Charged-particle beam defect depth estimation
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Solution Overview
Problem
Existing methods for inspecting and measuring defects in semiconductor samples, such as voids, using charged-particle beams do not effectively estimate the size of defects in the depth direction.
Innovation Solution
A charged-particle beam device determines the brightness ratio at different irradiation positions and uses this information to estimate the position and size of defects in the depth direction by analyzing the energy of backscattered electrons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple brightness images are obtained by changing irradiation energy to detect defects, then defect detection capability is improved, but the ability to estimate defect size in depth direction remains insufficient
Solution Approach 1:
The patent changes the energy parameter of the charged particle beam to obtain multiple brightness images at different penetration depths. By analyzing how brightness values change with energy, the system can estimate both the presence and depth position of defects. This parameter variation approach transforms a single-energy detection limitation into a multi-depth detection capability.
Solution Approach 2:
The patent adds the energy dimension to the traditional two-dimensional image detection. By incorporating energy as a third dimension for data acquisition, the system can estimate the depth position of defects, effectively transforming 2D surface imaging into 3D defect characterization without requiring physical sectioning of the sample.
2Reliability
If conventional inspection methods are used to detect voids and foreign substances, then defect presence can be determined, but cross-sectional shape measurement requires sample destruction
Solution Approach 1:
The patent uses the charged particle beam to perform both defect detection and cross-sectional shape measurement on the intact sample. The beam's penetration and scattering characteristics provide information about both the presence of defects and the three-dimensional structure of patterns, eliminating the need for separate destructive sectioning procedures.
Solution Approach 2:
The inspection system performs multiple functions using a single measurement process: it detects voids, foreign substances, and simultaneously estimates the cross-sectional shape of patterns. This multi-functional approach uses the same charged particle beam data for both defect detection and structural characterization, avoiding the need for separate destructive analysis steps.
3Measurement precision
If higher sensitivity and accuracy are required for miniaturized patterns, then measurement precision is improved, but the complexity of analysis increases
Solution Approach 1:
The patent replaces complex physical sectioning and manual measurement methods with automated charged particle beam analysis. The system uses computational algorithms to automatically extract defect position, size, and shape information from brightness images, reducing manual intervention and simplifying the overall measurement process despite the high precision requirements.
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 accurate estimation of defect position and size in the depth direction from top-view images, simplifying the measurement of cross-sectional patterns without damaging the sample.
Implementation Method 1
generating a brightness image while changing the energy of an irradiation electron
Data Source
AI summary
The objective of the present invention is to use brightness images acquired under different energy conditions to estimate the size of a defect in the depth direction in a simple manner. A charged-particle beam device according to the present invention determines the brightness ratio for each irradiation position on a brightness image while changing parameters varying the signal amount, estimates the position of the defect in the depth direction on the basis of the parameters at which the brightness ratio is at a minimum, and estimates the size of the defect in the depth direction on the basis of the magnitude of the brightness ratio (see FIG. 5).