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]”
Section snippets
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.
References (13)
- et al.
Ni nanoparticle-decorated reduced graphene oxide for non-enzymatic glucose sensing: an experimental and modeling study
Electrochim. Acta
(2017) - et al.
Structural mechanism of ring-opening reaction of glucose by human serum albumin
J. Biol. Chem.
(2013) Semiempirical GGA-type density functional constructed with a long-range dispersion correction
J. Comput. Chem.
(2006)Free energy surface for brønsted acid-catalyzed glucose ring-opening in aqueous solution
J. Phys. Chem. B
(2013)- et al.
The water-catalyzed mechanism of the ring-opening reaction of glucose
Phys. Chem. Chem. Phys.
(2015) - et al.
Scaling laws for van der Waals interactions in nanostructured materials
Nat. Commun.
(2013)