Charged Particle Beam Scanning for Image Quality and Sample Protection
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Solution Overview
Problem
Existing charged particle beam microscopes face challenges in optimizing scanning parameters to balance image quality and acquisition time without damaging sensitive samples, particularly in time-intensive workflows, due to the difficulty in determining optimal dwell times and integration modes for various sample types.
Innovation Solution
A method for constructing a Charged Particle Beam microscope operational-settings prediction model that automatically selects scanning parameters by modeling the impact of parameters on image quality and acquisition time, using machine learning or explicit formulation, to optimize dwell time, integration mode, and other settings based on sample class.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed dwell times are used per area on a sample, then a usable signal above background noise is recorded, but the sample is damaged due to extended exposure time
Solution Approach 1:
The patent implements dynamic adjustment of dwell time based on real-time signal quality assessment. Instead of using fixed dwell times, the system continuously evaluates the signal-to-noise ratio and adapts the dwell time for subsequent pixels, allowing minimal exposure while maintaining acceptable image quality and reducing sample damage
Solution Approach 2:
The system changes the dwell time parameter dynamically during the scanning process. By monitoring signal quality metrics and adjusting the dwell time parameter in real-time, the system optimizes the balance between acquiring sufficient signal and minimizing cumulative beam exposure that causes sample damage
2Measurement precision
If extended dwell time is used to achieve desired signal magnitude, then measurement precision is improved, but analysis time is increased unnecessarily
Solution Approach 1:
The system incorporates feedback mechanisms where the signal quality from previously scanned pixels is used to determine the optimal dwell time for subsequent pixels. This feedback loop allows the system to achieve the desired signal magnitude efficiently by avoiding unnecessarily long dwell times while maintaining measurement precision
Solution Approach 2:
The patent applies partial action by using just sufficient dwell time to achieve acceptable signal quality rather than uniformly using excessive dwell times across all pixels. This approach achieves the necessary signal magnitude without the time penalty of over-exposure
3Ease of operation
If conventional fixed scanning parameters are used, then operation is simplified, but image quality varies for different sample types
Solution Approach 1:
The system performs self-service by automatically selecting and adjusting scanning parameters based on the specific sample being analyzed. The automated parameter selection eliminates the need for users to manually optimize settings for different sample types, maintaining ease of operation while ensuring optimal image quality through adaptive parameter adjustment
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 allows for the efficient acquisition of high-quality data while minimizing sample damage and reducing analysis time, by dynamically adjusting scanning parameters to achieve desired image quality metrics and preservation of the sample.
Implementation Method 1
Backscattered electrons (BSE) originate from the primary electron beam, which, as the name suggests, are scattered back (e.g., out of the sample) via elastic scattering upon interaction with the sample atoms
Data Source
AI summary
A method for constructing an operational-settings prediction model, comprises: (I) setting one or more microscope operational parameters to respective initial values; (II) directing a charged particle beam onto a location of a specimen of a known sample class and imaging or analyzing the location using the most recently set microscope operational parameters while detecting emissions from the specimen; (III) repeatedly: (i) changing a value of at least one of the one or more operational parameters; (ii) directing the charged particle beam onto the location and imaging or analyzing the location using the most recently set microscope operational parameters while detecting emissions from the location; and (iii) recording the values of the microscope operational parameters and recording a value that is a measure of the detected emissions from the location; and (IV) constructing and storing a mathematical relationship, pertaining to the known sample class, between at least one variable that represents a microscope operational parameter and a variable that represents the detected emissions.