Charged Particle Microscope Automatic Focusing via Sharpness Measure
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Solution Overview
Problem
Charged particle microscopes face difficulties in achieving optimal focusing of the charged particle beam due to the complex non-linear relationship between focusing lens excitations and x-y stigmator settings, requiring extensive trial and error for experienced users to obtain a satisfying focus.
Innovation Solution
An automatic focusing method for charged particle microscopes that iteratively adjusts settings based on a sharpness measure determined by analyzing intensity gradients or image properties in recorded images, using optimization methods like the downhill simplex method to maximize the sharpness measure, which is represented by image properties such as orientation and intensity gradients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual trial and error method is used to adjust focus and stigmator settings, then experienced users can obtain satisfying focusing, but it requires significant amount of time and iterative adjustments
Solution Approach 1:
The patent implements an automatic feedback mechanism where the sharpness measure is calculated from recorded images and fed back to the control unit. The control unit uses this feedback to automatically adjust focus and stigmator settings without requiring manual trial and error, thus resolving the contradiction between achieving precise focusing and reducing adjustment time.
Solution Approach 2:
The system performs self-adjustment by automatically calculating the sharpness measure and modifying its own settings based on this measure. The charged particle microscope system serves itself by autonomously optimizing focus and stigmator parameters without external human intervention, eliminating the time-consuming manual adjustment process while maintaining high focusing quality.
2Measurement precision
If the size of beam spot is used as the criterion for focusing, then the focusing quality can be evaluated, but the complex non-linear function relationship makes it difficult to find optimum settings
Solution Approach 1:
The patent changes the evaluation parameter from beam spot size to sharpness measure derived from image content analysis. This parameter transformation simplifies the optimization problem by providing a more direct and intuitive criterion that correlates with image quality, making the complex non-linear relationship more manageable through automated image-based assessment rather than manual beam spot measurement.
Solution Approach 2:
The patent replaces manual mechanical adjustment of focus and stigmator settings with an automated computer-controlled system. The control unit automatically modifies the settings based on sharpness measure calculations, substituting the manual mechanical adjustment process with an automated electronic control system that handles the complexity of the non-linear relationships.
3Productivity
If automatic focusing method is implemented using sharpness measure, then time and effort for focusing is significantly reduced, but requires iterative adjustments until stop criterion is met
Solution Approach 1:
The automatic focusing system uses continuous feedback from sharpness measure calculations to guide iterative adjustments. The control unit monitors the sharpness measure after each adjustment cycle and automatically terminates the process when a stop criterion is satisfied, providing an automated feedback-controlled system that achieves fast focusing while managing complexity through algorithmic decision-making.
Data Source
AI summary
A method of operating a charged particle microscope comprises: providing settings of a focus, an x-stigmator and an y-stigmator of the charged particle microscope; and then repeatedly performing adjusting the charged particle microscope to the settings, recording an image of an object using the settings, determining a sharpness measure from the recorded image, and changing at least one of the settings of the focus, the x-stigmator and the y-stigmator based on the sharpness measure until a stop criterion is fulfilled. Herein, the determining of the sharpness measure comprises: determining an orientation of an intensity gradient at each of a plurality of locations within one of the recorded image and a processed image generated by processing the recorded image, and determining the sharpness measure based on the plurality of determined orientations.