Proceedings of MATSUS Spring 2025 Conference (MATSUSSpring25)
DOI: https://doi.org/10.29363/nanoge.matsusspring.2025.197
Publication date: 16th December 2024
The activation of O2 through electrochemical reduction (ORR, oxygen reduction reaction) has shown promising results as alternative energy conversion technologies that can produce added-value chemicals from simple and abundant feedstocks. However, despite extensive efforts to develop catalytic materials with high reactivity and high selectivity, one can currently observe the lack of demonstrative performance for viable industrial applications. The deliberate surface modification of catalyst has been recently recognized as a powerful approach to design efficient and durable electrocatalysts [1]. It then becomes essential to obtain a good control over the spatial distribution of the chemical functions over the nanoobject surfaces. Recently, excellent catalytic properties towards ORR have been obtained in alkaline media of gold [2], silver [3], and platinum [4] nanoparticles when modified through the reductive grafting of rigid macrocycle calix[4]arene-tetradiazonium salts [5]. However, many fundamental questions, with important operational implications, remain open about these calixarene-modified surfaces. In particular, the conformation of the calixarene on the surface, and the structural, thermodynamic and electronic description of the interface. In addition, the C-Au bond has been poorly investigated in comparison to the S-Au bond.
Here, using spectroscopic studies coupled with computational modeling performed with density functional based tight-binding (DFTB) approaches, we investigate the interaction between calix[4]arene macrocycles and gold and platinum nanoparticles. After exploring the nature of the bond between the macrocycle and the gold surface thanks to a good agreement between measured and calculated Raman spectra, we describe the effect of calix[4]arenes on nanoparticles electrocatalytic properties [6].
The work was performed with funding from Agence Nationale pour la Recherche under grant ANR-21-CE50-0034 (MARCEL project). This work was granted access to the HPC resources of TGCC under the allocations 2022-A0130907682 made by GENCI.
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