Dr. Nan Qin Profile

Dr. Nan Qin

at Enthought Inc

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 26 March 2019 Paper

New method removing SEM image noise to characterize CD and LWR

Shinji Kobayashi, Satoru Shimura, Masashi Enomoto, Robert Kern, Timothy Diller, Tony McDaniel, Nan Qin, Thomas Reay, Roger Serwy

Proceedings Volume 10959, 109592N (2019) https://doi.org/10.1117/12.2514661

KEYWORDS: Line width roughness, Scanning electron microscopy, Image processing, Image analysis, Image filtering, Stochastic processes, Semiconducting wafers, Critical dimension metrology, Gaussian filters

Read Abstract +

It is important to remove image noise properly to measure critical dimension (CD) and roughness values from scanning electron microscope (SEM) images. In order to reduce image noise, the number of electron beam (EB) scans, or frame number, is increased. However, this excess EB irradiation damages the objects being measured and changes their size. In this paper, a new image analysis method is introduced to remove image noise without a typical noise filter. In this method, each image frame is used in a four dimensional array, and several artificial images are generated and edge coordinates are calculated. As a result of this new method, we can separate the line width roughness (LWR) components into process roughness and image noise, and analyze images with lower number of frames with minimal EB damage.

The impact of image noise on the accuracy of CD extraction is explained in the section on analysis of variance (ANOVA). The variation is separated as wafer to wafer (WTW), field to field (FTF), die to die (DTD), pattern to pattern (PTP), line width roughness (LWR), and stochastic pattern noise (SPN; which is random variation per a pattern) at this ANOVA. Roughness component from image noise is included in SPN. It is possible to remove the image noise component from SPN by applying this new image analysis method, and it is also possible to discuss the SPN from shot noise of exposure tool or variation of resist material component. ANOVA can put an end to discussion of measurement length of line pattern to know the state of low frequency roughness. LWR component of long wavelength is distributed to PTP and SPN when short patterns are measured. It is important to remove image nose properly and to compare the statistical analysis processed SPN value.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years