LVIII. On the effects of magnetic fields on the electric conductivity of Bismuth [PDF]
James B. Henderson
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The fabrication and post‐treatment via solvent annealing of poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate‐based electrodes using spray deposition in a roll‐to‐roll setup are presented. The decrease in sheet resistance and its correlation with nanostructure and molecular structure in the electrodes as a function of the processing parameters is ...
Marie Betker+10 more
wiley +1 more source
Effect of Tree Quantity and Distribution on the Electric Field under Transmission Lines
The electric field of transmission lines has serious negative impacts on residents’ production and life with the expansion of high voltage engineering.
Ziyu Wang+5 more
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III. On the potential of the electric field in the neighbourhood of a spherical bowl, charged or under influence [PDF]
J. Nieuwenhuyzen Kruseman
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Enhanced Fog Water Harvesting on Superhydrophobic Steel Meshes
Fog harvesting using mesh designs offers a sustainable solution to water scarcity. This study highlights key considerations for fog harvesting research and develops a methodology for a standardized protocol reflecting fog characteristics and environmental conditions.
Pegah Sartipizadeh+3 more
wiley +1 more source
The Electric Field Produced by an Eccentric Dipole in a Homogeneous Circular Conducting Lamina [PDF]
Robert H. Bayley
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Machine Learning‐Guided Discovery of Factors Governing Deformation Twinning in Mg–Y Alloys
This study uses interpretable machine learning to identify key microstructural and processing parameters related to twinning in magnesium‐yttrium (Mg–Y) alloys. It is identified that using only grain size, grain orientation, and total applied strain, grains can be classified with 84% accuracy based on whether the grain contains a twin.
Peter Mastracco+8 more
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Unipolar Potential Measurements in the Electric Field Produced by an Arbitrary Dipole in a Circular Homogeneous Lamina [PDF]
Robert H. Bayley
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Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani+4 more
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Plasma fluctuations in crossed electric and magnetic fields [PDF]
Hugh W. Batten+2 more
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