Publication date: 15th December 2025
The design of next-generation battery electrodes increasingly relies on advanced additive-manufacturing techniques capable of tuning transport properties through precise architectural control. Among the most widely used additive-manufacturing approaches is Direct Ink Writing (DIW), which enables the fabrication of architected electrodes by extruding printable inks while maintaining low processing temperatures and material versatility [1].
In parallel, the semi-empirical master-curve model proposed by Tian et al. [2] has emerged as a predictive tool for describing the master curve (capacity vs. current relationship) in conventional planar electrodes, using electrode thickness as the sole geometric parameter. However, this model is intrinsically restricted to flat architectures and cannot capture the transport phenomena introduced by structured 3D geometries.
In this work, we fabricate 3D-structured LFP electrodes via DIW, implementing different vertical and periodic architectures, as well as planar electrodes of various thicknesses as references. Electrochemical measurements show that these structured electrodes exhibit a consistent enhancement in high-rate performance, directly demonstrating the key influence of geometry on ionic and electronic transport.
Motivated by the inability of the original model [2] to describe structured electrodes, we present a generalization of the master-curve model applicable to any electrode geometry. The extended formulation replaces the thickness-based descriptor with geometry-independent transport parameters obtained from a single cross-section image of the electrode: Ionic Medium Path (IMP), Electronic Medium Path (EMP), ionic interfacial area (Aᵢ), electronic interfacial area (Aₑ), and electrode volume (V).
By applying the model to our different experimental electrode geometries, we are able to determine which transport process is rate-limiting and identify the optimal geometry within our experimental limitations.
This work has received funding from the Comunidad de Madrid under the program Programa de atracción de talento de la Comunidad de Madrid (grant agreement 2022-T1/IND-23776) and from the Spanish State Research Agency (AEI) and the European Union (EU) under the project Optimization strategies for 3D battery electrodes (B3ES), PID2023-148703OA-I00
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