PorousGen: An Efficient Algorithm for Generating Porous Structures with Accurate Porosity and Uniform Density Distribution

TL;DR

PorousGen is a new algorithm that efficiently generates porous structures with accurate porosity and uniform density, outperforming existing tools like PoreSpy in precision and computational efficiency.

Contribution

The paper introduces PorousGen, a novel algorithm that accurately controls porosity and enhances computational efficiency for large-scale porous structure generation.

Findings

PorousGen closely matches target porosity within a small error margin.

Generated structures yield gas diffusion coefficients within 5% of experimental values.

PorousGen is faster and uses less memory than PoreSpy.

Abstract

This work presents a novel algorithm for generating porous structures as an alternative to the PoreSpy program suite. Unlike PoreSpy, which often produces structures whose porosity deviates from the target value, our proposed algorithm generates structures whose porosity closely matches the specified input, within a defined error margin. Furthermore, parallel computation enables efficient generation of large-scale structures, while memory usage is reduced compared to PoreSpy. To evaluate performance, structures were generated using both PoreSpy and the proposed method with parameters corresponding to X-ray ptychography experiments. The porosity mismatch in PoreSpy led to a relative error exceeding 20% in the computed gas diffusion coefficients, whereas our method reproduced the experimental values within 5%. These results demonstrate that the proposed method provides an efficient, high-precision approach for generating porous structures and supports reliable prediction of material properties. The program called PorousGen is publicly available under the MIT License from https://github.com/YoshidomeGroup-Hydration/PorousGen.