Quantum-accelerated supercomputing atomistic simulations for corrosion inhibition

JSON Export

{
  "updated": "2024-12-30T09:21:39.734078+00:00", 
  "created": "2024-12-21T11:28:02.875483+00:00", 
  "revision": 9, 
  "id": "2511", 
  "metadata": {
    "title": "Quantum-accelerated supercomputing atomistic simulations for corrosion inhibition", 
    "edited_by": 576, 
    "is_last": true, 
    "doi": "10.24435/materialscloud:e2-dr", 
    "license": "MIT License", 
    "publication_date": "Dec 30, 2024, 10:21:39", 
    "mcid": "2024.211", 
    "contributors": [
      {
        "email": "egkarim@gmail.com", 
        "affiliations": [
          "Independent researcher, V\u00e4ster\u00e5s, Stockholm, Sweden"
        ], 
        "familyname": "Elgammal", 
        "givennames": "Karim"
      }, 
      {
        "email": "marc.maussner@infoteam.de", 
        "affiliations": [
          "Infoteam Software AG, Bubenreuth, Germany"
        ], 
        "familyname": "Mau\u00dfner", 
        "givennames": "Marc"
      }
    ], 
    "status": "published", 
    "owner": 908, 
    "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.", 
    "_files": [
      {
        "checksum": "md5:151fcfb7162e60c1968601b1aa48e53e", 
        "size": 63988595, 
        "description": "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.", 
        "key": "KE_MM_arXiv_2412.00951.zip"
      }, 
      {
        "checksum": "md5:3bc7b50fa286b968e39a3820ef67092f", 
        "size": 5033, 
        "description": "Detailed readme documentation of directory structure, file formats, and technical specifications for quantum-accelerated corrosion inhibition simulations, including calculation parameters and workflow descriptions.", 
        "key": "README.md"
      }
    ], 
    "keywords": [
      "corrosion inhibition", 
      "DFT", 
      "Aluminum", 
      "triazole", 
      "quantum computing", 
      "HPC", 
      "VQE", 
      "adaptVQE", 
      "qiskit", 
      "CP2K"
    ], 
    "conceptrecid": "2510", 
    "references": [
      {
        "comment": "Preprint on arXiv where the data is discussed", 
        "citation": "K. Elgammal, M. Mau\u00dfner, arXiv:2412.00951 (2024) https://arxiv.org/abs/2412.00951", 
        "type": "Preprint", 
        "url": "https://arxiv.org/abs/2412.00951"
      }
    ], 
    "version": 1, 
    "_oai": {
      "id": "oai:materialscloud.org:2511"
    }, 
    "license_addendum": "", 
    "id": "2511"
  }
}