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At least 1,135 records · Page 63

A High Energy X-ray Diffraction Study of Amorphous Indomethacin

Amorphous pharmaceuticals often possess a wide range of molecular conformations and bonding arrangements. The x-ray pair distribution function (PDF) method is a powerful technique for the characterization of variations in both intra-molecular and inter-molecular packing arrangements. Here, the x-ray PDF of amorphous Indomethacin is shown to be particularly sensitive to the preferred orientations of the chlorobenzyl ring found in isomers in the crystalline state. In some cases, the chlorobenzyl ring has no preferred torsional angle in the amorphous form, while in others evidence of distinct isomer orientations are observed. Amorphous samples with no preferred torsion angles of the chlorobenzyl ring are found to favor enhanced inter-molecular hydrogen bonding, and this is reflected in the intensity of the first sharp diffraction peak. These significant variations in structure rule out amorphous Indomethacin as a possible standard for x-ray PDF measurements. At high humidity, time resolved PDF's for >40 h reveal water molecules forming hydrogen bonds with Indomethacin molecules. Finally, a simple linear hydrogen bond model indicates that water molecules in the wet amorphous form have similar hydrogen bond strengths to those found between Indomethacin dimers or chains in the dry amorphous form.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solar-assisted gas-energy water-heating feasibility for apartments

Studies of residential energy use, solar-energy technology for buildings, and the requirements for implementing technology in the housing industry led to a project to develop a solar water heater for apartments. A design study for a specific apartment was used to establish a solar water-heater cost model which is based on plumbing contractor bids and manufacturer estimates. The cost model was used to size the system to minimize the annualized cost of hot water. The annualized cost of solar-assisted gas-energy water heating is found to be less expensive than electric water heating but more expensive than gas water heating. The feasibility of a natural gas utility supplying the auxiliary fuel is evaluated. It is estimated that gas-utilizing companies will find it profitable to offer solar water heating as part of a total energy service option or on a lease basis when the price of new base-load supplies of natural gas reaches $2.50-$3.00 per million Btu.

Davis, E. S.↗

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set.

Gulden, L. E.↗

Climate-Water-Electricity Interactions in the U.S. Under Alternative Decarbonized Futures

The U.S. electric sector is rapidly evolving, with widespread renewable energy deployment, building and transport electrification, and nuanced decarbonization policies. Climate change influences the supply and demand for electricity by altering water resources for cooling and hydropower, thermal plant efficiencies, and heating and cooling demand. This research combines global climate model data, asset-level water and streamflow modeling, and electric sector capacity expansion modeling to study climate-water-electricity interactions across myriad future climate and electricity scenarios that consider electrification and decarbonization using renewable, hydrogen, carbon capture, and nuclear technologies. Multi-model integration leads to insights into power-water sector interactions and their impacts on grid economics and environmental outcomes.

climate change↗

Thermal migration of water on the Galilean satellites

We have modeled the thermal migration of water on the Galilean satellites under the assumption of ballistic molecular trajectories. It is found that water migrating owing to solar radiation on an ice-covered satellite will build up in temperate latitudes, in general not reaching the poles. As much as 50 m of ice may have been lost by this process from the equatorial regions of Europa over the age of the solar system. The disappearance of patches of ice - for instance, the bright rays surrounding some impact craters - from the equatorial regions of Ganymede and Callisto may approach a value (the irreversible evaporation rate) three orders of magnitude larger than the net equatorial loss rate for ice-covered Europa. The presence of water ice pole caps on Ganymede extending to the latitudes at which thermal migration becomes important suggests that some process distributed an extensive, thin covering of water on the satellite, and that the equatorial regions were subsequently cleared by the thermal process.

Purves, N. G.↗

Modeled and Empirical Approaches for Retrieving Columnar Water Vapor from Solar Transmittance Measurements in the 0.72, 0.82, and 0.94 Micrometer Absorption Bands

A Sun photometer (18 channels between 300 and 1024 nm) has been used for measuring the columnar content of atmospheric water vapor (CWV) by solar transmittance measurements in absorption bands with channels centered at 719, 817, and 946 nm. The observable is the band-weighted transmittance function defined by the spectral absorption of water vapor and the spectral features of solar irradiance and system response. The transmittance function is approximated by a three-parameter model. Its parameters are determined from MODTRAN and LBLRTM simulations or empirical approaches using CWV data of a dual-channel microwave radiometer (MWR) or a Fourier transform spectrometer (FTS). Data acquired over a 2-year period during 1996-1998 at two different sites in Switzerland, Bern (560 m above sea level (asl)) and Jungfraujoch (3580 m asl) were compared to MWR, radiosonde (RS), and FTS retrievals. At the low-altitude station with an average CWV amount of 15 mm the LBLRTM approach (based on recently corrected line intensities) leads to negligible biases at 719 and 946 nm if compared to an average of MWR, RS, and GPS retrievals. However, at 817 nm an overestimate of 2.7 to 4.3 mm (18-29%) remains. At the high-altitude station with an average CWV amount of 1.4 mm the LBLRTM approaches overestimate the CWV by 1.0, 1.4. and 0.1 mm (58, 76, and 3%) at 719, 817, and 946 nm, compared to the ITS instrument. At the low-altitude station, CWV estimates, based on empirical approaches, agree with the MWR within 0.4 mm (2.5% of the mean); at the high-altitude site with a factor of 10 less water vapor the agreement of the sun photometers (SPM) with the ITS is 0.0 to 0.2 mm (1 to 9% of the mean CWV there). Sensitivity analyses show that for the conditions met at the two stations with CWV ranging from 0.2 to 30 mm, the retrieval errors are smallest if the 946 nm channel is used.

Ingold, T.↗

The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO 2 , temperature, water, and nitrogen (version 1.0)

Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate

Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

soil↗

Fluids During Diagenesis and Sulfate Vein Formation in Sediments at Gale Crater, Mars

We model the fluids involved in the alteration processes recorded in the Sheep bed Member mudstones of Yellowknife Bay (YKB), Gale crater, Mars, as revealed by the Mars Science Laboratory Curiosity rover investigations. We compare the Gale crater waters with fluids modeled for shergottites, nakhlites, and the ancient meteorite ALH 84001, as well as rocks analyzed by the Mars Exploration rovers, and with terrestrial ground and surface waters. The aqueous solution present during sediment alteration associated with phyllosilicate formation at Gale was high in Na, K, and Si; had low Mg, Fe, and Al concentrations relative to terrestrial ground waters such as the Deccan Traps and other modeled Mars fluids; and had near neutral to alkaline pH. Ca and S species were present in the 10(exp -3) to 10(exp -2) concentration range. A fluid local to Gale crater strata produced the alteration products observed by Curiosity and subsequent evaporation of this ground water- type fluid formed impure sulfate- and silica-rich deposits veins or horizons. In a second, separate stage of alteration, partial dissolution of this sulfate-rich layer in Yellowknife Bay,or beyond, led to the pure sulfate veins observed in YKB. This scenario is analogous to similar processes identified at a terrestrial site in Triassic sediments with gypsum veins of the Mercia Mudstone Group in Watchet Bay, UK.

Gale Crater↗

Theory of hydrophobicity: transient cavities in molecular liquids

Observation of the size distribution of transient cavities in computer simulations of water, n-hexane, and n-dodecane under benchtop conditions shows that the sizes of cavities are more sharply defined in liquid water but the most-probable-size cavities are about the same size in each of these liquids. The calculated solvent atomic density in contact with these cavities shows that water applies more force per unit area of cavity surface than do the hydrocarbon liquids. This contact density, or "squeezing" force, reaches a maximum near cavity diameters of 2.4 angstroms. The results for liquid water are compared to the predictions of simple theories and, in addition, to results for a reference simple liquid. The numerical data for water at a range of temperatures are analyzed to extract a surface free energy contribution to the work of formation of atomic-size cavities. Comparison with the liquid-vapor interfacial tensions of the model liquids studied here indicates that the surface free energies extracted for atomic-size cavities cannot be accurately identified with the macroscopic surface tensions of the systems.

NASA Center ARC↗

Combining Distributed Electrochemical Measurements with a Semi-Empirical Model to Identify Local Variations in Overpotentials for PEM Water Electrolyzers

Abstract A segmented cell and PCB approach was used to demonstrate an advanced technique for measuring and understanding the electrochemical behavior of PEM water electrolyzers. By employing a semi-empirical model, discrete modes of overpotential and their spatial distributions were identified in an operating cell. Distributed area-specific resistance (DASR measurements indicate that local dehydration of the polymer electrolyte membrane is the primary driver of increased polarization, behaving similarly to mass transport-limited currents at low flow rates due to ineffective gas-phase bubble removal. To improve quantification, the overall ohmic overpotential is divided into background (η Ohm,b ) and mass transport-coupled (η Ohm,mt ) components. Two types of anode diffusion media, a baseline PTL and a thin foil liquid/gas diffusion layer (LGDL), were examined. The results show significant variations in η Ohm,b and highlight that ineffective bubble removal leads to pronounced local dehydration. The effect of cell temperature on various overpotentials was also examined. Negligible differences in diffusion overpotential were observed when comparing PEWE performance using the PTL and LGDL, despite major differences in two-phase fluid transport within each diffusion media. This underscores the critical role of the catalyst layer's micro-porous structure in diffusion processes. The study highlights the complex nature and intricacies of mass transport limitations within PEWEs.

Roy, Anirban (ORCID:0000000163803386)↗

Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes

Both lateral surface and subsurface water flow affect soil moisture dynamics, yet most land surface models only solve subsurface water movement vertically. Here, we use a 3D ecosystem model that considers both land surface and subsurface hydrologic processes to simulate soil moisture, which is then used to drive a 1-D vertical soil thermal model to simulate the soil moisture effects on soil thermal dynamics in central Alaska. Our coupled model improves soil temperature (ST) estimates by 43.5% in comparison with observational data. Soil moisture has little effect on ST during the wet season (-1.5%) and a substantial influence during the dry season (60%). Spatially, water lateral flow has significant impacts on both soil moisture and ST, causing model estimates for thawed areas in the transition season to increase by ~10% in the study area. Our results highlight the importance of considering dynamical soil moisture, as well as lateral flow effects, on soil thermal dynamics in permafrost regions.

54 ENVIRONMENTAL SCIENCES↗

Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

54 ENVIRONMENTAL SCIENCES↗

Neural Networks for Prediction of Complex Chemistry in Water Treatment Process Optimization

Water chemistry plays a critical role in the design and operation of water treatment processes. Detailed chemistry modeling tools use a combination of advanced thermodynamic models and extensive databases to predict phase equilibria and reaction phenomena. The complexity and formulation of these models preclude their direct integration in equation-oriented modeling platforms, making it difficult to use their capabilities for rigorous water treatment process optimization. Neural networks (NN) can provide a pathway for integrating the predictive capability of chemistry software into equation-oriented models and enable optimization of complex water treatment processes across a broad range of conditions and process designs. Herein, we assess how NN architecture and training data impact their accuracy and use in equation-oriented water treatment models. We generate training data using PhreeqC software and determine how data generation and sample size impact the accuracy of trained NNs. The effect of NN architecture on optimization is evaluated by optimizing hypothetical black-box desalination processes using a range of feed compositions from USGS brackish water data set, tracking the number of successful optimizations, and testing the impact of initial guess on the final solution. Our results clearly demonstrate that data generation and architecture impact NN accuracy and viability for use in equation-oriented optimization problems.

Dudchenko, Alexander V↗

NUMERICAL INVESTIGATION OF AIR DEHUMIDIFICATION THROUGH WATER DROPLETS DIELECTROPHORESIS

This paper numerically investigated the dehumidification of moist airflow in a converging rectangular duct with electrically enhanced condensation. The aim was to develop a condensation model that predicted water vapor condensation by employing the dielectrophoresis principle. The charged droplets were injected into the computational domain to produce a gradient electric field. The dielectrophoretic interaction between the droplets and vapor molecules of the humid air resulted in local water vapor condensation at the vapor and liquid droplet interface. This phenomenon is described in detail in this paper. A hybrid Eulerian-Lagrangian solver SprayFoam was developed based on OpenFOAM® to simulate condensation in two-phase gas-liquid mixtures. The following developments were made based on the standard compressible multiphase flow solver SprayFoam in OpenFOAM®: (1) Eulerian solver for gas phase (2) multi-component species transport, and (3) Lagrangian solver for gas-droplet two-phase flows and sub-models for liquid droplets. The newly developed numerical model was experimentally validated with data from a series of tests conducted in the authors' laboratory. The results showed that the simulations followed the same trends as the data, and the model predicted the condensation due to the electro-spray injection process in the air stream. The injected water droplets, which are electrically charged to their Rayleigh limits, increased in size while wiping out the humidity from the air. The simulations indicated that the dehumidification was about 1% for 0.5 cubic feet per minute airflow rate. Scaling up to larger flows is a future follow-up work.

Yel Mahi, *Maliha↗

Mesoscale modelling of dynamic porosity in cement hydrate gel during a water sorption cycle: A lattice Boltzmann study

We describe a lattice Boltzmann modelling framework for fluid sorption coupled to a dynamic model of cement hydrate microstructure upon which it is possible to explore ideas of water sorption in cement emergent from NMR and other recent experimental studies. The results of the first simulations using the model are presented. We show that it is possible to extract transport and microstructural relaxation parameters from the simulations that are in good qualitative agreement with experiment. We discuss limitations of the methodology.

36 MATERIALS SCIENCE↗

Metal oxide candidates for thermochemical water splitting obtained with a generative diffusion model

Generative diffusion models (DMs) for inorganic crystalline materials are being actively investigated for their potential to expand the chemical and structural design spaces for known functional materials. Generative candidates are particularly useful for applications where few functional, let alone commercially viable, materials currently exist, such as metal oxides for thermochemical water-splitting, which have strict requirements for defect thermodynamics and host stability. Here, we critically examine generated metal oxides from the M ATTER G EN DM conditioned on select chemical systems for thermochemical water splitting applications. Perhaps most notably, we find that M ATTER G EN predicts a novel, thermodynamically stable, quinary metal oxide, Ba 2 SrInFeO 6 , although this compound represents an ordered and layered substitution within the same A 3 B 2 O 6 structural prototype as its two ternary end members. Detailed density functional theory calculations and spin configuration sampling for this material and its possible decomposition products—beyond what existed in M ATTER G EN training data—are required to quantitatively validate hull energy predictions and conclusions of stability. Furthermore, the material exhibits oxygen defect formation energies appropriate for thermochemical water splitting, warranting targeted investigation in an experimental validation campaign, along with other future M ATTER G EN candidates in this application space.

36 MATERIALS SCIENCE↗

Measuring and Modeling of the Dielectric Properties and Attenuation of Vegetation

The dielectric properties and attenuation of vegetation was measured and modeled. The purpose was to: (1) measure the microwave dielectric properties of vegetation material as a function of moisture content and microwave frequency; (2) develop dielectric mixing models for the vegetation-water mixture; (3) develop a model for the loss factor of a vegetation canopy; (4) relate the results of (1) and (2) to (3); and (5) test the model in (3) against direct canopy transmission measurements.

F Ulaby↗