CN106528899A - Graph selection method used for light source-mask optimization - Google Patents
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Abstract
The invention provides a graph selection method used for light source-mask optimization. The graph selection method comprises the steps of calculating power spectrum density of each feature graph in a plurality of feature graphs; calculating a difference degree between any two feature graphs in the feature graphs based on the calculated power spectrum density of each feature graph; and selecting the feature graphs with the difference degree greater than or equal to a predetermined threshold in the feature graphs as test graphs used for the light source-mask optimization. According to the graph selection method used for the light source-mask optimization, provided by the invention, the test graphs used for the light source-mask optimization can be efficiently and quickly selected, and any key graph is not omitted, so that efficient and high-accuracy light source-mask optimization is realized.
Description
Technical field
The present invention relates to technical field of semiconductors, is used for light source-mask in particular to a kind of
The figure selecting method of optimization (source-mask optimization, SMO).
Background technology
With the complexity more and more higher of integrated circuit, characteristic size also becomes less and less.When
The characteristic size of integrated circuit be close to the system limits of photo-etching machine exposal, i.e. characteristic size be close to or
During less than photolithography light source, the domain produced on silicon chip occurs significantly distortion.For this photoetching
System must strengthen (RET) technology using resolution, to improve image quality.
As technology develops toward the less direction of critical size, only implement the routine of optimization to mask
Optical proximity correction (Optical Proximity Correction, OPC) possibly cannot meet day
The specification requirement of the strict critical size of benefit.In such a case, it is possible to irradiation source/light source
Optimization is also carried out, to improve photoetching fidelity, that is, enters line light source-mask optimization (SMO).
Light source-mask optimization is a kind of important RET, and the technology was to optimizing
Resolution chart used in journey has more serious dependency.Therefore, the selection of resolution chart
It is extremely important.However, generally relying on SMO user to the selection of resolution chart in prior art
Skill and experience, such system of selection inefficiency, and result is unreliable.
The content of the invention
For the deficiencies in the prior art, the present invention provides a kind of figure for light source-mask optimization
Shape system of selection, the figure selecting method include：Calculate each feature in multiple feature patterns
The power spectral density of figure；Power spectral density based on each feature pattern for being calculated calculates institute
State the diversity factor between any two feature pattern in multiple feature patterns；And the plurality of
Characteristic pattern of the diversity factor more than or equal to predetermined threshold between selecting in feature pattern
Shape optimizes for light source-mask as resolution chart.
In one embodiment of the invention, it is described to calculate any two in the plurality of feature pattern
Diversity factor between individual feature pattern is further included：Calculate in the plurality of feature pattern arbitrarily
Between two feature patterns vector cosine angle distance (Vector Cosine Angle Distance,
VCAD)。
In one embodiment of the invention, it is described to calculate each characteristic pattern in multiple feature patterns
The power spectral density of shape is further included：Discrete fourier change is carried out to described each feature pattern
Change (Discrete Fourier Transform, DFT)；And become based on the discrete fourier
Change the power spectral density that result calculates each feature pattern.
In one embodiment of the invention, the power spectral density of each feature pattern passes through
Formula fuv=| DFT (I)uv|2Calculated,Wherein DFT (I)uvIt is characterized the direct computation of DFT of figure
Leaf transformation, wherein u and v are frequency variable.
In one embodiment of the invention, the discrete Fourier transform of each feature pattern
It is formulated as：
Wherein, M and N are the order of diffraction (diffraction order) of each feature pattern.
In one embodiment of the invention, any two characteristic pattern in the plurality of feature pattern
The calculating of the vector cosine angle distance between shape is formulated as：
Wherein, f represents in the plurality of feature pattern, and g represents the plurality of feature
Another in figure.
In one embodiment of the invention, the predetermined threshold is defined by user.
In one embodiment of the invention, the vector cosine angle distance between two feature patterns
Size it is sensitive to the pitch (pitch) of described two feature patterns.
In one embodiment of the invention, the plurality of feature pattern is included for determining exposure
The figure (anchor pattern) of energy, the One Dimension Periodic resolution chart with different pitches,
Line end resolution chart and/or random logic figure.
In one embodiment of the invention, the figure selecting method can be applied to light source-
Mask-polarization optimization (source-mask-polarization optimization).
Figure selecting method for light source-mask optimization provided by the present invention can be efficiently fast
The resolution chart for light source-mask optimization is selected fastly, while any crucial figure will not be omitted
Shape, so that realize light source-mask optimization of efficient, pinpoint accuracy.
Description of the drawings
The drawings below of the present invention is used for understanding the present invention in this as the part of the present invention.It is attached
Embodiments of the invention and its description is shown in figure, for explaining the principle of the present invention.
In accompanying drawing：
Fig. 1 shows the figure selecting for light source-mask optimization according to embodiments of the present invention
The flow chart of method；
Fig. 2 shows the example of multiple feature patterns according to embodiments of the present invention；
Fig. 3 shows the vector in multiple feature patterns of Fig. 2 between any two feature pattern
The number list of cosine angle distance；
Fig. 4 shows existing figure selecting method and figure choosing according to embodiments of the present invention
Selection number list of the selection method to various features figure；
Fig. 5 A- Fig. 5 D show using Fig. 4 in the selected figure of each figure selecting method
Enter the simulation result of line light source optimization；And
Fig. 6 shows the run time of each figure selecting method in Fig. 4.
Specific embodiment
In the following description, a large amount of concrete details are given to provide to the present invention more
Thoroughly understand.It is, however, obvious to a person skilled in the art that of the invention
Can be carried out without the need for one or more of these details.In other examples, in order to keep away
Exempt to obscure with the present invention, for some technical characteristics well known in the art are not described.
It should be appreciated that the present invention can be implemented in different forms, and it is not construed as office
It is limited to embodiments presented herein.Disclosure will be made thoroughly and complete on the contrary, providing these embodiments
Entirely, and those skilled in the art be will fully convey the scope of the invention to.
The purpose of term as used herein is only that description specific embodiment and not as this
Bright restriction.When here is used, " one " of singulative, " one " and " described/should "
It is also intended to include plural form, unless context is expressly noted that other mode.It is also to be understood that art
Language " composition " and/or " including ", when using in this specification, determine the feature,
The presence of integer, step, operation, element and/or part, but be not excluded for it is one or more its
The presence or addition of its feature, integer, step, operation, element, part and/or group.
When here is used, term "and/or" includes any and all combination of related Listed Items.
In order to thoroughly understand the present invention, detailed step and in detail will be proposed in following description
Thin structure, to explain technical scheme proposed by the present invention.Presently preferred embodiments of the present invention is detailed
Carefully it is described as follows, but in addition to these detailed descriptions, the present invention can also be with other enforcement
Mode.
SMO is a kind of important RET, and the technology is to used in optimization process
Resolution chart have more serious dependency.Accordingly, it would be desirable to resolution chart is carefully selected,
To carry out equilibrium between cycle for adjusting in light source and precision.In existing method, usually rely on
The skill and experience of SMO user is selecting figure.For example, it is generally directed to target process selection
Key graphic, used as by the input of optimised little feature pattern (clip).On the one hand, select
The figure selected is more, and the calculating time of cost is longer.On the other hand, if the figure amount for selecting
It is not enough, it will to affect the precision of later stage optimization.
In order to select representative key graphic from multiple feature patterns, need to these
Feature pattern makes a distinction.The present invention provides a kind of figure selecting for light source-mask optimization
Method.Figure selecting method according to embodiments of the present invention can analyze multiple feature patterns, tool
Multiple feature patterns can be transformed into domain space by Fourier transformation, by its frequency body
The diffraction pattern of domain space relatively distinguishing these feature patterns.Then therefrom select typical
Figure simultaneously filters unwanted figure, and for light source-mask optimization, pass is not being omitted in realization
Time cost is greatly reduced in the case of key figure.
Fig. 1 shows the figure selecting for light source-mask optimization according to embodiments of the present invention
The flow chart of method 100.As shown in figure 1, figure selecting method 100 is comprised the following steps：
Step 101：Calculate the power spectral density of each feature pattern in multiple feature patterns.
Wherein, multiple feature patterns can be the multiple figures for representing whole chip, and which can wrap
Include the representative figure for carrying out considering required for SMO.For example, multiple feature patterns
Can include for determine exposure energy anchor figures, (for example save with different pitches
Away from from small to large) One Dimension Periodic resolution chart, line end resolution chart, SRAM and/or
Random logic figure.Fig. 2 shows showing for multiple feature patterns according to embodiments of the present invention
Example, will be described after a while.
According to one embodiment of present invention, in a step 101, calculate in multiple feature patterns
The power spectral density of each feature pattern may further include：Each feature pattern is carried out from
Scattered Fourier transformation, and the power of each feature pattern is calculated based on discrete Fourier transform result
Spectrum density.For example, the power spectral density of each feature pattern can pass through formula
fuv=| DFT (I)uv|2Calculated,Wherein DFT (I)uvThe discrete fourier for being characterized figure becomes
Change, can be calculated by formula (1)：
Wherein, M and N are the order of diffraction of each feature pattern, and wherein u and v is frequency
Rate variable.
Step 102：Power spectral density based on each feature pattern for being calculated calculates multiple spies
Levy the diversity factor between any two feature pattern in figure.
The difference between any two feature pattern can be carried out quantitatively using diversity factor.Its
In, diversity factor for example can be represented apart from VCAD using vector cosine angle.VCAD can
To represent distance of two figures in domain space, its size can be represented between two figures
Diversity factor.
According to one embodiment of present invention, calculate any two characteristic pattern in multiple feature patterns
Diversity factor between shape is further included：Calculate any two feature pattern in multiple feature patterns
Between vector cosine angle distance.Wherein, in multiple feature patterns any two feature pattern it
Between vector cosine angle can be calculated by formula (2) apart from VCAD：
Wherein, f represents in multiple feature patterns, during g represents multiple feature patterns
Another.
Step 103：Between selecting in multiple feature patterns, diversity factor is more than or equal to pre-
The feature pattern of threshold value is determined as resolution chart, for light source-mask optimization.
According to one embodiment of present invention, predetermined threshold can be defined by user.User
Rule of thumb or can attempt selecting most suitable threshold value.Based on the calculating in step 102, when
When diversity factor (such as VCAD) between two feature patterns is less than predetermined threshold, can be by
Two feature patterns are considered as identical figure, take one of as representative.When two
When diversity factor (such as VCAD) between feature pattern is more than or equal to predetermined threshold, then will
Two feature patterns are considered as different graphic.Finally, it is selected in multiple feature patterns of candidate
Different graphic is between the figure for eventually serving as resolution chart selected.As such, it is possible to
Ensure not leak the crucial figure of choosing in the case of reducing selected figure sum as far as possible, so as to
Both calculating time cost had been saved, the precision of light source-mask optimization processing had been in turn ensured that.
Describe according to embodiments of the present invention for light source-mask optimization method below by example
Figure selecting method.As described above, Fig. 2 shows multiple spies according to embodiments of the present invention
Levy the example of figure.Specifically, 10 one-dimensional spies of the numbering from #0 to #9 are shown in Fig. 2
Levy figure.These feature patterns have identical or different critical size (CD) and pitch.
For example, represent that its CD is 60 for figure #0,60/120, pitch is 120.Wherein, it is right
In figure #0 and figure #1, its CD and pitch all same, figure #0 skews are differed only in
20 nanometers.Figure #0 is identical with the pitch of figure #2, and CD sizes are close.Figure #0 and
The CD of figure #3 is identical, and pitch size is close.Figure #7, figure #8 and figure #9 have
Identical pitch, but CD sizes are different.
To the diversity factor between figure #0 to the #9 calculating any two figures in Fig. 2 for example
VCAD, as a result as shown in the list in Fig. 3.Assume that predetermined threshold is 0.05, then Fig. 3
In list, overstriking font is VCAD numerical value of the VCAD less than threshold value.From the list of Fig. 3
As can be seen that section of the size of the VCAD between two feature patterns to two feature patterns
It is sensitive away from (pitch).Based on above-mentioned calculating, figure can be selected in this 10 figures
#0, #4, #6, #7, #8 and #9 are used as final resolution chart.
As described above, figure selecting method according to embodiments of the present invention can ensure precision
In the case of greatly reduce time cost.The figure selecting that below existing method is provided with the present invention
Method is compared to illustrate the advantage of the present invention.Fig. 4 shows existing figure selecting method
The selection number of various features figure is arranged with figure selecting method according to embodiments of the present invention
Table.Fig. 5 A- Fig. 5 D show using Fig. 4 in the selected figure of each figure selecting method
Enter the simulation result of line light source optimization.Fig. 6 shows the fortune of each figure selecting method in Fig. 4
The row time.
As shown in figure 4, existing figure selecting method can include whole graphic-arts techniques, artificial figure
Shape system of selection A and artificial figure selecting method B.The selected figure of every kind of method is typically
Including anchor figures, SRAM, line end resolution chart and logic figure.Wherein, all scheme
Shape method selects to represent whole figures of whole chip, and such as sum is 143 figures.
The figure for being drawn in this way is used for the best performance of light source-mask optimization, as shown in Figure 5A
, but its run time is very long, as shown in Figure 6.Artificial figure selecting method A
Carry out empirically carrying out the biography of selection with skill for engineer with artificial figure selecting method B
System method.As shown in figure 4, manually the selected figure number of figure selecting method A is few,
Although run time is shorter, resulting simulation result (as shown in Figure 5 B) is poor；People
The selected figure number of work figure selecting method B is slightly more, and resulting simulation result is (such as
Shown in Fig. 5 C) preferably, but its run time is longer.By contrast, according to present invention enforcement
The equal more than two manual method of the selected figure number of figure selecting method of example, it is resulting
Simulation result (as shown in Figure 5 D) is good, and run time and artificial figure selecting method
B is compared with whole graphic-arts techniques and is greatly reduced.
Based on above description, according to an embodiment of the invention for light source-mask optimization
Figure selecting method can efficiently and rapidly select the resolution chart for light source-mask optimization,
Any key graphic will not be omitted simultaneously, so as to realize the light source-mask of efficient, pinpoint accuracy
Optimization.Additionally, the figure selecting method can also be applied to light source-mask-polarization optimization
(source-mask-polarization optimization)。
The present invention is illustrated by above-described embodiment, but it is to be understood that, it is above-mentioned
Embodiment is only intended to citing and descriptive purpose, and is not intended to limit the invention to described
Scope of embodiments in.In addition it will be appreciated by persons skilled in the art that the present invention not office
It is limited to above-described embodiment, teaching of the invention can also be made more kinds of modifications and repair
Change, within these variants and modifications all fall within scope of the present invention.The present invention's
Protection domain is defined by the appended claims and its equivalent scope.
Claims (10)
1. a kind of figure selecting method for the optimization of light source-mask, it is characterised in that described
Figure selecting method includes：
Calculate the power spectral density of each feature pattern in multiple feature patterns；
Power spectral density based on each feature pattern for being calculated calculates the plurality of characteristic pattern
Diversity factor in shape between any two feature pattern；And
Between selecting in the plurality of feature pattern, the diversity factor is more than or equal to pre-
The feature pattern of threshold value is determined as resolution chart, for light source-mask optimization.
2. figure selecting method as claimed in claim 1, it is characterised in that the calculating
Diversity factor in the plurality of feature pattern between any two feature pattern is further included：Meter
Calculate the vector cosine angle distance between any two feature pattern in the plurality of feature pattern.
3. figure selecting method as claimed in claim 2, it is characterised in that the calculating
In multiple feature patterns, the power spectral density of each feature pattern is further included：
Discrete Fourier transform is carried out to described each feature pattern；And
The power spectrum of each feature pattern is calculated based on the discrete Fourier transform result
Density.
4. figure selecting method as claimed in claim 3, it is characterised in that it is described each
The power spectral density of feature pattern passes through formula fuv=| DFT (I)uv|2Calculated, wherein
DFT(I)uvThe discrete Fourier transform of figure is characterized, wherein u and v is frequency variable.
5. figure selecting method as claimed in claim 4, it is characterised in that it is described each
The discrete Fourier transform of feature pattern is formulated as：
Wherein, M and N are the order of diffraction of each feature pattern.
6. figure selecting method as claimed in claim 5, it is characterised in that the plurality of
The calculating formula of the vector cosine angle distance in feature pattern between any two feature pattern
It is expressed as：
Wherein, f represents in the plurality of feature pattern, and g represents the plurality of feature
Another in figure.
7. the figure selecting method as described in any one of claim 1-6, its feature exist
In the predetermined threshold is defined by user.
8. the figure selecting method as described in any one of claim 1-6, its feature exist
In the size of the vector cosine angle distance between two feature patterns is to described two feature patterns
Pitch it is sensitive.
9. the figure selecting method as described in any one of claim 1-6, its feature exist
In, the plurality of feature pattern include for determine exposure energy figure, with different pitches
One Dimension Periodic resolution chart, line end resolution chart and/or random logic figure.
10. the figure selecting method as described in any one of claim 1-6, its feature exist
In the figure selecting method can be applied to light source-mask-polarization optimization.
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| CN111399336A (en) * | 2020-04-17 | 2020-07-10 | 中国科学院上海光学精密机械研究所 | Method for screening key graph for optimizing full-chip light source mask based on profile representation |
| CN111624850A (en) * | 2020-06-08 | 2020-09-04 | 中国科学院上海光学精密机械研究所 | Key graph screening method for full-chip light source mask optimization |
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