Design of Co-Sn bimetallic nanoalloys as electrocatalyst for alkaline methanol oxidation reaction: Exploring the effect of electroactivation process

dc.contributor.authorDabirifar, Zeynab
dc.contributor.authorKhadempir, Sara
dc.contributor.authorKardan, Alireza
dc.contributor.authorKaraman, Ceren
dc.contributor.authorKaraman, Onur
dc.contributor.authorYola, Mehmet Lutfi
dc.date.accessioned2022-08-10T14:08:33Z
dc.date.available2022-08-10T14:08:33Z
dc.date.issuedJUL 1 2022en_US
dc.departmentHKÜ, Sağlık Bilimleri Fakültesi, Beslenme ve Diyetetik Bölümüen_US
dc.description.abstractThe engineering of cost-effective and durable electrocatalysts for the methanol oxidation reaction (MOR) is required for the commercialization of direct methanol fuel cells (DMFCs). Herein, a series of Co-x-Sn100-x alloy nanoparticles were synthesized to optimize the Co/S ratio, and the alloy nanoparticle which offered the best electrochemical performance towards MOR was employed as electrocatalyst for further experiments. Moreover, two different electroactivation approaches including i) activation in phosphate buffer medium, and ii) in-situ activation were explored to enlighten their effect on electrochemical characteristics of nanocatalyst. In this regard, the chronoamperometry measurements were carried out at a constant potential over a fixed period of 300 s. Additionally, the pH of the phosphate buffer solution in a range of 3-12, the activation potential ranging -0.7 V to -2.0 V were optimized by evaluating the recorded cyclic voltammograms. Moreover, to predict the effect of phosphate buffer pH in the activation process on the electrocatalytic activity of catalyst were artificial neural network (ANN) approach was implemented. Amongst the various nanoalloys, Co-65-Sn-35 nanoparticles were determined as the optimal one thanks to their uniform dispersion and less aggregation feature. In the activation process with phosphate buffer at pH of 10 was determined as the optimal, and at this condition a hydrogen evolution reaction also occurred in the range of applied activation potential. The findings revealed that activation in phosphate buffer solution led to the formation of more -OH species, thereby boosting the electrocatalytic activation towards MOR in alkaline media. Similarly, for the in-situ activation approach, the optimum potential was determined as -1.3 V to achieve the maximum current density. The findings offered that the electroactivation in phosphate buffer solution (pH = 10) at -1.3 V could result in a highly active electrocatalyst to be utilized in alkaline DMFCs. This research lays the door for tailoring high-performance, low-cost electrocatalysts that could be used in energy conversion systems instead of commercial noble-metal-based electrocatalysts.en_US
dc.identifier.citationDabirifar, Z., Khadempir, S., Kardan, A., Karaman, C., Karaman, O., & Yola, M. L. (July 01, 2022). Design of Co-Sn bimetallic nanoalloys as electrocatalyst for alkaline methanol oxidation reaction: Exploring the effect of electroactivation process. Fuel, 319.en_US
dc.identifier.doi10.1016/j.fuel.2022.123727
dc.identifier.issn0016-2361
dc.identifier.issn1873-7153
dc.identifier.orcid0000-0001-7424-3425en_US
dc.identifier.scopus2-s2.0-85125561176
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.fuel.2022.123727
dc.identifier.urihttps://hdl.handle.net/20.500.11782/2633
dc.identifier.volume319en_US
dc.identifier.wosWOS:000783233800007
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherELSEVIER SCI LTDen_US
dc.relation.ispartofFUEL
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial neural networksen_US
dc.subjectCo-Sn Nanoparticlesen_US
dc.subjectBimetallic alloysen_US
dc.subjectDirect Methanol Fuel Cellen_US
dc.subjectElectrocatalysten_US
dc.titleDesign of Co-Sn bimetallic nanoalloys as electrocatalyst for alkaline methanol oxidation reaction: Exploring the effect of electroactivation process
dc.typeArticle

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