CN101482697B - Method for reducing OPC model residual error - Google Patents
Method for reducing OPC model residual error Download PDFInfo
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- CN101482697B CN101482697B CN2008100323430A CN200810032343A CN101482697B CN 101482697 B CN101482697 B CN 101482697B CN 2008100323430 A CN2008100323430 A CN 2008100323430A CN 200810032343 A CN200810032343 A CN 200810032343A CN 101482697 B CN101482697 B CN 101482697B
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Abstract
The present invention provides a method for reducing OPC model residual error, the method comprises: multiplying the obtained OPC model residual error and the CD data of selected influencing factor value correction OPC model simulation pattern; then calculating the average value of the correction model residual error and calculating the average value of the OPC model residual error obtained under different influence factors by changing the influence factor values; integrative comparing the average values of the model residual errors calculated by different influence factors to determine the corresponding influence factor value when the model residual error average value is minimum; multiplying the influence factor and the residual error value of design pattern sampling point simulated by the OPC model to correct the CD data of design pattern sampling point simulated by the OPC model, thereby effectively reducing the OPC model residual error, improving the accuracy of the OPC model and improving the OPE correcting efficiency.
Description
Technical field
The present invention relates to optical proximity effect correction (OPC) field, relate in particular to the method that reduces of the OPC model residual error that is applied to OPC.
Background technology
Along with the integrated level of integrated circuit is high more, its manufacturing technology is constantly to the development of small-feature-size more.Yet lithographic process becomes limit ic is made main bottleneck from development to small-feature-size more.The main principle of lithographic process is to be projected on the wafer by the design layout of light source with integrated circuit on the light shield.Yet along with reducing of characteristic dimension, optic distortion that the image that throws on the wafer presents and abnormal shape make the characteristic dimension (Critical Dimension:CD) of the small-feature-size pattern that projection goes out be difficult to reach the expection requirement, thereby influence the yield rate of whole lithographic process.Optical proximity effect correction (Optical ProximityCorrection:OPC) is to be used to compensate these deformation, and the feasible image that is projected at last on the wafer obtains the control of preferable characteristic dimension.In general being used for lithographic process below 0.18 micron need be aided with OPC and just can obtain photoetching quality preferably.
In the OPC of reality process, model OPC is used morely.This OPC model is according to the optical system correlation parameter, and photoresistance parameter and other correlation parameters are simulated the pattern behind the graphic pattern projection that designs on the light shield on the wafer.Yet there is error in the pattern that test pattern exposes to the sun on wafer on pattern and the actual light shield after the projection that employing OPC pattern die is drawn up.This error is called model residual error (Model Residual Error:MRE).Normally obtain the model residual error of test pattern on the light shield by the following method, see also Fig. 1.Step S1: provide test pattern, and the test sampled point of test pattern and sampled point are projected in the CD data on the wafer with a series of sampled points.Step S2: adopt OPC model, the pattern after the CD data of test pattern up-sampling point are exposed as the CD digital simulation test pattern of the layout sampled point of OPC modeling based on certain projective parameter.Step S3: sampled point is projected on the exposing patterns of OPC modeling among CD data on the wafer and the step S2 difference corresponding to the CD data of the position of test pattern sampled point and just can obtains data at the model residual error of a series of sampled points on the test pattern among the comparison step S1.Wherein, projective parameter generally is the optical parametric that comprises the lithographic projection system, photoresistance parameter and etching parameter.
Because the existence of this error has also just limited the precision of OPC model.When model residual error is big, can cause this OPC model accuracy not high, influence the correction efficient of OPE (Optical Proximity Effect:OPE).
Summary of the invention
The object of the present invention is to provide a kind of method of the OPC of reducing model residual error, to solve the not high problem of OPC model accuracy that bigger model residual error causes.
For addressing the above problem, a kind of method that reduces the OPC model residual error of the present invention, wherein the OPC model can be used for the pattern behind the board design pattern exposure, this method may further comprise the steps: step 11: the model residual error value at a series of sampled points on the test pattern is provided, chooses the initial value of factor of influence; Step 12: will revise the CD data of test pattern up-sampling point after the model residual error of all sampled points on the test pattern upward factor of influence value on duty; Step 13: with the test pattern up-sampling point CD data revised in the step 12 as the sampled point CD data of the layout of OPC modeling after the model residual error of acquisition test pattern sampled point, and calculate the mean value of model residual error of the test pattern sampled point of described acquisition; Step 14: as factor of influence value in the step 12, return step 12 after the change factor of influence value, after several times change the value of factor of influence, execution in step 15; Step 15: the model residual error mean value size of the test pattern sampled point that calculates of Different Effects factor values relatively, the model residual error mean value of determining the test pattern sampled point is hour corresponding factor of influence value; Step 16: the CD data of revising the layout sampled point of OPC modeling after the model residual error value of the factor of influence of the model residual error mean value minimum that step 15 is the definite upward layout sampled point of OPC modeling on duty.
Wherein, the value of the factor of influence that the model residual error value of all sampled points is multiplied by respectively in the step 12 is all identical, and the value of described factor of influence greater than 0 less than 1.Changing the factor of influence value in step 14 is to increase progressively the factor of influence value, the initial value minimum of the factor of influence of choosing in the step 11; Changing the factor of influence value in step 14 is the factor of influence value of successively decreasing, the initial value maximum of the factor of influence of choosing in the step 11.The mean value that calculates the model residual error value of described sampled point in the step 13 is to ask root mean square formula to calculate by following:
M＝[(MRE
1)
2+(MRE
2)
2...+(MRE
i)
2+...(MREn)
2]
1/2
Wherein, M is the model residual error root-mean-square value of a series of sampled points, MRE
1Be the model residual error of sampled point 1, MRE
2Be the model residual error of sampled point 2, MRE
iBe the model residual error of sampled point i, MRE
nModel residual error for sampled point n.Revising the CD data of revising the layout sampled point of OPC modeling in the CD data of test pattern sampled point and the step 16 in the step 12 and being all is that model residual error that CD data with pattern up-sampling point add sampled point is multiplied by after the value of the definite factor of influence of step 15 the CD data as the layout sampled point of OPC modeling.
Compare with the using method of existing OPC model, the method that reduces the OPC model residual error of the present invention, be multiplied by certain factor of influence by the model residual error data that will draw and make the root-mean-square value minimum of model residual error, and feed back to the sampled data of test pattern OPC model, thereby can effectively reduce by the model residual error between OPC modeling and the actual wafer, improve the precision of OPC model, improve OPE and revise efficient.
Description of drawings
Be described in further detail below in conjunction with the method for the drawings and specific embodiments the OPC of reducing model residual error of the present invention.
Fig. 1 is the synoptic diagram that obtains OPC model residual error method.
Fig. 2 is the synoptic diagram that the present invention reduces OPC model residual error method.
Embodiment
The preparation method synoptic diagram of OPC model residual error sees also Fig. 1.Therefore no longer this has given unnecessary details in existing in front relevant detailed description.The method that reduces the OPC model residual error of the present invention sees also Fig. 2.It comprises six steps altogether.Step S11 provides the model residual error value at a series of sampled points on the test pattern, chooses the initial value of factor of influence.The model residual error value of a series of sampled points can obtain by method shown in Figure 1 on the test pattern.Step S12 is with the CD data of correction test pattern up-sampling point after the value of the model residual error of all sampled points on the test pattern upward factor of influence on duty.And the factor of influence value that the model residual error of all sampled points of test pattern is multiplied by is all identical, and the value of factor of influence greater than 0 less than 1.Step S13, the CD data of the test pattern up-sampling point revised among the step S12 are obtained the model residual error of test pattern sampled point after as the sampled point CD data of the layout of OPC modeling, and calculate the mean value of model residual error of the test pattern sampled point of described acquisition.The mean value that calculates the model residual error of sampled point in this step is to ask root mean square formula to calculate by following:
M＝[(MRE
1)
2+(MRE
2)
2...+(MRE
i)
2+...(MREn)
2]
1/2
Wherein M is the root-mean-square value of the correction model residual error value of this series of samples point, supposes to have n sampled point just to have n model residual error, MRE
1Be the model residual error of sampled point 1, MRE
2Be the model residual error of sampled point 2, MRE
iBe the model residual error of sampled point i, MRE
nModel residual error for sampled point n.
Step S14 as factor of influence value among the step S12, returns step S12 after the change factor of influence value, after several times change the value of factor of influence, and execution in step S15.For making things convenient for step S14 to change the factor of influence value, can choose factor of influence according to certain step-length, for example choose factor of influence 0.2,0.4,0.6,0.8 according to 0.2 step-length, can choose factor of influence with littler step-length for improving precision.If changing the factor of influence value among the step S14 is the value that increases progressively factor of influence, then the initial value minimum of the factor of influence of choosing among the step S11.If step S14 increases progressively the factor of influence value by 0.2 step-length, then the initial value of the factor of influence of choosing among the step S11 is 0.2, and to increase progressively gradually be 0.4,0.6,0.8 to the value of factor of influence then.If step S14 increases progressively the factor of influence value by 0.1 step-length, then the initial value of the factor of influence of choosing among the step S11 is 0.1, and to increase progressively gradually be 0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9 to the value of factor of influence then.Dwindle step-length and help step S15 and find optimized factor of influence, improve the OPC model accuracy, but also increased the data computing amount simultaneously.The step-length of in actual applications can OPC model accuracy as required selecting factor of influence.
Step S15, the model residual error mean value size of the test pattern sampled point that calculates of the Different Effects factor is relatively determined the factor of influence value of the model residual error mean value minimum of test pattern sampled point.The data of amassing the sampled point of revising OPC modeling layout that the model residual error of different factors of influence and test pattern up-sampling point multiplies each other, pattern after the test pattern that causes OPC to simulate like this exposes is different with the model residual error of test pattern actual exposure between the pattern on the wafer, by the OPC model residual error that the Different Effects factor relatively draws, choose hour corresponding factor of influence of model residual error mean value.Step S16, the CD data of the layout sampled point of correction OPC modeling after the model residual error value of the factor of influence of the model residual error mean value minimum that step S15 is the definite upward layout sampled point of OPC modeling on duty.Revising the CD data of revising the layout sampled point of OPC modeling among the CD data of test pattern sampled point and the step S16 among the step S12 and being all is that model residual error that CD data with pattern up-sampling point add sampled point is multiplied by after the value of the definite factor of influence of step S15 the CD data as the layout sampled point of OPC modeling.Can simply represent by following formula:
CD
Ri＝CD
i±MRE
i·f
k
CD
iBe the CD data value of the layout/test pattern up-sampling point i of OPC modeling, MRE
iBe the model residual error of layout up-sampling point i/ test pattern up-sampling point i, f
kBe the value of factor of influence, CD
RjFor revising the CD data value of post-sampling point.
Be multiplied by among the present invention the optimization factor of influence of determining by the model residual error data that will draw and revise the model residual error value that the CD data of the layout up-sampling point of OPC modeling can reduce the layout that employing OPC modeling draws, thereby effectively improve the precision of OPC model, improve the correction efficient of OPE.
Claims (5)
1. method that reduces the OPC model residual error, the OPC model can be used for the pattern behind the board design pattern exposure, it is characterized in that, and it may further comprise the steps:
Step 11: the model residual error value at a series of sampled points on the test pattern is provided, chooses the initial value of factor of influence;
Step 12: will revise the characteristic dimension data of described test pattern up-sampling point after the model residual error of all sampled points on the described test pattern upward factor of influence value on duty;
Step 13: with the test pattern up-sampling point characteristic dimension data revised described in the step 12 as the sampled point characteristic dimension data of the layout of described OPC modeling after the model residual error of acquisition test pattern sampled point, and calculate the mean value of model residual error of the test pattern sampled point of described acquisition;
Step 14: as factor of influence value in the described step 12, return step 12 after the change factor of influence value, after several times change the factor of influence value, execution in step 15;
Step 15: the model residual error mean value size of the described test pattern sampled point that calculates of Different Effects factor values relatively, the model residual error mean value of determining described test pattern sampled point is hour corresponding factor of influence value;
Step 16: the characteristic dimension data of revising the layout sampled point of OPC modeling after the model residual error value of the layout sampled point of factor of influence the above OPC modeling on duty of the model residual error mean value minimum that described step 15 is definite;
The initial value of the factor of influence that the model residual error value of all sampled points is multiplied by respectively in the described step 11 is all identical, and the value of described factor of influence greater than 0 less than 1.
2. the method that reduces the OPC model residual error as claimed in claim 1 is characterized in that, changing the factor of influence value in the described step 14 is to increase progressively the factor of influence value, the initial value minimum of the factor of influence of choosing in the described step 11.
3. the method that reduces the OPC model residual error as claimed in claim 1 is characterized in that, changing the factor of influence value in the described step 14 is the factor of influence value of successively decreasing, the initial value maximum of the factor of influence of choosing in the described step 11.
4. the method that reduces the OPC model residual error as claimed in claim 1 is characterized in that, the mean value that calculates the model residual error value of described sampled point in the described step 13 is to ask root mean square formula to calculate by following:
M＝[(MRE
1)
2+(MRE
2)
2...+(MRE
i)
2+...(MREn)
2]
1/2
Wherein, M is the model residual error root-mean-square value of a series of sampled points, MRE
1Be the model residual error of sampled point 1, MRE
2Be the model residual error of sampled point 2, MRE
iBe the model residual error of sampled point i, MRE
nModel residual error for sampled point n.
5. the method that reduces the OPC model residual error as claimed in claim 1, it is characterized in that revising the characteristic dimension data of revising the layout sampled point of OPC modeling in the characteristic dimension data of test pattern sampled point and the step 16 in the described step 12 and being all is that model residual error that characteristic dimension data with pattern up-sampling point add sampled point is multiplied by after the value of the definite factor of influence of step 15 the characteristic dimension data as the layout sampled point of described OPC modeling.
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| CN103186032B (en) * | 2011-12-31 | 2016-01-13 | 无锡华润上华科技有限公司 | Optical proximity effect modification method and corresponding mask pattern formation method |
| CN103781095B (en) * | 2012-10-23 | 2016-03-30 | 华为技术有限公司 | A kind of bearing calibration of TDOA measure error, transfer point and system |
| CN104516206B (en) * | 2013-09-27 | 2017-03-08 | 中芯国际集成电路制造(上海)有限公司 | A kind of optics that optimizes closes on the method for revising fitting result |
| CN103777460A (en) * | 2014-03-04 | 2014-05-07 | 上海集成电路研发中心有限公司 | Method for improving precision of optical proximity effect correction model |
| CN110361927B (en) * | 2018-04-11 | 2023-02-10 | 中芯国际集成电路制造(上海)有限公司 | Lithography model generation method and OPC correction method |
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| CN1406347A (en) * | 2000-02-29 | 2003-03-26 | 先进微装置公司 | Method of evaluation of reticle image using aerial image simulator |
| CN1692311A (en) * | 2003-02-17 | 2005-11-02 | 索尼株式会社 | Mask correcting method |
| CN1776695A (en) * | 2004-11-18 | 2006-05-24 | 国际商业机器公司 | Method for verification of resolution enhancement techniques and optical proximity correction in lithography |
| JP2007199256A (en) * | 2006-01-25 | 2007-08-09 | Fujitsu Ltd | Device and method for designing integrated circuit, and program |
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|---|---|---|---|---|
| CN1406347A (en) * | 2000-02-29 | 2003-03-26 | 先进微装置公司 | Method of evaluation of reticle image using aerial image simulator |
| CN1692311A (en) * | 2003-02-17 | 2005-11-02 | 索尼株式会社 | Mask correcting method |
| CN1776695A (en) * | 2004-11-18 | 2006-05-24 | 国际商业机器公司 | Method for verification of resolution enhancement techniques and optical proximity correction in lithography |
| JP2007199256A (en) * | 2006-01-25 | 2007-08-09 | Fujitsu Ltd | Device and method for designing integrated circuit, and program |
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