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At least 73 records · Page 4

Leveraging hyperspectral imaging to identify drought tolerant Populus species and genotypes within species

The aim of this study was to identity variation in drought tolerance across genotypes of Populus deltoides, Populus trichocarpa, and hybrids of the two species. A panel of 102 Populus genotypes, comprising 37 genotypes of P. trichocarpa, 37 of P. deltoides and 28 unique hybrid genotypes (P. trichocarpa x P. deltoides and P. deltoides x P. trichocarpa) were evaluated in the greenhouse under two treatments, well-watered (WW) and drought (DS). Plant physiological data were collected throughout the experiment once the drought treatment began. Throughout the experiment, we tracked soil volumetric water content, pot weight, stomatal conductance, quantum yield of photosystem II, and electron transport rate. In addition to those measurements, upon completion of the experiment, we assessed above and belowground plant biomass, plant height and stem diameter, leaf number, specific leaf area, relative water content, total protein, and total chlorophyll. We obtained hyperspectral signatures of one leaf from each plant at the end of the experiment. Columns BC – LL are hyperspectral averages for one leaf from each plant at each wavelength as described in the column header.

Hyper-spectral imaging, Populus, plant stress tole↗

1.4.2.402 - Water Risk for the Bulk Power System: Asset to Grid Impacts

Utilities and stakeholders need a standardized mechanism for evaluating how future climate and hydrologic conditions translate to water-related risks for power grid assets and systems to support planning decisions. Yet, no such mechanism exists. To address this need, our goals are to: (1) Develop and execute a state-of-the-art multi-model framework to assess future climate-water impacts and risks to the grid, including sensitivities to varying hydrologic drivers and infrastructure scenarios. (2) Create a standardized interactive visualization platform, using data from the climate-water risk assessments, that enables stakeholders to evaluate climate-water impacts, risks, and adaptation measures for power systems.

bulk power system↗

Next-Generation Ecosystem Experiments–Tropics Flyer

Tropical forests cycle more carbon and water than any other ecosystem, and they play critical roles in determining Earth’s energy balance. Additionally, intact tropical forests are estimated to be Earth’s largest carbon sink, yet the processes controlling tropical forest carbon cycling are not well established. Understanding of carbon and related water and energy exchanges between tropical forests and the atmosphere lags that of other ecosystems, and poor model representation of these processes is the most significant source of terrestrial uncertainty in climate projections. To address these challenges, the Terrestrial Ecosystem Science (TES) program within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) is supporting a next-generation ecosystem experiments project in the tropics (NGEE–Tropics).

54 ENVIRONMENTAL SCIENCES↗

Engineered Water for Improved Oil Recovery from Fractured Reservoirs (Final Scientific/Technical Report)

The goal of this proposal is to field test the novel technology of engineered water (modifying ionic composition and/or adding surfactants or nanoparticles) injection to improve oil recovery from the carbonate matrix in fractured reservoirs. Carbonate reservoirs tend to be oil-wet/mixed-wet due to positively charged carbonate mineral surfaces and negatively charged acidic/asphaltic components in the oil. Many carbonate reservoirs are also highly fractured. Water injection does not work efficiently in fractured oil-wet reservoirs because water does not imbibe into the matrix. The water composition can be engineered with ionic modification, surfactants and nanoparticles which can change the wettability of carbonate rocks towards more water-wet conditions which can imbibe water into the matrix and push the oil into the fractures. The engineered water can also lower interfacial tension and minimize capillary forces so that gravity can push the oil up and out of the matrix. Wettability alteration also increases water relative permeability which can also improve oil recovery in non-fractured carbonate reservoirs. This technology, if successful, can be a game changer for West Texas carbonates.

02 PETROLEUM↗

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↗

Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region

Abstract. Streamflow variability plays a crucial role in shaping the dynamics and sustainability of Earth's ecosystems, which can be simulated and projected by a river routing model coupled with a land surface model. However, the simulation of streamflow at large scales is subject to considerable uncertainties, primarily arising from two related processes: runoff generation (hydrological process) and river routing (hydraulic process). While both processes have impacts on streamflow variability, previous studies only calibrated one of the two processes to reduce biases in the simulated streamflow. Calibration focusing only on one process can result in unrealistic parameter values to compensate for the bias resulting from the other process; thus other water-related variables remain poorly simulated. In this study, we performed several experiments with the land and river components of the Energy Exascale Earth System Model (E3SM) over the Pantanal region to disentangle the hydrological and hydraulic controls on streamflow variability in coupled land–river simulations. Our results show that the generation of subsurface runoff is the most important factor for streamflow variability contributed by the runoff generation process, while floodplain storage effect and main-channel roughness have significant impacts on streamflow variability through the river routing process. We further propose a two-step procedure to robustly calibrate the two processes together. The impacts of runoff generation and river routing on streamflow are appropriately addressed with the two-step calibration, which may be adopted by developers of land surface and earth system models to improve the modeling of streamflow.

54 ENVIRONMENTAL SCIENCES↗

Tripogon loliiformis tolerates rapid desiccation after metabolic and transcriptional priming during initial drying

Abstract Crop plants and undomesticated resilient species employ different strategies to regulate their energy resources and growth. Most crop species are sensitive to stress and prioritise rapid growth to maximise yield or biomass production. In contrast, resilient plants grow slowly, are small, and allocate their resources for survival in challenging environments. One small group of plants, termed resurrection plants, survive desiccation of their vegetative tissue and regain full metabolic activity upon watering. However, the precise molecular mechanisms underlying this extreme tolerance remain unknown. In this study, we employed a transcriptomics and metabolomics approach, to investigate the mechanisms of desiccation tolerance in Tripogon loliiformis , a modified desiccation-tolerant plant, that survives gradual but not rapid drying. We show that T. loliiformis can survive rapid desiccation if it is gradually dried to 60% relative water content (RWC). Furthermore, the gene expression data showed that T. loliiformis is genetically predisposed for desiccation in the hydrated state, as evidenced by the accumulation of MYB, NAC, bZIP, WRKY transcription factors along with the phytohormones, abscisic acid, salicylic acid, amino acids (e.g., proline) and TCA cycle sugars during initial drying. Through network analysis of co-expressed genes, we observed differential responses to desiccation between T. loliiformis shoots and roots. Dehydrating shoots displayed global transcriptional changes across broad functional categories, although no enrichment was observed during drying. In contrast, dehydrating roots showed distinct network changes with the most significant differences occurring at 40% RWC. The cumulative effects of the early stress responses may indicate the minimum requirements of desiccation tolerance and enable T. loliiformis to survive rapid drying. These findings potentially hold promise for identifying biotechnological solutions aimed at developing drought-tolerant crops without growth and yield penalties.

59 BASIC BIOLOGICAL SCIENCES↗

KARRIKIN INSENSITIVE2 regulates leaf development, root system architecture and arbuscular‐mycorrhizal symbiosis in Brachypodium distachyon

SUMMARY KARRIKIN INSENSITIVE2 (KAI2) is an α/β‐hydrolase required for plant responses to karrikins, which are abiotic butenolides that can influence seed germination and seedling growth. Although represented by four angiosperm species, loss‐of‐function kai2 mutants are phenotypically inconsistent and incompletely characterised, resulting in uncertainties about the core functions of KAI2 in plant development. Here we characterised the developmental functions of KAI2 in the grass Brachypodium distachyon using molecular, physiological and biochemical approaches. Bdkai2 mutants exhibit increased internode elongation and reduced leaf chlorophyll levels, but only a modest increase in water loss from detached leaves. Bdkai2 shows increased numbers of lateral roots and reduced root hair growth, and fails to support normal root colonisation by arbuscular‐mycorrhizal (AM) fungi. The karrikins KAR 1 and KAR 2 , and the strigolactone (SL) analogue rac ‐GR24, each elicit overlapping but distinct changes to the shoot transcriptome via BdKAI2. Finally, we show that BdKAI2 exhibits a clear ligand preference for desmethyl butenolides and weak responses to methyl‐substituted SL analogues such as GR24. Our findings suggest that KAI2 has multiple roles in shoot development, root system development and transcriptional regulation in grasses. Although KAI2‐dependent AM symbiosis is likely conserved within monocots, the magnitude of the effect of KAI2 on water relations may vary across angiosperms.

Meng, Yongjie↗

Benefits and Critical Knowledge Gaps in Determining the Role of Floating Photovoltaics in the Energy-Water-Food Nexus

Floating solar photovoltaic (FPV) systems have become an increasingly attractive application of photovoltaics (PV) because of land-use constraints, the cost of land and site preparation, and the perceived energy and environmental co-benefits. Despite the increasing interest in FPV systems, a robust validation of their suggested co-benefits and impacts on the nexus of energy, water, and food (EWF) systems is lacking. This information gap makes it challenging for decision makers to justify its adoption—potentially suppressing FPV deployment. To address this gap and to help de-risk this PV deployment opportunity, we (1) review the suggested co-benefits of FPV systems with a focus on the impacts that could alleviate pressures on EWF systems and (2) identify areas where further research is needed to reduce uncertainty around FPV system performance. Our review reveals that EWF nexus-relevant co-benefits, such as improved panel efficiency and reduced land usage, are corroborated in the literature, whereas others, such as water quality impacts, lack empirical evidence. Our findings indicate that further research is needed to quantify the water-related and broader economic, environmental, social, sustainability, justice, and resilience co-benefits and impacts of FPV systems.

14 SOLAR ENERGY↗

An overview of visualization and visual analytics applications in water resources management

Recent advances in information, communication, and environmental monitoring technologies have increased the availability, spatiotemporal resolution, and quality of water-related data, thereby leading to the emergence of many innovative big data applications. Among these applications, visualization and visual analytics, also known as the visual computing techniques, empower the synergy of computational methods (e.g., machine learning and statistical models) with human reasoning to improve the understanding and solution toward complex science and engineering problems. These approaches are frequently integrated with geographic information systems and cyberinfrastructure to provide new opportunities and methods for enhancing water resources management. Here, we present a comprehensive review of recent hydroinformatics applications that employ visual computing techniques to (1) support complex data-driven research problems, and (2) support the communication and decision-makings in the water resources management sector. Then, we conduct a technical review of the state-of-the-art web-based visualization technologies and libraries to share our experiences on developing shareable, adaptive, and interactive visualizations and visual interfaces for water resources management applications. We close with a vision that applies the emerging visual computing technologies and paradigms to develop the next generation of hydroinformatics applications.

54 ENVIRONMENTAL SCIENCES↗

Surface water and groundwater FTICR-MS, NPOC, and TN from nine wetlands and three upland wells at the Tanglewood Biological Station, Alabama

This dataset supports a broader study examining wetland hydrobiogeochemical responses to flood disturbance and the subsequent impacts on watershed nutrient export. The study was designed following ICON (integrated, coordinated, open, and networked) principles. Samples were collected from nine wetlands and three upland wells at the Tanglewood Biological Station, Alabama in August 2024 and February 2025, during the dry and wet season, respectively. The contents include geochemistry (dissolved organic carbon measured as non-purgeable organic carbon; total dissolved nitrogen) and organic matter characterization (FTICR-MS). Related water level data from the same locations can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/2530253. Additional geochemistry will be published in a separate data package. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; (7) the field protocol; and (8) a subfolder with sample data. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total nitrogen data and averages; (3) methods codes; and (4) a subfolder of 12 Tesla (12T) Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

Coupled Gas-Exchange Model for C4 Leaves Comparing Stomatal Conductance Models

Plant simulation models are abstractions of plant physiological processes that are useful for investigating the responses of plants to changes in the environment. Because photosynthesis and transpiration are fundamental processes that drive plant growth and water relations, a leaf gas-exchange model that couples their interdependent relationship through stomatal control is a prerequisite for explanatory plant simulation models. Here, we present a coupled gas-exchange model for C4 leaves incorporating two widely used stomatal conductance submodels: Ball–Berry and Medlyn models. The output variables of the model includes steady-state values of CO2 assimilation rate, transpiration rate, stomatal conductance, leaf temperature, internal CO2 concentrations, and other leaf gas-exchange attributes in response to light, temperature, CO2, humidity, leaf nitrogen, and leaf water status. We test the model behavior and sensitivity, and discuss its applications and limitations. The model was implemented in Julia programming language using a novel modeling framework. Our testing and analyses indicate that the model behavior is reasonably sensitive and reliable in a wide range of environmental conditions. The behavior of the two model variants differing in stomatal conductance submodels deviated substantially from each other in low humidity conditions. The model was capable of replicating the behavior of transgenic C4 leaves under moderate temperatures as found in the literature. The coupled model, however, underestimated stomatal conductance in very high temperatures. This is likely an inherent limitation of the coupling approaches using Ball–Berry type models in which photosynthesis and stomatal conductance are recursively linked as an input of the other.

59 BASIC BIOLOGICAL SCIENCES↗

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗

Field intercomparison of ice nucleation measurements: the Fifth International Workshop on Ice Nucleation Phase 3 (FIN-03)

Abstract. The third phase of the Fifth International Ice Nucleation Workshop (FIN-03) was conducted at the Storm Peak Laboratory in Steamboat Springs, Colorado, in September 2015 to facilitate the intercomparison of instruments measuring ice-nucleating particles (INPs) in the field. Instruments included two online and four offline measurement systems for INPs, which are a subset of those utilized in the laboratory study that comprised the second phase of FIN (FIN-02). The composition of the total aerosols was characterized using the Particle Analysis by Laser Mass Spectrometry (PALMS) and Wideband Integrated Bioaerosol Sensor (WIBS) instruments, and aerosol size distributions were measured by a laser aerosol spectrometer (LAS). The dominant total particle compositions present during FIN-03 were composed of sulfates, organic compounds, and nitrates, as well as particles derived from biomass burning. Mineral-dust-containing particles were ubiquitous throughout and represented 67 % of supermicron particles. Total WIBS fluorescing particle concentrations for particles with diameters of > 0.5 µm were 0.04 ± 0.02 cm−3 (0.1 cm−3 highest; 0.02 cm−3 lowest), typical of the warm season in this region and representing ≈ 9 % of all particles in this size range as a campaign average. The primary focus of FIN-03 was the measurement of INP concentrations via immersion freezing at temperatures > −33 °C. Additionally, some measurements were made in the deposition nucleation regime at these same temperatures, representing one of the first efforts to include both mechanisms within a field campaign. INP concentrations via immersion freezing agreed within factors ranging from nearly 1 to 5 times on average between matched (time and temperature) measurements, and disagreements only rarely exceeded 1 order of magnitude for sampling times coordinated to within 3 h. Comparisons were restricted to temperatures lower than −15 °C due to the limits of detection related to sample volumes and very low INP concentrations. Outliers of up to 2 orders of magnitude occurred between −25 and −18 °C; a better agreement was seen at higher and lower temperatures. Although the 5–10 factor agreement of INP measurements found in FIN-03 aligned with the results of the FIN-02 laboratory comparison phase, giving confidence in progress of this measurement field, this level of agreement still equates to temperature uncertainties of 3.5 to 5 °C that may not be sufficient for numerical cloud modeling applications that utilize INP information. INP activity in the immersion-freezing mode was generally found to be an order of magnitude or more, making it more efficient than in the deposition regime at 95 %–99 % water relative humidity, although this limited data set should be augmented in future efforts. To contextualize the study results, an assessment was made of the composition of INPs during the late-summer to early-fall period of this study inferred through comparison to existing ice nucleation parameterizations and through measurement of the influence of thermal and organic carbon digestion treatments on immersion-freezing ice nucleation activity. Consistent with other studies in continental regions, biological INPs dominated at temperatures of > −20 °C and sometimes colder, while arable dust-like or other organic-influenced INPs were inferred to dominate below −20 °C.

54 ENVIRONMENTAL SCIENCES↗

Enhanced Salt Tolerance of Torreya grandis Genders Is Related to Nitric Oxide Level and Antioxidant Capacity

Nitric oxide (NO), a bioactive molecule, is often involved in the regulation of physiological and biochemical processes in stressed plants. However, the effects of NO donors on dioecious plants remain unclear. Using a pot experiment, female and male Torreya grandis were used to study the role of sex and NO in salt stress tolerance. In the present study, female and male T. grandis seedlings pretreated with an NO donor (sodium nitroprusside, SNP) were exposed to salt stress, and then leaf relative water content (RWC), photosynthetic pigments, chlorophyll fluorescence parameters, NO and glutathione levels, oxidative damage, and antioxidant enzyme activities were investigated. Female T. grandis plants had better tolerance to salinity, as they were characterized by significantly higher RWC, pigment content, and photochemical activities of photosystem II (PSII) and fewer negative effects associated with higher nitrate reductase (NR) activity and NO content. Pretreatment with an NO donor further increased the endogenous NO content and NR activity of both female and male T. grandis plants compared with salt treatment. Moreover, pretreatment with an NO donor alleviated salt-induced oxidative damage of T. grandis , especially in male plants, as indicated by reduced lipid peroxidation, through an enhanced antioxidant system, including proline and glutathione accumulation, and increased antioxidant enzyme activities. However, the ameliorating effect of the NO donor was not effective in the presence of the NO scavenger (Nω-nitro-L-arginine methyl ester, L-name). In conclusion, enhanced salt tolerance in T. grandis plants is related to nitric oxide levels and the supply of NO donors is an interesting strategy for alleviating the negative effect of salt on T. grandis . Our data provide new evidence to contribute to the current understanding of NO-induced salt stress tolerance.

Liu, Yang↗

Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles

Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Petrophysical and geomechanical properties of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well

Knowledge of petrophysical and geomechanical properties of gas hydrate-bearing sediments are essential for predicting reservoir response due to gas production from gas hydrate reservoirs. That information will be critical parameters for designing production well completion such as specification of depressurization pump, water storage tank, and mesh size of sand screen. In December 2018, Stratigraphic Test Well Hydrate-01 was drilled in the western part of the Prudhoe Bay Unit, Alaska North Slope as part of the technical planning effort for a future long-term production test by collaborative team of DOE/NETL, USGS, and MH21-S (Boswell et al., 2020, Collett et al., 2020, Okinaka et al., 2020). Data set of logging-while-drilling (LWD) were acquired (Haines et al., 2020, Suzuki et al., 2019) and core sampling depth was determined on-site.Side-wall pressure coring was conducted to recover gas hydrate-bearing sediments from two reservoir sections named Unit-B and Unit-D. A total of 34 cores were successfully recovered by 5 runs of a wire-line deployed pressure corer (CoreVault® System - Halliburton). Core analysis scheme of this project are shown in Figure 1. All cores were quenched in liquid nitrogen while at high pressure in the laboratory of Stratum Reservoir, LLC. at Anchorage (Figure 1, a)). And the cores were removed from the pressure corer autoclave with temperature support of dry ice and stored under liquid nitrogen at atmospheric pressure. 19 damaged cores were processed to index property measurements directly such as grain size, grain density. 4 of another 17 cores were depressurized and trimmed for making a plug to analyze petrophysical properties of host sediments. Unsteady-state permeability test was conducted to obtain relative water permeability to gas and core scale NMR T2 distribution measurement was performed for evaluating pore size distribution at Houston (Figure 1, b)). Remained high quality 13 cores were preserved with gas hydrate for advanced laboratory analysis. National Institute of Advanced Industrial Science and Technology, as a part of the Japanese National Hydrate Research Program (MH21-S, funded by Ministry of Economy, Trade and Industry), received the samples at Sapporo, Japan for advanced core analysis. High-resolution X-ray CT was used to analyze the quality of the samples, which showed undisturbed lithological layers. Cores were lathed into cylindrical shape and distributed for multi property measurements (Figure 1, c)).<p>As a result, sediment from Unit-D is categorized as silty sand at ~37% porosity with ~80% gas hydrate saturation. An average hydration number n = 6.16 was measured by Raman spectroscopy. An average intrinsic permeability of ~400 mD and in situ effective permeability (with hydrate) on the order of ~10 mD. The Unit B recovered cores consisted of well sorted sand at ~40% porosity with ~95% gas hydrate saturation. An average intrinsic permeability of ~1 Darcy and in situ effective permeability on the order of ~30 mD was measured for the Unit B cores. There was a small permeability reduction due to porosity loss with increasing effective stress that simulated consolidation behavior along with depressurization in the highly permeable sandy sediment. The apparent minimum change in porosity and permeability may be caused by the low compressibility of quartz sand grains in the recovered cores. XRD and thermal conductivity analysis also suggested high quartz content. Triaxial compression tests established internal friction angles based on the Mohr-Coulomb's failure criterion, which are 40° for hydrate-bearing sediment and 29.8° for hydrate free sediment.</p>

Yoneda, Jun↗

Platinum and Palladium Monolayer Electrocatalysts for Formic Acid Oxidation

The direct formic acid fuel cell holds great promise as a next generation portable power source. In this paper we report an experimental study on Pt and Pd monolayer (Pt* and Pd*) atop the close-packed facet of transition metal substrates (denoted Pt*/M or Pd*/M, where M = Pt, Pd, Ir, Au, Rh and Ru) model catalysts for formic acid oxidation (FAO) and demonstrate a promotional effect on Pt*/Au(111) and Pd*/Pt(111) surfaces. Contrary to findings on monometallic surfaces, in situ infrared reflection adsorption spectroscopy collected during formic acid oxidation at potentials anodic of 375 mV reveal that the poisoning reaction intermediate CO is not formed on the monolayer surfaces, suggesting a promotion of the direct mechanisms of FAO at the expense of the indirect mechanism through CO. Our density functional theory calculations on model surfaces with 1:1 stoichiometry for overlayer to support metal atoms for the thermochemistry of the elementary steps defined by adsorbed CO, OH, COOH, and HCOO on the (111) facet of Pt, PtML/Au, Pd, and PdML/Pt largely attribute the promotional effect observed for the monolayer catalysts to easier removal of CO brought about by easier activation of water, relative to the monometallic catalysts. This synergy between experiments and theory brings us closer to a fundamental understanding of FAO electrocatalysts under reaction conditions, paving the way to achieving more active electrocatalysts possibly with less Pt or Pd; a pre-requisite for the mass commercialization of this technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗