Predicting EUV Dose via PAG Molecular Orbital Parameters
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Solution Overview
Problem
In EUV lithography, there is a challenge in achieving sufficient acid generation from photoacid generators (PAGs) due to insufficient power for laser irradiation, limiting the EUV dose and affecting pattern formation in semiconductor devices.
Innovation Solution
A method is developed to predict the EUV dose by analyzing the entire photochemical reaction mechanism of PAGs, obtaining key parameters such as the LUMO energy level and additional parameters through simulations, and using a two-parameter linear regression model to efficiently predict the EUV dose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If EUV lithography is used for pattern miniaturization, then manufacturing precision is improved, but the available power for laser irradiation is insufficient, limiting the EUV dose and acid generation efficiency
Solution Approach 1:
The patent applies parameter changes by developing a predictive model that analyzes molecular orbital energy levels (LUMO, HOMO) and photochemical reaction parameters to optimize PAG molecule design. This allows selection of PAGs with appropriate energy level parameters that maximize acid generation efficiency under the constrained EUV dose conditions, effectively resolving the power limitation through molecular parameter optimization rather than increasing system power.
2Productivity
If the EUV dose is increased to generate sufficient acid from PAG, then acid generation efficiency is improved, but the available power from the laser source is insufficient
Solution Approach 1:
The patent uses parameter changes by establishing a predictive model based on molecular orbital energy levels and photochemical parameters to identify PAG molecules with optimal characteristics for low-dose EUV lithography. The model predicts acid generation efficiency without requiring actual high-power exposure, enabling selection of PAGs that achieve high productivity under limited power conditions through molecular design optimization.
Solution Approach 2:
The patent applies preliminary action by performing computational predictions of EUV dose requirements and acid generation efficiency before actual lithography experiments. The predictive model allows researchers to pre-screen and select optimal PAG candidates in silico, avoiding trial-and-error experimentation and enabling proactive optimization of acid generation efficiency before committing to actual high-dose exposure processes.
3Power
If traditional lithography methods are used, then sufficient power is available for exposure, but pattern miniaturization capability is insufficient
Solution Approach 1:
The patent resolves this contradiction by changing the molecular parameters of the PAG substances used in EUV lithography. The predictive model identifies PAG molecules with specific orbital energy level configurations that enhance sensitivity to low-dose EUV radiation, enabling traditional EUV systems with limited power to achieve pattern miniaturization capabilities previously only possible with higher-power systems.
4Productivity
If a two-parameter linear regression model is used to predict EUV dose, then prediction efficiency is improved, but model complexity increases compared to simpler prediction methods
Solution Approach 1:
The patent applies parameter changes by selecting two specific molecular parameters (LUMO energy level and another photochemical parameter) that provide optimal predictive power for EUV dose requirements. This balanced approach achieves high prediction efficiency without excessive complexity, as the model uses a manageable number of computationally obtainable parameters rather than requiring complex multi-parameter or machine learning models.
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 allows for the efficient prediction of EUV dose and improves prediction consistency, enabling the design of new PAG molecules with superior acid generation yield and performance at lower EUV doses, thus enhancing semiconductor device manufacturing.
Implementation Method 1
analyzing an entire photochemical reaction mechanism until a photoacid generator (PAG) molecule releases a proton from a PAG-cation under EUV exposure
Implementation Method 2
obtaining a lowest unoccupied molecular orbital (LUMO) energy level by performing a simulation for structural optimization of the PAG-cation
Data Source
AI summary
In a method of predicting extreme ultraviolet (EUV) dose, an entire photochemical reaction mechanism until a photoacid generator (PAG) molecule releases a proton from a PAG-cation under EUV exposure may be analyzed. A lowest unoccupied molecular orbital (LUMO) energy level may be obtained by performing a simulation for structural optimization of the PAG-cation. An additional parameter different from the LUMO energy level may be obtained by performing a simulation for structural optimization of at least one intermediate molecular structure formed by the entire photochemical reaction mechanism. A two-parameter linear regression model for predicting the EUV dose may be obtained based on the LUMO energy level and the additional parameter.