{"id":124130,"date":"2021-06-22T18:23:32","date_gmt":"2021-06-23T01:23:32","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2021\/06\/an-ally-for-alloys-ai-helps-design-high-performance-steels"},"modified":"2021-06-22T18:23:32","modified_gmt":"2021-06-23T01:23:32","slug":"an-ally-for-alloys-ai-helps-design-high-performance-steels","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2021\/06\/an-ally-for-alloys-ai-helps-design-high-performance-steels","title":{"rendered":"An ally for alloys: AI helps design high-performance steels"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/an-ally-for-alloys-ai-helps-design-high-performance-steels.jpg\"><\/a><\/p>\n<p>Machine learning techniques have contributed to progress in science and technology fields ranging from health care to high-energy physics. Now, machine learning is poised to help accelerate the development of stronger alloys, particularly stainless steels, for America\u2019s thermal power generation fleet. Stronger materials are key to producing energy efficiently, resulting in economic and decarbonization benefits.<\/p>\n<p>\u201cThe use of ultra-high-strength steels in power plants dates back to the 1950s and has benefited from gradual improvements in the materials over time,\u201d says Osman Mamun, a postdoctoral research associate at Pacific Northwest National Laboratory (PNNL). \u201cIf we can find ways to speed up improvements or create new materials, we could see enhanced efficiency in plants that also reduces the amount of carbon emitted into the atmosphere.\u201d<\/p>\n<p>Mamun is the lead author on two recent, related journal articles that reveal new strategies for machine learning\u2019s application in the design of advanced alloys. The articles chronicle the research outcomes of a joint effort between PNNL and the National Energy Technology Laboratory (NETL). In addition to Mamun, the research team included PNNL\u2019s Arun Sathanur and Ram Devanathan and NETL\u2019s Madison Wenzlick and Jeff Hawk.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine learning techniques have contributed to progress in science and technology fields ranging from health care to high-energy physics. Now, machine learning is poised to help accelerate the development of stronger alloys, particularly stainless steels, for America\u2019s thermal power generation fleet. Stronger materials are key to producing energy efficiently, resulting in economic and decarbonization benefits. [\u2026]<\/p>\n","protected":false},"author":396,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[39,1495,219,6],"tags":[],"class_list":["post-124130","post","type-post","status-publish","format-standard","hentry","category-economics","category-health","category-physics","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/124130","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\/396"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=124130"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/124130\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=124130"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=124130"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=124130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}