Charged-Particle Microscope Sub-Surface Imaging via Vector Field Deconvolution
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Solution Overview
Problem
Current sub-surface imaging techniques in charged-particle microscopy, such as HAADF-STEM tomography, face limitations in depth resolution and interference between sub-sources due to non-linear imaging models and loss of phase information, which restricts the ability to effectively deconvolve and separate contributions from different layers within a specimen.
Innovation Solution
The method employs integrated vector field (iVF) imaging with a variable beam parameter of focus position, using a segmented detector to produce vector outputs that are mathematically processed through two-dimensional integration and Source Separation techniques like Principal Component Analysis (PCA) to achieve depth-resolved imagery, allowing for linear treatment and minimal interference between sub-sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HAADF-STEM tomography is used for sub-surface imaging, then imaging capability is achieved, but depth resolution is limited due to non-linear imaging models and interference between sub-sources
Solution Approach 1:
The patent replaces the non-linear mechanical/optical imaging model of HAADF-STEM with a linear imaging model using integrated vector field (iVF) imaging. This substitution allows the use of linear deconvolution algorithms instead of complex non-linear reconstruction algorithms, improving depth resolution while reducing computational complexity. The linear model enables direct mathematical separation of signals from different depths without iterative non-linear optimization.
Solution Approach 2:
The patent changes the imaging parameter from intensity-based detection to vector field-based detection. By measuring the vector field (direction and magnitude of particle flow) instead of just intensity, the system obtains phase information that enables linear deconvolution and improves depth resolution. This parameter change transforms the imaging model from non-linear to linear, allowing effective separation of sub-sources at different depths.
2Loss of information
If conventional tomography methods are used, then imaging is performed, but phase information is lost leading to interference between sub-sources
Solution Approach 1:
The patent substitutes conventional intensity-based detection with vector field detection that preserves phase information. The segmented detector measures both magnitude and direction of transmitted particles, creating a vector field that encodes phase information. This substitution enables linear deconvolution algorithms to effectively separate contributions from different depths without the interference that plagues conventional methods.
Solution Approach 2:
The patent introduces the vector field as an intermediary between the specimen and the final image. Instead of directly detecting intensity, the system detects the vector field (which preserves phase information) and then processes it through linear deconvolution. This intermediary enables the preservation of phase information while facilitating effective separation of sub-sources through mathematical processing.
3Measurement precision
If focus position is varied for depth resolution, then multiple images are acquired, but non-linear processing is required increasing complexity
Solution Approach 1:
The patent replaces non-linear processing of focus-series images with linear processing by using vector field detection. When the beam focus is varied and vector field images are acquired at each focus position, the linear imaging model allows direct mathematical deconvolution to separate depth information. This substitution eliminates the need for complex non-linear reconstruction algorithms while maintaining depth resolution capability.
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 enables high-depth resolution imaging by effectively separating contributions from different layers within the specimen, preserving phase information and maintaining lateral resolution, thereby improving the accuracy of sub-surface imaging compared to conventional methods.
Implementation Method 1
Providing a beam of charged particles that is directed from a source along a particle-optical axis through an illuminator so as to irradiate the specimen; Providing a detector for detecting a flux of charged particles traversing the specimen
Data Source
AI summary
A method of performing sub-surface imaging of a specimen in a charged-particle microscope of a scanning transmission type, comprising the following steps:Providing a beam of charged particles that is directed from a source along a particle-optical axis through an illuminator so as to irradiate the specimen;Providing a detector for detecting a flux of charged particles traversing the specimen;Causing said beam to follow a scan path across a surface of said specimen, and recording an output of said detector as a function of scan position, thereby acquiring a scanned charged-particle image I of the specimen;Repeating this procedure for different members n of an integer sequence, by choosing a value Pn of a variable beam parameter P and acquiring an associated scanned image In, thereby compiling a measurement set M={(In, Pn)};Using computer processing apparatus to automatically deconvolve the measurement set M and spatially resolve it into a result set representing depth-resolved imagery of the specimen,wherein:Said variable beam parameter P is focus position along said particle-optical axis;Said scanned image I is an integrated vector field image, obtained by;Embodying said detector to comprise a plurality of detection segments;Combining signals from different detection segments so as to produce a vector output from the detector at each scan position, and compiling this data to yield a vector field;Mathematically processing said vector field by subjecting it to a two-dimensional integration operation.