Segmented STEM Imaging for Single-Scan 3D Thick Sample Reconstruction
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Solution Overview
Problem
Current scanning transmission charged-particle microscopes (STCPMs) face challenges in obtaining reliable 3D images of thick samples due to sample drift, alignment issues, and the need for multiple scans at different focus depths, which increases time and complexity.
Innovation Solution
The method involves using a segmented STEM detector and theoretical descriptions to construct a linear set of equations for each k-vector of the Fourier transform of segmented STEM images, allowing for the derivation of phase shifts induced by sample slices, enabling 3D reconstruction from a single scan without compensating for stage drift and providing deconvolution of information from different depths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple scans at different focus depths are performed to obtain 3D images of thick samples, then the depth resolution and 3D reconstruction quality are improved, but the measurement time and operational complexity increase
Solution Approach 1:
The detector is divided into multiple segments that can independently detect signals from different depth ranges. Each detector segment corresponds to a specific focus depth range, allowing simultaneous capture of information from multiple depths in a single scan, thereby resolving the contradiction between depth resolution and measurement time
Solution Approach 2:
The patent introduces a spectral dimension by assigning different energy windows to different detector segments. This allows the system to distinguish signals from different depths based on their energy characteristics, enabling 3D reconstruction from a single scan without requiring multiple focus depth adjustments
2Measurement precision
If multiple scans at different focus depths are performed for 3D reconstruction, then the 3D image quality is improved, but the alignment accuracy deteriorates due to sample drift
Solution Approach 1:
By segmenting the detector into multiple depth-sensitive regions, the system captures all depth information simultaneously in a single scan. This eliminates the temporal separation between measurements, preventing sample drift from affecting alignment accuracy while maintaining 3D reconstruction quality
Solution Approach 2:
The detector segments are pre-configured with specific energy windows and detection ranges before the scan. This preliminary setup ensures that each segment is optimized to detect signals from its corresponding depth range, allowing accurate 3D reconstruction without requiring post-scan alignment corrections for drift
3Measurement precision
If a segmented detector with multiple energy windows is used, then the depth sectioning capability is improved, but the device complexity increases
Solution Approach 1:
The detector is divided into multiple segments that can be implemented using standard detector technologies. Each segment is assigned a specific energy window, allowing depth sectioning without requiring fundamentally new detector components. This modular segmentation approach improves depth capability while managing device complexity through systematic design
Solution Approach 2:
The segmented detector serves multiple functions simultaneously: it detects signals from different depths, performs energy discrimination, and enables 3D reconstruction all within a single device. This multi-functionality reduces the need for separate specialized components, thereby managing overall device complexity while achieving superior depth sectioning capability
Data Source
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AI summary
A computer-implemented method of processing image data according to the present disclosure comprises: receiving the image data, wherein the image data is scanning transmission charged-particle microscope (STCPM) image data representing a STCPM scan obtained at a first focus depth; and processing a system of equations expressing the image data as a sum of contributions from a plurality of slices of the sample at a plurality of focus depths, wherein each equation of the system of equations relates at least a portion of the image data to: at least one of a plurality of contrast transfer functions of the STCPM, each contrast transfer function of the STCPM being determined at a different respective focus depth; and at least one set of unknown objects of the STCPM, each unknown object in a set being at a different respective focus depth. The step of processing comprises solving the system of equations to obtain at least one of the plurality of unknown objects of the STCPM.