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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24

Characterization of Coal Refuse Sites in West Virginia: Stream Loss, Volume Estimation, and Land Cover Analysis for Restoration Feasibility

Coal refuse disposal across Appalachia has resulted in widespread environmental degradation, including stream burial, landscape destabilization, and long-term hydrologic impacts. This study provides a GIS-based spatial characterization of 623 coal refuse sites in West Virginia, evaluating their potential for ecological and economic restoration. Stream loss was quantified through digitization of historic topographic maps, revealing over 194,500 meters of historically present streams lost, with 105,000 meters directly buried beneath refuse piles. Volume estimation using empirical Bayesian kriging and modern LiDAR surfaces indicated approximately 1.96 billion cubic meters of deposited refuse. Land cover analysis based on NAIP-derived classification showed that 48% of the total site area was forested, while 15% remained barren. These results highlight not only the environmental footprint of legacy refuse deposits but also their potential for restoration through stream daylighting and beneficial reuse. Emerging opportunities, including rare earth element recovery and mitigation banking, may offer economic incentives to facilitate reclamation. This work establishes a spatial framework to prioritize refuse sites for restoration, balancing ecological uplift with feasible material management strategies.

58 GEOSCIENCES↗

Catalysis: Volume 36 (Preface)

This volume reviews the extensive literature published in the area of microwave-assisted catalytic approaches for waste conversion, non-reductive CO2 conversion, CO₂ utilization, heterogeneous catalysis and its integration with solid oxide electrolysis cell (SOEC) systems for chemical production, mechanistic pathways in ethylene epoxidation.

CO2 utilization↗

Attribute-Aware RBFs: Interactive Visualization of Time Series Particle Volumes Using RT Core Range Queries

Smoothed-particle hydrodynamics (SPH) is a mesh-free method used to simulate volumetric media in fluids, astrophysics, and solid mechanics. Visualizing these simulations is problematic because these datasets often contain millions, if not billions of particles carrying physical attributes and moving over time. Radial basis functions (RBFs) are used to model particles, and overlapping particles are interpolated to reconstruct a high-quality volumetric field; however, this interpolation process is expensive and makes interactive visualization difficult. Existing RBF interpolation schemes do not account for color-mapped attributes and are instead constrained to visualizing just the density field. To address these challenges, we exploit ray tracing cores in modern GPU architectures to accelerate scalar field reconstruction. We use a novel RBF interpolation scheme to integrate per-particle colors and densities, and leverage GPU-parallel tree construction and refitting to quickly update the tree as the simulation animates over time or when the user manipulates particle radii. We also propose a Hilbert reordering scheme to cluster particles together at the leaves of the tree to reduce tree memory consumption. Finally, we reduce the noise of volumetric shadows by adopting a spatially temporal blue noise sampling scheme. Our method can provide a more detailed and interactive view of these large, volumetric, time-series particle datasets than traditional methods, leading to new insights into these physics simulations.

Particle Volumes↗

Single and Dual-Solute Transport in Quaternary Ammonium-Functionalized Anion Exchange Membranes: Isolating the Impact of Water Volume Fraction

Membranes are essential components of photoelectrochemical CO 2 reduction cells (PEC-CRC), as they regulate solute transport and impact device efficiency. These cells are a promising approach for converting carbon dioxide into valuable chemicals. However, electrochemical reactions involve not just a single electrolyte; membrane transport typically includes multiple electrolytes. When a mixture of solutes is present, the presence of one solute in the membrane can impact the diffusion and sorption of other solutes. In complex systems where multiple solutes are diffusing simultaneously through a hydrated, dense polymer membrane, the resulting transport behavior is poorly understood. This study highlights the individual and two solute transport behavior of potassium formate, acetate, and bicarbonate ions in neutral membranes and quaternary ammonium-functionalized anion exchange membranes (AEMs) based on phenyl acrylate polymer backbones. By isolating the effect of water content, we emphasize how fixed charge density and solute-membrane interactions influence transport behavior. In neutral membranes, the diffusivity follows the order of potassium formate > potassium acetate > potassium bicarbonate. However, in AEMs, the order shifts due to changes in ion-membrane interactions, with potassium bicarbonate diffusivity surpassing that of potassium acetate. These results underscore the importance of ion exchange membranes and ion-membrane interaction in modulating transport properties, providing valuable insights for optimizing membranes in electrochemical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CoordNet: Data Generation and Visualization Generation for Time-Varying Volumes via a Coordinate-Based Neural Network

Although deep learning has demonstrated its capability in solving diverse scientific visualization problems, it still lacks generalization power across different tasks. To address this challenge, we propose CoordNet, a single coordinate-based framework that tackles various tasks relevant to time-varying volumetric data visualization without modifying the network architecture. The core idea of our approach is to decompose diverse task inputs and outputs into a unified representation (i.e., coordinates and values) and learn a function from coordinates to their corresponding values. We achieve this goal using a residual block-based implicit neural representation architecture with periodic activation functions. We evaluate CoordNet on data generation (i.e., temporal super-resolution and spatial super-resolution) and visualization generation (i.e., view synthesis and ambient occlusion prediction) tasks using time-varying volumetric data sets of various characteristics. Here, the experimental results indicate that CoordNet achieves better quantitative and qualitative results than the state-of-the-art approaches across all the evaluated tasks. Source code and pre-trained models are available at https://github.com/stevenhan1991/CoordNet.

97 MATHEMATICS AND COMPUTING↗