Issue 1, 2019

Catalytic performance of graphene quantum dot supported manganese phthalocyanine for efficient oxygen reduction: density functional theory approach

Abstract

We investigate the catalytic performance of manganese phthalocyanine, as well as manganese phthalocyanine functionalized with a graphene quantum dot matrix, in oxygen-reduction reactions from a thermodynamic perspective. Associative mechanism is found to be energetically favored over the dissociative mechanism for the entire oxygen-reduction reaction process, in both the manganese phthalocyanine and manganese phthalocyanine/graphene quantum dot systems. The initial reduction reaction that forms OOH* is the rate-determining step with reaction barriers of 0.96 eV and 0.83 eV for the manganese phthalocyanine and manganese phthalocyanine/graphene quantum dot systems, respectively. In addition, we perform density of state analyses and construct Gibbs free-energy diagrams for each intermediate step in the overall oxygen-reduction reaction process for both systems, which reveal that the inclusion of the graphene quantum dot increases the number of transferred electrons in the manganese phthalocyanine. Interestingly, the highest operating potential of the manganese phthalocyanine/graphene quantum dot system is higher than that of pristine manganese phthalocyanine. We conclude that the manganese phthalocyanine functionalized with the graphene quantum dot matrix has improved oxygen-reduction reaction activity compared to that of pristine manganese phthalocyanine, and is a potential candidate for use in polymer electrolyte membrane fuel cells.

Graphical abstract: Catalytic performance of graphene quantum dot supported manganese phthalocyanine for efficient oxygen reduction: density functional theory approach

Article information

Article type
Paper
Submitted
07 Oct 2018
Accepted
26 Nov 2018
First published
26 Nov 2018

New J. Chem., 2019,43, 348-355

Catalytic performance of graphene quantum dot supported manganese phthalocyanine for efficient oxygen reduction: density functional theory approach

N. N. T. Pham, J. S. Park, H. Kim, H. Kim, Y. Son, S. G. Kang and S. G. Lee, New J. Chem., 2019, 43, 348 DOI: 10.1039/C8NJ05093G

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements