High-throughput Screening of Multifunctional Nanocoatings Based on Combinations of Polyphenols and Catecholamines

Abstract Biomimetic surface coatings based on plant polyphenols and catecholamines have been used broadly in a variety of applications. However, lack of a rational cost-effective platform for screening these coatings and their properties limits the true potential of these functional materials to be unleashed. Here, we investigated oxidation behavior and coating formation ability of a library consisting of 45 phenolic compounds and catecholamines. UV-vis spectroscopy demonstrated significant acceleration of oxidation and polymerization under UV irradiation. We discovered that, several binary mixtures resulted in non-additive behaviour (synergistic or antagonistic effect) yielding much thicker or thinner coatings than individual compounds measured by ellipsometry. To investigate properties of coatings derived from new combinations, we used a miniaturized high-throughput strategy to screen 2532 spots coated with single, binary, and ternary combinations of coating precursors in one run. We evaluated the use of machine learning models to learn the relation between chemical structure of the precursors and thickness of the nanocoatings. Formation and stability of nanocoatings were investigated in a high-throughput manner via discontinuous dewetting. 30 stable combinations (hits) were used to tune the surface wettability and to form water droplet microarray and spot size gradients of water droplets on the coated surface. No toxicity was observed against eukaryotic HeLa cells and P. aeruginosa (strain PA30) bacteria after 24 h incubation at 37 °C. The strategy introduced here for high-throughput screening of nanocoatings derived from combinations of coating precursors enables the discovery of new functional materials for various applications in science and technology in a cost-effective miniaturized manner.