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Rutile (β-)MnO2 surfaces and vacancy formation for high electrochemical and catalytic performance


Reference:

Tompsett, D. A., Parker, S. C. and Islam, M. S., 2014. Rutile (β-)MnO2 surfaces and vacancy formation for high electrochemical and catalytic performance. Journal of the American Chemical Society, 136 (4), pp. 1418-1426.

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Official URL:

http://dx.doi.org/10.1021/ja4092962

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Abstract

MnO2 is a technologically important material for energy storage and catalysis. Recent investigations have demonstrated the success of nanostructuring for improving the performance of rutile MnO2 in Li-ion batteries and supercapacitors and as a catalyst. Motivated by this we have investigated the stability and electronic structure of rutile (β-)MnO2 surfaces using density functional theory. A Wulff construction from relaxed surface energies indicates a rod-like equilibrium morphology that is elongated along the c-axis, and is consistent with the large number of nanowire-type structures that are obtainable experimentally. The (110) surface dominates the crystallite surface area. Moreover, higher index surfaces than considered in previous work, for instance the (211) and (311) surfaces, are also expressed to cap the rod-like morphology. Broken coordinations at the surface result in enhanced magnetic moments at Mn sites that may play a role in catalytic activity. The calculated formation energies of oxygen vacancy defects and Mn reduction at key surfaces indicate facile formation at surfaces expressed in the equilibrium morphology. The formation energies are considerably lower than for comparable structures such as rutile TiO2 and are likely to be important to the high catalytic activity of rutile MnO2.

Details

Item Type Articles
CreatorsTompsett, D. A., Parker, S. C. and Islam, M. S.
DOI10.1021/ja4092962
Related URLs
URLURL Type
http://www.scopus.com/inward/record.url?scp=84893449444&partnerID=8YFLogxKUNSPECIFIED
DepartmentsFaculty of Science > Chemistry
Research CentresCentre for Sustainable Chemical Technologies
EPSRC Centre for Doctoral Training in Statistical Mathematics (SAMBa)
RefereedYes
StatusPublished
ID Code38652

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