{"id":211644,"date":"2025-04-17T02:29:10","date_gmt":"2025-04-17T07:29:10","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/04\/crystallography-informed-ai-achieves-high-performance-in-predicting-novel-crystal-structures"},"modified":"2025-04-17T02:29:10","modified_gmt":"2025-04-17T07:29:10","slug":"crystallography-informed-ai-achieves-high-performance-in-predicting-novel-crystal-structures","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/04\/crystallography-informed-ai-achieves-high-performance-in-predicting-novel-crystal-structures","title":{"rendered":"Crystallography-informed AI achieves high performance in predicting novel crystal structures"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/crystallography-informed-ai-achieves-high-performance-in-predicting-novel-crystal-structures3.jpg\"><\/a><\/p>\n<p>A research team from the Institute of Statistical Mathematics and Panasonic Holdings Corporation has developed a machine learning algorithm, ShotgunCSP, that enables fast and accurate prediction of crystal structures from material compositions. The algorithm achieved world-leading performance in crystal structure prediction benchmarks.<\/p>\n<p>Crystal structure prediction seeks to identify the stable or metastable crystal structures for any given chemical compound adopted under specific conditions. Traditionally, this process relies on iterative <a href=\"https:\/\/phys.org\/tags\/energy\/\" rel=\"tag\" class=\"\">energy<\/a> evaluations using time-consuming first-principles calculations and solving energy minimization problems to find stable atomic configurations. This challenge has been a cornerstone of materials science since the early 20th century.<\/p>\n<p>Recently, advancements in computational technology and generative AI have enabled new approaches in this field. However, for large-scale or <a href=\"https:\/\/phys.org\/tags\/complex+molecular+systems\/\" rel=\"tag\" class=\"\">complex molecular systems<\/a>, the exhaustive exploration of vast phase spaces demands enormous computational resources, making it an unresolved issue in materials science.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A research team from the Institute of Statistical Mathematics and Panasonic Holdings Corporation has developed a machine learning algorithm, ShotgunCSP, that enables fast and accurate prediction of crystal structures from material compositions. The algorithm achieved world-leading performance in crystal structure prediction benchmarks. Crystal structure prediction seeks to identify the stable or metastable crystal structures for [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19,41,2229,6],"tags":[],"class_list":["post-211644","post","type-post","status-publish","format-standard","hentry","category-chemistry","category-information-science","category-mathematics","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/211644","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/427"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=211644"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/211644\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=211644"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=211644"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=211644"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}