a00ff7dfa6510bc1913f · Machine learning enabling high-throughput and remote operations at large-scale user facilities

{
  "title_en": "Machine learning enabling high-throughput and remote operations at large-scale user facilities",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2022-05-18",
  "date_original": "May 18, 2022",
  "url": "https://www.nist.gov/publications/machine-learning-enabling-high-throughput-and-remote-operations-large-scale-user",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Bruce D. Ravel , Tatiana Konstantinova, Phillip Michael Maffettone, Stuart Campbell, Andi Barbour, Daniel Olds",
  "abstract_excerpt_en": "Imaging, scattering, and spectroscopy are fundamental in understanding and discovering new functional materials. Contemporary innovations in automation and experimental techniques have led to these measurements being performed much faster and with higher",
  "id": "a00ff7dfa6510bc1913f",
  "sources": [
    "NIST Publications"
  ],
  "source_records": [
    {
      "title_en": "Machine learning enabling high-throughput and remote operations at large-scale user facilities",
      "designation": "",
      "series": "",
      "status": "",
      "date": "2022-05-18",
      "date_original": "May 18, 2022",
      "url": "https://www.nist.gov/publications/machine-learning-enabling-high-throughput-and-remote-operations-large-scale-user",
      "source": "NIST Publications",
      "display_en": "",
      "authors_en": "Bruce D. Ravel , Tatiana Konstantinova, Phillip Michael Maffettone, Stuart Campbell, Andi Barbour, Daniel Olds",
      "abstract_excerpt_en": "Imaging, scattering, and spectroscopy are fundamental in understanding and discovering new functional materials. Contemporary innovations in automation and experimental techniques have led to these measurements being performed much faster and with higher"
    }
  ],
  "translation_state": "none"
}