Sun Zhaozong, Curto Anthony, Rodríguez-Fernández Jonathan, Wang Zegao, Parikh Ayush, Fester Jakob, Dong Mingdong, Vojvodic Aleksandra, Lauritsen Jeppe V
Interdisciplinary Nanoscience Center (iNANO), Aarhus University, 8000 Aarhus C, Denmark.
Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
ACS Nano. 2021 Nov 23;15(11):18226-18236. doi: 10.1021/acsnano.1c07219. Epub 2021 Nov 2.
The addition of iron (Fe) can in certain cases have a strong positive effect on the activity of cobalt and nickel oxide nanoparticles in the electrocatalytic oxygen evolution reaction (OER). The reported optimal Fe dopant concentrations are, however, inconsistent, and the origin of the increased activity due to Fe dopants in mixed oxides has not been identified so far. Here, we combine density functional theory calculations, scanning tunneling microscopy, and OER activity measurements on atomically defined Fe-doped Co oxyhydroxide nanoparticles supported on a gold surface to establish the link between the activity and the Fe distribution and concentration within the oxyhydroxide phase. We find that addition of Fe results in distinct effects depending on its location on edge or basal plane sites of the oxyhydroxide nanoparticles, resulting in a nonlinear OER activity as a function of Fe content. Fe atom substitution itself does not lead to intrinsically more active OER sites than the best Co sites. Instead, the sensitivity to Fe promoter content is explained by the strong preference for Fe to locate on the most active edge sites of oxyhydroxide nanoparticles, which for low Fe concentrations stabilizes the particles but in higher concentrations leads to a shell structure with less active Fe on all edge positions. The optimal Fe content thereby becomes dependent on nanoparticle size. Our findings demonstrate that synthesis strategies that adjust not only the Fe concentration in mixed oxides but also its distribution within a catalyst nanoparticle can lead to enhanced OER performance.
在某些情况下，添加铁（Fe）对钴和氧化镍纳米颗粒在电催化析氧反应（OER）中的活性具有强烈的积极影响。然而，报道的最佳铁掺杂浓度并不一致，并且到目前为止，尚未确定混合氧化物中由于铁掺杂导致活性增加的原因。在这里，我们结合密度泛函理论计算、扫描隧道显微镜以及对负载在金表面的原子级定义的铁掺杂氢氧化钴纳米颗粒进行的析氧反应活性测量，以建立活性与氢氧化氧物相中铁的分布和浓度之间的联系。我们发现，根据铁在氢氧化氧物纳米颗粒边缘或基面位置的不同，添加铁会产生不同的影响，导致析氧反应活性作为铁含量的函数呈非线性变化。铁原子取代本身并不比最佳钴位点产生本质上更具活性的析氧反应位点。相反，对铁促进剂含量的敏感性可以通过铁强烈倾向于位于氢氧化氧物纳米颗粒最活跃的边缘位点来解释，对于低铁浓度，这会使颗粒稳定，但在较高浓度下会导致壳层结构，所有边缘位置的铁活性较低。因此，最佳铁含量取决于纳米颗粒的尺寸。我们的研究结果表明，不仅能调节混合氧化物中铁浓度，还能调节其在催化剂纳米颗粒内部分布的合成策略，可以提高析氧反应性能。
