Speaker
Description
Recent studies on electrochemical energy storage devices, such as electrodes (anodes and cathodes) for Li-ion batteries and supercapacitors, have increasingly emphasized the critical role of the pore network [1, 2]. It is now well recognized that pore structure can either facilitate or hinder charge/ discharge or redox processes. In this context, the three-dimensional porous architecture of an electrode plays a decisive role in fast-charging mechanisms. This raises key questions: does pore architecture directly control fast charging, and if so, how can it be optimized? What structural “recipe” leads to high-performance electrodes?
In this work, we investigate a range of porous architectures and, by explicitly elucidating the role of tortuosity, propose a more informative and physically grounded framework for characterizing and optimizing porous electrodes. Various laser-based strategies reported in the literature have been used to create engineered porous geometries consisting of conical or cylindrical wells arranged in linear, rectangular, triangular, or grid-like patterns [3]. Such laser-engraved architectures have demonstrated promising improvements in the electrochemical performance of electrodes. In this work, we compare these well-defined patterns with an alternative laser-scanning strategy in which only the upper portion of the electrode (approximately half of its thickness) is continuously modified, while the bottom region remains intact. The resulting structures are computationally reconstructed and analyzed in terms of pore-network complexity, including tortuosity, connectivity, anisotropy, and the presence of isolated or dead-end regions that may impede ionic transport.
Three-dimensional transport simulations are performed within these topologies to evaluate ion accessibility and effective charge-storage utilization. The results reveal strong anisotropy between in-plane and through-plane transport, with tortuosity differing substantially between directions. Under such conditions, classical models based on effective medium theory, such as the Bruggeman relation fail to accurately describe transport behavior. This breakdown arises from the highly irregular pore geometries, including slit-like pores and strongly disordered networks, characteristic of the nano-carbon slurry–based electrodes investigated here. By solving diffusion transport equations within the actual reconstructed geometries, we demonstrate pronounced discrepancies between theoretical predictions and structure-resolved transport, particularly at length scales of a few nanometers.
We propose a hierarchical design methodology in which porous architectures are first characterized geometrically using available imaging or visualization techniques and subsequently optimized at the computational level before being selectively implemented experimentally [4]. Within this framework, a library of three-dimensional porous geometries is generated using computer-aided design and analyzed numerically to extract key structural descriptors, including tortuosity, connectivity, anisotropy, and the fraction of inactive or dead-end pore regions. These descriptors are correlated with simulated transport performance, enabling the identification of favorable architectural features. A classification algorithm is then used to associate optimized geometries with experimentally accessible fabrication parameters, thereby linking the numerical design space to practical preparation routes.
By restricting experimental efforts to a reduced subset of pre-optimized architectures, this strategy minimizes experimental cost and time and enables efficient iteration toward high-performance porous electrodes. The proposed workflow thus provides a general and scalable approach for rational pore-architecture optimization that moves beyond porosity-based design rules.
| References | [1] Kress, T., X. Liu, and A.C. Forse, Pore network tortuosity controls fast charging in supercapacitors. Nature Materials, 2025: p. 1–7. [2] Tjaden, B., D.J. Brett, and P.R. Shearing, Tortuosity in electrochemical devices: a review of calculation approaches. International Materials Reviews, 2018. 63(2): p. 47–67. [3] Goel, V., et al., Optimization of laser-patterned electrode architectures for fast charging of Li-ion batteries using simulations parameterized by machine learning. Energy Storage Materials, 2023. 57: p. 44–58. [4] Torayev, A., et al., Probing and interpreting the porosity and tortuosity evolution of Li-O2 cathodes on discharge through a combined experimental and theoretical approach. The Journal of Physical Chemistry C, 2021. 125(9): p. 4955–4967. |
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| Country | Greece |
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