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Morphology and Crystal Planes Effects on Supercapacitance of CeO 2 Nanostructures: Electrochemical and Molecular Dynamics Studies
Author(s) -
Jeyaranjan Aadithya,
Sakthivel Tamil Selvan,
Molinari Marco,
Sayle Dean C.,
Seal Sudipta
Publication year - 2018
Publication title -
particle and particle systems characterization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 56
eISSN - 1521-4117
pISSN - 0934-0866
DOI - 10.1002/ppsc.201800176
Subject(s) - nanorod , nanostructure , materials science , capacitance , supercapacitor , nanotechnology , nanoparticle , cyclic voltammetry , chemical engineering , surface charge , morphology (biology) , cerium oxide , electrochemistry , crystal (programming language) , oxide , electrode , chemistry , computer science , metallurgy , engineering , programming language , biology , genetics
Nano cerium oxide (CeO 2 ) is a promising supercapacitor material, but the effect of morphology on charge storage capacity remains elusive. To determine this effect, three different morphologies, nanorods, cubes, and particles are synthesized by a one‐step hydrothermal process. Electrochemical evaluation through cyclic voltammetry and galvanostatic charge–discharge techniques reveals specific capacitance to be strongly dependent on the nanostructure morphology. The highest specific capacitance in nanorods (162.47 F g −1 ) is due to the substantially larger surface area relative to the other two morphologies and the predominant exposure of the highly reactive {110} and {100} planes. At comparable surface areas, exposed crystal planes exhibit a profound effect on charge storage. The exposure of highly reactive {100} planes in nanocubes induce a greater specific capacitance compared to nanoparticles, which are dominated by the less reactive {111} facets. The experimental findings are supported by reactivity maps of the nanostructures generated by molecular dynamics simulations. This study indicates that supercapacitors with higher charge storage can be designed through a nanostructure morphology selection strategy.