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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Stromataxic Stabilization of a Metastable Layered ScFeO3 Polymorph

Metastable polymorphs--materials with the same stoichiometry as the ground state but a different crystal structure--enable many critical technologies. This work describes the development of a stabilization approach for metastable polymorphs that are difficult to achieve through other stabilization techniques (such as epitaxy or quenching) called stromataxy. Stromataxy is a method based on controlling the precursor structure during the initial stages of material growth to dictate phase formation. To illustrate this approach, we controlled the atomic layering of the precursors of ScFeO3 and stabilized the metastable P63cm phase, under conditions that previously led to the ground-state Ia3¯ bixbyite phase. Ab initio mechanistic calculations highlight the importance of the variable oxidation state of Fe and the layer stability during layer-by-layer growth. The broad applicability of a stromataxy approach was demonstrated by stabilizing this metastable phase on substrates that have previously been shown to stabilize other polymorphs under continuous growth. Stromataxy is shown as a viable option for accessing polymorphs that are close in energy, difficult to differentiate by strain, or that lack a well epitaxially matched substrate.

calculations↗
DOE OSTI2024

Assessing Composite Structure in Metal–Organic Framework-Polymer Mixed-Matrix Membranes

Metal-organic frameworks (MOFs) are renowned for their tunable structure, porosity, and internal chemistry, with demonstrated applications in molecular separations, storage, and conversion. While they are widely usable, the powdery characteristics of MOF materials can be limiting for large-scale processing and implementation in devices. Incorporating MOF particles into polymer supports affords engineering solutions to overcome these issues, yet the nature of the resulting composites is difficult to assess. Here, in this work, we present spectroscopic and calorimetric methods that we believe help establish a holistic physicochemical picture of the composite structure using a series of Zr MOFs with different pore sizes as a testbed. Power law decays are observed in X-ray scattering profiles in low q-space ranging between 2.4 and 3.3, which we interpret as changes in scattering due to polymer infiltrating MOF particles. This interpretation is supported by solid-state nuclear magnetic resonance spectroscopy and differential scanning calorimetry measurements that identify populations of the MOF-associated polymer. Additionally, positron annihilation lifetime spectroscopy measurements collected on a series of composites with different MOF-polymer ratios show multiple decay constants, each correlated to a different free volume elements. In combination with the spectroscopic, calorimetric, and scattering results, we utilize the trends in decay constants as a function of polymer mass fraction to hypothesize a polymer infiltration mechanism whereby large pores are preferentially filled, followed by small pores and, later still, interstitial spaces between particles. Even with vigorous investigation of polymer, MOF, and interface characteristics, the complex and heterogeneous nature of the composites makes absolute structural assertions difficult. We envision that the approaches demonstrated here will be a useful foundation to assess and ultimately guide the design of future MOF-polymer composites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Contrasting Trivalent Lanthanide and Actinide Complexation by Polyoxometalates via Solution-State NMR

Deciphering the solution chemistry and speciation of actinides is inherently difficult due to radioactivity, rarity, and cost constraints, especially for transplutonium elements. In this context, the development of new chelating platforms for actinides and associated spectroscopic techniques is particularly important. In this study, we investigate a relatively overlooked class of chelators for actinide binding, namely, polyoxometalates (POMs). We provide the first NMR measurements on americium–POM and curium–POM complexes, using one-dimensional (1D) 31 P NMR, variable-temperature NMR, and spin-lattice relaxation time (T 1 ) experiments. The proposed POM–NMR approach allows for the study of trivalent f-elements even when only microgram amounts are available and in phosphate-containing solutions where f-elements are typically insoluble. The solution-state speciation of trivalent americium, curium, plus multiple lanthanide ions (La 3+ , Nd 3+ , Sm 3+ , Eu 3+ , Yb 3+ , and Lu 3+ ), in the presence of the model POM ligand PW 11 O 39 7– was elucidated and revealed the concurrent formation of two stable complexes, [M III (PW 11 O 39 )(H 2 O) x ] 4– and [M III (PW 11 O 39 ) 2 ] 11– . Interconversion reaction constants, reaction enthalpies, and reaction entropies were derived from the NMR data. The NMR results also provide experimental evidence of the weakly paramagnetic nature of the Am 3+ and Cm 3+ ions in solution. Furthermore, the study reveals a previously unnoticed periodicity break along the f-element series with the reversal of T 1 relaxation times of the 1:1 and 1:2 complexes and the preferential formation of the long T 1 species for the early lanthanides versus the short T 1 species for the late lanthanides, americium, and curium. Furthermore, given the broad variety of POM ligands that exist, with many of them containing NMR-active nuclei, the combined POM–NMR approach reported here opens a new avenue to investigate difficult-to-study elements such as heavy actinides and other radionuclides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Natural Charge-Transfer Analysis: Eliminating Spurious Charge-Transfer States in Time-Dependent Density Functional Theory via Diabatization, with Application to Projection-Based Embedding

For many types of vertical excitation energies, linear-response time-dependent density functional theory (LR-TDDFT) offers a useful degree of accuracy combined with unrivaled computational efficiency, although charge-transfer excitation energies are often systematically and dramatically underestimated, especially for large systems and those that contain explicit solvent. As a result, low energy electronic spectra of solution-phase chromophores often contain tens to hundreds of spurious charge-transfer states, making LR-TDDFT needlessly expensive in bulk solution. More nefariously, intensity borrowing by the low-energy charge-transfer states can affect intensities of the valence excitations even if those excitation energies are accurate. At higher excitation energies, it is difficult to distinguish spurious CT states from genuine charge-transfer-to-solvent (CTTS) excitations. In this work, we introduce an automated diabatization scheme that enables fast and effective screening of the CTTS acceptor space in bulk solution. Our procedure introduces the concept of “natural charge-transfer orbitals”, which provide a means to isolate characteristic pairs of orbitals that are most likely to participate in a CTTS excitation. The projection of these orbitals onto solvent-centered virtual orbitals provides a criterion for defining the most important solvent molecules in a given excitation. We apply this method to analyze an ab initio molecular dynamics (MD) trajectory of I-(aq) and report the lowest-energy CTTS band in the absorption spectrum. Our results are in excellent agreement with experimental measurements for bulk I-(aq), and only one-third of the water molecules in the I-(H2O)96 simulation cell need to be described with LR-TDDFT in order to obtain excitation energies that are converged to < 0.1 eV. The tools introduced herein will improve the accuracy, efficiency, and usability of LR-TDDFT in solution-phase environments

Carter-Fenk, Kevin D.↗
DOE OSTI2021

Actinide Molten Salts: A Machine-Learning Potential Molecular Dynamics Study

We know that actinide molten salts represent a class of important materials in nuclear energy. Understanding them at a molecular level is critical to proper and optimal design of relevant technological applications. Yet, owing to the complexity of electronic structure due to the 5f orbitals, computational studies of heavy elements in condensed phases using ab initio potentials to study the structure and dynamics of these elements embedded in molten salts are difficult. This lack of efficient computational protocols makes it difficult to obtain information on properties that require extensive statistical sampling like transport. To tackle this problem, we adopted a machine-learning approach to study ThCl 4 -NaCl and UCl 3 -NaCl binary systems. The machine-learning potential, with the density functional theory accuracy, allows us to obtain long molecular dynamics trajectories (ns) for large systems (10 3 atoms) at a considerably low computing cost, thereby efficiently gaining information about their bonding structures, thermodynamics, and dynamics at a range of temperature. We observed a considerable change in the coordination environments of actinide elements and their characteristic coordination-sphere lifetime. Our study also suggests that actinides in molten salts may not follow well known entropy-scaling laws.

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

Voltage-Based Strategies for Preventing Battery Degradation under Diverse Fast-Charging Conditions

Maintaining safe operating conditions is a key challenge for high-performance lithium-ion battery applications. The lithium-plating reaction remains a risk during charging, but limited studies consider the highly variable charging conditions possible in commercial cells. Here we combine pseudo-2D electrochemical modeling with data visualization methods to reveal important relationships between the measurable cell voltage and difficult-to-predict Li-plating onset criteria. An extensively validated model is used to compute Li plating for thousands of multistep charging conditions spanning diverse rates, temperatures, states-of-charge, and cell aging. Here we observe an empirical cell operating voltage limit below which plating does not occur across all conditions, and this limit varies with the battery state-of-charge and aging. A model sensitivity analysis also indicates that, when comparing two charging voltage profiles, the capacity difference at 4.0 V correlates well with the difference in the plating onset capacity. These results encourage simple strategies for Li-plating prevention that are complementary to existing battery controls.

25 ENERGY STORAGE↗
DOE OSTI2020

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Ultranano Titania: Selectively Ridding Water of Persistent Organic Pollutants

Persistent organic pollutants, including the EPA's “dirty dozen”, are difficult to remove from water supplies due to their chemical stability. Here, we report a stable oxide photocatalyst, ultranano titania (d < 2 nm) doped with iron, Fe•TiUNP, that efficiently mineralizes multiple persistent pollutants including aromatic compounds plus common troublesome, difficult-to-oxidize intermediates such as formaldehyde and acetone, netting mineralization of persistent pollutants. Efficiency stems from a direct charge-transfer pathway. The key role of iron doping is to lower the reduction potential of the photogenerated electron so that it is insufficient to reduce water, thus eliminating competition from the hydrogen evolution reaction. The reduction potential of the localized electron is similarly insufficient to reduce quinone, enabling breaking aromaticity. Specific results for degrading acetone, phenol, benzoic acid, and 1,4-benzoquinone are reported.

alcohols↗
DOE OSTI2023

Chemical Recycling of Polybutadiene Rubber with Tailored Depolymerization Enabled by Microencapsulated Metathesis Catalysts

The effective management of plastic waste streams to prevent plastic land and water pollution is a growing problem that is also one of the most important challenges in polymer science today. Polymer materials that are stable over their lifetime and can also be cheaply recycled or repurposed as desired could more easily be diverted from waste streams. However, this is difficult for most commodity plastics. It is especially difficult to conceive this with intractable, cross-linked polymers such as rubbers. In this work, we explore the utility of microencapsulated Grubbs’ catalysts for the in-situ depolymerization and reprocessing of polybutadiene (PB) rubber. Second-generation Hoveyda-Grubbs catalyst (HG2) contained within glassy thermoplastic microspheres can be dispersed in PB rubber below the microsphere’s glass transition temperature (T g ) without adverse depolymerization, evidenced by rubber with and without these microspheres obtaining similar shear storage moduli of ≈16 and ≈28 kPa, respectively. The thermoplastic’s T g can be used to tune the depolymerization temperature, via release of HG2 into the rubber matrix. For example, using poly(lactic acid) (PLA) vs polysulfone results in an 85 and 162 °C depolymerization temperature, respectively. Liquefaction of rubber to a mixture of small molecules and oligomers is demonstrated using a 0.01 mol % catalyst loading using PLA as the encapsulant. Furthermore, at that same catalyst loading, depolymerization occurs to a greater extent in comparison to two ex-situ approaches, including a conventional solvent-assisted method, where it occurs at roughly twice the extent at each given catalyst loading. In addition, depolymerization of the microsphere-loaded rubbers was demonstrated for samples stored under nitrogen for 23 days. Lastly, we show that the depolymerized products can be reprocessed back into solid rubber with a shear storage modulus of ≈32 kPa. Thus, we envision that this approach could be used to recycle and reuse cross-linked rubbers at the end of their product lifetime.

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

An assessment of Earth's climate sensitivity using multiple lines of evidence

In this work, we assess evidence relevant to Earth's equilibrium climate sensitivity per doubling of atmospheric CO 2 , characterized by an effective sensitivity S . This evidence includes feedback process understanding, the historical climate record, and the paleoclimate record. An S value lower than 2 K is difficult to reconcile with any of the three lines of evidence. The amount of cooling during the Last Glacial Maximum provides strong evidence against values of S greater than 4.5 K. Other lines of evidence in combination also show that this is relatively unlikely. We use a Bayesian approach to produce a probability density (PDF) for S given all the evidence, including tests of robustness to difficult-to-quantify uncertainties and different priors. The 66% range is 2.6-3.9 K for our Baseline calculation, and remains within 2.3-4.5 K under the robustness tests; corresponding 5-95% ranges are 2.3-4.7 K, bounded by 2.0-5.7 K (although such high-confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent, and because of greater confidence in understanding feedback processes and in combining evidence. We identify promising avenues for further narrowing the range in S , in particular using comprehensive models and process understanding to address limitations in the traditional forcing-feedback paradigm for interpreting past changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Collar Properties and Measurement Time Confer Minimal Bias Overall on Annual Soil Respiration Estimates in a Global Database

Abstract Measuring the soil‐to‐atmosphere carbon dioxide (CO 2 ) flux (soil respiration, R S ) is important to understanding terrestrial carbon balance and to forecasting climate change. Such measurements are frequently made using measurement collars permanently inserted into the soil surface. However, differences in measurement duration and frequency, as well as collar properties, may lead to biases in the estimation of annual R S . Using a newly updated global R S database (SRDB‐V5), we investigated the annual R S bias associated with five methodological factors: collar height, collar coverage area, collar insertion depth, measurement duration, and measurement frequency. We found that annual R S was negatively correlated with collar insertion depth, consistent with the idea that collar insertion cuts roots and thus reduces R S . Annual R S was also negatively related with collar height and collar coverage area, perhaps because uniform head‐space mixing is difficult to achieve in larger volume chambers; however, these effects were quantitatively small (bias of ~2% to 10% of mean R S ). We found no correlation of measurement duration or measurement frequency with annual R S . These findings suggest that variation in R S methodology generally introduces minimal bias overall. Therefore, compilations of minimally adjusted annual R S measurements provide a reliable resource for synthesis studies, global annual R S modeling, and investigation of how soil carbon responds to climate change.

Jian, Jinshi↗
DOE OSTI2021

Tropical Cirrus in Global Storm-Resolving Models. Part II: Cirrus Life Cycle and Top-of-Atmosphere Radiative Fluxes

Cirrus clouds of various thicknesses and radiative characteristics extend over much of the tropics, especially around deep convection. They are difficult to observe due to their high altitude and sometimes small optical depths. They are also difficult to simulate in conventional global climate models, which have coarse grid spacings and simplified parameterizations of deep convection and cirrus formation. We investigate the representation of tropical cirrus in global storm-resolving models (GSRMs), which have higher spatial resolution and explicit convection and could more accurately represent cirrus cloud processes. This study uses GSRMs from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project. The aggregate life cycle of tropical cirrus is analyzed using joint albedo and outgoing longwave radiation (OLR) histograms to assess the fidelity of models in capturing the observed cirrus cloud populations over representative tropical ocean and land regions. The proportions of optically-thick deep convection, anvils, and cirrus vary across models and are portrayed in the vertical distribution of cloud cover and top-of-atmosphere radiative fluxes. Model differences in cirrus populations, likely driven by subgrid processes such as ice microphysics, dominate over regional differences between convectively-active tropical land and ocean locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Association Between Injection and Microseismicity in Geothermal Fields With Multiple Wells: Data-Driven Modeling of Rotokawa, New Zealand, and Húsmúli, Iceland

Understanding injection-induced microseismicity in geothermal systems can provide insight into reservoir connectedness. However, fault and reservoir complexity are difficult to represent in simple analytical models, which makes it difficult to discern clear relationships from incidental associations. Here, we have used data-driven models to study how fluid injection and microseismicity are related in the Rotokawa (New Zealand) and Hellisheiði (Iceland) geothermal fields. We tested two classes of model: (a) lagged linear regression of seismicity rate as a function of well injection rates; and (b) systematic extraction of injection time series features that are then evaluated for associations with the seismicity. These models allowed us to determine which wells had the greatest correlation with microseismicity and to explain this association in a reservoir context. Finally, exploring different data types and transformations, we were unable to establish a link between rapid changes in injection rate and seismicity spikes, as suggested by some theoretical models.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Revisiting the Relationship Between Induced Polarization and Surface Conductivity: Ratios From Laboratory to Field

Abstract Among the subsurface geophysical methods used in the critical zone investigations, induced polarization (IP) shows great vitality thanks to its unique ability to assess porosity via bulk conduction and estimate permeability through surface conduction and/or polarization. However, such an advantageous separation between bulk and surface is mostly implemented by multi‐salinity experiments in the laboratory, which is incredibly difficult to realize in the field. One promising approach to address such an obstinate issue is to gauge the surface conductivity ( σ s ) from the quadrature conductivity ( σ ″) or normalized chargeability ( M n ) with the ratios between ( l = σ ″/ σ s , l mn = M n / σ s ). While these ratios are known not to be universal, the underlying principles are not fully understood and relevant theoretical studies are rare, which makes quantitative IP applications difficult. Here we scrutinize the conduction and polarization mechanisms of geomaterials and pinpoint that the two ratios are inherently functions of salinities and frequencies rather than only determined by the properties of the electrical double layer (EDL), hence representative samples from the investigated field must be calibrated in the laboratory and a characteristic frequency should be chosen for their usage. Besides the macro‐scale ratios l and l mn , we define two micro‐scale ratios χ and χ mn directly from the EDL, such that the new ratios exclude the effect of salinity and frequency and offer the opportunity to characterize and monitor changes of the EDL. Our study demonstrates that the existing macro‐scale ratios converge toward the values of novel micro‐scale ratios at high water salinity.

Qi, Youzheng [Earth and Environmental Sciences Are↗
DOE OSTI2025

Evaluating How Climate Adaptation Measures Affect the Interconnected Water‐Energy Resource Systems of the Western United States

Abstract The Western US faces increasing water stress from the impacts of climate change, making it difficult to meet water demands for the region's cities, agriculture, and hydropower generators. Existing literature suggests that climate adaptation measures such as water conservation, cropland retirement, wastewater recycling, and managed aquifer recharge can alleviate some of these challenges. Few analyses, however, compare the relative efficacy and system‐wide effects of these adaptations under different climate projections across the entire Western United States. Here we use a Western US‐wide water systems model to evaluate, by sector and sub‐region, how the widespread implementation of these adaptive measures impacts water demands, water deliveries, and electricity use related to the water system for three different climate projections. We find that wastewater recycling has greater potential to lower unmet indoor water demands than urban indoor water conservation measures. However, when implemented at scale, indoor water conservation reduces electricity use by an average of 683 Terawatt hours while wastewater recycling increases energy use by an average of 721 Terawatt hours, cumulatively from 2020 to 2070. Cropland retirement and aquifer recharge adaptations increase the ability to meet agricultural water demand, increase groundwater storage, and reduce summertime electricity use. While most of these findings are consistent across different climate projections, the benefits of aquifer recharge are sensitive to spatial variation of precipitation. Given the limitations and tradeoffs of each individually, the results suggest that a portfolio of adaptation measures will be needed for a climate‐resilient water and energy future in the Western US. Plain Language Summary The Western US faces increased water stress from the impacts of climate change, making it difficult to meet demands for cities, agriculture, and hydropower facilities. Adaptation measures like water conservation, retiring agricultural lands, recycling wastewater, and storing water underground can address these challenges. However, there is little modeling to understand the impact of these adaptations if they were implemented across the entire Western US while also considering climate change. We use a Western US‐wide water systems model to evaluate how implementing adaptation measures impacts groundwater levels, the ability to meet water demands, and electricity use related to water in three different possible climate futures. We find that recycling wastewater to drinking water standards does a better job of meeting urban water demands than water conservation measures. However, indoor water conservation reduces energy use for water while recycling wastewater increases energy use for water. Retiring agricultural lands and storing water underground both increase the ability to meet agricultural water demands, increase underground water storage, and reduce summertime energy use. No adaptation measures provides benefits across every metric we track. Therefore, multiple adaptation measures will likely be needed to achieve a climate‐resilient future for energy and water in the Western US. Key Points Water‐related climate change adaptations have different benefits and tradeoffs for interconnected water‐energy systems in the Western U.S. Wastewater recycling most increases urban water coverage, but has a significant tradeoff in the form of greater electricity use Cropland retirement and aquifer recharge benefit water and electricity systems most in the summer when those systems are most stressed

Singhal, A↗
DOE OSTI2026

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗
DOE OSTI2025

Transition Zones at the Changing Coastal Terrestrial‐Aquatic Interface

Coastal soils are a significant but highly uncertain component of global biogeochemical cycles. These systems experience spatial and temporal variability in biogeochemical processes, driven by marsh‐to‐upland gradients and hydrological fluctuations. These fluctuations make it difficult to understand and predict biogeochemical processes in these highly dynamic systems. We studied coastal soil biogeochemistry and its variability (a) at regional scales and (b) across transects from upland forest to marsh, in two contrasting regions—Lake Erie, a freshwater lacustrine system, and Chesapeake Bay, a saltwater estuarine system. Salinity‐related analytes were a key source of variability in soil biogeochemistry, not just in the saltwater system, but surprisingly, also in the freshwater system. We had hypothesized linear trends in biogeochemical parameters along the TAI—however, contrary to expectations, transition soils were not consistently intermediate between upland and marsh endmembers; the non‐monotonic trends of C, P, Fe along our transects suggest that these do not behave as expected and may be difficult to model and predict—thus these are key analytes to study in our regions. Rapidly changing soil factors across coastal gradients (e.g., Ca, K, CEC, and TS) may act as precursors to ecosystem shifts. Our comprehensive soil characterization represents a snapshot of a single timepoint of surface soils and provides essential data for mechanistic modeling of ecosystem dynamics across coastal transects.

Patel, Kaizad F. [Pacific Northwest National Labor↗
DOE OSTI2023

Insights into solvent and surface charge effects on Volmer step kinetics on Pt (111)

Abstract The mechanism of pH-dependent hydrogen oxidation and evolution kinetics is still a matter of significant debate. To make progress, we study the Volmer step kinetics on platinum (111) using classical molecular dynamics simulations with an embedded Anderson-Newns Hamiltonian for the redox process and constant potential electrodes. We investigate how negative electrode electrostatic potential affects Volmer step kinetics. We find that the redox solvent reorganization energy is insensitive to changes in interfacial field strength. The negatively charged surface attracts adsorbed H as well as H + , increasing hydrogen binding energy, but also trapping H + in the double layer. While more negative electrostatic potential in the double layer accelerates the oxidation charge transfer, it becomes difficult for the proton to move to the bulk. Conversely, reduction becomes more difficult because the transition state occurs farther from equilibrium solvation polarization. Our results help to clarify how the charged surface plays a role in hydrogen electrocatalysis kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗