Source code and simulation data for the prediction of the electrodeposition mechanism of nanostructured metallic coatings

This data article presents a simulation model based on quantum mechanics and energy potentials for obtaining simulation data that allows, from the perspective of materials informatics, the prediction of the electrodeposition mechanism for forming nanostructured metallic coatings. The development of...

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Bibliographic Details
Published in:Data in brief 2023-06, Vol.48, p.109269-109269, Article 109269
Main Authors: Rosano-Ortega, G., Bedolla-Hernández, M., Sánchez-Ruiz, F.J., Bedolla-Hernández, J., Schabes-Retchkiman, P.S., Vega-Lebrún, C.A., Vargas-Viveros, E.
Format: Article
Language:English
Subjects:
Data
Electrochemistry
Interdiffusion
Nanocoatings
Programming in Cuda
Quantum chemistry
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Summary:This data article presents a simulation model based on quantum mechanics and energy potentials for obtaining simulation data that allows, from the perspective of materials informatics, the prediction of the electrodeposition mechanism for forming nanostructured metallic coatings. The development of the research is divided into two parts i) the formulation (Quantum mechanical model and Corrected model for electron prediction; using a modified Schrödinger equation) and ii) the implementation of the theoretical prediction model (Discretization of the model). For the simulation process, the finite element method (FEM) was used considering the equation of electric potential and electroneutrality with and without the inclusion of quantum leap. We also provide the code to perform QM simulations in CUDA®, and COMSOL® software, the simulation parameters, and data for two metallic arrangements of chromium nanoparticles (CrNPs) electrodeposited on commercial steel substrate. (CrNPs-AISI 1020 steel and CrNPs-A618 steel). Data collection shows the direct relationship between applied potential (VDC), current (A), concentration (ppm), and time (s) for the homogeneous formation of the coating during the electrodeposition process, as estimated by the theoretical model developed. Their potential reuse data is done to establish the precision of the theoretical model in predicting the formation and growth of nanostructured surface coatings with metallic nanoparticles to give surface-mechanical properties.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2023.109269