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• W4221128131 endingPage "109404" @default.
• W4221128131 startingPage "109404" @default.
• W4221128131 abstract "Recently, polymer composite-based flexible electronic designs and applications have been gradually increased. Production process flows cause cost in time and budget without predefined percolation threshold that is the most critical level of polymer conductor composites (PCC). Also, the onset of the percolation threshold is defined in this study which is the starting and avalanche point of the conduction regime. By knowing the percolation threshold, the composite ingredient ratio can be altered for proper conduction. This yields a lean conductive composite design with the potential to be utilized prior to fabrication. Determining the main recipe of composite becomes faster and easier. This article evaluates the methodologies for finding the onset of the percolation threshold and provides a reduction in the number of experiments to determine the recipe. Experimentally, materials containing different ratios of carbon black (CB) were tested. Simulation software is created, and the results are verified with the experimental findings. Accordingly, the percolation onset was around 5.6% by weight. To create a suitable methodology, models based on resistive networks were worked out. A*, A* Depth, Best First Search, Breadth-First Search, Dijkstra's Fastest Pathfinding Algorithms are run for different CB ratios. With this study, a feasible simulation was designed for all composites in which the percolation threshold changes depending on the tunneling distance." @default.
• W4221128131 created "2022-04-03" @default.
• W4221128131 creator A5005895894 @default.
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• W4221128131 date "2022-06-01" @default.
• W4221128131 modified "2023-09-26" @default.
• W4221128131 title "Determining electrical percolation threshold of randomly distributed conductor materials in polymer composites via pathfinding algorithms" @default.
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• W4221128131 doi "https://doi.org/10.1016/j.compscitech.2022.109404" @default.
• W4221128131 hasPublicationYear "2022" @default.
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