Simulation Calibration Using Defect-Based Process Windows

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Solution Overview

Problem

Existing device manufacturing processes face challenges in accurately calibrating simulation processes to achieve optimal process windows, leading to defects in printed patterns.

Innovation Solution

A method is provided to calibrate simulation processes by determining characteristic limits and reference process windows, adjusting parameter values, and generating retargeted patterns to meet these limits, using dose and mask probability density functions to refine process windows.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If existing device manufacturing processes are used without calibration, then the process can be executed with standard parameters, but the simulation accuracy is insufficient and defects occur in printed patterns

Engineering Contradiction:
Improvesimulation accuracyVSAvoidprocess complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent applies preliminary action by performing calibration of simulation processes before actual manufacturing. This involves determining characteristic limits and reference process windows in advance, adjusting parameter values beforehand, and generating retargeted patterns prior to production. This preliminary calibration ensures simulation accuracy is established before manufacturing begins, preventing defects while managing complexity through structured pre-processing steps.

Inventive Principle:
Principle #10Preliminary action

2Manufacturing precision

If parameter values are adjusted to meet characteristic limits, then the quality of printed patterns improves, but the calibration process becomes more complex and time-consuming

Engineering Contradiction:
Improvepattern qualityVSAvoidcalibration time
Core Design Contradiction:
Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent implements feedback by using measured characteristic limits from actual printed patterns to adjust simulation parameter values. The process window determination provides feedback on acceptable parameter ranges, and retargeted pattern generation uses this feedback to optimize future prints. This closed-loop feedback mechanism improves pattern quality while reducing calibration time by systematically using measurement data to guide parameter adjustments rather than trial-and-error approaches.

Inventive Principle:
Principle #23Feedback

3Productivity

If characteristic limits are determined based on threshold failure rate, then the process window can be optimized, but the measurement and analysis process becomes more complex

Engineering Contradiction:
Improveprocess optimizationVSAvoidmeasurement complexity
Core Design Contradiction:
ProductivityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent replaces complex physical measurement systems with simulation-based approaches. Instead of relying solely on extensive physical experimentation to determine characteristic limits, the method uses calibrated simulation processes with probability density functions to predict and analyze pattern characteristics. This substitution reduces measurement complexity while maintaining productivity by using computational models to guide process optimization.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250355366A1Method for calibrating simulation process based on defect-based process window
Publication Date: 2025.11.20 ASML NETHERLANDS BV
  • US20250355366A1 patent drawing
  • US20250355366A1 patent drawing
  • US20250355366A1 patent drawing

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.