A closer look at graphene electrodes

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Made up of a few very small, opaque components packed closely together, looking at all of the processes going on inside a battery is not an easy task for scientists, and difficulties in clearly observing and modeling some of these processes is still a major hurdle for research institutes.

Scientists at the University of Houston (UH) in the United States, working with funding from the U.S. Air Force Office of Scientific Research, looked into one method that’s commonly used in the computational modeling of battery electrodes, known as the porous media model, and noted several shortcomings that could lead to the inaccurate characterization of materials. Such models, argue the researchers, tend to assume uniformity in the material’s porous structure, and to overestimate ion diffusion properties.

“We wanted to convey that the conventional models out there, which are porous media-based models, may not be accurate enough for designing these new nano-architectured materials and investigating these materials for electrodes or other energy storage devices,” said UH Associate Professor Haleh Ardebili. “The porous media model may be convenient, but it is not necessarily accurate. For state-of-the-art devices, we need more accurate models to better understand and design new electrode materials.”

The group demonstrated another approach, which replaces assumptions used in the porous media model with an approach called nano-architecture computational modeling, which begins modeling at a smaller particle than others and takes into account different structuring of the materials at the nano scale.

To validate their model, the group modeled two different nanostructures for a structural supercapacitor electrode made from reduced graphene oxide and aramid nanofiber: a ‘house of cards’ and a ‘layered’ structure. After computational modeling, the group sought to validate the models by experimenting with the actual materials. Their results, published in ACS Nano, demonstrated that this approach to modeling leads to more accurate assumptions.

The research revealed promising attributes for the graphene oxide/aramid nanofiber electrodes, which exhibited both good electrode performance and mechanical strength. According to the researchers, this potentially makes the electrode suitable for a variety of use cases, including unspecified military applications.

The group further notes that its modeling approach can help to improve understanding of material structures in a battery, ultimately leading to better products. “Evaluation of microscopic properties such as porosity, tortuosity, and effective diffusivity through both experiment and simulation is essential to understand the material behavior and to improve its performance,” note the scientists in the published paper.