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At least 469 records · Page 26

Comparative Analysis of Imaging and Measurements of Micrometer-Scale Fracture Aperture Fields Within a Heterogeneous Rock Using PET and X-ray CT

Knowledge of the spatial distribution of fracture apertures is essential for reliable characterization of flow and transport processes in fractured systems and for better understanding of physicochemical matrix–fracture interactions. Here, we propose and test two image-based methods, thereby extending the current experimental capabilities to characterize aperture size distribution in structurally heterogeneous geologic porous media noninvasively. The first approach utilizes an inversion method based on the dataset acquired from positron emission tomography (PET) and the second approach considers an extension of the classic missing attenuation technique that relies on clinical X-ray computed tomography (X-ray CT). Independent sets of imaging experiments are conducted on a fractured basalt core with heterogeneous matrix properties and aperture distributions to compare the two methodologies. A repeat of each experiment is conducted to verify the proposed workflows. The performance of these two imaging techniques is systematically evaluated through the analysis of signal-to-noise ratio, minimum fracture size detectability, and measurement errors. While both approaches provide a reliable estimation of fracture aperture distributions, PET yields a signal-to-noise ratio that is substantially higher than the corresponding X-ray CT measurements. Furthermore, uncertainties of the aperture values for PET are considerably lower ($\bar {\sigma}_{\text {d}} = 15\%$) compared to those obtained from X-ray CT ($\bar {\sigma}_{\text {d}} = 29\%$), allowing for the detection of minimum aperture sizes of 20 $\mu$m with 70% confidence level. Finally, these approaches provide key experimental tools for better understanding dynamic hydromechanical fracture properties in geologic systems.

58 GEOSCIENCES↗

Exploring viral particle, soil, and extraction buffer physicochemical characteristics and their impacts on extractable viral communities

Viruses are expected to be pivotal members of soil ecosystems, and recent advances in viral size fraction metagenomic (viromic) approaches have improved our ability to interrogate soil viral ecology. However, viromics relies on extraction buffers to effectively desorb viral particles from the soil matrix for downstream analysis, and viral extraction efficiency could be affected by the interplay between viral particles, soils, and extraction buffer chemistry. Here, we investigated whether extraction buffer chemistry affected extractable viral community composition measured by viromics from different soil types, for both biological (samples collected 1 m apart) and technical (subsamples from the same soil homogenate) replicates. We investigated pH manipulation of protein-supplemented phosphate-buffered saline buffer (PPBS, pHs 4.5, 5.5, 6.5, and 7.5) on forest, grassland and wetland soils that exhibited different soil edaphic properties, and we tested different buffer chemistries (PPBS, Carbonated Buffer, Glycine, and Saline Magnesium) on just the wetland soil. Spatial distance (i.e., biological replicate) was the primary driver of extractable viral community composition across all buffers and soils tested. Differences in viral community composition according to extraction buffer properties were only observed in the grassland technical replicates at PPBS buffer pH 4.5, and in both the wetland technical and biological replicates treated with different buffer chemistries, but the effects of buffer chemistry were secondary to spatial distance in the biological replicates. The lack of buffering capacity in the grassland soil technical replicates likely increased sorption of viral particles at pH 4.5, but neither protein composition nor isoelectric point explained this phenomenon. In conclusion, given that most soil viral ecological studies to date include sample collection over distances much farther apart than the 1-m distances considered here, results suggest that extraction buffer chemistry is likely of much lower importance than ecological considerations, such as spatial distance, in the design of future soil viral ecological investigations.

59 BASIC BIOLOGICAL SCIENCES↗

Cyclic strain enhances the early stage mineral nucleation and the modulus of demineralized bone matrix

The adaptive response of bones to mechanical loading is essential for musculoskeletal development. Despite the importance of collagen in bone mineralization, little is known about how cyclic strain influences physicochemical responses of collagen, especially at the early stage of mineralization when the levels of strain are higher than those in mature bones. The findings in this study show that, without any cell-mediated activity, cyclic strain increases nucleation rates of calcium phosphate (CaP) nanocrystals in highly-organized collagen matrices. The cyclic strain enhances the transport of mineralization fluids with nucleation precursors into the matrix, thus forming more CaP nanocrystals and increasing the elastic modulus of the collagen matrix. The results also suggest that the multiscale spatial distribution of nanocrystals in the fibrous collagen network determines tissue-level mechanical properties more critically than the total mineral content. Furthermore, by linking nano- and micro-scale observations with tissue-level mechanical properties, we provide new insights into designing better biomaterials.

36 MATERIALS SCIENCE↗

Growth and Stability of Stratiform Carrollite (CuCo2S4) in the Tenke-Fungurume Ore District, Central African Copperbelt

Abstract Carrollite (CuCo2S4) is the main ore mineral of the critical battery metal cobalt, yet, surprisingly, detailed characterization of its thermodynamic properties and of its trace element contents remain sparse in the scientific literature. To fill these knowledge gaps, we generated the first thermodynamic data set for carrollite using well-characterized samples obtained from the stratiform sulfide mineralization style at Fungurume 88 deposit in the Democratic Republic of Congo. Detailed mineralogical investigation of these same samples suggests that carrollite has limited ability to incorporate other ‘sweetener’ elements (except Cu and Ni) by substitution mechanisms. Modeling using CHNOSZ 2.0.0. software and an integrated Cu-Co-S-O thermodynamic data set provides insights into the stability of carrollite relative to other Co-bearing minerals under physicochemical conditions relevant to the Central African Copperbelt. Further exploration of these models indicates that dropping redox potential in the mineralizing system is insufficient to explain the mineral-scale and deposit-scale zonation patterns commonly observed in Cu-Co deposits of the Central African Copperbelt. Instead, factors such as increasing pH, decreasing T, decreasing sulfur activity, or some combination of changing physicochemical parameters may need to be invoked to explain these zonation trends. At the Fungurume 88 deposit, the absence of linnaeite (Co3S4) suggests that ore precipitation occurred at temperatures cooler than 211 °C. From our pH-logfO2 diagrams, and relative to higher temperatures, such a lower T regime is marked by a greater degree of offset between the modeled Cu and Co solubility contours, thus facilitating a more differentiated and zoned distribution of these two metals at the deposit scale. Our models are offered to the geoscience community as exceptionally useful tools for modeling and visualizing the Cu-Co-S-O systematics and may be applied to a variety of geological and geometallurgical questions in the Central African Copperbelt and other deposits elsewhere.

Mineralogy↗

Single-Particle Spectroscopy as a Versatile Tool to Explore Lower-Dimensional Structures of Inorganic Perovskites

The remarkable defect tolerant nature of inorganic cesium halide perovskites leading to near unity photoluminescence (PL) quantum yield (QY) and narrow emission linewidth across the entire visible spectrum, have provided a tantalizing platform for a development of a plethora of light-emitting applications. Recently, lower dimensional (2D, 1D, and 0D) perovskites have attracted further attention due to the enhanced thermal, photo and chemical stability as compared to their three-dimensional (3D) analogues. Combination of the external size quantization and internal octahedral organization provides a unique opportunity to study and harness “multidimensional” electronic properties engineered both on atomic scale and the nanoscale. However, crucial research to understand the elementary charge carrier dynamics in lower dimensional perovskites lags far behind the enormous effort to incorporate them into optoelectronic devices. In this Perspective, we provide a review of recent developments that focus on studies of the dynamics of excitonic complexes in Cs-based perovskite nanocrystals using single-particle time-resolved PL spectroscopy and photon correlation measurements. Single photon statistical studies not only offer the unprecedented level of detail to directly assess various recombination pathways but also provide insights into specifics of carrier’s localization. Further, we discuss the underlying physicochemical processes that govern PL emission and draw attention to a number of attributes within this class of the materials, especially lower-dimensional perovskites that may indicate the common origin of the PL emission, as well as provide a route map for the vast unexplored territories where single particle spectroscopy can be a powerful tool to unravel crucial information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Latex–collagen membrane: an alternative treatment for tibial bone defects

Due to the difficulty of consolidation, the risk of fractures, and the high cost of therapy, the orthopedic field views the restoration of bony defects or post-traumatic diseases as a significant issue. In recent years, efforts have been made toward guided bone regeneration as a viable solution. In this study, natural rubber latex (NRL) and latex–collagen (NRL-COL) membranes were developed and characterized, and their effects on bone regeneration in rat tibial lesions were assessed. According to the physicochemical findings, the hydrolyzed COL was effectively incorporated into the NRL membrane to produce a more robust membrane (348% increase in stress) and showed good biocompatibility for human dermal fibroblast cells and in hemolytic activity assay. According to bone analysis using computed microtomography, a substantial difference in bone volume (BV) was found among NRL, control (CONT), and NRL-COL. NRL-COL exhibited the greatest value for the bone volume/total volume ratio (BV/TV). The presence of NRL and COL was significant for the analysis of BV and BV/TV, respectively. All the experimental groups demonstrated a higher bone quality and fracture resistance, as shown by the mechanical properties of the bone. In the COL group, both neoformation of bone and total collagen levels were greater, indicating that treated defects had been closed and mature bone cells were present. Due to its angiogenic properties and the low cost of NRL membrane production, the NRL-COL membrane could be a good substitute for upcoming bone regeneration applications.

Marcela Britto de Paiva↗

Mitigation of Gaseous Emissions from Swine Manure with the Surficial Application of Biochars

Environmental impact associated with odor and gaseous emissions from animal manure is one of the challenges for communities, farmers, and regulatory agencies. Microbe-based manure additives treatments are marketed and used by farmers for mitigation of emissions. However, their performance is difficult to assess objectively. Thus, comprehensive, practical, and low-cost treatments are still in demand. We have been advancing such treatments based on physicochemical principles. The objective of this research was to test the effect of the surficial application of a thin layer (¼ inches; 6.3 mm) of biochar on the mitigation of gaseous emissions (as the percent reduction, % R) from swine manure. Two types of biochar were tested: highly alkaline and porous (HAP) biochar made from corn stover and red oak (RO), both with different pH and morphology. Three 30-day trials were conducted with a layer of HAP and RO (2.0 & 1.65 kg∙m−2, respectively) applied on manure surface, and emissions of ammonia (NH3), hydrogen sulfide (H2S), greenhouse gases (GHG), and odorous volatile organic compounds (VOCs) were measured. The manure and biochar type and properties had an impact on the mitigation effect and its duration. RO significantly reduced NH3 (19–39%) and p-cresol (66–78%). H2S was mitigated (16~23%), but not significantly for all trials. The phenolic VOCs had relatively high % R in most trials but not significantly for all trials. HAP reduced NH3 (4~21%) and H2S (2~22%), but not significantly for all trials. Significant % R for p-cresol (91~97%) and skatole (74~95%) were observed for all trials. The % R for phenol and indole ranged from (60~99%) and (29~94%) but was not significant for all trials. The impact on GHGs, isobutyric acid, and the odor was mixed with some mitigation and generation effects. However, larger-scale experiments are needed to understand how biochar properties and the dose and frequency of application can be optimized to mitigate odor and gaseous emissions from swine manure. The lessons learned can also be applicable to surficial biochar treatment of gaseous emissions from other waste and area sources.

Meiirkhanuly, Zhanibek↗

Ultrasound-Assisted Nonthermal, Nonequilibrium Separation of Organic Molecules from Their Binary Aqueous Solutions: Effect of Solute Properties on Separation

The separation of organic molecules in downstream processes, such as distillation, plays a vital role in biobased chemical production. A comprehensive study was performed here using ultrasonic energy to separate 11 organic molecules from their binary aqueous solutions under nonthermal, nonequilibrium, and phase-change free conditions. A batch sonoseparator with a three-stage mist collection unit allowed direct analysis of ultrasound-generated mist with an HPLC/GC and differentiation and quantification of the vapor and mist. The results showed that the alcohols (1-butanol, ethanol, 1-propanol, and methanol) and acetone were enriched in the ultrasound-generated mist with enrichment ratios of 3.2–5. On the other hand, ethylene glycol, glycerol, γ-valerolactone (GVL), glucose, and sucrose were diluted with dilution ratios in the range of 2.04–15.7 in the mist and vapor generated by ultrasound (or concentrated in the bulk solution). No enrichment nor dilution of acetic acid was observed. The role of various physicochemical parameters such as dynamic viscosity, surface tension, Henry’s law of solubility constant, vapor pressure, and octanol–water partition coefficient in the enrichment was examined. Furthermore, the hydrophobicity of the organic molecules represented by the octanol–water partition coefficient was found to play a crucial role in determining the separation characteristics of the molecules in ultrasound-generated mist and vapor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bifunctional Electrocatalysts with High-Entropy Alloys: Bridging Hydrogen Evolution and Oxygen Reduction

High-entropy alloys (HEAs) have emerged as a promising class of bifunctional electrocatalysts capable of simultaneously driving the hydrogen evolution reaction (HER) and the oxygen reduction reaction (ORR) with high activity and durability. Their near-equiatomic multicomponent compositions give rise to unique physicochemical characteristics, including lattice distortion, sluggish diffusion, high-entropy stabilization, and pronounced electronic heterogeneity, that collectively generate diverse and synergistic active sites inaccessible in conventional alloys. This review summarizes recent progress in HEA-based bifunctional electrocatalysis, with a focus on the fundamental mechanisms governing HER and ORR activity, stability, and selectivity. We discuss advances in synthesis strategies, ranging from confined growth and step-alloying to scalable continuous-flow methods, that enable precise control over composition, size, and surface structure. Complementary computational and data-driven approaches, including density functional theory, machine-learning-assisted screening, and descriptor development, are highlighted as essential tools for navigating the vast HEA design space and establishing structure−property relationships. Particular attention is paid to adsorption-energy distributions, multisite cooperativity, and environmental effects under realistic electrochemical conditions. Finally, we outline current challenges and future opportunities for integrating mechanistic understanding with AI-guided, closed-loop design frameworks to accelerate the discovery of next-generation HEA bifunctional electrocatalysts for sustainable energy conversion.

Alloys↗

Effect of interfacial vibrational coupling on surface wettability and water transport

Here, we report that the atomic-scale vibrational coupling at the solid-fluid interface can substantially alter the interfacial properties such as wettability and fluid slip. The wettability of water droplets on substrates subjected to various vibrational frequencies is studied using molecular dynamics simulation. The contact angle increases (i.e., becomes more hydrophobic) when the oscillation frequency of the substrate matches the intermolecular bending frequency of liquid water. We investigate the underlying mechanism by examining the dynamics of water molecules at the interface and find that the temporal contact between the solid and fluid is shorter when the frequencies match, resulting in weak solid-fluid adsorption. We further report that the vibrational match at the interface reduces wall-fluid friction and enhances water transport through the nanopore. Our findings demonstrate the importance of the atomic-scale vibrational coupling at the solid-fluid interface on the physicochemical behavior of nanodevices and biological nanochannels.

74 ATOMIC AND MOLECULAR PHYSICS↗

Machine learning-guided design, synthesis, and characterization of atomically dispersed electrocatalysts

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. Here, we review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An activatable NIR fluorescent rosol for selectively imaging nitroreductase activity

Hypoxia (i.e., pO 2 ≤ ~1.5 %) is an important characteristic of tumor microenvironments that directly correlates with resistance against first-line therapies and tumor proliferation/infiltration. The ability to accurately identify hypoxic tumor cells/tissue could afford tailored therapeutic regimens for personalized treatment, the development of more-effective therapies, and discerning the mechanisms underlying disease progression. Fluorogenic constructs currently developed for identifying such tumor cells/tissue operate by targeting the bioreductive activity of primarily the nitroreductase (NTR) class of enzymes, but collectively such constructs unfortunately present photophysical and/or physicochemical shortcomings that could limit their effectiveness upon implementation. To overcome these limitations, we present the rational design, development, and evaluation of the first activatable ultracompact xanthene core-based molecular probe (NO 2 -Rosol) for selectively imaging NTR activity that affords an “OFF-ON” near-infrared (NIR) fluorescence response (ca. > 700 nm) alongside a remarkable Stokes shift (ca. > 150 nm) via NTR activity-facilitated modulation to its energetics whereby the resultant interplay discontinues an intramolecular d-PET fluorescence-quenching mechanism transpiring between directly-linked electronically-uncoupled π-systems comprising its components. DFT calculations guided selection of a suitable fluorogenic scaffold and nitroaromatic moiety candidate that when adjoined could (i) afford such photophysical response upon bioreduction by upregulated NTR activity in hypoxic tumor cells/tissue and (ii) employ a retention mechanism strategy that capitalizes on an inherent physical property of the NIR fluorogenic scaffold for achieving signal amplification. NO 2 -Rosol demonstrated 705 nm NIR fluorescence emission and a 157 nm Stokes shift, selectivity for NTR over relevant bioanalytes, and a 28- and 12-fold fluorescence enhancement in solution and between cells cultured under different oxic conditions, respectively. Finally, in establishing feasibility for NO 2 -Rosol to provide favorable contrast levels in in solutioand in vitrostudies, we anticipate NO 2 -Rosol similarly doing so in future studies towards its translation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Noble Gas Transport in the MSRE

This study explores the relationship between the physicochemical parameter known as Henry’s gas constant and gas transport across a two-layer film interface. The investigation utilized the Gibbs free energy, incorporating surface and volume terms to elucidate trends in enthalpy and entropy. Notably, our findings align with experimental data and offer predictive insights into the Henry’s gas constants for helium and krypton, which hold significance for future experiments and theoretical developments. Furthermore, this study enhances the Gibbs free energy theory pertaining to the liquid–gas interface. It underscores the substantial contribution of noble gases in this region to volumetric energy as temperature increases. Additionally, we employed Monte Carlo simulations to analyze the effective thermal neutron multiplication factor, denoted as k eff . Our analysis reveals a linear correlation between graphite density and uniform density as a function of temperature. For the 1D Molten Salt Reactor Experiment (MSRE) system, we employed the Mole code to conduct heat and mass transfer calculations. These computations enable us to ascertain the distribution of fuel temperature based on coefficients and thermal properties. We also studied delayed neutron precursors during fuel cycling, taking into account the drift of cycling fuel through Mole–Griffin coupling. Our model represents k eff and β eff across various volume flow rates and salinity compositions. Finally, this study leveraged xenon-135 for continuous on-line monitoring of fuel salts to investigate the impact of steady-state xenon-135 on the MSRE and to better understand its distribution. These efforts build upon previous research related to removal processes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Summer Aerosol and Trace Gas Observations in Houston, Texas Using an Adaptable Mobile Facility

An aerosol container featuring a shared inlet system was deployed to Houston, Texas in July 2022, enabling direct, high-time-resolution in situ measurements of aerosols and trace gases. The internal rack system and floorplan was designed for adaptable modularity to elucidate aerosol physicochemical processes at fine scales. The design allowed for the deployment of a core instrument suite and additional customized research grade instruments. A heterogeneous mixture of aerosols was observed during three regimes: (1) intermittent black carbon (BC) and diurnal variations in aerosol chemical composition, (2) observed particle growth associated with SO 2 , (3) transported supermicron dust. The high variability of observed particles and gases in high time resolution indicated a complex urban area with multiple local and regional sources and processes. Particle growth rates of 7–16 nm/hr were observed for submicron particles during periods when SO 2 was >0.5 ppbv. Two periods of multi-day long-range transport events of dust from the African Sahara were observed in the supermicron and submicron particle modes with total mass concentrations up to 30 μg m −3 . Aerosol scattering angstrom exponents and extinction coefficients (B ext ) increased with humidity as a function of particle composition. The measurements demonstrate collaborative capabilities that can be used to increase observations of aerosol processing, microphysical and optical properties, internal mixing state, and supermicron aerosol that are not parameterized or missing in global Earth energy system models.

54 ENVIRONMENTAL SCIENCES↗

Geochemistry and metagenomics analyses of bacterial community structure in selected waste dumpsites in Lagos Metropolis, Nigeria

Dumpsites are reservoirs of persistent organic pollutants (POPs) and heavy metals (HMs), constituting environmental hazards to humanity. Autochthonous microorganisms in dumpsites exhibit various degrees of responses to contaminants. Unfortunately, there is a dearth of information on the types and concentration of pollutants and the array of microorganisms in these dumpsites which may play important roles in the metabolism of such pollutants or other community processes. Therefore, determining the microbial community structure in such contaminated sites across a municipality is essential for profiling the taxa that would serve as consensus degraders of the pollutants. In this study, soil samples from three dumpsites (Cele, CS; Solous, SS; and Computer Village, CVS) were characterized for geochemical properties using GC-MS, MP-AES, and other analytical protocols, while the dynamics of bacterial communities were evaluated based on their 16S rRNA gene barcodes. A significant difference in the bacterial communities was observed among the dumpsites in relation to the extent of pollution caused by POPs and HMs. CVS, with the highest HM contamination, was rich in Actinobacteria (41.7%) and Acidobacteria (10.2%), in contrast to CS and SS. Proteobacteria (34.1%) and Firmicutes (20%) were the dominant phyla in CS (highest POP contamination), while Bacteroidetes (45.5%) and Proteobacteria (39.9%) were dominant in SS soil.Bacilluswas the dominant genus in the most polluted dumpsite. Canonical correspondence analysis revealed that polycyclic aromatic hydrocarbons (PAHs) and HMs shaped the structure of the bacterial operational taxonomic units (OTUs) in the most polluted dumpsite. Out of a total of 706 OTUs, 628 OTUs exhibited a significant correlation (>50%) with benzo(b)fluoranthene, azobenzene, dibenzofurans, pyrene, dibenzo(a,l)pyrene, Cu, and Zn. In particular, Proteobacteria (Achromobactersp. andSerratiasp.), Bacteroidetes (Zhouiasp.), and Firmicutes (Bacillussp.) were suggested to be pivotal to the ecophysiology of dumpsite soils contaminated with POPs and HMs. The results generally underscored the importance of metagenomic and physicochemical analyses of polluted systems in enabling correlations for useful prediction of drivers of such ecosystems. This will further improve our understanding of the metabolic potential and adaptation of organisms in such systems.

Environmental Sciences & Ecology↗

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Quantifying Drivers of Methane Hydrobiogeochemistry in a Tidal River Floodplain System

The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine learning (ML) framework to identify and rank the most influential processes, properties, and conditions controlling methane behavior in a freshwater floodplain responding to recently restored seawater inundation. Our unique multivariate, multiyear, and multi-site dataset comprises tidal creek and floodplain porewater observations encompassing water level, salinity, pH, temperature, dissolved oxygen (DO), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), partial pressure of carbon dioxide (pCO 2 ), nitrous oxide (pN 2 O), methane (pCH 4 ), and the stable isotopic composition of methane (δ 13 CH 4 ). Additionally, we incorporated topographical data, soil porosity, hydraulic conductivity, and water retention parameters for UQ analysis using a previously developed 3D variably saturated flow and transport floodplain model for a physical mechanistic understanding of factors influencing groundwater levels and salinity and, therefore, CH 4 . Principal component analysis revealed that groundwater level and salinity are the most significant predictors of overall biogeochemical variability. The ensemble ML models and UQ analyses identified DO, water level, salinity, and temperature as the most influential factors for porewater methane levels and indicated that approximately 80% of the total variability in hourly water levels and around 60% of the total variability in hourly salinity can be explained by permeability, creek water level, and two van Genuchten water retention function parameters: the air-entry suction parameter α and the pore size distribution parameter m. These findings provide insights on the physicochemical factors in methane behavior in coastal ecosystems and their representation in local- to global-scale Earth system models.

54 ENVIRONMENTAL SCIENCES↗

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.

25 ENERGY STORAGE↗