Tomography-Assisted TEM Lamella Preparation Automation
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Solution Overview
Problem
The existing methods for automating the charged particle beam sample lamella preparation process are inefficient and labor-intensive, particularly in achieving ultra-thin samples for TEM examination, due to the difficulty in accurately determining the endpointing process, which requires skilled operators and multiple iterations, and often necessitates separate TEM device scans.
Innovation Solution
The implementation of a dual-beam SEM/FIB system with tomography-assisted automation workflow, utilizing 'skinny tomography' and limited choice intervention menus, to minimize operator intervention and automate the endpointing process by identifying feature positions and depths through STEM projections, allowing for precise milling and reducing the need for high-resolution data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual endpointing observation is performed by operators, then the feature exposure can be determined, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual operator observation and decision-making with an automated system using STEM imaging and image analysis algorithms. The automated endpointing system captures STEM images during FIB milling, processes them through image analysis to detect feature exposure, and automatically controls the milling process, eliminating the need for manual intervention and significantly reducing endpointing time while maintaining or improving accuracy.
Solution Approach 2:
The system enables self-service automation where the endpointing process performs its own monitoring and decision-making. The automated endpointing system independently captures images, analyzes feature exposure status, determines when the endpoint is reached, and controls the milling process without requiring external operator intervention, making the process autonomous and efficient.
2Measurement precision
If high-resolution TEM scans are performed to determine endpointing, then accurate feature positioning is achieved, but the process requires separate device scans and increases complexity
Solution Approach 1:
The patent merges the endpointing monitoring function with the FIB milling process by integrating STEM imaging capability into the dual-beam system. Instead of performing separate TEM scans to determine endpointing, the system simultaneously performs FIB milling and STEM imaging, allowing real-time monitoring of feature exposure during the milling process itself, thereby eliminating separate scanning steps and reducing overall process complexity.
Solution Approach 2:
The patent introduces STEM imaging as an intermediary method between FIB milling and final TEM analysis. STEM images serve as a real-time proxy for monitoring feature exposure and determining endpointing, providing sufficient resolution to detect feature appearance without requiring repeated high-resolution TEM scans, thus simplifying the overall workflow.
3Manufacturing precision
If multiple iterations of thinning are performed, then the desired lamella thickness is achieved, but sample handling and re-alignment are required frequently
Solution Approach 1:
The patent implements real-time feedback control in the thinning process. The automated endpointing system continuously monitors STEM images during FIB milling, provides immediate feedback on feature exposure status, and automatically adjusts the milling process. This closed-loop feedback enables precise control of lamella thickness and feature positioning in a single continuous operation, eliminating the need for multiple iterations with sample handling and re-alignment.
Solution Approach 2:
The patent enables continuous FIB milling with real-time STEM monitoring without interruption for sample handling. The automated system maintains continuous milling action while continuously capturing and analyzing STEM images, allowing the thinning process to proceed in a single uninterrupted sequence rather than requiring multiple discrete steps with sample removal and re-mounting, thereby significantly improving productivity.
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 significantly reduces the time and skill required for endpointing, increases productivity by minimizing sample handling and re-alignment, and enables the preparation of ultra-thin lamellae with the feature of interest accurately positioned, ready for high-resolution TEM analysis.
Implementation Method 1
capturing STEM projections of the workpiece lamella at a plurality of tilt angles
Implementation Method 2
The FIB mill is configured to mill the workpiece lamella
Data Source
AI summary
Provided is a process for lamella thinning and endpointing that substitutes a series of automated small angle tilts for the motions in the conventional endpointing sequence. STEM images or through-surface BSE scans are acquired at each tilt. The results are analyzed automatically to determine feature depths, and an intervention request is made requesting a user decision based on marked-up images and summary information displayed.