Elsevier

Electrochimica Acta

Volume 300, 20 March 2019, Pages 145-149
Electrochimica Acta

Responses to comments on “Ni nanoparticle-decorated reduced graphene oxide for non-enzymatic glucose sensing: An experimental and modeling study [Electrochim. Acta 240 (2017) 388–398]”

https://doi.org/10.1016/j.electacta.2019.01.081Get rights and content

Abstract

In our recent work [Electrochim. Acta 240 (2017) 388–398], we examined the adsorption energy of glucose on graphene via Ni nanoparticles. In the present study, we have responded to comments to clarify the intricacies of dispersion effect and adsorption energies in our previous work. We have explored the performance and accuracy of some established and promising theoretical schemes, namely, the two-, three- (DFT-D2/3), and many-body (MBD@rSC) dispersion approaches, to account properly for the dispersive force contributions, which were not previously included in the system. Incorporating dispersive forces drastically increased the adsorption energy of glucose (Eads), where different active sites were obtained. The calculated energies were in the order Eads(DFT−D2) < Eads(DFT−D3) < Eads(MBD@rSC). However, because the accuracy of the preferred MBD@rSC method is closely related to the mesh-grid, it is too early to conclude which theoretical approach gives the most satisfactory results. The dependence of the glucose active site and adsorption energy was sensitive to the used theoretical approximation. Therefore, the accuracy of the selected theoretical method should be always tested or compared with the experimental data.

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Computational methods

In addition to the computational details shown in Ref. [1], to account for the dispersive forces, the DFT-D2 and DFT-D3 methods were used as implemented in the Vienna Ab initio Simulation Package (VASP) (5.3.5), and the MBD@rSC method was used as incorporated in VASP (5.4.1). The dispersion was included from the beginning and throughout geometry optimization until convergence was reached. To allow our results to be reproduced, We included the xyz structure of our system optimized without

Acknowledgments

The authors are grateful for the use of the Numerical Materials Simulator Station in the National Institute for Materials Science (NIMS), Japan, and for the use of the newly implemented MAterials Science Supercomputing system for Advanced MUlti-scale simulations towards NExt-generation Institute for Materials Research (MASAMUNE-IMR) in the Centre for Computational Materials Science of the Institute for Materials Research (CCMS-IMR), Tohoku University, Japan. We are also thankful for Prof.

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