Catalyst Layer Ink Interactions That Affect Coatability
Source abstract
Abstract
Catalyst layer inks are examples of biphasic material systems composed of a solid material, a polymer, and a solvent. Nanoscale interactions between the individual constituents can alter macroscopic properties that are relevant for coating and manufacturing processes (i.e. viscosity, surface tension, aggregation, and rheology). Control over these macroscale properties are important for controlled electrode formation during scalable roll-to-roll manufacturing. The underlying interactions include polymer|particle, particle|solvent, and polymer|solvent interactions. In this work we systematically investigate polymer|particle interactions via studying a range of formulated inks composed of different solvents (methanol, isopropyl alcohol, octanol, and water), varying polymer loadings, and particles with different surface charges. Ink aging is also addressed and over short time periods (<1 hr shelf life) the addition of a perfluorosulfonic acid ionomer was shown to stabilize the ink and also decrease the aggregation size. However, over long time periods (168 hrs) the aggregation size is independent of polymer loading, and approaches a steady state aggregation size around 350 nm. This equilibrium point suggests that the polymer is free to diffuse, adsorb, and relax within the excluded volume region. Furthermore, these results suggest that primary aggregates can be broken up with the addition of very low polymer loadings (15% I:C). A semi-empirical model is used to describe polymer|particle interactions within the ink, and the polymer coverage at the surface of the carbon was found to be the most sensitive parameter dictating ink stability. Finally, coating and rheology experiments are completed on all inks.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Fuel Cells and Related Materials · Electrocatalysts for Energy Conversion · Electrochemical Analysis and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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