Pattern Measuring Apparatus for SADP Gap Classification
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Solution Overview
Problem
Current methods for measuring pattern dimensions in semiconductor manufacturing, particularly with Self-Aligned Double Patterning (SADP), face challenges in discerning different types of gaps formed by multiple exposure steps, leading to increased inspection and measurement time, which reduces throughput.
Innovation Solution
A pattern measuring apparatus that uses charged particle beam scanning to extract features from both ends of patterns, compares profiles to discern gap types based on signal values, and employs techniques like waveform matching and profile analysis to differentiate between core and spacer gaps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional electron microscope imaging is used to measure pattern dimensions, then measurement capability is provided, but inspection and measurement time increases, reducing throughput
Solution Approach 1:
The patent segments the measurement process by automatically identifying and classifying different gap types (core gaps vs. spacer gaps) between patterns. The apparatus divides the inspection task into distinct measurement zones, allowing for targeted analysis of each gap type rather than uniform processing of all patterns, thereby reducing overall measurement time while maintaining precision.
Solution Approach 2:
The apparatus performs preliminary classification of gap types before detailed dimension measurement. By pre-identifying whether a gap is a core gap or spacer gap using signal characteristics, the system prepares measurement parameters and expectations in advance, enabling faster subsequent measurement operations and improving throughput without sacrificing accuracy.
2Manufacturing precision
If multiple exposure steps are used to form patterns (SADP), then smaller pattern dimensions are achieved, but the complexity of discerning different gap types increases
Solution Approach 1:
The patent introduces signal characteristics as an intermediary to indirectly identify gap types. Instead of directly analyzing complex structural differences between core gaps and spacer gaps, the apparatus uses secondary electron signal characteristics (intensity, distribution patterns) as a mediator to classify gap types, simplifying the identification process while maintaining accuracy in distinguishing different gap formations from multiple exposure steps.
Solution Approach 2:
The apparatus replaces direct physical/structural analysis of gap types with signal-based classification. Instead of mechanically or physically examining the structural differences between core and spacer gaps, the system substitutes this with electronic signal analysis of secondary electron emissions, enabling automated and rapid differentiation of gap types formed by multiple exposure steps.
3Measurement precision
If detailed profile analysis is performed to discern gap types, then measurement accuracy is improved, but inspection time increases
Solution Approach 1:
The apparatus applies partial profile analysis by focusing on specific critical signal characteristics rather than performing exhaustive analysis of entire profiles. The system identifies and analyzes only the most discriminative portions of the secondary electron signals that are sufficient for gap type classification, achieving accurate identification without the time cost of complete detailed analysis of all signal aspects.
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
Enables high-throughput identification of gap types formed by SADP processes, allowing for precise measurement and control of pattern dimensions without compromising inspection speed.
Implementation Method 1
measuring pattern dimensions based on a signal obtained by irradiating a sample with a charged particle beam
Data Source
AI summary
Provided are a pattern measuring apparatus and a computer program which determine whether a gap formed in a sample (201) is a core gap (211) or a spacer gap (212). The secondary electron profile of the sample (201) is acquired, the feature quantities of the secondary electron profile at the positions of edges (303, 305) are detected, and based on the detected feature quantities, whether each gap adjacent to each of the edges (303, 305) is the core gap (211) or the spacer gap (212) is determined. Furthermore, the waveform profile of the spacer (207) is previously stored, the secondary electron profile of the sample (201) is acquired, a matching degree of the secondary electron profile and the stored waveform profile at the position of each spacer (207) is detected, and based on the detected matching degree, whether the each gap adjacent to each spacer (207) is the core gap (211) or the spacer gap (212) is determined.