool for mechanism discovery and an enabling capability for catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Regulating Multiple Variables To Understand the Nucleation and Growth and Transformation of PbS Nanocrystal Superlattices

Nanocrystals (NCs) can self-assemble into ordered superlattices with collective properties, but the ability for controlling NC assembly remains poorly understandable toward achievement of desired superlattice. This paper regulates several key variables of PbS NC assembly (e.g., NC concentration and solubility, solvent type, evaporation rate, seed mediation and thermal treatment), and thoroughly exploits the nucleation and growth as well as subsequent superlattice transformation of NC assembles and underneath mechanisms. PbS NCs in toluene self-assemble into a single face-centered-cubic (fcc) and body-centered-cubic (bcc) superlattice, respectively, at concentrations ≤17.5 and ≥70 mg/mL, but an intermediate concentration between them causes the coexistence of the two superlattices. Differently, NCs in hexane or chloroform self-assemble into only a single bcc superlattice. Distinct controls of NC assembly in solvent with variable concentrations confirm the NC concentration/solubility mediated nucleation and growth of superlattice, in which an evaporation-induced local gradient of NC concentration causes simultaneous nucleation of the two superlattices. The observation for the dense packing planes of NCs in fast growing fcc rather than bcc reveals the difference of entropic driving forces responsible for the two distinct superlattices. Decelerating the solvent evaporation does not amend the superlattice symmetry, but improves the superlattice crystallinity. In addition to shrinking the superlattice volume, thermal treatment also transforms the bcc to an fcc superlattice at 175 °C. Through a seed-meditated growth, the concentration-dependent superlattice does not change lattice symmetry over the course of continuous growth, whereas the newly nucleated secondary small nuclei through a concentration change have relatively higher surface energy and quickly dissolve in solution, providing additional NC sources for the ripening of the primarily nucleated larger and stable seeds. Finally, the observations under multiple controls of assembly parameters not only provide insights into the nucleation and growth as well as transformation of various superlattice polymorphs but also lay foundation for controlled fabrication of desired superlattice with tailored property.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Understanding Structure–Property Relationships of MoO 3 -Promoted Rh Catalysts for Syngas Conversion to Alcohols

Rh-based catalysts have shown promise for the direct conversion of syngas to higher oxygenates. Although improvements in higher oxygenate yield have been achieved by combining Rh with metal oxide promoters, details of the structure of the promoted catalyst and the role of the promoter in enhancing catalytic performance are not well understood. In this work, we show that MoO 3 -promoted Rh nanoparticles form a novel catalyst structure in which Mo substitutes into the Rh surface, leading to both a 66-fold increase in turnover frequency and an enhancement in oxygenate yield. By applying a combination of atomically controlled synthesis, in situ characterization, and theoretical calculations, we gain an understanding of the promoter-Rh interactions that govern catalytic performance for MoO 3 -promoted Rh. We use atomic layer deposition to modify Rh nanoparticles with monolayer-precise amounts of MoO 3 , with a high degree of control over the structure of the catalyst. Through in situ X-ray absorption spectroscopy, we find that the atomic structure of the catalytic surface under reaction conditions consists of Mo–OH species substituted into the surface of the Rh nanoparticles. Furthermore, using density functional theory calculations, we identify two roles of MoO 3 : first, the presence of Mo–OH in the catalyst surface enhances CO dissociation and also stabilizes a methanol synthesis pathway not present in the unpromoted catalyst; and second, hydrogen spillover from Mo–OH sites to adsorbed species on the Rh surface enhances hydrogenation rates of reaction intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Toward an Understanding of Linear Scaling Relations through Energy Decomposition Analysis

The discovery of linear scaling relations has fundamentally changed the field of heterogeneous catalysis. The scaling relations have been rationalized based on the d-band theory, specifically a separation of sp and d electron contributions to adsorption energies. Within the framework of energy decomposition analysis, a full understanding of such a separation would require one to further break down the adsorption energy into distinct energy components such as electrostatics, polarization, charge transfer, and van der Waals interactions, and to examine the sp and d contributions to each of them. As a step in this direction, we analyzed the interaction energy between CH x (x = 1–4) adsorbates and fcc(100) transition metal surfaces (M = Cu, Ag, Au, Rh, and Pt), with the surfaces represented both as slabs in plane-wave density functional theory (pw-DFT) calculations and as atomic clusters in atomic-orbital basis density functional theory (ao-DFT) calculations. Through an absolutely localized molecular orbital (ALMO) based energy decomposition analysis of the ao-DFT adsorption energy, each of the interaction energy components (electrostatics, polarization, van der Waals, and charge transfer) was found to follow its own scaling relations, with an intricate interplay among these energy components yielding the overall scaling relations for the total adsorption energies. Using the recently introduced ALMO-based polarization and charge-transfer analysis schemes, we further dissected polarization into metal surface and adsorbate contributions, and charge transfer into metal → adsorbate and adsorbate → metal contributions. The contributions from the sp and d electrons of the metal to these terms were further quantified, and the dominant role of the metal d electrons was reaffirmed. These results shed light on how CHx adsorbates interact with metal surfaces and further reveal the physical origin of the scaling relations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Understanding the eco-geomorphologic feedback of coastal marsh under sea level rise: vegetation dynamic representations, processes interaction, and parametric sensitivity

A growing number of coastal eco-geomorphologic modeling studies have been conducted to understand coastal marsh evolution under sea-level rise (SLR). Although these models quantify marsh topographic change as a function of sedimentation and erosion, their representations of vegetation dynamics that control organic sedimentation differ. How vegetation dynamic schemes contribute to simulation outcomes is not well quantified. Additionally, the sensitivity of modeling outcomes to parameter selection in the available formulations has not been rigorously tested to date, especially under the influence of an accelerating SLR. In this paper, we used a coastal eco-geomorphologic model with different vegetation dynamic schemes to investigate the eco-geomorphologic feedbacks of coastal marshes and parametric sensitivity under SLR scenarios. We found that marsh platform relief increased with sea level rise rate. The simulations with different vegetation schemes exhibited different spatial-temporal variations in elevation and biomass. The nonlinear Spartina scheme presented the most resilient prediction with generally the highest marsh accretion and vegetation biomass, and the least elevation relief under SLR. But the linear Spartina scheme predicts the lowest unvegetated-vegetated ratio. We also found that vegetation-related parameters and sediment diffusivity, which were not well measured or discussed in previous studies, were identified as some of the most critical parameters. Additionally, the model sensitivity to vegetation-related parameters increased with SLR rates. The identified most sensitive parameters may inform how to appropriately choose modeling representations of key processes and parameters for different coastal marsh landscapes under SLR, and demonstrate the importance of future field measurements of these key parameters.

58 GEOSCIENCES↗
DOE OSTI2022

Understanding the Microphysical Control and Spatial‐Temporal Variability of Warm Rain Probability Using CloudSat and MODIS Observations

Abstract By combining measurements from MODIS and the CloudSat radar, we develop a parameterization scheme to quantify the combined microphysical controls by liquid water path (LWP) and cloud droplet number concentration (CDNC) of the probability of precipitation (PoP) in marine low cloud over tropical oceans. We demonstrate that the spatial‐temporal variation of grid‐mean in‐cloud can be largely explained by the variation of the joint probability density function of LWP and CDNC in the phase space specified by the bivariate PoP (LWP and CDNC) function. Through a series of sensitivity tests guided by this understanding, we find that in the Southeastern Pacific and Atlantic the stratocumulus to cumulus transition of the is mainly due to the variation of CDNC while the annual cycle is mainly due to the variation of LWP. The results of this study provide a viable way to diagnose the root cause of warm rain problems in global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Exploiting SMILEs and the CMIP5 Archive to Understand Arctic Climate Change Seasonality and Uncertainty

Arctic Amplification (AA) exhibits a distinct seasonal dependence; it is weakest in boreal summer and strongest in winter. Here, we analyze simulations from single-model initial-condition large ensembles and Coupled Model Intercomparison Project Phase 5 to decipher the seasonal evolution of Arctic climate change. Models agree that the annual maximum AA shifts from autumn into winter over the 21st century, accompanied by similar shifts in sea-ice loss and surface turbulent heat fluxes, whereas the maximum precipitation shifts only into late autumn. However, the exact seasonal timing and magnitude of these shifts are highly uncertain. Decomposing the uncertainty into model structural differences, emission scenarios, and internal variability reveals that model differences dominate the total uncertainty, which also undergo autumn-to-winter shifts. We also find that the scenario uncertainty is unimportant for projections of AA. These results highlight that understanding model differences is critical to reducing uncertainty in projected Arctic climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Understanding Precipitation Bias Sensitivities in E3SM-Multi-Scale Modeling Framework From a Dilution Framework

We investigate a set of Energy Exascale Earth System Model Multi-scale modeling framework (MMF) (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding the Cascade: Removing GCM Biases Improves Dynamically Downscaled Climate Projections

Polarization surrounding bias correction (BC) in creating climate projections arises from its lack of physicality. Here, we perform and analyze 18 dynamical downscaling simulations (with and without BC) to better understand the physical impacts of BC, applied before downscaling, on regional climate output across the western United States. Without BC, downscaled precipitation is systematically and unrealistically wet biased compared to a hierarchy of observationally based datasets over the 1980–2014 period due to cascading mean–state Global Climate Model (GCM) biases: (a) overly strong lower–tropospheric lapse rates (5 K/km), (b) overly cold (2 K) tropospheric temperatures, and (c) anomalous mid–tropospheric cyclonic vorticity advection. With BC, downscaled precipitation (snow) biases are virtually eliminated (halved). Identified GCM biases are common to the broader Coupled Model Intercomparison Project ensemble. Physical effects of BC on the quality of the regionalized projections, pending an evaluation of BC's distortion of the downscaled climate response, may motivate its broader application by dynamical downscalers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Expanded Understanding of the Western Antarctic Peninsula Sea‐Ice Environment Through Local and Regional Observations at Palmer Station

Abstract The Western Antarctic Peninsula (WAP) has been experiencing rapid regional warming since at least the 1950s, however, the impacts of this warming at the local scale are variable and nuanced. Previous studies that have linked sea‐ice variability to biogeochemical cycles and food web dynamics often combine local‐scale biogeochemical data with coarse‐resolution regional satellite sea‐ice data, which may not adequately capture local sea‐ice conditions. In this study, we analyzed local‐scale in situ sea‐ice observations collected as part of a 28‐year record (1992–2020) from the Palmer Long‐Term Ecological Research site at Anvers Island, mid‐WAP, in conjunction with isotopically‐derived sea‐ice meltwater (SIM) fractions and satellite‐derived sea‐ice motion and concentration, to quantify the variability and long‐term trends in local sea‐ice behavior. In situ sea ice observations at Palmer Station displayed higher variability than satellite observations and showed no significant declines over this time, despite region‐wide declines identified in prior studies. Higher spring SIM fractions were attributed to strong northward sea‐ice motion throughout the winter. Applying these local‐scale sea‐ice insights to similarly scaled stratification and chlorophyll‐ a measurements, we found that a longer‐lasting, more consistent sea‐ice pack led to greater water column stratification following the spring sea‐ice retreat. Greater sea‐ice persistence and stronger stratification led to larger peaks in chlorophyll‐ a , though sea‐ice metrics did not explain the positive temporal trends in either stratification strength or chlorophyll‐ a . Through this study, we identify how local sea‐ice observations and meltwater data can enhance satellite data to build an understanding of the intricate connections between ice, water column dynamics, and phytoplankton.

Goodell, E.↗
DOE OSTI2024

Permafrost Carbon: Progress on Understanding Stocks and Fluxes Across Northern Terrestrial Ecosystems

Significant progress in permafrost carbon science made over the past decades include the identification of vast permafrost carbon stocks, the development of new pan-Arctic permafrost maps, an increase in terrestrial measurement sites for CO 2 and methane fluxes, and important factors affecting carbon cycling, including vegetation changes, periods of soil freezing and thawing, wildfire, and other disturbance events. Process-based modeling studies now include key elements of permafrost carbon cycling and advances in statistical modeling and inverse modeling enhance understanding of permafrost region C budgets. By combining existing data syntheses and model outputs, the permafrost region is likely a wetland methane source and small terrestrial ecosystem CO 2 sink with lower net CO 2 uptake toward higher latitudes, excluding wildfire emissions. For 2002–2014, the strongest CO2 sink was located in western Canada (median: -52 g C m -2 y -1 ) and smallest sinks in Alaska, Canadian tundra, and Siberian tundra (medians: -5 to -9 g C m -2 y -1 ). Eurasian regions had the largest median wetland methane fluxes (16–18 g CH4 m -2 y -1 ). Quantifying the regional scale carbon balance remains challenging because of high spatial and temporal variability and relatively low density of observations. More accurate permafrost region carbon fluxes require: (a) the development of better maps characterizing wetlands and dynamics of vegetation and disturbances, including abrupt permafrost thaw; (b) the establishment of new year-round CO 2 and methane flux sites in underrepresented areas; and (c) improved models that better represent important permafrost carbon cycle dynamics, including non-growing season emissions and disturbance effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Insights on Simulating Summer Warming of the Great Lakes: Understanding the Behavior of a Newly Developed Coupled Lake-Atmosphere Modeling System

The Laurentian Great Lakes are the world's largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one-dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two-way coupled modeling system using the Weather Research and Forecasting model and a three-dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake-atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two-way coupled modeling system and our observation-driven modeling system, we find that coupled-lake atmosphere dynamics can lead to a higher LST during June-September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability

Snow plays a critical role in carbon cycling, vegetation dynamics, and permafrost hydrology at high latitudes by influencing surface energy exchange. Predicting snow distribution patterns is essential for understanding the evolution of Arctic ecosystems, yet scaling process-level knowledge to landscape predictions remains challenging. Here, we analyze snow depth (2019 and 2022), terrain elevation, and vegetation height from a watershed on the Seward Peninsula, Alaska, to examine how topography and shrubs shape snow redistribution across spatial scales. We find that snow depth is strongly coupled to terrain at scales below ∼60 m but becomes increasingly decoupled at larger scales. The topographic model of snow depth variation, which transforms terrain data to align with these scale-dependent snow patterns, is well correlated with local snow depth variations (linear fit R 2 > 0.5 for 85% of 100-m patches). A machine learning reconstruction of shrub canopy snow trapping reveals a simple exponential relationship between canopy structure and snow accumulation ( R 2 = 0.59), highlighting the combined influence of topography and vegetation on snow distribution. Together, these empirical relationships capture much of the observed snow variability in the watershed ( R 2 = 0.49, root mean square error (RMSE) = 30 cm), though systematic limitations persist in areas of strong scour and at coarser scales where wind-terrain interactions are more complex. These findings provide a framework for more efficient snow depth prediction and offer insights to improve snow-vegetation feedback representation in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗
DOE OSTI2025

Understanding the Recent Increase in Landfalling Tropical Cyclones Over Florida's Gulf Coast

Unlike Florida's Atlantic Coast, the Gulf Coast of Florida has seen heightened tropical cyclone (TC) activity in recent decades with several destructive landfalls. Here, we attempt to understand this regional contrast using a suite of observations for the period 1979–2024. First, we demonstrate that while the El Niño Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO) can explain ~23% of the interannual variability in landfalls over the Gulf Coast, the variance explained by them for the Atlantic Coast is statistically insignificant. Next, we show that this striking difference may be attributed to the regional patterns of wind shear, steering flow and air-sea thermodynamic state excited by those modes of variability. The differential control exerted by ENSO, AMO, and NAO on landfalling Florida TCs, in combination with decadal trends in those modes, is likely responsible for the observed increases in landfalls over Florida's Gulf Coast.

Florida↗
DOE OSTI2017

Understanding materials challenges for rechargeable ion batteries with in situ transmission electron microscopy

An in-depth understanding of material behaviours under complex electrochemical environment is critical for the development of advanced materials for the next-generation rechargeable ion batteries. The dynamic conditions inside a working battery had not been intensively explored until the advent of various in situ characterization techniques. Real-time transmission electron microscopy of electrochemical reactions is one of the most significant breakthroughs poised to enable radical shift in our knowledge on how materials behave in the electrochemical environment. This review, therefore, summarizes the scientific discoveries enabled by in situ transmission electron microscopy, and specifically emphasizes the applicability of this technique to address the critical challenges in the rechargeable ion battery electrodes, electrolyte and their interfaces. New electrochemical systems such as lithium–oxygen, lithium–sulfur and sodium ion batteries are included, considering the rapidly increasing application of in situ transmission electron microscopy in these areas. A systematic comparison between lithium ion-based electrochemistry and sodium ion-based electrochemistry is also given in terms of their thermodynamic and kinetic differences. The effect of the electron beam on the validity of in situ observation is also covered. This review concludes by providing a renewed perspective for the future directions of in situ transmission electron microscopy in rechargeable ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2017

Molecular understanding of polyelectrolyte binders that actively regulate ion transport in sulfur cathodes

Polymer binders in battery electrodes may be either active or passive. This distinction depends on whether the polymer influences charge or mass transport in the electrode. Though it is desirable to understand how to tailor the macromolecular design of a polymer to play a passive or active role, design rules are still lacking, as is a framework to assess the divergence in such behaviors. We reveal the molecular-level underpinnings that distinguish an active polyelectrolyte binder designed for lithium-sulfur batteries from a passive alternative. The binder, a cationic polyelectrolyte, is shown to both facilitate lithium-ion transport through its reconfigurable network of mobile anions and restrict polysulfide diffusion from mesoporous carbon hosts by anion metathesis, which we show is selective for higher oligomers. These attributes then allow cells to be operated for > 100 cycles with excellent rate capability using cathodes with areal sulfur loadings up to 8.1 mg cm -2 .

25 ENERGY STORAGE↗
DOE OSTI2018

Understanding the apparent fractional charge of protons in the aqueous electrochemical double layer

A detailed atomic-scale description of the electrochemical interface is essential to the understanding of electrochemical energy transformations. In this work, we investigate the charge of solvated protons at the Pt(111) | H 2 O and Al(111) | H 2 O interfaces. Using semi-local density functional theory as well as hybrid functionals and embedded correlated wavefunction methods as higher-level benchmarks, we show that the effective charge of a solvated proton in the electrochemical double layer or outer Helmholtz plane at all levels of theory is fractional, when the solvated proton and solvent band edges are aligned correctly with the Fermi level of the metal ( E F ). In conclusion, the observed fractional charge in the absence of frontier band mis-alignment arises from a significant overlap between the proton and the electron density from the metal surface, and results in an energetic difference between protons in bulk solution and those in the outer Helmholtz plane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗