Literature DB >> 26523404

Fe- and Co-P4-embedded graphenes as electrocatalysts for the oxygen reduction reaction: theoretical insights.

Liyan Feng1, Yuejie Liu2, Jingxiang Zhao1.   

Abstract

Encouraged by the great promise of metal-nitrogen-carbon (M-N-C) materials in replacing Pt for catalyzing the oxygen reduction reaction (ORR), metal-P species were successfully introduced into carbon matrices in experiments and have exhibited high catalytic activity for the ORR. Here, by means of comprehensive density functional theory (DFT) computations, we investigated the origin and the mechanism of the ORR occurring on Fe- and Co-P-embedded graphenes. Our computations have revealed that the Fe- and Co-P4 moiety-embedded graphenes possess good stability and high chemical reactivity for O2 activation, thus facilitating the subsequent ORR steps, and a more efficient 4e pathway in both acidic and alkaline media is more energetically favorable. Furthermore, by analyzing the computed free energy profiles, the Fe-P4 species-embedded graphene is a more efficient electrocatalyst for the ORR in an alkaline medium than the Co-P4 species-embedded graphene. Our DFT computations will be useful for gaining deeper insight into the high activity of metal-P species.

Entities:  

Year:  2015        PMID: 26523404     DOI: 10.1039/c5cp05551b

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  3 in total

1.  First-principles study of strain on BN-doped arsenene.

Authors:  Jianlin He; Guili Liu; Xinyue Li; Haonan Wang; Guoying Zhang
Journal:  J Mol Model       Date:  2022-06-17       Impact factor: 1.810

2.  Electronic structure and optical properties of B-, N-, and BN-doped black phosphorene using the first-principles.

Authors:  Jianlin He; Guili Liu; Xinyue Li; Guoying Zhang
Journal:  J Mol Model       Date:  2022-07-26       Impact factor: 2.172

3.  A Trifunctional Ni-P/Fe-P Collaborated Electrocatalyst Enables Self-Powered Energy Systems.

Authors:  Rui Yang; Xiaozhong Zheng; Minkai Qin; Binbin Lin; Xiaoyun Shi; Yong Wang
Journal:  Adv Sci (Weinh)       Date:  2022-05-22       Impact factor: 17.521

  3 in total

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