Полные импортированные сведения карточки
{
"title_en": "The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design",
"designation": "",
"series": "",
"status": "",
"date": "2020-11-12",
"date_original": "November 12, 2020",
"url": "https://www.nist.gov/publications/joint-automated-repository-various-integrated-simulations-jarvis-data-driven-materials",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Kamal Choudhary , Kevin Garrity , Andrew C. Reid , Brian DeCost , Adam Biacchi , Angela R. Hight Walker , Zachary Trautt , Jason Hattrick-Simpers , Aaron Kusne , Andrea Centrone , Albert Davydov , Francesca Tavazza , Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, David Vanderbilt, Karin Rabe",
"abstract_excerpt_en": "The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques",
"id": "2d1112efa534dfe4a448",
"sources": [
"NIST Publications"
],
"source_records": [
{
"title_en": "The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design",
"designation": "",
"series": "",
"status": "",
"date": "2020-11-12",
"date_original": "November 12, 2020",
"url": "https://www.nist.gov/publications/joint-automated-repository-various-integrated-simulations-jarvis-data-driven-materials",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Kamal Choudhary , Kevin Garrity , Andrew C. Reid , Brian DeCost , Adam Biacchi , Angela R. Hight Walker , Zachary Trautt , Jason Hattrick-Simpers , Aaron Kusne , Andrea Centrone , Albert Davydov , Francesca Tavazza , Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, David Vanderbilt, Karin Rabe",
"abstract_excerpt_en": "The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques"
}
],
"translation_state": "none"
}