Critical dimension error analysis method

Patent metadata

Field	Value
Publication number	US-12288725-B2
Application number	US-202017776637-A
Country	US
Kind code	B2
Filing date	Jul 23, 2020
Priority date	Nov 29, 2019
Publication date	Apr 29, 2025
Grant date	Apr 29, 2025

Abstract

The present invention disclosures a critical dimension error analysis method, comprising: S 01 : performing lithography processes on a wafer, measuring the critical dimension (CD) values of the test points in each of the fields respectively; M and N are integers greater than 1; S 02 : removing extreme outliers from the critical dimension (CD) values; S 03 : rebuilding remaining CD values by a reconstruction model fitting method, and obtaining rebuilt critical dimension (CD″) values, according to relative error between CD″ and CD, dividing the rebuilt critical dimension (CD″) values into scenes and the number of the scenes is A; S 04 : calculating components and corresponding residuals of the test points in each of the scenes under a reference system corresponding to a correction model by parameter estimation; S 05 : modifying machine parameters and masks by the correction model according to above calculation results. The present invention uses an outer limit to remove extreme outliers, so as to analyze a critical dimension error during a lithography process quickly and accurately.

First claim

What is claimed is:

1. A critical dimension error analysis method, comprising:
S 01 : performing lithography processes on a wafer, wherein the wafer comprises fields and the number of the fields is M, the lithography processes are the same in each of the fields, setting the same number of test points in each of the fields and the number of the test points is N, measuring the critical dimension (CD) values of the test points in each of the fields respectively; M and N are integers greater than 1;
S 02 : removing extreme outliers from the critical dimension (CD) values;
S 03 : rebuilding remaining CD values by a reconstruction model fitting method, and obtaining rebuilt critical dimension (CD″) values, according to relative error between CD″ and CD, dividing the rebuilt critical dimension (CD″) values into scenes and the number of the scenes is A, and the same test points in the fields are in the same scene, and the relative error between CD″ and CD of any two fields in each of the scenes is non-periodic in spatial distribution; A is an integer greater than 0;
S 04 : calculating components and corresponding residuals of the test points in each of the scenes under a reference system corresponding to a correction model by parameter estimation;
S 05 : modifying machine parameters and masks by the correction model according to above calculation results.

2. The method of claim 1 , wherein in step S 02 , removing the extreme outliers by the parameter estimation, which comprises:
S 021 : setting the critical dimension value (CD i,j ) of the j-th test point in the i-th field as CD ij =inter i +intra j +Er i,j , wherein, inter i is an inter-field component of the j-th test point, intra j is an intra-field component of the j-th test point, and Er i,j is error; treating inter; and intra j as dummy variables of an inter-field component set (inter) and an intra-field component set (intra) respectively, taking inter i and intra j as parameters without considering Er i,j , and estimating parameters of CD to obtain the inter-field component (inter 0 i ) and the intra-field component (intra0 j ) of the j-th test point, and after reconstruction, the rebuilt critical dimension value (CD′) of the j-th test point equals inter0 i plus intra0 j , which is CD′=inter0 i +intra0 j ;
S 022 : setting the relative error (Er_r′) between CD′ and CD as Er_r′=(CD′-CD)/CD′, and calculating an outer limit of the relative error between CD′ and CD;
S 023 : removing extreme outliers which exceed the outer limit of the relative error between CD′ and CD;
S 024 : repeating from step S 021 to S 023 until the extreme outliers is removed, or ratio of number of remaining test points to number of original test points is less than a number threshold after removing, or number of iterations is greater than a iteration threshold.

3. The method of claim 2 , wherein in step S 023 , a calculation method for the outer limit comprises sorting the relative error between CD′ and CD, and calculating a 25th quantile (Q 1 ) and a 75th quantile (Q 3 ), and setting IQR=Q 3 -Q 1 , a lower limit of the outer limit is Q 1 - 3 *IQR, and an upper limit of the outer limit is Q 3 + 3 *IQR.

4. The method of claim 2 , wherein the approach to the parameter estimation is maximum likelihood estimation.

5. The method of claim 1 , wherein step S 03 comprises:
S 031 : inputting a global coordinates of the wafer as independent variables into the reconstruction model, and inputting the remaining critical dimension values as dependent variables into the reconstruction model, and reconstructing the critical dimension values by adjusting reconstruction model parameters to obtain the rebuilt critical dimension (CD″) values after reconstruction;
S 032 : calculating the relative error (Er”) between CD” and CD and Er “=(CD”-CD)/CD″, and dividing the remaining critical dimension values into the scenes according to the relative error between CD″ and CD, and the number of the scenes is A;
S 033 : recording the reconstruction model parameters corresponding to each of the scenes.

6. The method of claim 5 , wherein the reconstruction model is a Gradient Boosting Decision Tree (GBDT) model or an Extreme Gradient Boosting (XGBoost) model.

7. The method of claim 1 , wherein in S 03 , determining whether the relative error between CD″ and CD of any two fields in each of the scenes is periodic in the spatial distribution by a Pearson coefficient; while the Pearson coefficient of any two fields in one scene is less than a set threshold, then the relative error between CD″ and CD of the two fields in the scene is non-periodic in the spatial distribution.

8. The method of claim 1 , wherein in S 04 , the components and the corresponding residuals of the test points under the reference system corresponding to the correction model comprise an overall residual, intra-field X components, intra-field Y components, intra-field residuals, inter-field X components, inter-field Y components, and inter-field residuals of the test points.

9. The method of claim 8 , wherein in S 04 comprises:
S 041 : setting the critical dimension value (CD i,j ″) of the j-th test point in the i-th field as CD i,j ″=inter i “+intra j ” +res i,j , wherein, inter i ” is the inter-field component of the j-th test point, intra j ” is the intra-field component of the j-th test point, and res i,j is the overall residual; treating inter i ” and intra j ” as dummy variables of an inter-field component set (inter) and an intra-field component set (intra) respectively, taking inter j ” and intra j ” as parameters without considering res i,j , and estimating parameters of CD″ to obtain the inter-field component (inter0 i ”) and the intra-field component (intra0 j ”) of the j-th test point, the overall residual (res i,j ) equals CD i,j ” minus inter0 i ” minus intra0 j “, which is res i,j CD i,j ” -inter 0 ; “-intraOj” ;
S 042 : setting the inter-field component (inter k,1 ″) of the k-th row and the 1-th column on the wafer as inter k,1 ″=inter_x k ″+inter_y 1 ″+inter_res k,1 ″, wherein, inter_x k ” is the inter-field X component between fields, inter_y 1 is the inter-field Y component between fields, and inter res k,1 ″ is the inter-field residual between fields; treating inter_x k ” and inter_y 1 ” as dummy variables of an inter-field X component set (inter_x) and an inter-field Y component set (inter y) respectively, taking inter_x k ” and inter y 1 ” as parameters without considering inter_res k,1 ″, and estimating parameters of inter x k ″ and inter y 1 ” to obtain the inter-field X component (inter_x0 k ”) and the inter-field Y component (inter_y0 1 ”) between fields, and the inter-field residual (inter_res k,1 ″) between fields equals inter k,1 ″ minus inter_x0 k ” minus inter_y0 1 ″, which is inter_res k,1 ″=inter k,1 ″-inter_x0 k ″-inter_y0 1 ″;
S 043 : setting the intra-field component (intra m,n ″) of the m-th row and the n-th column in the i-th field as intra m,n ″=intra_x m “+intra_y n ” +intra_res m,n ″, wherein, intra_x m ” is the intra-field X component of the j-th test point, intra_y n ” is the intra-field Y component of the field, and intra_res m,n ″ is the intra-field residual of the field; treating intra_x m ” and intra_y n ” as dummy variables of an intra-field X component set (intra_x) and an intra-field Y component set (intra_y) respectively, taking intra_x m ” and intra_y n ” as parameters without considering intra_res m,n ″, and estimating parameters of intra x m ” and intra y n ” to obtain the intra-field X component (intra_x0 m ”) and the intra-field Y component (intra_y0 n ”) of the field, and the inter-field residual (inter_res k,1 ″) of the field equals intra m,n ″ minus intra_x0 m ” minus intra_y0 n “, which is inter res k,1 ″=in

Assignees

• Shanghai Ic R&D Ct Co Ltd

Inventors

• Yu Xueru
• Sun Hongxia
• Li Chen
• Wang Pengfei
• Duan Jiebin
• Wang Xiucui
• Fu Hao
• Zhou Tao
• Yan Yan
• Xu Bowen
• Guo Lingyi
• Li Liren

Classifications

• H10P74/238

  comprising acting in response to an ongoing measurement without interruption of processing, e.g. endpoint detection or in-situ thickness measurement · CPC title

• H10P74/203 Primary

  Structural properties, e.g. testing or measuring thicknesses, line widths, warpage, bond strengths or physical defects · CPC title

• H10P74/23 Primary

  characterised by multiple measurements, corrections, marking or sorting processes · CPC title

• Y02P90/30

  Computing systems specially adapted for manufacturing · CPC title

• H01L22/26

  Electricity · mapped topic