{
  "abstract": "This study presents a hybrid biomass–geothermal energy system for simultaneous power generation and ammonia production. The system integrates biomass conversion via gasification or anaerobic digestion, a gas turbine cycle, a geothermal-assisted organic Rankine cycle (ORC), thermoelectric generation, water electrolysis for hydrogen production, and catalytic ammonia synthesis. An optimization framework combining surrogate-based modeling and a metaheuristic algorithm is developed to determine optimal operating conditions. The system’s performance is evaluated in terms of net power output, thermodynamic efficiency, product cost, and environmental impact under a gate-to-gate boundary. The developed framework enables the evaluation of multi-generation energy systems and supports decision-making for sustainable energy planning. The optimization results demonstrate that the proposed integrated system can achieve a maximum net power output of 16.34 MW, an exergy efficiency of 48.43%, a minimum product cost of 19.03 $/GJ, and a minimum emission index of 0.4005 kg/kWh under scenarios. Comparative analysis shows that the digester-based configuration outperforms the gasifier-based system due to higher methane content and improved combustion characteristics. Overall, the results indicate that the proposed hybrid system offers a promising pathway for sustainable power and green ammonia production with improved thermodynamic and environmental performance.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Industrial Engineering, College of Engineering, University of Ha’il",
    "College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU)",
    "Department of Civil Engineering, College of Engineering, Cihan University-Erbil",
    "Department of Mechanical Engineering, College of Engineering, University of Zakho",
    "Physics Department, Faculty of Science, Islamic University of Madinah",
    "Department of Mechanical Engineering, College of Engineering, Najran University",
    "Faculty of Data Science and Information Technology, INTI International University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yassine Bouazzi"
    },
    {
      "affs": [
        1
      ],
      "name": "Karim Kriaa"
    },
    {
      "affs": [
        2
      ],
      "name": "Saman Ahmad Aminian"
    },
    {
      "affs": [
        3
      ],
      "name": "Ali I. Hameed"
    },
    {
      "affs": [
        4
      ],
      "name": "Mohamed Shaban"
    },
    {
      "affs": [
        5
      ],
      "name": "Husam Rajab"
    },
    {
      "affs": [
        6
      ],
      "name": "Narinderjit Singh Sawaran Singh"
    },
    {
      "affs": [
        1
      ],
      "name": "Khalil Hajlaoui"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ccn3k72dhq1yd.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-70407-7",
  "fulltext_url": "https://doi.org/10.1038/s41598-026-70407-7",
  "id": "ccn3k72dhq1yd",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://doi.org/10.1038/s41598-026-70407-7",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "Q"
    ],
    [
      "lcc",
      "R"
    ],
    [
      "openalex",
      "2210|Thermodynamic and Exergetic Analyses of Power and Cooling Systems"
    ]
  ],
  "openalex": "W7214554271",
  "pdf_url": "https://www.nature.com/articles/s41598-026-70407-7_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-01",
  "publisher": "Nature Portfolio",
  "ris": "https://research.draconitic.com/paper/ccn3k72dhq1yd.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T14:21:19Z",
      "native_id": "030973b5aa004d0b8b7005407809245c",
      "source": "doaj",
      "url": "https://doi.org/10.1038/s41598-026-70407-7"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "lcc:R",
      "subfield": "general"
    }
  ],
  "title": "Data-driven optimization of a biomass–geothermal system for power and green ammonia production",
  "title_text": "Data-driven optimization of a biomass–geothermal system for power and green ammonia production",
  "type": "peer-reviewed",
  "updated_at": "2026-11-03T14:20:46Z",
  "url": "https://research.draconitic.com/paper/ccn3k72dhq1yd",
  "venue": "Scientific Reports",
  "versions": []
}