Acoustic Scanning Probe Microscopy Subsurface Feature Dimensioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing acoustic scanning probe microscopy methods face challenges in accurately determining the dimensions of subsurface features due to noise and artefacts, particularly for features buried deeply within samples.
Innovation Solution
A method utilizing a scanning probe microscopy system that applies an acoustic input signal and senses the acoustic output signal using a probe with a cantilever and probe tip. The method involves obtaining measurement values of the acoustic output signal, constructing a location-dependent subsurface topography signal, and using a MUSIC algorithm to generate an autocorrelation matrix and perform Eigenvalue decomposition to estimate spatial periodicity, thereby improving the accuracy of dimension determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If acoustic scattering methods are used to detect deeply buried subsurface features, then detection capability is improved, but measurement precision deteriorates due to noise and artefacts
Solution Approach 1:
The patent applies preliminary signal processing actions (Fourier transform, bandpass filtering, autocorrelation) to the acoustic output signal before dimension determination. These preprocessing steps enhance the signal quality and reduce noise/artifact interference in advance, enabling accurate dimension measurement of deeply buried features that would otherwise be undetectable or imprecise
Solution Approach 2:
The patent introduces intermediate processing steps (autocorrelation function, spectral analysis) as mediators between the raw acoustic signal and the final dimension measurement. These intermediaries extract meaningful periodicity information from noisy signals, bridging the gap between detection capability and measurement precision
2Measurement precision
If signal processing complexity is increased to improve dimension determination accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the signal processing into distinct modular steps: (1) Fourier transform to frequency domain, (2) bandpass filtering to isolate relevant frequencies, (3) inverse Fourier transform to time domain, (4) autocorrelation to extract periodicity. This segmentation makes the complex processing manageable and implementable while achieving high measurement precision
Solution Approach 2:
The patent replaces complex mechanical/direct measurement approaches with signal processing-based methods. Instead of physically resolving fine dimensional details directly, the system uses acoustic scattering combined with spectral analysis and autocorrelation to indirectly determine dimensions, reducing the need for mechanically complex high-resolution measurement systems
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 method enhances the accuracy of determining dimensions of subsurface features by exploiting periodicity in subsurface topographies, even in the presence of noise or artefacts, which is particularly beneficial in applications like semiconductor manufacturing.
Implementation Method 1
applying, using a transducer, an acoustic input signal to the sample; sensing in a plurality of locations on a surface of the sample an acoustic output signal representative of acoustic waves responsive to the acoustic input signal
Implementation Method 2
high frequency acoustic SPM operates at signal typically above 500 MHz and above up to e.g. 100 gigahertz (GHz) and is based on the principle of scattering of these signals at features buried within the sample
Implementation Method 3
sensing in a plurality of locations on a surface of the sample an acoustic output signal using a probe, the probe including a cantilever and a probe tip
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present document relates to a method to determine dimensions of features of a subsurface topography of a sample, the features having a spatial periodicity. The subsurface topography is obtained using scanning probe microscopy. The method includes obtaining measurement values of an acoustic output signal in at least N locations and generating a location dependent subsurface topography signal. The method further comprises providing an autocorrelation matrix by performing a cross-correlation of the subsurface topography signal in respect of each further location to yield the autocorrelation matrix having size N*N. Thereafter, the method includes performing an Eigenvalue decomposition for obtaining Eigenvalues of the matrix, and selecting a subset of Eigenvalues having the largest values. From these a frequency estimation function is constructed and at least one output value indicative of the spatial periodicity is obtained therefrom. The document also describes a scanning probe microscopy system and a computer program product.