Karim Elgammal^1*, Marc Maußner^2*

1 Independent researcher, Västerås, Stockholm, Sweden

2 Infoteam Software AG, Bubenreuth, Germany

* Corresponding authors emails: egkarim@gmail.com, marc.maussner@infoteam.de

DOI10.24435/materialscloud:e2-dr [version v1]

Publication date: Dec 30, 2024

How to cite this record

Karim Elgammal, Marc Maußner, Quantum-accelerated supercomputing atomistic simulations for corrosion inhibition, Materials Cloud Archive 2024.211 (2024), https://doi.org/10.24435/materialscloud:e2-dr

Description

This dataset supports a systematic implementation of hybrid quantum-classical computational methods for investigating corrosion inhibition mechanisms on aluminum surfaces. The work presents an integrated workflow combining density functional theory (DFT) with quantum algorithms through an active space embedding scheme, specifically applied to studying 1,2,4-Triazole and 1,2,4-Triazole-3-thiol inhibitors on Al111 surfaces. The methodology employs the orb-d3-v2 machine learning potential for rapid geometry optimizations, followed by accurate DFT calculations using CP2K with PBE functional and Grimme's D3 dispersion corrections. Our implementation leverages the ADAPT-VQE quantum algorithm with benchmarking against classical DFT calculations, achieving binding energies of -0.386 eV and -1.279 eV for 1,2,4-Triazole and 1,2,4-Triazole-3-thiol, respectively.

Materials Cloud sections using this data

Files

File name	Size	Description
KE_MM_arXiv_2412.00951.zip MD5md5:151fcfb7162e60c1968601b1aa48e53e	61.0 MiB	Dataset for quantum-accelerated simulations of corrosion inhibition on aluminum surfaces. Contains quantum chemistry calculations, visualization data, and analysis for triazole-based inhibitors. Includes python scripts, molecular structures (xyz), quantum calculation results (json), and visualization files (png/svg). Associated with arXiv:2412.00951.
README.md MD5md5:3bc7b50fa286b968e39a3820ef67092f	4.9 KiB	Detailed readme documentation of directory structure, file formats, and technical specifications for quantum-accelerated corrosion inhibition simulations, including calculation parameters and workflow descriptions.

License

Files and data are licensed under the terms of the following license: MIT License.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Keywords

corrosion inhibition DFT Aluminum triazole quantum computing HPC VQE adaptVQE qiskit CP2K