Abstract
Abstract Mass transport in confined geometry in a paddle cell was studied using numerical simulation with an attempt to extrapolate an explicit correlation to understand the transport physics and to predict the electrodeposition rate of metal microstructures. A moving boundary in conjunction with mapped mesh was used to allow the reciprocating movement of the flow. A correlation was obtained based on a generalized additive model using multivariant linear regression. Neural networks were also used to analyze the efficacy of such correlation and to determine the descriptor characterizing the error in prediction. A two-step convectional mass transport process, one in the bulk electrolyte outside the patterns and the other inside the micro-trenches, were demonstrated to better describe the overall transport physics and improve the correlation.
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