Journal article
Feature evolution simulations of copper seed layer deposition using atomic-level particle scattering information
IEEE transactions on plasma science, v 27(5), pp 1433-1440
Oct 1999
Abstract
One of the most important processing steps during copper metallization is the deposition of a thin yet conformal copper seed layer, often using ionized physical vapor deposition, prior to electroplating. A key need in designing this step is assuring that copper of sufficient thickness is deposited at all points within a high aspect ratio (AR) feature. In this work, we present feature evolution simulations of copper seed layer deposition, using ion reflection and neutral copper sputtering distributions calculated using molecular dynamics simulations. Independent variables in the model include neutral-ion and ion-ion flux ratios as well as substrate bias voltage. We show that trenches of AR=5 can be conformally lined with proper variation of these independent variables using a simple composition and ion energy cycling strategy. Furthermore, we show that the use of reflection and sputtering distributions obtained by molecular dynamics simulation results in qualitatively different feature shape predictions than when using isotropic (cosine) sputtering distributions with no possibility of ion reflection, with the degree of difference a function of the ion-neutral flux ratio and the ion energy.
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Details
- Title
- Feature evolution simulations of copper seed layer deposition using atomic-level particle scattering information
- Creators
- M.A Vyvoda - Dept. of Chem. Eng., California Univ., Berkeley, CA, USAC.F AbramsD.B Grave
- Publication Details
- IEEE transactions on plasma science, v 27(5), pp 1433-1440
- Publisher
- IEEE
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Chemical and Biological Engineering
- Web of Science ID
- WOS:000083453000026
- Scopus ID
- 2-s2.0-0033204910
- Other Identifier
- 991014969752104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Physics, Fluids & Plasmas