METHOD AND SYSTEM FOR OPTIMIZING OPTICAL INSPECTION OF PATTERNED STRUCTURES

• US 20160284077A1
• Filed: 02/23/2016
• Published: 09/29/2016
• Est. Priority Date: 06/17/2010
• Status: Active Grant

• Current Assignee: Nova Ltd.
• Original Assignee: Nova Measuring Instruments Limited (Honeywell International Inc.)
• Inventors: BRILL, Boaz
• Granted Patent: US 9,904,993 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01B 11/02 for measuring length, width or thickness G01B11/08 takes precedence
• CPC Class Codes: G01B 21/02 for measuring length, width, or thickness G01B21/10 takes precedence
• CPC Class Codes: G01B 2210/56 Measuring geometric parameters of semiconductor structures, e.g. profile, critical dimensions or trench depth
• CPC Class Codes: G03F 7/70625 Dimensions, e.g. line width, critical dimension [CD], profile, sidewall angle or edge roughness
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06T 7/80 Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

Abstract

A system and method are presented for use in inspection of patterned structures. The system comprises: data input utility for receiving first type of data indicative of image data on at least a part of the patterned structure, and data processing and analyzing utility configured and operable for analyzing the image data, and determining a geometrical model for at least one feature of a pattern in said structure, and using said geometrical model for determining an optical model for second type of data indicative of optical measurements on a patterned structure.

Claims

1. A method for use in measuring of patterned structures, the method comprising:

providing first type measured data and second type measured data about the structure, the first and second types of measured data corresponding to first and second measurements based on different physical principles and being therefore different from one another; and

processing and analyzing the first and second types measured data and further optimizing at least one of first and second data interpretation models for interpretation of at least one of the first type measured data and the second type measured data.

2. A method according to claim 1, wherein said second type measured data comprises scatterometric data.

3. A method according to claim 1, wherein said first type measured data comprises image data.

4. A method according to claim 2, wherein said first type measured data comprises image data.

5. A method according to claim 2, wherein said scatterometry data comprises optical response data indicative of a profile of the pattern.

6. A method according to claim 2, wherein said scatterometry data comprises Optical Critical Dimension (OCD) data.

7. A method according to claim 1, wherein said processing and analyzing of the first and second types measured data comprises determining a correlation function between the first and second types measured data, and utilizing said correlation function for said optimizing of the at least one of the first and second data interpretation models.

8. A method according to claim 1, wherein said processing and analyzing comprises utilizing a predetermined common interpretation model of the first and second types measured data for said optimizing of the at least one of the first and second data interpretation models.

9. A method according to claim 1, wherein said optimizing of the at least one of the first and second types measured data comprises performing a fitting process between the measured data and theoretical data provided by the respective data interpretation model for said at least one of the first and second types measured data.

10. A method according to claim 1, wherein the first data interpretation model is a geometrical model of at least a part of the pattern, and the second data interpretation model is an optical model.

11. A method according to claim 1, wherein the first measured data is obtained from at least one of SEM or AFM.

12. A method according to claim 1, wherein said processing and analyzing of the first and second types measured data comprises:

utilizing theoretical data about a theoretical profile of the patterned structure and said first and second interpretation models for simulating measured data of the first type and simulating measured scatterometry data of the second type from said theoretical profile;

comparing first simulated data with the first type measured data, and comparing second simulated data with the second type measured data;

determining an optimized pattern profile corresponding to optimized comparison data; and

using said optimized pattern profile for said optimizing of the at least one of said first and second data interpretation models.

13. A method according to claim 1, wherein the first measured data comprises one or more of the following pattern parameters:

side wall angle (SWA), a line width profile, height.

14. A method according to claim 1, wherein said optimizing of the second data interpretation model comprises setting of at least one of model parameters.

15. A method according to claim 14, wherein said optimizing comprises fixing the at least one model parameters.

16. A method according to claim 14, wherein said at least one model parameter comprises at least one geometric parameter.

17. A method according to claim 14, wherein said at least one model parameters comprises parameter related to optical properties of materials in the structure.

18. A method according to claim 1, wherein said optimized first data interpretation model comprises parameters characterizing extraction of secondary charge carriers from different regions of the structure comprising at least one of different depths, different materials and different geometries.

19. A method according to claim 12, wherein said comparing of the simulated data comprises determining first and second errors between the first simulated and measured data and the second simulated and measured data, respectively;

and combining the first and second errors into a total error presenting the optimized comparison data.

20. A method according to claim 19, wherein the error is determined as a residual error or a Merit Function.

22. A computer system for carrying out the method of claim 1, the system comprising:

data input utility for receiving said different first and types measured data; and

data processing and analyzing utility configured and operable for applying said processing to the first and second types measured data and generating data indicative of at least one optimized data interpretation model for interpretation of at least one of the first type measured data and the second type measured data.

21. A method for use in modeling of interpretation of measured data from patterned structures, the method comprising:

processing first and second measured data of different first and second types, the second type measured data being scatterometric data; and

optimizing at least one of first and second data interpretation models for interpretation of the first type measured data and the second type measured data.