semi合集-English.pdf - 第5999页
SEMI P43-0304 © SEMI 2004 8 (clipped) feature area los s . Note that the value of the absolute ( clipped) f eature area deviation is always positive. Same mandatory in formation as in (clipped) feature area gain. NOTE 17…

SEMI P43-0304 © SEMI 2004 7
• additionally if clipped: region of interest, clipping
details.
8.2.2.2 (clipped) feature area gain — area in the actual
(clipped) feature contour outside of the nominal
(clipped) feature (see Figure 8). Additional mandatory
information:
• relative position of actual and nominal feature (see
Section 8.4).
8.2.2.2.1 Note that the value of the (clipped) feature
area gain is always positive.
Figure 8
Illustration of feature area (top: nominal feature,
center: actual feature) and bottom: feature area
gain (light gray), feature area loss (black) and
overlapping area (medium gray)
8.2.2.3 (clipped) feature area loss — (clipped) area
outside of the actual feature, still inside of the nominal
feature (see Figure 8).
8.2.2.3.1 Same mandatory information as in (clipped)
feature area gain.
8.2.2.3.2 Note that the value of the (clipped) feature
area loss is always positive.
(a)
(b)
Figure 9
Illustration that edge roughness can influence
feature area deviation, unlike feature area
difference.
(a) without edge roughness (or with severe
smoothing)
(b) with edge roughness: area gain and area loss are
larger than in case (a), but can compensate each-
other when using feature area difference
8.2.2.4 (clipped) feature area difference — (clipped)
feature area gain minus (clipped) feature area loss. This
is also equal to the (clipped) feature area of the actual
feature minus the (clipped) feature area of the nominal
feature. The value of the (clipped) feature area
difference may be positive or negative accordingly.
Same mandatory information as in (clipped) feature
area gain.
NOTE 16: This qualification parameter is recommended for
contacts or dots, because in these cases it is of relatively
minor importance where the gain and loss are situated.
8.2.2.5 absolute (clipped) feature area deviation — the
sum of the values of (clipped) feature area gain and

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(clipped) feature area loss. Note that the value of the
absolute (clipped) feature area deviation is always
positive. Same mandatory information as in (clipped)
feature area gain.
NOTE 17: This qualification parameter is recommended for
features for which it does matter where the gain and loss are
situated.
NOTE 18: This reasoning could be extended to Pattern area
gain /loss /difference /deviation if several features are present
in the region of interest.
NOTE 19: Edge roughness may influence feature area
deviation, unlike feature area difference, in which the effect
of edge roughness is filtered out by allowing the resulting area
gain and area loss to cancel out (see Figure 9).
NOTE 20: Normalized feature area, normalized feature area
gain, normalized feature area loss, normalized feature area
difference and normalized feature area deviation are defined
as the ratio between the actual value of the considered
parameter and the nominal feature area.
8.2.3 Specific Case of Corner Rounding (CR)
8.2.3.1 corner rounding — deviation of an actual
feature corner from the nominal one.
8.2.3.1.1 The definition above is qualitative, and can be
quantified in all practical cases by treating it as a
special case of feature area difference (see further in
Sections 8.2.3.2–7). Quantitative determination
requires as mandatory information:
• the designed angle (see Figure 10), DEFAULT
angle is 90 degrees.
• feature tone: dark vs. clear.
• corner type: outer vs. inner. Corner type is ambig-
uous without feature tone specified (see Figure 11).
• other features or feature corners within the
proximity range from the corner of interest,
DEFAULT is an isolated corner.
• orientation of the corner (determined by the 2
linear sections, e.g., 90^ 180, 160^ 210,…, (see
Figure 10). DEFAULT is all 4 orientations with
linear sections along X- and Y-axes (Figure 12) for
both dark and clear feature tone.
NOTE 21: The purpose of the default corners is to help the
user of this document to select representative features to
qualify, for example, the corner rounding fingerprint of a
mask making process.
Y
X
α
β
(α , β)
Figure 10
Nomenclature of Feature Corners by the Angles of
Their Linear Sections
(a)
(b)
Figure 11
Illustration of nomenclature used for feature
corners (elbow as example)
(a) dark feature; (b) clear feature;
bottom left in each sub-figure: inner corner;
top right in each sub-figure: outer corner.

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Figure 12
The 4 Default Orientations of a 90º Corner
8.2.3.2 corner area gain — special case of clipped
feature area gain, in which the region of interest
contains one corner of a feature.
8.2.3.3 corner area loss — special case of clipped
feature area loss, in which the region of interest
contains one corner of a feature.
NOTE 22: In non-corrected isolated cases normally there is
only a loss for outer corners and a gain for inner corners. In
other cases (i.e., corrected corners) there may be a loss and a
gain, which makes it necessary to also define the difference
and deviation, as done below.
8.2.3.4 corner area difference — corner area gain
minus corner area loss. As such it is a special case of
clipped feature area difference, in which the region of
interest contains one corner of a feature.
8.2.3.5 corner area deviation — the sum of corner
area gain and corner area loss. As such it is a special
case of clipped feature area deviation, in which the
region of interest contains one corner of a feature.
NOTE 23: As the corner shape is expected not to be decisive
for its printability (at least for an isolated corner), but rather
the balance between area gain and loss, it is recommended to
use area difference for corner qualification rather than area
deviation.
NOTE 24: Certain features with non-isolated corners, such as
line-ends and contacts, have specific definitions listed in
Sections 8.2.4 and beyond.
8.2.3.6 In present practice, corner rounding quantifica-
tion is done without comparison to the nominal corner.
However, this is only valid if the corner is isolated,
non-corrected, and its area gain is negligible. Typically
it is done based on the determination of a reference
corner which is obtained by the extrapolation of the
linear sections of the corner, if present (Figure 13).
Figure 13
Corner Rounding Determination by Extrapolation
of the Linear Sections of the Actual Feature Contour
8.2.3.7 equivalent corner rounding radius (ECRR) —
an equivalent, effective corner rounding radius
calculated from the area difference. It assumes that the
corner is a circular arc. The ECRR is calculated as
ECRR = sqrt( 4 * corner area difference / (π - 4) ), for a
90 degree corner.
8.2.3.7.1 The ECRR is defined only for negative corner
area differences, i.e., where the corner area loss is
larger than the corner area gain.
NOTE 25: This definition actually gives a 1D representation
for a 2D quality assessement, but it is found useful when
comparing mask quality to wafer printing results, which are
typically characterized by 1D measurements, such that a
dimensionless MEEF (mask error enhancement factor) can be
used. As with area based assessment, also this term
disregards the shape at the feature corner.
NOTE 26: Current methods to determine a corner rounding
radius based on fitting a circle to an actual corner have been
experimentally shown to deliver unreliable results and are
therefore strongly discouraged.
8.2.3.8 corner pull-back (CPB) — the distance
between the reference corner and the actual feature
contour
. This may be based on the minimum distance
(minimum CPB) or that determined along the bisectric
(bisectric CPB) (see Figure 14). The choice of CPB
technique is mandatory information.
NOTE 27: Edge roughness may have an important influence
on the corner pull-back, such that contour averaging may be
necessary to produce a meaningful result. The method of
contour averaging is mandatory information for corner pull-
back, if used.