Charged Particle Microscope FOV Adjustment With Adaptive Sampling
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Solution Overview
Problem
Existing charged particle microscope techniques face challenges in minimizing sample damage while maintaining accurate field-of-view adjustment, as the initial selection of sampling cardinality is not adjustable, leading to potential over-sampling and increased damage.
Innovation Solution
The method involves setting reference data, defining regions of interest, and using a rough sampling coordinate group to generate pixel value groups, reconstructing images, estimating correspondence relationships among these regions, and adjusting them based on these relationships to minimize sample damage while maintaining field-of-view accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the sample is fully sampled by preliminary imaging, then the accuracy of field-of-view adjustment is maintained, but damage to the sample increases
Solution Approach 1:
The patent applies partial action by performing preliminary imaging only on a subset of sampling points rather than fully sampling the entire field-of-view. The controller selects specific sampling points based on reference data to capture sufficient information for field-of-view adjustment while minimizing the number of charged particle irradiations, thereby reducing sample damage while maintaining adjustment accuracy
Solution Approach 2:
The patent uses reference data obtained in advance to pre-determine optimal sampling points and regions of interest before actual preliminary imaging. This preliminary preparation allows the system to plan the minimal necessary sampling strategy, avoiding unnecessary irradiation of the sample while ensuring adequate information is collected for accurate field-of-view adjustment
2Object-affected harmful factors
If the cardinality N is reduced to minimize sample damage, then damage to the sample decreases, but it becomes difficult to set a necessary minimum cardinality since the cardinality N selected once is not adjusted
Solution Approach 1:
The patent implements dynamic adjustment of sampling cardinality by allowing the controller to modify the number and positions of sampling points based on feedback from reconstructed images. After initial sampling and reconstruction, the system can adaptively determine whether additional sampling is needed, making the sampling cardinality flexible rather than fixed, thus balancing sample damage reduction with maintenance of necessary sampling adequacy
Solution Approach 2:
The system employs feedback mechanisms where reconstructed images from preliminary imaging are evaluated to determine if the current sampling cardinality is sufficient for accurate field-of-view adjustment. Based on this feedback, the controller can adjust the sampling strategy for subsequent imaging, ensuring that the minimum necessary cardinality is maintained while minimizing unnecessary sampling that would increase sample damage
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
This approach effectively reduces sample damage while ensuring accurate field-of-view adjustment by optimizing the sampling process through the use of reference data and correspondence relationships among regions of interest.
Implementation Method 1
the sample is irradiated with charged particles based on the sampling coordinate group to obtain a corresponding pixel value group
Data Source
AI summary
Provided is a method for adjusting a field-of-view of a charged particle microscope device, in which reference data for a sample is set, a plurality of regions of interest are set for the reference data, a rough sampling coordinate group is set for each of the plurality of regions of interest, the sample is irradiated with charged particles based on the sampling coordinate group to obtain a corresponding pixel value group, a plurality of reconstructed images corresponding to the plurality of regions of interest are generated based on the pixel value group, a correspondence relationship among the plurality of regions of interest is estimated based on the plurality of reconstructed images, and the plurality of regions of interest are adjusted based on the correspondence relationship. Here, the sampling coordinate group is set based on the reference data.