Proceedings of MATSUS Fall 2024 Conference (MATSUSFall24)
DOI: https://doi.org/10.29363/nanoge.matsusfall.2024.002
Publication date: 28th August 2024
Copper-based electrocatalysts are showing great promise for converting CO2 into valuable products through electrochemical processes. However, achieving high selectivity for higher carbon number (C2+) products is still a major hurdle for their commercial use. In our study, we have developed a range of electrocatalysts using octadecylamine (ODA) coated Cu2O nanoparticles. High-resolution transmission electron microscopy (HRTEM) has shown that these coatings vary in thickness from 1.2 to 4 nanometers. Density functional theory (DFT) calculations indicate that with low coverage, ODA molecules tend to spread out on the surface of Cu2O, exposing hydrophilic areas. In contrast, at higher coverage, the ODA molecules pack closely together, which can hinder mass and charge transfer. This variation in the arrangement of ODA molecules on the nanoparticles significantly impacts the selectivity of the products.
Further insights were gained through in situ Raman spectroscopy, which demonstrated that the ideal ODA thickness helps stabilize important intermediates in the production of C2+ products, particularly ethanol. Additional tests using electrochemical impedance spectroscopy and pulse voltammetry have shown that thicker ODA coatings increase resistance to charge transfer, whereas thinner ODA layers facilitate quicker desorption of intermediates. The optimal thickness of the ODA layer results in the slowest rate of intermediate desorption, correlating with the highest observed concentration of these intermediates via in situ Raman spectroscopy. Consequently, this leads to a Faradaic efficiency exceeding 73% for ethanol and ethylene production. This study highlights the critical role of molecular coating thickness in tuning the performance of Cu-based electrocatalysts for efficient and selective CO2 conversion.
Financial support by the Spanish Ministry of Science and Innovation (CEX-2021-001230-S and PDI2021-0126071-OB-CO21 funded by MCIN/AEI/ 10.13039/501100011033) and Generalitat Valenciana (Prometeo 2021/038 and Advanced Materials programme Graphica MFA/2022/023 with funding from European Union NextGenerationEU PRTR-C17.I1). Participation in the EU project ECO2Fuel is grateful acknowledged. J.A. thanks the Spanish Ministry of Science and Innovation for a Ramon y Cajal research associate contract (RYC2021–031006-I financed support by MCIN/AEI/10.13039/501100011033 and by European Union/NextGenerationEU/ PRTR), and Generalitat Valenciana (CIGE 2022-093) financed by European Union-Next Generation EU, through the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital. J.H. thanks the Chinese Scholarship Council for doctoral fellowship. S.O. acknowledges the National Science Centre, Poland (grant no. UMO/2020/39/I/ST4/01446) and the “Excellence Initiative – Research University” (IDUB) Program, Action I.3.3 – “Establishment of the Institute for Advanced Studies (IAS)” for funding (grant no. UW/IDUB/2020/25). The computation was carried out with the support of the Interdisciplinary Center for Mathematical and Computational Modeling at the University of Warsaw (ICM UW) under grants no. G83-28 and GB80-24.
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