Photomask SRAF Generation Using TCC Kernel Decomposition
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Solution Overview
Problem
Current photolithography techniques face challenges in producing features smaller than the wavelength of light used, leading to diffraction errors and inaccuracies in pattern reproduction, especially when creating sub-resolution features in semiconductor devices.
Innovation Solution
The method involves constructing a transmission cross coefficient matrix to generate kernels with odd symmetry, creating field maps, and assigning sub-resolution assist features (SRAFs) to improve pattern fidelity, using a systematic approach that includes SRAF rule processing and kernel convolutions to enhance photomask design for sub-resolution photolithography.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional photolithography is used to produce smaller circuit features, then circuit density increases, but diffraction errors cause pattern fidelity to deteriorate
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing transmission cross coefficient (TCC) matrices and their decomposed kernels before actual photomask design. This pre-computed data is then rapidly applied during SRAF generation, allowing the system to compensate for diffraction effects in advance rather than dealing with them during the actual lithography process.
Solution Approach 2:
The patent introduces an intermediary computational framework that uses TCC matrix decomposition and field map convolution as intermediate steps between the desired pattern and the actual photomask design. This intermediary process calculates sub-resolution assist features (SRAFs) that mediate the diffraction effects, enabling accurate pattern reproduction at sub-resolution dimensions.
2Measurement precision
If inverse lithography techniques are used to generate SRAF maps, then pattern accuracy improves, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent segments the complex inverse lithography problem into manageable components by decomposing the TCC matrix into individual kernels. Each kernel represents a specific spatial frequency component, allowing the system to process and combine them systematically through convolution operations, thereby reducing overall computational complexity while maintaining accuracy.
Solution Approach 2:
The patent changes the computational parameters by using pre-decomposed TCC kernels instead of performing full inverse lithography calculations. This parameter change transforms the problem from solving a complex optimization problem to executing efficient convolution operations with pre-computed kernels, significantly reducing processing time and computational resources.
3Manufacturing precision
If full chip photomask design is performed with detailed SRAF generation, then feature fidelity improves, but manufacturing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing TCC matrices and their kernel decompositions for different illumination conditions and process parameters. This pre-computation is performed once and reused across multiple photomask designs, significantly reducing the computational burden and manufacturing time for each new full-chip photomask while maintaining high feature fidelity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach results in more accurate and computationally efficient generation of SRAF maps, enabling the production of semiconductor devices with improved feature fidelity and practicality for full chip devices, surpassing the limitations of existing inverse lithography techniques.
Implementation Method 1
an illumination source for supplying light to transmit through the photomask and a pupil for focusing the transmitted light onto a target substrate
Implementation Method 2
compensate for diffraction and other errors introduced in the photolithography process at sub resolution levels
Data Source
AI summary
A method of making a photomask includes constructing a transmission cross coefficient (TCC) matrix representing an illumination source for supplying light to transmit through the photomask and a pupil for focusing the transmitted light onto a target substrate to produce a set of main features, generating kernels through decomposition of the TCC matrix, selecting ones of the kernels having odd symmetry, generating a field map kernel as a sum of self-convolutions of the odd symmetry kernels, generating a first field map by convolving an area of the photomask corresponding to the set of main features with the field map kernel, and making the photomask corresponding to the first field map. The method may include assigning first sub-resolution assist features (SRAFs) to those portions of the photomask area having corresponding said first field map values exceeding a nonnegative threshold, and making the photomask corresponding to the main features and first SRAFs.