Numerical algorithms for modelling electrodeposition: Tracking the deposition front under forced convection from megasonic agitation

Hughes, Michael S.; Strussevitch, Nadia; Bailey, C.; McManus, Kevin; Kaufmann, Jens Georg; Flynn, David; Desmulliez, Marc Phillipe Yves

doi:10.1002/fld.2140

Cited by 14 publications

(12 citation statements)

References 13 publications

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“…Where the ionic mobility u i , is assumed to be related to the diffusion coefficient D i by the Nernst-Einstein equation [32] that demonstrates the benefits of modeling of electrodeposition to predict plating outcomes [25][26][27]. For example Obaid et al, modeled the electroplating of hexavalent chromium to optimize the electrode spacing and anode height to obtain uniform thickness of the coating [28].…”

Section: Introductionmentioning

confidence: 99%

Modeling and simulation of electrodeposition: effect of electrolyte current density and conductivity on electroplating thickness

Mahapatro¹,

Suggu²

2018

Adv Mater Sci

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Electroplating or electrodeposition is a process carried out in an electrochemical cell where a current is used to form a coating on a metal surface. Developing and optimizing conditions for electroplating is time consuming and modeling and simulation could be used to optimize the electrodeposition process. Electrolyte current density and conductivity are important parameters for an electrodeposition system as they dictate the overall efficiency of flow of ions in the electrolyte system and thus optimization of these parameters is necessary. In this manuscript we report the development of a mathematical model to predict the electrodeposition of copper on cobalt chrome alloy in an electrochemical cell with copper and cobalt chrome alloy as the electrodes and copper sulfate as the electrolyte. The developed model was validated using experiments. The coating thickness of the samples was characterized using scanning electron microscope (SEM) and a thickness gage. At 30 min the model predicted the copper thickness to be 11.7 µm while experimentally the coating thickness was found to be 9.445+/-1.79 (mean +/-SD) using SEM and 12.375+/-1.36 (mean +/-SD) using thickness gauge. When predicting effect of current density the model accurately predicts general trends however the model seems to vary from experimental values in regions where there is significant effect of the electrochemical double layer that the model does not account for. The model accurately predicts the trend of effect of electrolyte conductivity on coating formation. The model can thus be used as a starting point to predict effect of process parameters on electrodeposition thickness

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Section: Introductionmentioning

confidence: 99%

Modeling and simulation of electrodeposition: effect of electrolyte current density and conductivity on electroplating thickness

Mahapatro¹,

Suggu²

2018

Adv Mater Sci

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“…As a result, in each time step we know the exact position of the interface. The EITM is implemented in FORTRAN, its preliminary version is described in [6,7]. At the end of each time step, the method determines the current position of the interface, computes the amount of copper deposited in this step, and updates the distribution of copper ions in the part of the domain that corresponds to the electrolyte.…”

Section: Modelingmentioning

confidence: 99%

Parametric modeling study of basic electrodeposition in microvias

Strusevich

Patel

Bailey

2012

2012 14th International Conference on Electronic Materials and Packaging (EMAP)

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In this paper, we present the results of a modeling study that investigates the material behavior in the electroplating process for the fabrication of micro-vias into printed circuit boards. The simulations are based on the technique that allows explicit tracking of the interface between the electrolyte and the deposited metal in each time step. The control parameters are the aspect ratio, copper ions concentration and initial current density. The response parameters are the filling time and two filling performance metrics.

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“…For Eulerian description of particle transport, an m-th order deposition reaction [23][24][25] can be conveniently used. Asphaltene particle deposition [23], SiO2 deposition [26] and copper electrodeposition [27] have been modeled as first order reaction. Besides, experimentally developed empirical correlations for modeling of particle deposition has been proposed and employed [28].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Particle Deposition in a Two-Fluid Flow Environment

Yap¹,

Goharzadeh²

2021

IJHT

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Particle deposition occurs in many engineering multiphase flows. A model for particle deposition in two-fluid flow is presented in this article. The two immiscible fluids with one carrying particles are model using incompressible Navier-Stokes equations. Particles are assumed to deposit onto surfaces as a first order reaction. The evolving interfaces: fluid-fluid interface and fluid-deposit front, are captured using the level-set method. A finite volume method is employed to solve the governing conservation equations. Model verifications are made against limiting cases with known solutions. The model is then used to investigate particle deposition in a stratified two-fluid flow and a cavity with a rising bubble. For a stratified two-fluid flow, deposition occurs more rapidly for a higher Damkholer number but a lower viscosity ratio (fluid without particle to that with particles). For a cavity with a rising bubble, deposition is faster for a higher Damkholer number and a higher initial particle concentration, but is less affected by viscosity ratio.

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Numerical algorithms for modelling electrodeposition: Tracking the deposition front under forced convection from megasonic agitation

Cited by 14 publications

References 13 publications

Modeling and simulation of electrodeposition: effect of electrolyte current density and conductivity on electroplating thickness

Modeling and simulation of electrodeposition: effect of electrolyte current density and conductivity on electroplating thickness

Parametric modeling study of basic electrodeposition in microvias

Modeling of Particle Deposition in a Two-Fluid Flow Environment

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