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Pattern matching for automated E-beam testing
MicroelectronicEngineering24 (1994) 271-278 Elsevier
Pattern Matching
for Automated
271
E-Beam Testing
K. Okubo, H. Teguri, and A. Ito Fujitsu Laboratories Ltd. 10-l Morinosato-Wakamiya, Atsugi 243-01, Japan
Pattern matching between the LSI mask layout database and SEM image is essential for automated e-beam testing. Techniques for calibrating wiring width, compensating for layer misalignment, and generating template images taking into account theeffect of passivation films have been developed. We combined these techniques with projection edge extraction correlation (PEC) and had registered wiring probed automatically. Positioning time, which includes stage movement, SEM image acquisition, and pattern matching, was less than 20 s. Positioning accuracy (30) was 0.19 I.trn for metal and 0.55 pm for passivated wiring of an IC with a 2-pm minimum wiring width.
1. Introduction The measurement accuracy of an e-betm tester is mainly affected by the local field effect ’ and amplitude reduction in insulating film . To reduce these effects, which become severe in submicron wiring, the e-beam probe must be placed at the center of the wiring with a positioning error less than 10% of the wiring width. The positioning time must be shorter than or equal to the voltage waveform acquisition time (30 to 60 s). This requires fast pattern matching that handles the effects of wiring width error, mask misalignment, and changes in passivation film contrast.
2. Projection
Edge Extraction
Correlation
We used an e-beam tester, controlled by a SUN workstation (Fig. 1) , to crosscorrelate the SEM image and mask layout. In conventional pattern matching, the mask layout is scaled to match the SEM image, then the two are crosscorrelated. After the magnification is calibrated, some wiring width differences still remain, however, and this may result in positioning errors (Fig. 2). Due to this wiring width differences, left and right (upper and lower) edges of the SEM image and mask layout do not match at the same time. Mask misalignment also causes errors. Projection edge extraction correlation was developed for edge-based pattern matching to solve these problems3. PEC matches X and Y independently, significantly reducing positioning time without sacrificing accuracy as long as the initial error is sufficiently smaller than the average wiring length. In edge operations and fast pattern matching, PEC uses right, left, and neutral correlation 0167-9317/94/$07.000 1994 - Elsevier Science B.V. All rights reserved.
matrices specified by magnification change m and image shift s. Edges in the mask layout are specif%d by the start and end points and the layer and directional attributes. Edges are divided into three classes corresponding to the three matrices. The edge matrices are a crosscorrelation between the right (left) edges in the SEM image and right (left) edges of wiring in the mask layout. The neutral edge handles missing and degenerated edges of passivated ICs (Fig. 3). Threshold levels thl and th2 (thlXh2) generate the neutral edge matrix. A pair of right and left edges closer than thl and apart from th2 are replaced by a neutral edge at the center. Edges closer than th2 are removed. Thresholds are adjusted manually with the initial value of thl as the thickness of the passivation film and that of th2 as th1/2. The right and left edges, which form neutral edges, are removed when generating the right and left edge matrices. Wiring width variations and mask misalignment are compensated for combining edge operations (Fig. 4): a) b) c) d)
3.
Compensating for mask misalignment by introducing layer-to-layer shift Shifting the image by inphase shifting of all edges Changing the magnification by scaling the mask layout Changing the wiring widths by antiphase shifting of left and righ edges
Positioning The positioning
Sequence sequence
is divided
into three setup stages and one positioning
stage (Fig.
5). Using 256k-byte frame memory (512x512 pixels) for SEM image acquisition, we found that the optimum field size for ICs with 2-pm minimum wiring widths was 120 pm. A larger field size is preferable to gather targets for matching, but the pixel size must not exceed about 10% of the minimum wiring width. For NxN pixels, the default field size for a (pm) width wiring is (N/lO)a (pm).
K. Okubo et al. / Pattern matching for automated e-beam testing
(a) SEM image
(b) Mask layout
Figure 3 Degenerated and missing edges in passivated IC: (a) SEM image of passivated IC. (b) Mask layout corresponding to the SEM image. Edge degeneration (vertical edges) and missing edges (horizontal edges) muat be considered in pattern matching as the passivation film becomes thicker.
(a) Mask layout (without operation)
(c) Magnification
change
(b) Image shift
(d) Wiring width change
Figure 4 Edge operations: (a) Original mask layout. (b) Image shift. All edges are shifted equally. (c) Magnification change by scaling. (d) Wiring width change. Antiphase shift to right and left edges is introduced. Wirings is expanded or reduced relative to its center.
273
274
K. Okuho
et al. I Pattern
matching
Image rotation (axis inclination) must be smaller than l/5 12 radians (0.11 degrees) to ensure single-pixel positioning accuracy. X and Y inclinations are compensated for independently by using a rotation circuit. The Yaxis inclination angle is estimated by the power of the high-frequency component of the projection with angle $ (Fig. 6). Magnification and wiring width errors, mask misalignment, edge degeneration, and missing edges are compensated for using a graphic user interface (GUI) (Fig. 7). PEC is used to roughly calibrate magnification and wiring widths. The result is verified by overlaying the SEM image and edges on the mask layout. Crosscorrelation contributions from wiring in different layers are plotted against the image shift to confirm the result of mask misalignment compensation. After the setup sequence, the acquisition sequence starts and voltage waveforms are acquired automatically for predetermined probe points. In the acquisition sequence, PEC is used to finely adjust the magnification, wiring width, and image shift.
512_ t -_r1 @
,for automated
e-6aam
tcstini:
Starl
I
4
)
Setup field size $ Calibrate
image rotation 4
Cancel differences between SIN imayc and mask layout: Magnification Wiring width Mask misatignmcnt Contrast of passivateti wiring, e.g., edge degerreration and missing + Repeat positioning and waveform acquisrtion sequence for prcdctermined probe poinrs 4 End
275
K. Okubo et al. i Pattern matching for automated e-becm testing
,
Ail3 ,
A: Upper layer Lower layer
Image shift (pm)
(a) SEM image with mask layout overlay
(b) Crosscorrelation
of upper and lower layer
Figure 7 GUIs for setup: (a) Pattern matching results are confirmed by overlaying the SEM image with edges on the mask layout. (b) Crosscorrelation contributions from polygons in different layers used to calibrate mask misalignment and wiring width. The mask misalignment is determined from the peak positions of upper and lower layers. When a wirmg width is incorrect, a peak splits into two fine peaks, broadening the peak.
4. Matrix Operations Edge operations are done with matrices (Fig. 4). Crosscorrelation between the SEM image and mask layout for magnification change m and image shift s are calculated from the three matrices defined for each layer. The left correlation matrix for i-th layer Cl(i,s,m) is obtained by correlating left edges of polygons in the mask layout of the i-th layer with edges extracted from the SEM image. Right correlation matrix Cr(i,s,m) and neutral correlation matrix for degenerated edges Cn(i,s,m) arc defined similarly. By introducing wiring width change w, the contribution to the crosscorrelation from the i-th layer is expressed as the sum of these matrices (Fig. 8): Cs(i,s,m,w) = Cr(i,s+w/2,m)
+ Cl(i,s-w/2,m) + Cn(i,s,m)
Scanning w in a certain range obtains the maximum Cs, Cm: is obtained. Cm(i,s,m) = Cs(i,s,m,wopt(i,s,m)) where wopt(i,s,m) is a wiring width change that maximizes Cs for a given s and m. Last, Cm are summed for all layers: Ctot(s,m) = Xm(i,s+G(i),m) i where 6(i) is mask misalignment, which is set during setup. By maximizing Ctot, image shift s and magnification change m are obtained.
Left matrix: Cl(s,m)
Right matrix: Cr(s,m)
Neutral matrix: Cn(s,m)
Cl(s-wr
4 m
5
2 Cm(&)
-2.5
1
r--10.0 -5.0 0.0
= Cl(s-k/2,mj+‘Cr(s+w/2,mj+Cn(s,m)
5.0
10.0
Image shift (pm) (b) Crosscorrelation
Ctot
5. Fast Matrix
= Cr(s,m)
+ e(p(m)+s)
Using this algorithm, operation (Fig. 9).
matrix elements
can be updated
with a simple,
fast, read-add-store
K. Okubo Ed al. I Pattern matching for automated e-beam testing
Mask layout
SEM image
area
Projection
Matrix row data for magnification change m *
4
Cr(s,m) = Cr(s,m) + e(p(m)+s)
-ds
0
S
ds
Image shift (pixels) Figure 9 Data flow of matrix generation: A cell in the grid corresponds to matrix element CT. Projection area is defined by the edge position and magnitude of errors. Pixels in the area are projected onto the X axis and converted to edge data e(x). Matrix Cr is generated from the edge data by read-add-store operation. An edge in the mask layout mapped onto the left half of the SEM image+ draws a right-side-up contour in the matrix.
277
278 6.
K. Okubo et al. I Pattern matching ,for outornated c-ham
testing
Discussion Processing
time T (s) was measured
by a SPARCstation2:
T = 0.03 N E/F + 0.5 where N is the number of edges in the mask layout, E the shift error, and F the field size, and the minimum wiring width is 2 pm. Magnification error is 5% and the maximum wiring width variation is 1.0 pm. For a typical situation, where N is 200, E is 2 pm, and F is 120 pm, the processing time was 0.6 s. The total positioning time, including stage movement, SEM image acquisition, and image processing, was less than 30 s, which is shorter than the voltage waveform acquisition time. Positioning accuracy (30) was 0.19 pm for metal wiring and 0.55 ym for passivated wiring. However, PEC may not provide proper positioning for a strongly periodic pattern with a stage error larger than half a period. To probe very fine wirings stage error must be reduced and pattern matching improved.
7.
Conclusion
We developed PEC for aligning mask layouts with SEM images. We used correlation ma trices that handles wiring variations and degenerated edges of passivated wirings. Using three matrices, PEC handles wiring variation, mask misalignment, edge degeneration, and missing edges within a reasonable processing time.
&References 1 H. P. Feuerbaum, SEM/l, pp 285-296 (1979). 2 K. Okubo, Extended Abstract, 171st meeting, ECS (1987). 3 T. Anbe, Proceedings, ME ‘92 (1992).
Pattern Matching
for Automated
271
E-Beam Testing
K. Okubo, H. Teguri, and A. Ito Fujitsu Laboratories Ltd. 10-l Morinosato-Wakamiya, Atsugi 243-01, Japan
Pattern matching between the LSI mask layout database and SEM image is essential for automated e-beam testing. Techniques for calibrating wiring width, compensating for layer misalignment, and generating template images taking into account theeffect of passivation films have been developed. We combined these techniques with projection edge extraction correlation (PEC) and had registered wiring probed automatically. Positioning time, which includes stage movement, SEM image acquisition, and pattern matching, was less than 20 s. Positioning accuracy (30) was 0.19 I.trn for metal and 0.55 pm for passivated wiring of an IC with a 2-pm minimum wiring width.
1. Introduction The measurement accuracy of an e-betm tester is mainly affected by the local field effect ’ and amplitude reduction in insulating film . To reduce these effects, which become severe in submicron wiring, the e-beam probe must be placed at the center of the wiring with a positioning error less than 10% of the wiring width. The positioning time must be shorter than or equal to the voltage waveform acquisition time (30 to 60 s). This requires fast pattern matching that handles the effects of wiring width error, mask misalignment, and changes in passivation film contrast.
2. Projection
Edge Extraction
Correlation
We used an e-beam tester, controlled by a SUN workstation (Fig. 1) , to crosscorrelate the SEM image and mask layout. In conventional pattern matching, the mask layout is scaled to match the SEM image, then the two are crosscorrelated. After the magnification is calibrated, some wiring width differences still remain, however, and this may result in positioning errors (Fig. 2). Due to this wiring width differences, left and right (upper and lower) edges of the SEM image and mask layout do not match at the same time. Mask misalignment also causes errors. Projection edge extraction correlation was developed for edge-based pattern matching to solve these problems3. PEC matches X and Y independently, significantly reducing positioning time without sacrificing accuracy as long as the initial error is sufficiently smaller than the average wiring length. In edge operations and fast pattern matching, PEC uses right, left, and neutral correlation 0167-9317/94/$07.000 1994 - Elsevier Science B.V. All rights reserved.
matrices specified by magnification change m and image shift s. Edges in the mask layout are specif%d by the start and end points and the layer and directional attributes. Edges are divided into three classes corresponding to the three matrices. The edge matrices are a crosscorrelation between the right (left) edges in the SEM image and right (left) edges of wiring in the mask layout. The neutral edge handles missing and degenerated edges of passivated ICs (Fig. 3). Threshold levels thl and th2 (thlXh2) generate the neutral edge matrix. A pair of right and left edges closer than thl and apart from th2 are replaced by a neutral edge at the center. Edges closer than th2 are removed. Thresholds are adjusted manually with the initial value of thl as the thickness of the passivation film and that of th2 as th1/2. The right and left edges, which form neutral edges, are removed when generating the right and left edge matrices. Wiring width variations and mask misalignment are compensated for combining edge operations (Fig. 4): a) b) c) d)
3.
Compensating for mask misalignment by introducing layer-to-layer shift Shifting the image by inphase shifting of all edges Changing the magnification by scaling the mask layout Changing the wiring widths by antiphase shifting of left and righ edges
Positioning The positioning
Sequence sequence
is divided
into three setup stages and one positioning
stage (Fig.
5). Using 256k-byte frame memory (512x512 pixels) for SEM image acquisition, we found that the optimum field size for ICs with 2-pm minimum wiring widths was 120 pm. A larger field size is preferable to gather targets for matching, but the pixel size must not exceed about 10% of the minimum wiring width. For NxN pixels, the default field size for a (pm) width wiring is (N/lO)a (pm).
K. Okubo et al. / Pattern matching for automated e-beam testing
(a) SEM image
(b) Mask layout
Figure 3 Degenerated and missing edges in passivated IC: (a) SEM image of passivated IC. (b) Mask layout corresponding to the SEM image. Edge degeneration (vertical edges) and missing edges (horizontal edges) muat be considered in pattern matching as the passivation film becomes thicker.
(a) Mask layout (without operation)
(c) Magnification
change
(b) Image shift
(d) Wiring width change
Figure 4 Edge operations: (a) Original mask layout. (b) Image shift. All edges are shifted equally. (c) Magnification change by scaling. (d) Wiring width change. Antiphase shift to right and left edges is introduced. Wirings is expanded or reduced relative to its center.
273
274
K. Okuho
et al. I Pattern
matching
Image rotation (axis inclination) must be smaller than l/5 12 radians (0.11 degrees) to ensure single-pixel positioning accuracy. X and Y inclinations are compensated for independently by using a rotation circuit. The Yaxis inclination angle is estimated by the power of the high-frequency component of the projection with angle $ (Fig. 6). Magnification and wiring width errors, mask misalignment, edge degeneration, and missing edges are compensated for using a graphic user interface (GUI) (Fig. 7). PEC is used to roughly calibrate magnification and wiring widths. The result is verified by overlaying the SEM image and edges on the mask layout. Crosscorrelation contributions from wiring in different layers are plotted against the image shift to confirm the result of mask misalignment compensation. After the setup sequence, the acquisition sequence starts and voltage waveforms are acquired automatically for predetermined probe points. In the acquisition sequence, PEC is used to finely adjust the magnification, wiring width, and image shift.
512_ t -_r1 @
,for automated
e-6aam
tcstini:
Starl
I
4
)
Setup field size $ Calibrate
image rotation 4
Cancel differences between SIN imayc and mask layout: Magnification Wiring width Mask misatignmcnt Contrast of passivateti wiring, e.g., edge degerreration and missing + Repeat positioning and waveform acquisrtion sequence for prcdctermined probe poinrs 4 End
275
K. Okubo et al. i Pattern matching for automated e-becm testing
,
Ail3 ,
A: Upper layer Lower layer
Image shift (pm)
(a) SEM image with mask layout overlay
(b) Crosscorrelation
of upper and lower layer
Figure 7 GUIs for setup: (a) Pattern matching results are confirmed by overlaying the SEM image with edges on the mask layout. (b) Crosscorrelation contributions from polygons in different layers used to calibrate mask misalignment and wiring width. The mask misalignment is determined from the peak positions of upper and lower layers. When a wirmg width is incorrect, a peak splits into two fine peaks, broadening the peak.
4. Matrix Operations Edge operations are done with matrices (Fig. 4). Crosscorrelation between the SEM image and mask layout for magnification change m and image shift s are calculated from the three matrices defined for each layer. The left correlation matrix for i-th layer Cl(i,s,m) is obtained by correlating left edges of polygons in the mask layout of the i-th layer with edges extracted from the SEM image. Right correlation matrix Cr(i,s,m) and neutral correlation matrix for degenerated edges Cn(i,s,m) arc defined similarly. By introducing wiring width change w, the contribution to the crosscorrelation from the i-th layer is expressed as the sum of these matrices (Fig. 8): Cs(i,s,m,w) = Cr(i,s+w/2,m)
+ Cl(i,s-w/2,m) + Cn(i,s,m)
Scanning w in a certain range obtains the maximum Cs, Cm: is obtained. Cm(i,s,m) = Cs(i,s,m,wopt(i,s,m)) where wopt(i,s,m) is a wiring width change that maximizes Cs for a given s and m. Last, Cm are summed for all layers: Ctot(s,m) = Xm(i,s+G(i),m) i where 6(i) is mask misalignment, which is set during setup. By maximizing Ctot, image shift s and magnification change m are obtained.
Left matrix: Cl(s,m)
Right matrix: Cr(s,m)
Neutral matrix: Cn(s,m)
Cl(s-wr
4 m
5
2 Cm(&)
-2.5
1
r--10.0 -5.0 0.0
= Cl(s-k/2,mj+‘Cr(s+w/2,mj+Cn(s,m)
5.0
10.0
Image shift (pm) (b) Crosscorrelation
Ctot
5. Fast Matrix
= Cr(s,m)
+ e(p(m)+s)
Using this algorithm, operation (Fig. 9).
matrix elements
can be updated
with a simple,
fast, read-add-store
K. Okubo Ed al. I Pattern matching for automated e-beam testing
Mask layout
SEM image
area
Projection
Matrix row data for magnification change m *
4
Cr(s,m) = Cr(s,m) + e(p(m)+s)
-ds
0
S
ds
Image shift (pixels) Figure 9 Data flow of matrix generation: A cell in the grid corresponds to matrix element CT. Projection area is defined by the edge position and magnitude of errors. Pixels in the area are projected onto the X axis and converted to edge data e(x). Matrix Cr is generated from the edge data by read-add-store operation. An edge in the mask layout mapped onto the left half of the SEM image+ draws a right-side-up contour in the matrix.
277
278 6.
K. Okubo et al. I Pattern matching ,for outornated c-ham
testing
Discussion Processing
time T (s) was measured
by a SPARCstation2:
T = 0.03 N E/F + 0.5 where N is the number of edges in the mask layout, E the shift error, and F the field size, and the minimum wiring width is 2 pm. Magnification error is 5% and the maximum wiring width variation is 1.0 pm. For a typical situation, where N is 200, E is 2 pm, and F is 120 pm, the processing time was 0.6 s. The total positioning time, including stage movement, SEM image acquisition, and image processing, was less than 30 s, which is shorter than the voltage waveform acquisition time. Positioning accuracy (30) was 0.19 pm for metal wiring and 0.55 ym for passivated wiring. However, PEC may not provide proper positioning for a strongly periodic pattern with a stage error larger than half a period. To probe very fine wirings stage error must be reduced and pattern matching improved.
7.
Conclusion
We developed PEC for aligning mask layouts with SEM images. We used correlation ma trices that handles wiring variations and degenerated edges of passivated wirings. Using three matrices, PEC handles wiring variation, mask misalignment, edge degeneration, and missing edges within a reasonable processing time.
&References 1 H. P. Feuerbaum, SEM/l, pp 285-296 (1979). 2 K. Okubo, Extended Abstract, 171st meeting, ECS (1987). 3 T. Anbe, Proceedings, ME ‘92 (1992).