Defect-Based Process Window Calibration for Lithography Simulation
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Solution Overview
Problem
Existing device manufacturing processes face challenges in accurately simulating and calibrating lithographic processes to achieve desired pattern transfer within acceptable process windows, leading to defects and inefficiencies in semiconductor fabrication.
Innovation Solution
A method for calibrating simulation processes by obtaining characteristic limits and reference process windows, adjusting parameter values, and generating retargeted patterns to meet these limits, while using probability density functions to optimize dose and mask parameters for improved process control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing simulation processes are used for lithographic pattern transfer, then the process can be executed with standard parameters, but the simulation accuracy and calibration precision are insufficient leading to defects
Solution Approach 1:
The patent applies parameter changes by adjusting process model parameters (such as optical parameters, resist parameters, and etch parameters) to calibrate the simulation process. The calibration involves comparing simulation results with actual measured data from test patterns and iteratively adjusting parameters until the simulation accurately predicts the process window and pattern outcomes, thereby improving both simulation accuracy and reducing defects
Solution Approach 2:
The patent implements feedback through a calibration loop where simulation results are compared with actual measured data from fabricated test patterns. The differences between simulated and measured process windows are used to adjust and refine the process model parameters, creating a continuous improvement cycle that enhances simulation accuracy and reliability
2Manufacturing precision
If process parameters are adjusted to improve pattern quality within process window, then manufacturing precision improves, but the complexity of calibration and optimization increases
Solution Approach 1:
The patent applies preliminary action by performing calibration using test patterns before actual production patterning. The process window is determined and process parameters are optimized in advance using simplified test structures, allowing the main production process to proceed with pre-calibrated parameters without requiring complex real-time adjustments
Solution Approach 2:
The patent segments the calibration process into distinct stages: first determining the process window using test patterns, then calibrating process models within that window, and finally applying the calibrated models to production. This segmentation breaks down the complex calibration task into manageable steps, reducing overall complexity
3Measurement precision
If characteristic limits and reference process windows are used for calibration, then simulation accuracy improves, but the time and resources required for calibration increase
Solution Approach 1:
The patent applies partial action by focusing calibration efforts on the most critical process parameters and the dominant portions of the process window. Rather than exhaustively calibrating all possible parameters across the entire parameter space, the method identifies and calibrates the key parameters that have the greatest impact on pattern fidelity, achieving sufficient accuracy more efficiently
Solution Approach 2:
The patent uses test patterns that replicate the critical features of production patterns. By creating simplified copies or representative structures that capture the essential physics and process behavior, the calibration can be performed on these copies rather than requiring exhaustive testing of all production patterns, reducing calibration time while maintaining accuracy
Data Source
AI summary
Methods related to improving a simulation processes and solutions (e.g., retargeted patterns) associated with manufacturing of a chip. A method includes obtaining a plurality of dose-focus settings, and a reference distribution based on measured values of a characteristic of a printed pattern associated with each setting of the plurality of dose-focus settings. The method further includes, based on an adjustment model and the plurality of dose-focus settings, determining a probability density function (PDF) of the characteristic such that an error between the PDF and the reference distribution is reduced. The PDF can be a function of the adjustment model and variance associated with dose, the adjustment model being configured to change a proportion of non-linear dose sensitivity contribution to the PDF. A process window can be adjusted based on the determined PDF of the characteristic.