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At least 775 records · Page 43

Domain epitaxial growth of ferroelectric films of barium strontium titanate on sapphire

A model of the epitaxial growth of crystalline multicomponent films on single-crystal substrates with a domain correspondence is presented using a solid solution of barium strontium titanate on sapphire substrates (r cut). The domain epitaxial growth suggests the matching of the lattice planes of the film and the substrate having similar structures by comparison of domain multiple of an integral number of the interplanar spacings. Variation of the component composition of the solid solution enables changes in the domain size in the range sufficient for epitaxial growth. This method can be used to project the epitaxial growth of films of various solid solutions on single-crystal substrates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kinetics of Early Decomposition Stages in Diluted bcc Fe–Сu–Ni–Al Alloy: MC+MD Simulation

A combined approach including the Monte Carlo and molecular-dynamics simulation, decomposition kinetics and segregation formation in the multicomponent low-alloy Fe–1.5Cu–2Ni–1.5Al (at %) alloy is studied. It is shown that the formation of Cu nanoparticles surface-enriched with Ni and Al (coprecipitation mode) includes several stages: (i) the formation of clusters consisting of several Cu atoms, (ii) their enrichment with Ni and Al atoms, and (iii) redistribution of Ni and Al atoms with the formation of a surface layer providing stabilization of Cu nanoparticles. Observed structural features of segregations and their stability in Fe–Cu–Ni–Al alloys is discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Specific Features of the Microstructure and Properties of Multielement Nitride Coatings Based on TiZrNbAlYCr

Multicomponent nanostructured coatings based on (TiZrNbAlYCr)N with a hardness as high as 47 GPa were obtained by cathodic arc deposition. The effect of partial nitrogen pressure P{sub N} (with constant bias potential U{sub b} =–200 V applied to the substrate) on the phase-composition variation, the size of crystallites, and their relation to the microstructure and hardness was investigated. An increase in the nitrogen pressure resulted in the formation of two phases with characteristic BCC (the lattice period is 0.342 nm) and FCC lattices with averaged nanocrystallite sizes of 15 and 2 nm. At a high pressure of 0.5 Pa, crystallites in the FCC phase with a lattice period of 0.437 nm grew in size to ~7 nm. The hardness of deposited coatings with larger (3.5 nm) FCC-phase crystallites and smaller (7 nm) BCC-phase crystallites was enhanced considerably.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A Locally Adapting Technique for Edge Detection using Image Segmentation

Rapid growth in the field of quantitative digital image analysis is paving the way for scientific researchers to make precise measurements about objects in an image. To compute quantities from an image such as the density of compressed materials or the velocity of a shockwave, object boundaries must first be determined. Images containing regions that each have a spatial trend in intensity are of particular interest here. For edge detection, we present a supervised, statistical image segmentation method that incorporates spatial information to locate boundaries between regions with overlapping intensity histograms, specifically for images where the regions are known but precise boundary locations are unknown. The segmentation of a pixel is determined by comparing its intensity to distributions from nearby pixel intensities, and a gradient of the segmented image indicates edge locations. Because of the statistical nature of the algorithm, we use maximum likelihood estimation to quantify uncertainty about each boundary. We demonstrate the success of this algorithm at locating boundaries and providing uncertainty bands on a radiograph of a multicomponent cylinder and on an optical image of a laser-induced shockwave.

97 MATHEMATICS AND COMPUTING↗

The Fascinating and Complex Dynamics of Geyser Eruptions

Geysers episodically erupt liquid and vapor. Despite two centuries of scientific study, basic questions persist-why do geysers exist? What determines eruption intervals, durations, and heights? What initiates eruptions? Through monitoring eruption intervals, analyzing geophysical data, taking measurements within geyser conduits, performing numerical simulations, and constructing laboratory models, some of these questions have been addressed. Geysers are uncommon because they require a combination of abundant water recharge, magmatism, and rhyolite flows to supply heat and silica, and large fractures and cavities overlain by low-permeability materials to trap rising multiphase and multicomponent fluids. Eruptions are driven by the conversion of thermal to kinetic energy during decompression. Larger and deeper cavities permit larger eruptions and promote regularity by isolating water from weather variations. Furthermore, the ejection velocity may be limited by the speed of sound of the liquid + vapor mixture.

58 GEOSCIENCES↗

On-Wafer Wide-Pore Anodic Aluminum Oxide

Anodized aluminum oxide (AAO) has been used as nanotemplates for nanomaterials and nanodevice fabrications. Microfabrication techniques are attracting attention for nanodevice synthesis. However, AAO requires a microfabrication-compatible substrate due to its brittleness. While there are studies that already show AAO on compatible substrates, the pore sizes may not be applicable for multicomponent nanodevices. In this study, wide pore AAOs with ohmic bottom contacts are fabricated on 76 mm Si wafers. Sputtering was used to deposit Al along with supporting layers to achieve this goal. A quiescent electropolishing technique was used to smooth the surface of Al. Standard photolithography was used to define the active area on the Al for anodization. Then 195 V two-step anodization was performed to fabricate wide pore AAOs with pore diameters ranging from 130 ± 32 nm to 400 ± 31 nm with interpore distance of 480 ± 47 nm. Furthermore, it also showed that the ordering of the pores depended on the current density over the more conventional anodization time.

25 ENERGY STORAGE↗

Electrochemical Measurement of Water Transport Numbers in Anion-Exchange Membranes

Anion-exchange membranes (AEMs) are a possible replacement for perfluorosulfonic-acid membranes in energy-conversion devices, primarily due to the hydroxide mobile ion allowing the devices to operate in alkaline conditions with less expensive electrocatalysts. However, the transport properties of AEMs remain understudied, especially electro-osmosis. In this work, an electrochemical technique, where the open-circuit voltage is measured between two ends of a membrane maintained at different relative humidities, is used to determine the water transport number of various ionomers, including Versogen and Sustainion AEMs and Nafion cation-exchange membrane (CEM), as a function of water content and temperature. In addition, the CEMs and AEMs are examined in differing single-ion forms, specifically proton and sodium (CEM) and hydroxide and carbonate (AEM). Carbonate-form AEMs have the highest transport number (∼11), followed by sodium-form CEMs (∼8), hydroxide-form AEMs (∼6), and proton-form CEMs (∼3). Finally, a multicomponent transport model based on the Stefan-Maxwell-Onsager framework of binary interactions is used to develop a link between water transport number and water-transport properties, extracting a range for the unmeasured membrane water permeability of Versogen as a function of water content.

30 DIRECT ENERGY CONVERSION↗

toughio v1.2.2

TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few. `toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. Currently, to the best of our knowledge, only PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments).

Luu, Keurfon↗

TOGA: A TOUGH code for modeling three-phase, multi-component, and non-isothermal processes involved in CO2-based Enhanced Oil Recovery (TOGA) v1.0

TOGA (TOUGH Oil, Gas, Aqueous) is a numerical reservoir simulator for modeling non-isothermal flow and transport of water, CO2, multicomponent oil, and related gas components for applications including CO2-enhanced oil recovery (CO2-EOR) and geologic carbon sequestration in depleted oil and gas reservoirs. TOGA uses an approach based on the Peng-Robinson equation of state (PR-EOS) to calculate the thermophysical properties of the gas and oil phases including the gas/oil components dissolved in the aqueous phase, and uses a mixing model to estimate the thermophysical properties of the aqueous phase.

Oldenburg, CurtisM↗

PFLOTRAN 5

PFLOTRAN leverages massively parallel, high performance computing to simulate large-scale non-isothermal multiphase flow, multicomponent reactive transport and electrical resistivity tomography (ERT) problems in the subsurface environment. Researchers have employed PFLOTRAN to simulate these Earth system processes on leadership class supercomputers for over two decades. The code is designed to predict the future estate of environmental systems and better inform stakeholders in the regulatory decision making process (e.g., fate of contaminants, long-term stewardship for nuclear waste, impact of climate change, etc.). A diverse team of scientists oversees PFLOTRAN development and maintenance under an open-source licensing agreement and manages contributions from an international community of researchers.

Hammond, Glenn↗

LBM3RT

Lattice Boltzmann Methods for Multiphase Multicomponent Reactive Transport

Kang, Qinjun↗

Compositional simulation of hydrocarbon recovery from oil shale reservoirs with diverse initial saturations of fluid phases by various thermal processes

We have studied the hydrocarbon production from oil shale reservoirs filled with diverse initial saturations of fluid phases by implementing numerical simulations of various thermal in-situ upgrading processes. We use our in-house fully functional, fully implicit, and non-isothermal simulator, which describes the in-situ upgrading processes and hydrocarbon recovery by multiphase-multicomponent systems. We have conducted two sets of simulation cases—five-spot well pattern problems and Shell In-situ Conversion Process (ICP) problems. In the five-spot well pattern problems, we have analyzed the effects of initial fluid phase that fills the single-phase reservoir and thermal processes by four cases—electrical heating in the single-phase-aqueous reservoir, electrical heating in the single-phase-gaseous reservoir, hot water injection in the single-phase-aqueous reservoir, and hot CO 2 -injection in the single-phase-gaseous reservoir. In the ICP problems, we have analyzed the effects of initial saturations of fluid phases that fill two-phase-aqueous-and-gaseous reservoir by three cases—initial aqueous phase saturations of 0.16, 0.44, and 0.72. Through the simulation cases, system response and production behavior including temperature profile, kerogen fraction profile, evolution of effective porosity and absolute permeability, phase production, and product selectivity are analyzed. In the five-spot well pattern problems, it is found that the hot water injection in the aqueous phase reservoir shows the highest total hydrocarbon production, but also shows the highest water-oil-mass-ratio. Productions of phases and components show very different behavior in the cases of electrical heating in the aqueous phase reservoir and the gaseous phase reservoir. In the ICP problems, it is found that the speed of kerogen decomposition is almost identical in the cases, but the production behavior of phases and components is very different. It is found that more liquid organic phase has been produced in the case with the higher initial saturation of aqueous phase by the less production of gaseous phase.

04 OIL SHALES AND TAR SANDS↗

Assessing the Effectiveness and Interactions of Instructional Coaches: Initial Psychometric Evidence for the Instructional Coaching Assessments–Teacher Forms

The conceptual foundation and initial psychometric evidence are provided for the Instructional Coaching Rating Scales and Interaction Style Scales–Teacher Forms. These forms are part of a multicomponent online assessment system designed to evaluate the effectiveness of coaching skills and interactions that support the needs of teachers and students. Specifically, the article presents the theory, evidence, and measurement framework for the system. Findings indicate that the Rating Scales and Interaction Style Scales–Teacher Forms have very good internal structures based on multiple fit statistics for confirmatory factor analyses, high internal consistency, good item-to-scale total correlations, and freedom from item bias. Collectively, this promising statistical evidence is supportive of valid score inferences. Study limitations and directions for research are discussed.

Reddy, Linda A.↗

Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

Abstract MF-LOGP, a new method for determining a single component octanol–water partition coefficients ( $$LogP$$ LogP ) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make $$LogP$$ LogP predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average $$RMSE$$ RMSE = 0.77 ± 0.007, $$MAE$$ MAE = 0.52 ± 0.003, and $${R}^{2}$$ R 2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ( $$RMSE$$ RMSE = 0.42–1.54, $$MAE$$ MAE = 0.09–1.07, and $${R}^{2}$$ R 2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures. Graphical Abstract

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Joint PP and PS plane-wave wave-equation migration-velocity analysis

Conventional joint PP and PS velocity analysis is based on ray tomography. We develop a joint PP and PS wave-equation migration-velocity-analysis method using plane-wave common-image gathers (CIGs) to produce accurate P- and S-wave velocity models. The objective function of our new method consists of three terms: The first and second terms penalize the moveout residuals computed from PP and PS plane-wave CIGs, respectively, and the third term constrains the nonzero relative depth shifts between the PP and PS migration images. The moveout of plane-wave CIGs is automatically picked using a semblance analysis method, and the relative depth shifts between the PP and PS images are automatically computed using dynamic warping or manually picking the depths of certain primary reflectors. The moveout residuals and the relative depth shifts are transformed into weighted image perturbations, and they are then projected into the velocity models to update the P- and S-wave velocity models using the scalar-wave equations and their linearized forms. Here, numerical tests with synthetic and multicomponent field data demonstrate that our method can simultaneously invert for accurate P- and S-wave velocity models for elastic migration.

58 GEOSCIENCES↗

Vector elastic deconvolution migration with dual wavefield decomposition

Here, we report elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

58 GEOSCIENCES↗

Quadri-joint inversion: Method and application to the Big Sky 9C 3D data set in northern Montana

The Kevin Dome [Formula: see text] storage project, located in northern Montana, attempted to characterize the Duperow Formation as a potential long-term storage zone for injected [Formula: see text]. A multicomponent (9C) seismic survey was acquired for the Big Sky Carbon Sequestration Partnership over a portion of the Kevin Dome using P- and S-wave sources. Prestack migrated PP, PS, SH, and SV data sets were generated. We then applied several stratigraphic inversion workflows using one or several kinds of seismic wavefield at the same time resulting in joint inversions of each data set. The aim of our study is to demonstrate the benefits of doing quadri-joint inversion of PP-, PS-, SH-, and SV-wavefields for the recovery of the elastic earth parameters, especially the S-wave impedance and density. These are crucial parameters because they can help determine lithology and porefill in the reservoir characterization workflow. Because the inversion workflow always uses the original seismic data recorded in its own time domain, it is necessary to compute registration laws between PP-PS-, PP-SH-, and PP-SV-wavefields using a time shift computation procedure (warping) based on inverted S-wave impedances from inversion of a single wavefield. This generated a significant improvement over methods that rely on attempting to match trace waveforms that may have a different phase, frequency content, and polarity. Finally, we wanted to investigate the reliability of the quadri-joint inversion results in the Bakken/Banff Formations, which have less lateral geologic variation than the underlying Duperow target. This interval shares many of the geophysical characterization challenges common to shale reservoirs in other North American basins. We computed geomechanical parameters, such as Poisson’s ratio and Young’s modulus, which are a proxy for brittleness. Comparison of these results with independent laboratory measurements in the Bakken interval demonstrates the superiority of the quadri-joint inversion method to the traditional inversion using P-wave data only.

Geochemistry & Geophysics↗

Model Data Archive Associated with Manuscript "Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon"

This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.

ATS↗