Lithographic Process Optimization for Etch Variation Tolerance
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Solution Overview
Problem
Current lithographic processes face challenges in optimizing the illumination source and design layout to achieve precise imaging and pattern transfer, particularly in low-k1 lithography, where feature sizes are below the classical resolution limit, leading to difficulties in reproducing intended patterns due to proximity effects and the need for sophisticated fine-tuning steps like OPC and source optimization.
Innovation Solution
A method is introduced to improve the lithographic process by determining evaluation points for variations in the etching process, computing a multi-variable cost function based on deviations from these points, and reconfiguring design variables such as illumination source, design layout, and projection optics to minimize errors and optimize process windows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the feature size is reduced below the classical resolution limit in low-k1 lithography, then higher integration density is achieved, but pattern reproduction accuracy deteriorates due to proximity effects
Solution Approach 1:
The patent applies optical proximity correction (OPC) and source optimization as preliminary actions before the actual lithographic exposure. These techniques pre-compensate for expected proximity effects by modifying the illumination source characteristics and design layout, thereby improving pattern reproduction accuracy even when feature sizes are reduced below the classical resolution limit
Solution Approach 2:
The patent employs sophisticated fine-tuning of process parameters including illumination source parameters, optical parameters, and resist processing parameters. By changing and optimizing these parameters, the system achieves better pattern fidelity at reduced feature sizes, resolving the contradiction between high integration density and pattern reproduction accuracy
2Manufacturing precision
If OPC and source optimization are applied to improve pattern fidelity, then manufacturing precision is improved, but process complexity increases
Solution Approach 1:
The patent implements automated optimization algorithms that self-adjust illumination source and design layout parameters based on simulated process outcomes. This self-service approach reduces the need for manual intervention and complex process management, thereby improving pattern fidelity while managing process complexity through automation
Solution Approach 2:
The patent uses simulation-based feedback loops where process outcomes are predicted, compared against targets, and used to iteratively refine illumination source and design layout parameters. This feedback mechanism systematically improves pattern fidelity while containing process complexity through structured optimization
3Manufacturing precision
If multiple fine-tuning steps like OPC and source optimization are implemented, then pattern transfer accuracy is improved, but manufacturing time increases
Solution Approach 1:
The patent performs OPC and source optimization as preliminary computational steps before actual manufacturing. By pre-calculating and pre-configuring the optimal parameters, the system achieves high pattern transfer accuracy while minimizing the time required during actual production cycles
Solution Approach 2:
The patent replaces iterative manual fine-tuning with automated computational optimization algorithms. This substitution of mechanical/manual processes with computational methods significantly reduces the time required to achieve optimal pattern transfer accuracy while maintaining or improving precision
Data Source
AI summary
A method to improve a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus and for transferring the imaged portion of the design layout to the substrate by an etching process, which method includes: determining a value of at least one evaluation point of the lithographic process for each of a plurality of variations of the etching process; computing a multi-variable cost function of a plurality of design variables that are characteristics of the lithographic process, wherein the multi-variable cost function is a function of deviation from the determined values of the at least one evaluation point; and reconfiguring the characteristics of the lithographic process by adjusting the design variables until a termination condition is satisfied. This method may reduce the need of repeated adjustment to the lithographic process when the etching process varies.