{
  "meta": {
    "api_type": "NWO Projects API",
    "version": "1.0.2",
    "licence": {
      "name": "CC0 1.0 Universal",
      "url": "https://creativecommons.org/publicdomain/zero/1.0",
      "description": "To the extent possible under law, all copyright and related or neighbouring rights have been waived worldwide to the data made available through this API."
    },
    "documentation": "https://doi.org/10.5281/zenodo.14918287",
    "release_date": "2025-08-20T00:00:00",
    "funder": "https://doi.org/10.13039/501100003246",
    "ror_id": "https://ror.org/04jsz6e67",
    "date": "2026-11-05T00:00:00",
    "count": 1,
    "per_page": 100,
    "pages": 1,
    "page": 1
  },
  "projects": [
    {
      "project_id": "NGF.1678.25.001",
      "title": "Quantum-enhanced Structural Health monitoring for  NXTGEN-SHM",
      "funding_scheme_id": 5008,
      "funding_scheme": "NGF - NXTGEN HIGHTECH Open call 2025",
      "department": "Toegepaste en Technische Wetenschappen",
      "sub_department": "Toegepaste en Technische Wetenschappen",
      "start_date": "2026-06-01T00:00:00",
      "reporting_year": 2025,
      "summary_nl": "Moderne vliegtuigen en windturbines maken gebruik van geavanceerde composietmaterialen die sterk en licht zijn, maar na verloop van tijd verborgen interne schade kunnen ontwikkelen. Het vroegtijdig opsporen hiervan is cruciaal voor veiligheid, kostenbesparing en duurzaamheid. Huidige monitoringsmethoden slagen er vaak niet in om dergelijke problemen tijdig te identificeren. Dit project introduceert een nieuwe generatie oplossingen die ultrasensitieve sensoren, energiezuinige computertechnologie en geavanceerde AI combineren om schade in een vroeg stadium te detecteren. Door betrouwbaarheid te verbeteren en afval te verminderen, ondersteunt het project schonere energie, veiliger vervoer en een duurzamere toekomst, met voordelen voor industrie, regelgevers en de samenleving.",
      "summary_en": "Modern aircraft and wind turbines rely on advanced composite materials that are strong and lightweight but can develop hidden internal damage over time. Detecting these early is critical for safety, cost savings, and sustainability. Current monitoring methods often fail to identify such issues before they become serious. This project introduces a next-generation solution combining ultra-sensitive sensors, energy-efficient computing, and advanced AI to detect damage at its earliest stage. By improving reliability and reducing waste, the project supports cleaner energy, safer travel, and a more sustainable future, benefiting industries, regulators, and society as a whole.",
      "award_amount": 2564086,
      "grant_id": "https://doi.org/10.61686/ZBGHM92220",
      "project_members": [
        {
          "role": "Co-applicant",
          "member_id": 325580,
          "last_name": "Zarouchas",
          "degree_pre_nominal": "dr.",
          "initials": "D.",
          "first_name": "Dimitrios",
          "organisation": "Technische Universiteit Delft||Faculteit Luchtvaart- en Ruimtevaarttechniek||Aerospace Structures and Materials",
          "organisation_id": 73427,
          "ror": "https://ror.org/02e2c7k09",
          "active": true
        },
        {
          "role": "Co-applicant",
          "member_id": 607183,
          "last_name": "Shahsavari",
          "degree_pre_nominal": "dr.",
          "initials": "M.",
          "first_name": "Mahyar",
          "organisation": "Radboud Universiteit Nijmegen||Donders Institute - Donders Institute for Brain, Cognition and Behaviour||Centre for Cognition",
          "organisation_id": 481123,
          "ror": "https://ror.org/016xsfp80",
          "active": true,
          "orcid": "https://orcid.org/0000-0001-7703-6835"
        },
        {
          "role": "Main Applicant",
          "member_id": 504807,
          "last_name": "Yaghoubi Nasrabadi",
          "degree_pre_nominal": "dr.",
          "initials": "V.",
          "first_name": "Vahid",
          "organisation": "Technische Universiteit Delft||Faculteit Luchtvaart- en Ruimtevaarttechniek||Aerospace Structures & Materials",
          "organisation_id": 75742,
          "ror": "https://ror.org/02e2c7k09",
          "active": true
        },
        {
          "role": "Project leader",
          "member_id": 504807,
          "last_name": "Yaghoubi Nasrabadi",
          "degree_pre_nominal": "dr.",
          "initials": "V.",
          "first_name": "Vahid",
          "organisation": "Technische Universiteit Delft||Faculteit Luchtvaart- en Ruimtevaarttechniek||Aerospace Structures & Materials",
          "organisation_id": 75742,
          "ror": "https://ror.org/02e2c7k09",
          "active": true
        },
        {
          "role": "Co-applicant",
          "member_id": 406894,
          "last_name": "Dunjko",
          "degree_pre_nominal": "prof. dr.",
          "initials": "V.",
          "first_name": "Vedran",
          "organisation": "Universiteit Leiden||Faculteit der Wiskunde en Natuurwetenschappen||Leiden Institute of Advanced Computer Science (LIACS)",
          "organisation_id": 76843,
          "ror": "https://ror.org/027bh9e22",
          "active": true
        }
      ]
    }
  ]
}