Fiber-Scale Discrete Element Modeling Approach for Microstructural Evolution in Carbon Felt Electrode Manufacturing
Abstract
Porous carbon components strongly influence transport, kinetics, and performance in electrochemical energy devices, like electrodes in redox flow batteries or gas diffusion layers in proton exchange membrane fuel cells. Yet quantitative links between industrial felt manufacturing and the resulting microstructure remain insufficiently understood. Recent studies have explored alternative bottom-up fabrication strategies to achieve greater microstructural control, while computational optimization often considers stochastic microstructures without accounting for manufacturability. Consequently, the extent to which conventional manufacturing processes can tailor microstructure remains unclear. Here, we develop a discrete element method framework that resolves fiber-scale interactions and microstructural evolution during mechanical processing of oxidized polyacrylonitrile precursor felts. The framework represents successive stages of fiber generation, web formation, web laying, needle punching, and calendering. At each stage, the evolving three-dimensional microstructure is resolved and quantified using fiber- and pore-scale descriptors, including pore-size distributions, fiber-orientation tensors, and transport-related properties. The simulations reveal process–structure–transport relationships, identifying key parameters governing pore-throat size, fiber reorientation, and effective diffusivity. These findings define the microstructural design space accessible through conventional felt manufacturing and provide a basis for future process optimization and integration with subsequent thermal-processing stages.
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BibTeX
@misc{sankar2026fiberscale,
title = {{Fiber-Scale Discrete Element Modeling Approach for Microstructural Evolution in Carbon Felt Electrode Manufacturing}},
author = {Arjun Sankar and Abhilash Valisammagari and Francisco Fernandez and Alejandro A. Franco},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15009145/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009145/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Fiber-Scale Discrete Element Modeling Approach for Microstructural Evolution in Carbon Felt Electrode Manufacturing
AU - Arjun Sankar
AU - Abhilash Valisammagari
AU - Francisco Fernandez
AU - Alejandro A. Franco
PY - 2026
DA - 2026/09/21
PB - ChemRxiv
DO - 10.26434/chemrxiv.15009145/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009145/v1
AB - Porous carbon components strongly influence transport, kinetics, and performance in electrochemical energy devices, like electrodes in redox flow batteries or gas diffusion layers in proton exchange membrane fuel cells. Yet quantitative links between industrial felt manufacturing and the resulting microstructure remain insufficiently understood. Recent studies have explored alternative bottom-up fabrication strategies to achieve greater microstructural control, while computational optimization often considers stochastic microstructures without accounting for manufacturability. Consequently, the extent to which conventional manufacturing processes can tailor microstructure remains unclear. Here, we develop a discrete element method framework that resolves fiber-scale interactions and microstructural evolution during mechanical processing of oxidized polyacrylonitrile precursor felts. The framework represents successive stages of fiber generation, web formation, web laying, needle punching, and calendering. At each stage, the evolving three-dimensional microstructure is resolved and quantified using fiber- and pore-scale descriptors, including pore-size distributions, fiber-orientation tensors, and transport-related properties. The simulations reveal process–structure–transport relationships, identifying key parameters governing pore-throat size, fiber reorientation, and effective diffusivity. These findings define the microstructural design space accessible through conventional felt manufacturing and provide a basis for future process optimization and integration with subsequent thermal-processing stages.
ER -