Multiple Image Metrology for Sub-Nanometer Precision
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In microfabrication processes, determining geometric relationships between features composed of different elements is challenging due to varying contrast levels in images, making it difficult to accurately measure dimensions using single images that do not adequately show all elements.
Innovation Solution
A method involving the combination of multiple images from charged particle beam systems, such as SEM, FIB microscopy, or STEM, to perform automated metrology measurements by registering and using software tools to locate and measure features across different elemental maps, even when elements have insufficient contrast in individual images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images from different charged particle beam systems are used to measure features composed of different elements, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple images from different charged particle beam systems (SEM, FIB, STEM) to create a comprehensive view of features composed of different elements. By merging information from multiple imaging modalities, the system achieves accurate measurement of spatial relationships between features that would be invisible or indistinct in any single image, thus resolving the technical contradiction between measurement precision and device complexity.
Solution Approach 2:
The patent employs an image registration and processing system that acts as an intermediary to align and integrate images from different charged particle beam systems. This intermediary processing enables the combination of multi-source image data to improve measurement precision while managing the complexity through automated registration algorithms that correlate features across different imaging modalities.
2Loss of information
If multiple images are combined to perform metrology measurements, then information completeness is improved, but processing complexity increases
Solution Approach 1:
The patent merges multiple images from different charged particle beam systems to create a comprehensive dataset that contains complete information about features composed of different elements. By combining the informational content of multiple images through registration and integration, the system recovers information that would be lost or insufficient in any single image, addressing the information completeness challenge.
Solution Approach 2:
The patent adds the dimension of multi-modal image integration by combining data from different charged particle beam systems (secondary electron imaging, backscattered electron imaging, energy-dispersive x-ray spectroscopy). This dimensional expansion in the data space allows complete characterization of features that cannot be achieved in a single imaging dimension, while automated processing manages the complexity.
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 measurement of spatial relationships and dimensions with sub-nanometer precision by leveraging multiple images to combine information and enhance visibility of features across different elemental maps.
Implementation Method 1
directing a charged particle beam toward a work piece; detecting first emissions from the work piece in response to the charged particle beam
Implementation Method 2
energy dispersive x-ray spectroscopy (EDS or EDX), which can be used for elemental analysis or chemical characterization of a sample. In EDX, an electron beam is directed toward a sample and the energies of x-rays coming from the sample in response to the electron beam are measured
Implementation Method 3
electron energy loss spectroscopy (EELS) and high-angle annular dark-field imaging (HAADF). EELS measures the energy absorbed as electrons pass through the sample. Different materials in the sample cause electrons to lose different amount of energy as they pass through
Implementation Method 4
HAADF is a method of mapping samples in a scanning transmission electron microscope (STEM). The images are formed by collecting only high angle scattered electrons using an annular dark-field detector and is sensitive to variations in the atomic number of atoms in a sample
Data Source
AI summary
Metrology is performed using multiple registered images derived from one or more charged particle beams. Measurements combine features from one image that may not be visible in a second image to determine relationships that cannot be determined from a single image. In one embodiment, measurements use features from different element maps to determine a relationship between features, such as a distance or angle between two features in the first image at a location determined by a distance from a feature on the second image.