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A comprehensive understanding of the relationship between rheological behavior and agglomerate dynamics in catalyst inks under shear flow is necessary for effectively designing and optimizing the processes from ink preparation to final catalyst coating on the media surface such as catalyst layer (CL) in polymer electrolyte fuel cells. This study establishes a quantitative methodology to analyze and visualize the applicability of the Usui thixotropy model for interpreting agglomerate dynamics and particle-solvent-ionomer interactions with systematically complex ink systems. By implementing viscosity curve segmentation across diverse ink formulations, including varying in alcohol solution type, carbon support, and mixing time, the model’s applicability to specific interparticle interactions was calculated for each shear rate segment. A major finding is that model applicability correlates directly with the shear-thinning rate, enabling the classification of ink behavior into three distinct and preparation-dependent rheological regimes. High applicability indicates the dominance of secondary agglomerate network breakup, whereas low applicability suggests alternative mechanisms, such as primary agglomerate internal deformation or structural relaxation under low shear. These interpretations were validated through independent analyses of particle size distribution and ionomer adsorption over mixing time. The novelty of this work lies in the creation of a quantitative framework that maps macroscopic rheological data to specific physical mechanisms. These findings provide essential and quantitative guidelines for the targeted optimization of catalyst ink formulations, offering a robust foundation to overcome current challenges in shear-dependent structural evolution and ensuring the precise dispersed phase characteristics required for high-performance CL microstructures. • Quantitative mapping of catalyst ink rheology to agglomerate structural dynamics. • Thixotropy model applicability defines three distinct rheological regimes. • High model fit implies secondary agglomerate network breakup dominates. • Low model fit suggests primary agglomerate deformation or structural relaxation. • Model applicability mapping is integrated with dispersed phase data for validation.
Takeshita et al. (Fri,) studied this question.