Microscope Stage Settling Feedback for Drift-Based Throughput Control
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Solution Overview
Problem
Charged particle microscopy systems face throughput limitations due to the need for extensive settling time after sample movement, which increases overhead and requires significant operator expertise, especially in applications requiring multiple stage movements for high-resolution imaging.
Innovation Solution
Implementing a computer-implemented method to estimate and dynamically adjust the stage settling wait duration based on image sequence analysis, using artificial neural networks to account for various inputs such as image drift, stage dynamics, and environmental factors, thereby optimizing settling time for each location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a fixed, extended stage settling wait duration is used to ensure image stability, then image quality is improved, but system throughput decreases due to unnecessary delays
Solution Approach 1:
The patent implements dynamic adjustment of the stage settling wait duration based on real-time drift measurements. Instead of using a fixed, conservative settling time, the system continuously monitors stage position and adaptively determines the minimum required settling time, allowing the wait duration to vary between 0 and several seconds based on actual stage behavior. This resolves the contradiction by eliminating unnecessary delays while maintaining image quality.
Solution Approach 2:
The system employs feedback control by measuring actual stage drift using image sequences and using this information to adjust the settling wait duration. The drift measurement feedback loop allows the system to determine when the stage has settled sufficiently, rather than waiting for a predetermined time. This feedback mechanism ensures image quality is maintained while minimizing throughput impact.
2Reliability
If a conservative stage settling time is used to account for variable drift conditions, then reliability of image stability is improved, but loss of time increases due to extended waiting periods
Solution Approach 1:
The system uses real-time drift measurement feedback to determine when settling is complete, rather than relying on conservative predetermined times. By continuously monitoring stage position through image sequences and comparing against stability thresholds, the system reliably determines the actual settling completion point, eliminating unnecessary waiting time while maintaining image stability requirements.
Solution Approach 2:
The system performs self-adjustment of settling time based on its own drift measurements. The automated drift detection and settling time determination allows the system to serve itself by eliminating the need for operator intervention or conservative fixed-time settings, adapting the settling duration to actual conditions rather than pre-programmed assumptions.
3Productivity
If automated drift-based settling time adjustment is implemented, then productivity increases by reducing unnecessary delays, but device complexity increases due to additional control algorithms
Solution Approach 1:
The system uses existing imaging data for drift measurement rather than requiring separate measurement systems. By analyzing the same image sequences used for scientific purposes, the system performs self-characterization of stage behavior, avoiding additional hardware complexity while enabling automated settling time optimization that improves productivity.
Solution Approach 2:
The drift measurement and analysis system serves multiple functions: it characterizes stage behavior for settling time optimization, provides quality control for acquired images, and enables adaptive adjustment of imaging parameters. This multi-functionality reduces the need for separate dedicated systems, limiting the increase in device complexity while maximizing productivity benefits.
4Manufacturing precision
If extended settling time is used to ensure stable imaging at multiple locations, then manufacturing precision is maintained, but loss of time accumulates across multiple stage movements
Solution Approach 1:
The system dynamically adjusts settling time at each stage location based on actual drift measurements rather than using a uniform fixed time. By adapting the settling duration to the specific behavior observed at each location, the system maintains imaging precision requirements while minimizing the cumulative time penalty across multiple movements, as shorter settling times are used when drift is minimal.
Data Source
AI summary
Computer-implemented methods for controlling a charged particle microscopy system include estimating a drift of a stage of the charged particle microscopy system based on an image sequence, and automatically adjusting a stage settling wait duration based on the drift estimate. Charged particle microscopy systems include an imaging system, a movement stage, and a processor and memory configured with computer-executable instructions that, when executed, cause the processor to estimate a stage settling duration of the movement stage based on an image sequence obtained with the imaging system, and automatically adjust a stage settling wait duration for the movement stage based on the stage settling duration.