Java Based Quantitative Imaging Tool: MetroScope for semiconductor data analysis

1. A Digital Image Processor for
Complex Shape Metrology
Qi-De Qian
IC Scope Research, 159 Gilbert Ave.
Santa Clara, CA 95051
qqian@icscope.com

2. Introduction
Recent advances in digital image processing and computer graphics are applied
to solve the complex shape metrology problem in IC and mask manufacturing.
A quantitative image analyzer, MetroScope™ have been developed to meet the
complex shape metrology needs arising from the semiconductor industry.
MetroScope™ consists of an image based metrology engine, a digital photo
album organization interface, and a web based image sharing framework. The
capability for MetroScope™ to extract feature shape, measure arbitrary area
and line edge roughness are demonstrated. This system extends the metrology
tool set by providing complex feature shape analysis capabilities. In mask
manufacturing, MetroScope™ can provide valuable new capabilities for tasks
such as: OPC feature characterization, defect metrology, and mask processing
capability evaluation.

3. Digital Photo Album for Data Images

4. MetroScope™ GUI Components
digiAlbum image processor pixel trace analyzer

5. Intrusion/Protrusion Defects
Scale bar
• With the digital album in
display, a raw image is loaded
into the main image processor
by a click on the thumbnail.
• This image contains a defect
that causes narrowing on part of
the line.
• We want to measure the size of
this defect by
– the amount of line width
narrowing it causes, and
– the total area of the defect.
What is the size of this defect?
The main image processor

6. Defect Size Measurement
Pull down menu
• Using the image processing Function panel
functions, we can easily obtain
the single pixel outline of the
features.
• Image processing functions are
located on the pull down menu
and the image processor function
panel.
• Line width in pixels are
measured with a mouse, and the
measurement positions are
indicated on the image.
• The actual line width in microns
is obtained by scaling with the
pixel count of the scale bar. Smaller CD as due to defect
The main image processor

7. Defect Area Measurement
Message box that
• An alternative way of displays the results
characterizing a defect is to
calculate the defect area.
• For intrusion/protrusion
defects, the user needs to draw
an assist line to isolate the
defect.
• The user calculates the area by
clicking inside the area
surrounded by the outline of
the defect and the assist line.
• In this example, we have
reversed the color for easy
viewing and printing.
Defect area calculated in pixels

8. Defect Area Measurement
Noise reduction Area = 1.27 um^2
160 160
140
Pixel Intensity
140
Pixel Intensity
120 120
100 100
80 80
60 60
0 50 100 150 200
0 50 100 150 200
Pixel Index Pixel Index

9. Corner Rounding Measurement
• Unlike the polygons on the IC Thumbnail of the Image after
layout database, the actual original image preprocessing
patterns on the chip have
rounded corners.
• Photomasks made with
scanning laser beam or low
energy e-beam technology all
have significant corner
rounding.
• The figure on the right shows
an SEM image being processed
by MetroScope™ for
subsequent corner rounding
measurements.
We want to measure the corner
rounding of this line end.

10. Measure Corner Pull Back
• One method to quantify corner Thumbnail of the Corner pull-back:
rounding is to measure the pull original image 39.6 (enlarged) pixels
back.
• To do that, we first draw two
assist lines that extend the two
sides of the corner.
• Pull back is measured from the
intersection of the two assist
lines to the tip of the corner.
• For perfectly circular corners,
the pull back is related to the
radius by
R=(Pull_Back)/(sqrt(2)-1) .
Corner pull-back:
60.8 (enlarged) pixels

11. Corner Rounding by Missing Area
Thumbnail of the Missing area: 2638
• We can also measure corner original image (enlarged) pixels
rounding in terms of missing
area.
• To do that, we simply
calculate the area between
the corner and the assist
lines.
• This method is often more
useful for mask pattern
fidelity analysis, since a
stepper responds to area
change when the area
concerned is small.
Missing area: 5350
(enlarged) pixels

12. Line Edge Roughness (LER)
• Edge roughness are a major
problem in the new 193nm or
157nm photoresist patterns.
• The SEM picture on the right
shows edge roughness in a
line/space pattern.
• MetroScope allows a user to
extract the line edge and
quantify its roughness as a
standard deviation.
Photoresist lines Spaces

13. LER Measurement
Std. Dev. :
1.21 pixels
(all edges)
Std. dev. 1.427 1.14 1.25 0.94 1.16
(pixels) 0.88 1.47 1.17 1.186 1.32

14. Summary
• MetroScope™ offers a highly flexible solution to
complex mask pattern metrology.
• In mask manufacturing, MetroScope™ it ideal for
tasks such as OPC characterization, defect
metrology, and process capability evaluation.
• We demonstrate the capability of MetroScope™ in
– Defect area and dimension measurement
– Corner rounding and pull back measurement
– Line edge roughness measurement