Introduce covariance function in the characterization module

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#4 opened on Jun 4, 2021 0 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty: 5/5
Estimated time: Over a week
Newbie friendliness: 25/100

Issue type: Feature
Clarity: Needs clarification
Activity status: Stale
Tech stack: matlab
Domain: computer-vision

Research direction

Start by locating the characterization module and the existing calculations for specific surface area and particle mean diameter. Read the cited covariance-function paper and compare its method with the current direct calculations; done means the module exposes the covariance-based calculations and their results can be compared for suitable electrode volumes.

Written by the indexing model from the issue text.

Description

enhancement

Introduce the covariance function used for calculation of the specific surface area and the particle mean diameter as done in previous work https://iopscience.iop.org/article/10.1149/07711.1095ecst.

That's low priority although, and will likely be added when i will transition the characterization module to app designer.
Reason being I do not think calculating surface area from 3D imaging is a good idea due to the fractal behavior of the surface area (although still interesting to compare electrodes imaged at the same voxel size). Anyway, the difference between the direct method and the covariance function has been investigated in the work cited above for NMC electrodes and: "Sp(geometric covariogram) / Sp(direct method x2/3) ranges from 1.028 to 1.094 for the 16 volumes. It corresponds to a relative error (for the direct method) inferior to 9%."
The method is interesting to get particle diameter although, but the issue with this method is that it requires a large field of view to get a smooth two-point correlation function and get the asymptot.

Dominant language: MATLAB
Stars: 76
Forks: 27
PR merge metrics: No merged PRs in 30d

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