Electron Microscope ROI Tracking With Automated Drift Correction
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Solution Overview
Problem
Current electron microscopy systems face challenges in accurately tracking and correcting for sample drift during in-situ studies, particularly when dynamic changes are applied to the sample, as existing automation methods are insufficient for large movements within the field of view.
Innovation Solution
A control system configured with a processor, memory, and microscope control components that registers movement associated with a region of interest within an electron microscope's field of view, allowing for dynamic centering and focusing adjustments, and applies in-situ stimuli to correct for drift, including X, Y, Z translations, and tilts, while tracking electron dose and dose rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital field of view shifting is used to correct for small sample movements, then image sharpness is improved, but the system cannot handle large sample movements that occur during in-situ studies
Solution Approach 1:
The system dynamically switches between digital field of view shifting for small movements and automated stage positioning for large movements. The control system continuously monitors sample position and adapts the correction method based on the magnitude of drift, enabling the system to handle both small and large sample movements effectively during in-situ studies
Solution Approach 2:
An automated stage positioning system acts as an intermediary between the sample and the detector, physically adjusting the sample position to compensate for large drift movements. This intermediary mechanism bridges the gap between the limited digital correction capability and the large-scale positional changes occurring during dynamic in-situ experiments
2Measurement precision
If manual tracking of region of interest is performed, then measurement accuracy is maintained, but time consumption and operator workload increase significantly
Solution Approach 1:
The system implements self-service automated tracking where the control software automatically identifies, tracks, and adjusts the position of the region of interest without operator intervention. The system uses image processing algorithms to autonomously locate features of interest and coordinates stage movements to maintain them in the field of view, eliminating manual tracking while preserving measurement accuracy
Solution Approach 2:
The system employs continuous feedback loops where the detected position of the region of interest is constantly monitored and fed back to the stage positioning system. This real-time feedback enables automatic correction of positional drift, maintaining tracking accuracy while reducing operator workload and time consumption
3Measurement precision
If higher electron dose rate is applied to improve image quality, then imaging resolution is enhanced, but beam damage to the sample increases
Solution Approach 1:
The system uses periodic imaging with optimized exposure timing, capturing images at strategically selected moments when the sample is relatively stable. By combining fewer, optimally-timed exposures with automated drift correction, the system achieves high-resolution imaging while minimizing cumulative electron dose and reducing beam damage to the sample
Data Source
AI summary
Methods and systems for calibrating a transmission electron microscope are disclosed. A fiducial mark on the sample holder is used to identify known reference points so that a current collection area and a through-hole on the sample holder can be located. A plurality of beam current and beam area measurements are taken, and calibration tables are extrapolated from the measurements for a full range of microscope parameters. The calibration tables are then used to determine electron dose of a sample during an experiment at a given configuration.