Charged-particle Microscope Depth-resolved Imaging via Energy Deconvolution
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Solution Overview
Problem
Existing charged-particle microscope methods struggle with depth-resolved imaging, requiring adjustments in landing energy and causing radiation damage, especially when dealing with inhomogeneous samples of unknown structure, and are limited by assumptions about the Point Spread Function (PSF).
Innovation Solution
A method involving a detector arrangement that records electron emissions as a function of kinetic energy, followed by computer processing to deconvolve and spatially resolve the data into depth-resolved images without adjusting the landing energy, using a mathematical framework that accounts for a general PSF and applies constraints to optimize the deconvolution process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If landing energy is adjusted to achieve depth-resolved imaging, then depth information can be obtained, but radiation damage increases and measurement time increases
Solution Approach 1:
The patent performs preliminary deconvolution processing on the entire dataset before reconstructing depth-resolved images. By calculating the Point Spread Function (PSF) once and applying it through deconvolution algorithms (such as Richardson-Lucy or Wiener deconvolution), the system extracts depth information from a single landing energy measurement, eliminating the need for multiple energy adjustments and thereby reducing cumulative radiation exposure to the sample.
Solution Approach 2:
The patent creates a computational model (PSF) that represents the relationship between landing energy and penetration depth. This model is then used to generate depth-resolved images through mathematical deconvolution, effectively creating a virtual copy of the depth structure without physically adjusting the beam energy multiple times on the actual sample, thus minimizing radiation damage.
2Measurement precision
If multiple landing energies are used to resolve depth information, then depth-resolved imagery is achieved, but measurement time increases
Solution Approach 1:
The patent replaces the mechanical approach of physically adjusting landing energy multiple times with a computational approach. A single landing energy measurement is taken, and then deconvolution algorithms process the data mathematically to extract depth information. This substitution of mechanical energy adjustment with computational processing dramatically reduces measurement time while maintaining depth resolution capability.
Solution Approach 2:
The PSF is calculated in advance based on known electron-sample interaction physics, allowing the deconvolution process to proceed efficiently without requiring multiple measurements. The preliminary establishment of the PSF model enables rapid computational extraction of depth information from a single measurement dataset.
3Device complexity
If assumptions about Point Spread Function are made to simplify processing, then computational complexity is reduced, but accuracy decreases for inhomogeneous samples
Solution Approach 1:
The patent allows the PSF parameters to vary based on local sample properties rather than assuming a fixed PSF throughout. By adapting the PSF calculation to account for changes in sample composition, density, and structure at different depths and locations, the system maintains computational tractability while significantly improving accuracy for inhomogeneous samples. This may involve adjusting PSF parameters iteratively or using depth-dependent PSF models.
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 depth-resolved imagery without adjusting the landing energy, reducing radiation damage and effectively handling inhomogeneous samples by converting convoluted data from different depths into spatially resolved results, providing detailed images of sample properties across various depth layers.
Implementation Method 1
Using a particle-optical column to direct at least one beam of particulate radiation onto a surface S of the sample, thereby producing an interaction that causes emitted radiation to emanate from the sample
Implementation Method 2
Embodiment of the detector arrangement to detect electrons in the emitted radiation
Data Source
AI summary
A method of examining a sample using a charged-particle microscope, comprising mounting the sample on a sample holder; using a particle-optical column to direct at least one beam of particulate radiation onto a surface S of the sample, thereby producing an interaction that causes emitted radiation to emanate from the sample; using a detector arrangement to detect at least a portion of said emitted radiation, the method of which comprises embodying the detector arrangement to detect electrons in the emitted radiation; recording an output On of said detector arrangement as a function of kinetic energy En of said electrons, thus compiling a measurement set M={(On, En)} for a plurality of values of En; using computer processing apparatus to automatically deconvolve the measurement set M and spatially resolve it into a result set R={(Vk, Lk)}, in which a spatial variable V demonstrates a value Vk at an associated discrete depth level Lk referenced to the surface S, whereby n and k are members of an integer sequence, and spatial variable V represents a physical property of the sample as a function of position in its bulk.