Skip to main navigation Skip to search Skip to main content

Multi-objective optimization of tungsten CMP slurry for advanced semiconductor manufacturing using a response surface methodology

  • Jihoon Seo
  • , Joo Hyun Kim
  • , Myoungjae Lee
  • , Keungtae You
  • , Jinok Moon
  • , Dong Hee Lee
  • , Ungyu Paik
  • Hanyang University
  • Samsung

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, a response surface methodology (RSM) coupled with a face center cube design (FCD) was used to optimize the three principal components (i.e., Fe(NO3)3, H2O2, and SiO2 abrasives) in polishing slurries for a W barrier chemical mechanical planarization (CMP) process. The experimental ranges of the three components were 10–50 ppm of Fe(NO3)3, 0.3–0.9 wt% of H2O2, and 1–5 wt% of SiO2 abrasives. Based on the experimental data from the FCD, the second-order models for the material removal rate (MRR) of the W and Oxide films were fitted; these were determined to be statistically valid and reliable. We have achieved the optimal conditions for the three components where the MRR is maximized and the selectivity between the W and Oxide MRRs is ~ 1. The predicted MRR and selectivity at the optimal conditions were well correlated with the results of a confirmation run, which was conducted by using the W barrier CMP process with W-patterned wafers. In addition, we employed a particular RSM called dual-response optimization in order to investigate the tradeoff between the MRR and selectivity. Based on the tradeoff information, process engineers can conduct the optimization of the three components more flexibly.

Original languageEnglish
Pages (from-to)131-138
Number of pages8
JournalMaterials and Design
Volume117
DOIs
StatePublished - 5 Mar 2017
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Chemical mechanical planarization
  • Optimization
  • Response surface methodology
  • Semiconductor manufacturing process
  • Slurries

Fingerprint

Dive into the research topics of 'Multi-objective optimization of tungsten CMP slurry for advanced semiconductor manufacturing using a response surface methodology'. Together they form a unique fingerprint.

Cite this