A Fully Differentiable Pore Network for Digital Reconstruction of Porous Media

Michael McKague; Mohammad Mehrnia; Mohammad A Sadeghi; JT Gostick

doi:10.1039/d5dd00455a

January 1, 2025Digital DiscoveryOpen Access

A Fully Differentiable Pore Network for Digital Reconstruction of Porous Media

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Key Points

The aim is to create a fully differentiable pore network model for studying transport processes in porous media.
Developed a differentiable model for pore network representation.
Applied the model to simulate transport in various porous materials.
Utilized computational techniques to facilitate accurate pore structure reconstruction.
Enhanced accuracy of transport process modeling in porous media.
Demonstrated the potential for better predictions in material behavior.
Provided a framework that supports efficient optimization of pore network structures.

Implication

Digital reconstruction of porous media improves transport modeling in porous materials, suggesting enhanced accuracy.

Abstract

Pore network models are useful for efficiently studying transport processes in porous materials at the pore scale. However, constructing accurate pore network representations is not always straight forward as it...

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Cite This Study

McKague et al. (2025) studied this question.

synapsesocial.com/papers/6997fa03ad1d9b11b3452e00 https://doi.org/10.1039/d5dd00455a

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A Fully Differentiable Pore Network for Digital Reconstruction of Porous Media

Key Points

Implication

Abstract

Discussion

Cite This Study

A Fully Differentiable Pore Network for Digital Reconstruction of Porous Media

Key Points

Implication

Abstract

Discussion

Cite This Study

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