High Fidelity Stochastic Electrode Microstructure Generation for Low Temperature Electrochemical Systems
Abstract
This work presents a MATLAB-based tool for stochastically generating realistic artificial catalyst layer microstructures, focusing on proton exchange membrane (PEM) water electrolyzer anodes as a case study. Our approach integrates multimodal experimental data to create 3D microstructures that reflect real-world electrodes. The microstructure generation algorithm can be used to investigate parameters like inter-particle connections, particle size distributions, ionomer coverage, and particle shapes. Our numerical method can be used to supplement insights from X-ray computed tomography, which has limited efficacy for low temperature polymer electrolyte systems as the X-ray beam is destructive to the ionomer phase. Physics based simulations were performed on the generated microstructures to study the impact of structural parameters on voltage, local electrochemical reaction rates, and ion fluxes. We also generated novel structures with gradient properties that significantly improved simulated performance. The results highlight the critical role of inter-particle connections in determining the connectivity and conductivity of the catalyst layer, which in turn directly influences the electrochemical performance. This approach provides a scalable platform for catalyst layer engineering to enhance the performance and durability of electrochemical systems.
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BibTeX
@misc{jayapragasam2026high,
title = {{High Fidelity Stochastic Electrode Microstructure Generation for Low Temperature Electrochemical Systems}},
author = {Puvikkarasan Jayapragasam and Gabriel Wosiak and Nilesh Sawant and Xin He and Serafina Fortiner and James Young and Makenzie Parimuha and Nancy N Kariuki and Jae Hyung Park and Haoran Yu},
howpublished = {ECSarXiv},
year = {2026},
month = sep,
doi = {10.1149/osf.io/964uk_v1},
url = {https://osf.io/preprints/ecsarxiv/964uk_v1/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - High Fidelity Stochastic Electrode Microstructure Generation for Low Temperature Electrochemical Systems
AU - Puvikkarasan Jayapragasam
AU - Gabriel Wosiak
AU - Nilesh Sawant
AU - Xin He
AU - Serafina Fortiner
AU - James Young
AU - Makenzie Parimuha
AU - Nancy N Kariuki
AU - Jae Hyung Park
AU - Haoran Yu
PY - 2026
DA - 2026/09/13
PB - ECSarXiv
DO - 10.1149/osf.io/964uk_v1
UR - https://osf.io/preprints/ecsarxiv/964uk_v1/
AB - This work presents a MATLAB-based tool for stochastically generating realistic artificial catalyst layer microstructures, focusing on proton exchange membrane (PEM) water electrolyzer anodes as a case study. Our approach integrates multimodal experimental data to create 3D microstructures that reflect real-world electrodes. The microstructure generation algorithm can be used to investigate parameters like inter-particle connections, particle size distributions, ionomer coverage, and particle shapes. Our numerical method can be used to supplement insights from X-ray computed tomography, which has limited efficacy for low temperature polymer electrolyte systems as the X-ray beam is destructive to the ionomer phase. Physics based simulations were performed on the generated microstructures to study the impact of structural parameters on voltage, local electrochemical reaction rates, and ion fluxes. We also generated novel structures with gradient properties that significantly improved simulated performance. The results highlight the critical role of inter-particle connections in determining the connectivity and conductivity of the catalyst layer, which in turn directly influences the electrochemical performance. This approach provides a scalable platform for catalyst layer engineering to enhance the performance and durability of electrochemical systems.
ER -