{"668626":{"#nid":"668626","#data":{"type":"news","title":"Supercomputing for Superconductors","body":[{"value":"\u003Cp\u003EResearchers at Georgia Tech and \u003Ca href=\u0022https:\/\/hust.edu.vn\/en\/\u0022\u003EHanoi University\u003C\/a\u003E have capitalized on a powerful supercomputer to build a database that could identify new superconducting materials that work at room temperature.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe team has identified two possible candidates using new machine learning models they developed and deployed with the capabilities of the San Diego Supercomputer Center at the University of California, San Diego. \u003Ca href=\u0022https:\/\/journals.aps.org\/prmaterials\/abstract\/10.1103\/PhysRevMaterials.7.054805\u0022\u003EThey published their progress recently in the journal Physical Review Materials.\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESuperconductors allow electricity to pass with no resistance, but conventional materials require temperatures near absolute zero (nearly -460 degrees Fahrenheit). For more than a century, scientists have been searching for materials able to accomplish the feat at room temperature and ambient pressure.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u201cThe main challenge of the [artificial intelligence\/machine learning] method is that we need, but never have, the desired database of superconductors,\u201d said \u003Ca href=\u0022https:\/\/mse.gatech.edu\/people\/huan-tran\u0022\u003EHuan Tran\u003C\/a\u003E, senior research scientist in the Georgia Tech \u003Ca href=\u0022https:\/\/mse.gatech.edu\/\u0022\u003ESchool of Materials Science and Engineering\u003C\/a\u003E. \u201cAll previous works relied on databases that are sometimes large enough, but completely lacking in atomic-level information \u2014 which is absolutely crucial for accurate predictions.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETran and Tuoc Vu from Hanoi University have been building a database with that atomic-level information, filling in a critical gap in available data so they can train machine learning models to accurately predict promising superconductive materials.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.sdsc.edu\/News%20Items\/PR20230718_superconductors_machine_learning.html\u0022\u003EMore details about their work from the San Diego Supercomputer Center.\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EMSE, Hanoi University, and UCSD team is developing a machine learning toolkit to discover room temperature superconducting materials.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"MSE, Hanoi University, and UCSD team is developing a machine learning toolkit to discover room temperature superconducting materials."}],"uid":"34760","created_gmt":"2023-07-28 12:01:53","changed_gmt":"2023-07-28 12:12:08","author":"Laurie Haigh","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2023-07-24T00:00:00-04:00","iso_date":"2023-07-24T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"groups":[{"id":"217141","name":"Georgia Tech Materials Institute"}],"categories":[],"keywords":[{"id":"186870","name":"go-imat"},{"id":"187915","name":"go-researchnews"}],"core_research_areas":[{"id":"39471","name":"Materials"}],"news_room_topics":[{"id":"71881","name":"Science and Technology"}],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EJoshua Stewart\u003C\/p\u003E\r\n","format":"limited_html"}],"email":["jstewart@gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}