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arxiv: cond-mat/0210139 · v1 · submitted 2002-10-07 · ❄️ cond-mat.mtrl-sci

A Novel Predictive Tool in Nanoengineering: Straightforward Estimation of Superconformal Filling Efficiency

classification ❄️ cond-mat.mtrl-sci
keywords alphabetadynamicefficiencyepsilonfillinggrowthphysical
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It is shown that the superconformal filling (SCF) efficiency ($\epsilon_{SCF}$) of nano-scale cavities can be rationalized in terms of relevant physical and geometric parameters. Based on extensive numerical simulations and using the dynamic scaling theory of interface growth, it is concluded that the relevant quantity for the evaluation of $\epsilon_{SCF}$ is the so-called "physical" aspect ratio $S_{P} = L/M^{\beta/\alpha}$, where $\alpha$ ($\beta$) is the roughness (growth) exponent that governs the dynamic evolution of the system and $L$ ($M$) is the typical depth (width) of the cavity. The theoretical predictions are in excellent agreement with recently reported experimental data for the SCF of electrodeposited copper and chemically deposited silver in confined geometries, thus giving the basis of a new tool to manage nanoengineering-related problems not completely resolved so far.

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