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

TL;DR

This paper introduces a new predictive tool for estimating superconformal filling efficiency in nanoengineering by relating it to physical and geometric parameters through dynamic scaling theory, validated by experimental data.

Contribution

It proposes a straightforward estimation method for superconformal filling efficiency using the physical aspect ratio and interface growth exponents, supported by numerical simulations and experimental validation.

Findings

The physical aspect ratio $S_P$ effectively predicts $ ext{SCF}$ efficiency.

Theoretical predictions align well with experimental data.

The method offers a new tool for nanoengineering applications.

Abstract

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.