Lithography Focus Inference Using Asymmetry and Dose Metrics

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing methods for focus inference in lithographic processes are inaccurate due to the effect of dose variations and processing effects, leading to inconsistencies in focus measurement and limited focus range.

Innovation Solution

A method that infers focus by determining both an asymmetry metric and a sum metric from measurement data, where the asymmetry metric is dependent primarily on focus and the sum metric is dependent primarily on dose, allowing for simultaneous inference of focus and dose, thereby reducing the impact of dose variations and expanding the measurable focus range.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional focus inference methods using single metrics are used, then the measurement process is simple, but the focus measurement accuracy deteriorates due to dose variations

Engineering Contradiction:
Improvefocus measurement accuracyVSAvoidmeasurement process complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The invention segments the focus measurement process by using multiple independent metrics (first metric with stronger focus dependence, second metric with stronger dose dependence) instead of a single metric. This segmentation allows independent analysis of focus and dose effects, resolving the contradiction by improving measurement accuracy through metric differentiation while maintaining manageable process complexity through systematic multi-metric evaluation

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The invention transitions from single-metric one-dimensional measurement to multi-metric two-dimensional measurement space. By evaluating both first and second metrics simultaneously and analyzing their intersection, the system adds a dimensional aspect to focus measurement that explicitly accounts for dose variations, thereby improving accuracy without excessive complexity increase

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Reliability

If focus inference is performed assuming fixed dose values, then the process control is simplified, but the reliability deteriorates due to dose variations affecting focus accuracy

Engineering Contradiction:
Improvefocus inference reliabilityVSAvoidprocess control complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The invention implements feedback by using the second metric (with stronger dose dependence) to detect actual dose variations, then feeding this information back into the focus inference process. The system adjusts focus determination based on the measured dose level indicated by the second metric, ensuring reliable focus inference under varying dose conditions while maintaining systematic process control

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The invention changes the measurement parameters from assuming fixed dose to actively measuring and adapting to variable dose conditions. By using two metrics with different dependencies and analyzing their combined information, the system dynamically adjusts focus inference based on actual process parameters, improving reliability without excessive control complexity

Inventive Principle:
Principle #35Parameter changes

3Manufacturing precision

If send-ahead wafers with focus exposure matrix are used to determine optimal settings, then the process optimization is thorough, but the productivity deteriorates due to additional processing steps

Engineering Contradiction:
Improvefocus optimization accuracyVSAvoidproduction throughput
Core Design Contradiction:
Manufacturing precisionVSProductivity

Solution Approach 1:

The invention applies preliminary action by pre-establishing the relationship between multiple metrics and process parameters through calibration. Once calibrated, the system can perform rapid focus and dose inference during production without requiring additional send-ahead wafer processing, thereby maintaining thorough optimization capability while improving productivity through faster in-line measurements

Inventive Principle:
Principle #10Preliminary action

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

The method provides more accurate focus inference with improved robustness and expanded focus range, enabling better process control and monitoring by explicitly accounting for dose variations and processing effects.

Implementation Method 1

Transfer of the pattern is typically via imaging onto a layer of radiation-sensitive material (resist) provided on the substrate

Methodology Applied
Scientific EffectPhotolithography: Photopolymerisation

Implementation Method 2

These devices direct a beam of radiation onto a target and measure one or more properties of the scattered radiation—e.g., intensity at a single angle of reflection as a function of wavelength; intensity at one or more wavelengths as a function of reflected angle; or polarization as a function of reflected angle—to obtain a diffraction 'spectrum'

Methodology Applied
Scientific EffectDiffraction: Diffraction

Data Source

PatentUS12619161B2Method for inferring a processing parameter such as focus and associated apparatuses and manufacturing method
Publication Date: 2026.05.05 ASML NETHERLANDS BV
  • US12619161B2 patent drawing
  • US12619161B2 patent drawing
  • US12619161B2 patent drawing

AI summary

A method of inferring a value for a first processing parameter of a lithographic process, the first processing parameter being subject to a coupled dependency of a second processing parameter. The method includes determining a first metric and a second metric from measurement data, each of the first metric and second metric being dependent on both the first processing parameter and second processing parameter The first metric shows a stronger dependence to the first processing parameter than the second processing parameter and the second metric shows a stronger dependence to the second processing parameter than the first processing parameter. The value for the first processing parameter is inferred from the first and second metrics.