System and method for mask verification using an individual mask error model

• US 7,587,704 B2
• Filed: 09/08/2006
• Issued: 09/08/2009
• Est. Priority Date: 09/09/2005
• Status: Active Grant

• Current Assignee: ASML Netherlands BV (ASML Holding NV)
• Original Assignee: Brion Technologies Incorporated (ASML Holding NV)
• Inventors: Ye, Jun, Hunsche, Stefan
• Primary Examiner(s): Do; Thuan
• Assistant Examiner(s): Dimyan; Magid Y
• Application Number:
  US11/530,402
• Publication Number:
  US 20070061772A1
• Time in Patent Office: 1,096 Days
• Field of Search: 716/19, 716/21, 430/5
• US Class Current: 716/51
• CPC Class Codes: G03F 1/36 Masks having proximity correction features; Preparation thereof, e.g. optical proximity correction [OPC] design processes
• CPC Class Codes: G03F 1/84 Inspecting
• CPC Class Codes: G03F 7/70441 Optical proximity correction [OPC]
• CPC Class Codes: G03F 7/705 Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions
• CPC Class Codes: G06F 30/398 Design verification or optimisation, e.g. using design rule check [DRC], layout versus schematics [LVS] or finite element methods [FEM] optical proximity correction [OPC] design processes G03F1/36

Abstract

Methods and systems are disclosed to inspect a manufactured lithographic mask, to extract physical mask data from mask inspection data, to determine systematic mask error data based on differences between the physical mask data and mask layout data, to generate systematic mask error parameters based on the systematic mask error data, to create an individual mask error model with systematic mask error parameters, to predict patterning performance of the lithographic process using a particular mask and/or a particular projection system, and to predict process corrections that optimize patterning performance and thus the final device yield.

Claims

1. A method comprising:

obtaining mask inspection data from a mask manufactured using mask layout data and a mask inspection tool configured to produce mask inspection data;

determining differences between the mask inspection data and the mask layout data;

generating systematic mask error data based on the differences between the mask inspection data and the mask layout data using a model-based mask data analysis system configured to extract physical mask data from the mask inspection data; and

generating systematic mask error parameters for an individual mask error model based on the systematic mask error data.

2. The method of claim 1, further comprising:

simulating a lithography process using the individual mask error model having the systematic mask error parameters to produce simulated results; and

analyzing the simulated results to evaluate a process window of the lithography process.

3. The method of claim 1, further comprising:

simulating a lithography process using the individual mask error model having the systematic mask error parameters to produce simulated results; and

analyzing the simulated results to verify the mask.

4. The method of claim 1, further comprising:

simulating a lithography process using the individual mask error model having the systematic mask error parameters to produce simulated results; and

comparing the simulated results to a design target.

5. The method of claim 1, further comprising:

simulating a lithography process using the individual mask error model having the systematic mask error parameters to produce simulated results;

simulating the lithography process using a nominal mask error model to produce nominal simulated results; and

comparing the simulated results and the nominal simulated results to verify the mask.

6. Thc method of claim 1, further comprising:

simulating a lithography process using the individual mask model having the systematic mask error parameters to produce simulated results;

simulating the lithography process using a post optical proximity correction (OPC) mask layout to produce ideal simulated results; and

comparing the simulated results and the ideal simulated results to verify the mask.

7. The method of claim 1, wherein the systematic mask error parameters are selected from the group consisting of linewidth bias, phase bias, corner rounding radii, line-edge roughness, etch depth, and sidewall angle.

8. The method of claim 1, wherein the mask inspection data is obtained by directly measuring pattern metrics of the mask using a metrology tool selected from the group consisting of a critical dimension scanning electron microscope (CD-SEM) tool, an imaging scanning electron microscope (SEM) tool, an atomic force microscope (AFM) tool, an optical microscope, a phase-shifting interferometer, and an ellipsometer.

9. The method of claim 1, wherein the mask inspection data is obtained by determining pattern metrics of an aerial image produced by an exposure tool and the mask using an image sensor array disposed in the exposure tool.

10. The method of claim 1, wherein the mask inspection data is obtained by determining pattern metrics of the mask using an inspection tool selected from the group consisting of an optical mask inspection tool, an electron beam mask inspection tool, and an aerial image measurement system.

11. The method of claim 1, wherein the mask layout data is circuit design data.

12. The method of claim 1, wherein the mask layout data is test pattern data.

13. A system comprising:

a mask inspection tool configured to produce mask inspection data;

a model-based mask data analysis system coupled to the mask inspection tool, the model-based mask data analysis system configured to extract physical mask data from the mask inspection data, to determine systematic mask error data based on differences between the extracted physical mask data and mask layout data, and configured to generate systematic mask error parameters for an individual mask error model based on the systematic mask error data.

14. The system of claim 13, wherein the systematic mask error parameters are selected from the group consisting of linewidth bias, phase bias, corner rounding radii, line-edge roughness, etch depth, and sidewall angle.

15. The system of claim 13, wherein the mask inspection tool is selected from the group consisting of a critical dimension scanning electron microscope (CD-SEM) tool, an imaging scanning electron microscope (SEM) tool, an atomic force microscope (AFM) tool, an optical microscope, a phase-shifting interferometer, and an ellipsometer.

16. The system of claim 13, wherein the mask inspection tool is an image sensor array disposed in an exposure tool.

17. The system of claim 14, wherein the mask inspection tool is selected from the group consisting of an optical mask inspection tool, an electron beam mask inspection tool, and an aerial image measurement system.