8196808f19ad0351b92c · Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

{
  "title_en": "Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2022-07-19",
  "date_original": "July 19, 2022",
  "url": "https://www.nist.gov/publications/quantum-materials-energy-efficient-neuromorphic-computing-opportunities-and-challenges",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Axel Hoffmann, Shriram Ramanathan, Julie Grollier, Andrew Kent, Marcelo Rozenberg, Ivan Schuller, Oleg Shpyrko, Robert Dynes, Yeshaiahu Fainman, Alex Frano, Eric Fullerton, Giulia Galli, Vitaliy Lomakin, Shyue Ping Ong, Amanda K. Petford-Long, Jonathan A. Schuller, Mark Stiles , Yayoi Takamura, Yimei Zhu",
  "abstract_excerpt_en": "Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device",
  "id": "8196808f19ad0351b92c",
  "sources": [
    "NIST Publications"
  ],
  "source_records": [
    {
      "title_en": "Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges",
      "designation": "",
      "series": "",
      "status": "",
      "date": "2022-07-19",
      "date_original": "July 19, 2022",
      "url": "https://www.nist.gov/publications/quantum-materials-energy-efficient-neuromorphic-computing-opportunities-and-challenges",
      "source": "NIST Publications",
      "display_en": "",
      "authors_en": "Axel Hoffmann, Shriram Ramanathan, Julie Grollier, Andrew Kent, Marcelo Rozenberg, Ivan Schuller, Oleg Shpyrko, Robert Dynes, Yeshaiahu Fainman, Alex Frano, Eric Fullerton, Giulia Galli, Vitaliy Lomakin, Shyue Ping Ong, Amanda K. Petford-Long, Jonathan A. Schuller, Mark Stiles , Yayoi Takamura, Yimei Zhu",
      "abstract_excerpt_en": "Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device"
    }
  ],
  "translation_state": "none"
}