METHOD FOR SELECTING AND OPTIMIZING EXPOSURE TOOL USING AN INDIVIDUAL MASK ERROR MODEL

• US 20070061773A1
• Filed: 09/08/2006
• Published: 03/15/2007
• 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
• Granted Patent: US 7,617,477 B2
• Time in Patent Office: Days
• US Class Current: 716/52
• 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 are disclosed for selecting and optimizing an exposure tool using an individual mask error model. In one embodiment, a method includes selecting a model of a lithography process including an optical model of an exposure tool and a resist model, creating an individual mask error model representing a mask manufactured using mask layout data, simulating the lithography process using the model of the lithography process and the individual mask error model to produce simulated patterns, determining differences between the simulated patterns and a design target, and optimizing settings of the exposure tool based on the differences between the simulated patterns and the design target.

Claims

1. A method comprising:

selecting an optical model for an exposure tool;

selecting a second optical model for a second exposure tool;

simulating operation of the exposure tool using the optical model and an individual mask error model of a mask to produce first simulated results;

simulating operation of the second exposure tool using the second optical model and the individual mask error model to produce second simulated results;

performing a comparison of the first simulated results to a design target;

performing a comparison of the second simulated results to the design target; and

comparing the performances of the exposure tool and the second exposure tool based on the comparisons.

2. The method of claim 1, wherein the individual mask error model includes systematic mask error parameters determined from an inspection of the mask.

3. The method of claim 1, further comprising selecting one of the exposure tool or the second exposure tool to exposure product wafers using the mask.

4. The method of claim 1, wherein the individual mask error model is created by:

obtaining mask inspection data from the mask, where the mask was manufactured using mask layout 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; and

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

5. A method comprising:

selecting a model of a lithography process, the model including an optical model of an exposure tool and a resist model;

creating an individual mask error model for a mask manufactured using mask layout data;

simulating the lithography process using the model of the lithography process and the individual mask error model to produce simulated patterns;

determining differences between the simulated patterns and a design target; and

modifying settings of the exposure tool based on the differences between the simulated patterns and the design target.

6. The method of claim 5, wherein the individual mask error model includes systematic mask error parameters determined from an inspection of the mask.

7. The method of claim 5, wherein the settings of the exposure tool are selected from the groups consisting of focus, exposure dose, numerical aperture, sigma, coherence, lens aberrations, and illumination shifts.

8. The method of claim 5, wherein the differences between the simulated patterns and the design target are selected from the group consisting of critical dimension, line-end pullback, and corner rounding.

9. The method of claim 5, wherein creating an individual mask error model comprises:

obtaining mask inspection data from the mask;

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; and

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

10. A method comprising:

selecting a plurality of optical models for a plurality of exposure tools, each optical model representing an individual exposure tool;

for each of the plurality of optical models, simulating a lithography process using the optical model and an individual mask error model for a mask to produce simulated results; and

evaluating the simulated results for each of the plurality of optical models to determine which of the plurality of exposure tools performs best with the mask.

11. The method of claim 10, wherein the individual mask error model includes systematic mask error parameters determined from an inspection of the mask.

12. The method of claim 10, wherein evaluating the simulated results for each of the plurality of optical models includes comparing the simulated results with a design target.

13. The method of claim 10, further comprising:

selecting the best-match exposure tool and the mask for wafer production.

14. The method of claim 10, wherein the individual mask error model is created by:

obtaining mask inspection data from the mask, where the mask was manufactured using mask layout 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; and

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