The University of Southampton
University of Southampton Institutional Repository

Effect of process parameters on the surface morphology and mechanical performance of silicon structures after deep reactive ion etching (DRIE)

Effect of process parameters on the surface morphology and mechanical performance of silicon structures after deep reactive ion etching (DRIE)
Effect of process parameters on the surface morphology and mechanical performance of silicon structures after deep reactive ion etching (DRIE)
The ability to predict and control the influence of process parameters during silicon etching is vital for the success of most MEMS devices. In the case of deep reactive ion etching (DRIE) of silicon substrates, experimental results indicate that etch performance as well as surface morphology and post-etch mechanical behavior have a strong dependence on processing parameters. In order to understand the influence of these parameters, a set of experiments was designed and performed to fully characterize the sensitivity of surface morphology and mechanical behavior of silicon samples produced with different DRIE operating conditions. The designed experiment involved a matrix of 55 silicon wafers with radius hub flexure (RHF) specimens which were etched 10 min under varying DRIE processing conditions. Data collected by interferometry, atomic force microscopy (AFM), profilometry, and scanning electron microscopy (SEM), was used to determine the response of etching performance to operating conditions. The data collected for fracture strength was analyzed and modeled by finite element computation. The data was then fitted to response surfaces to model the dependence of response variables on dry processing conditions
1057-7157
264-275
Chen, Kuo-Shen
948bab7a-ad0b-4d67-bdda-a8b1f5bcaae2
Ayon, A.A.
5af60c6b-b908-435b-9e9c-cabf8d51e480
Zhang, Xin
3056a795-80f7-4bbd-9c75-ecbc93085421
Spearing, S.M.
9e56a7b3-e0e8-47b1-a6b4-db676ed3c17a
Chen, Kuo-Shen
948bab7a-ad0b-4d67-bdda-a8b1f5bcaae2
Ayon, A.A.
5af60c6b-b908-435b-9e9c-cabf8d51e480
Zhang, Xin
3056a795-80f7-4bbd-9c75-ecbc93085421
Spearing, S.M.
9e56a7b3-e0e8-47b1-a6b4-db676ed3c17a

Chen, Kuo-Shen, Ayon, A.A., Zhang, Xin and Spearing, S.M. (2002) Effect of process parameters on the surface morphology and mechanical performance of silicon structures after deep reactive ion etching (DRIE). Journal of Microelectromechanical Systems, 11 (3), 264-275. (doi:10.1109/JMEMS.2002.1007405).

Record type: Article

Abstract

The ability to predict and control the influence of process parameters during silicon etching is vital for the success of most MEMS devices. In the case of deep reactive ion etching (DRIE) of silicon substrates, experimental results indicate that etch performance as well as surface morphology and post-etch mechanical behavior have a strong dependence on processing parameters. In order to understand the influence of these parameters, a set of experiments was designed and performed to fully characterize the sensitivity of surface morphology and mechanical behavior of silicon samples produced with different DRIE operating conditions. The designed experiment involved a matrix of 55 silicon wafers with radius hub flexure (RHF) specimens which were etched 10 min under varying DRIE processing conditions. Data collected by interferometry, atomic force microscopy (AFM), profilometry, and scanning electron microscopy (SEM), was used to determine the response of etching performance to operating conditions. The data collected for fracture strength was analyzed and modeled by finite element computation. The data was then fitted to response surfaces to model the dependence of response variables on dry processing conditions

Text
23018.pdf - Version of Record
Download (314kB)

More information

Published date: 2002

Identifiers

Local EPrints ID: 23018
URI: http://eprints.soton.ac.uk/id/eprint/23018
ISSN: 1057-7157
PURE UUID: db704c88-ffe8-4463-ae50-2d7664f46316
ORCID for S.M. Spearing: ORCID iD orcid.org/0000-0002-3059-2014

Catalogue record

Date deposited: 27 Mar 2006
Last modified: 16 Mar 2024 03:37

Export record

Altmetrics

Contributors

Author: Kuo-Shen Chen
Author: A.A. Ayon
Author: Xin Zhang
Author: S.M. Spearing ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×