Porous Structure Pore Distribution Analysis Using Voronoi Diagrams
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Solution Overview
Problem
Existing methods for analyzing pore distribution in porous structures, such as those used in lithium secondary battery separators, are qualitative and lack quantitative accuracy, particularly due to variations in pore size and distribution.
Innovation Solution
An analysis method using scanning electron microscopy (SEM) combined with a Voronoi diagram to quantify pore distribution by converting SEM images to binary images and applying a Voronoi diagram algorithm to calculate pore areas and locations, allowing for accurate pore size and location analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If qualitative evaluation methods involving observing a microscopic image with the naked eye are used, then the observation process is simple, but quantitative criteria cannot be deduced and measurement precision is insufficient
Solution Approach 1:
The patent replaces the manual qualitative observation method with an automated image processing system that uses algorithms to quantitatively analyze pore distribution. The system converts microscopic images into binary images and applies computational algorithms to calculate pore area ratios and distribution characteristics, eliminating the need for subjective human observation while providing precise quantitative data.
2Measurement precision
If the Euclidean distance algorithm is used to quantify pore distribution in SEM images, then pore distance can be measured, but the distance between pores is affected by pore size and results are inaccurate
Solution Approach 1:
The patent extracts the pore regions from the microscopic images by converting them into binary images, separating the pore areas from the surrounding structure. This extraction allows for independent analysis of pore distribution without the interference of pore size variations, enabling accurate calculation of pore area ratios and spatial distribution characteristics.
Solution Approach 2:
The patent changes the measurement parameter from Euclidean distance between pore centers to pore area ratio and spatial distribution metrics. By using the ratio of pore area to total image area and analyzing the distribution pattern of pore regions in binary images, the method provides accurate pore distribution characterization that is independent of individual pore size variations.
3Productivity
If population distribution is measured in a single image, then the measurement process is quick, but the results are inaccurate and pore distribution appears non-uniform
Solution Approach 1:
The patent divides the single image into multiple sub-regions or grids and calculates pore area ratios for each sub-region independently. This segmentation allows for local analysis of pore distribution uniformity while maintaining the efficiency of single-image processing. The method can identify whether pores are uniformly distributed across different regions of the membrane without requiring multiple images.
Data Source
AI summary
A method of analyzing the pore distribution of porous structures includes observing a cross-section of a porous structure using scanning electron microscopy (SEM) to obtain a raw image of the cross-section of the porous structure and quantifying a pore distribution of the obtained raw image through Voronoi diagram.