{"id":105844,"date":"2025-01-31T08:01:38","date_gmt":"2025-01-31T14:01:38","guid":{"rendered":"https:\/\/engineering.wisc.edu\/?p=105844"},"modified":"2025-01-31T08:01:39","modified_gmt":"2025-01-31T14:01:39","slug":"couet-leads-material-discovery-panel-during-u-s-doe-roundtable","status":"publish","type":"post","link":"https:\/\/engineering.wisc.edu\/blog\/couet-leads-material-discovery-panel-during-u-s-doe-roundtable\/","title":{"rendered":"Couet leads material discovery panel during U.S. DOE roundtable"},"content":{"rendered":"\n<p>Adrien Couet, Professor in the Nuclear Engineering and Engineering Physics Department at the University of Wisconsin-Madison, served as a panel lead in the &#8220;<a href=\"https:\/\/science.osti.gov\/-\/media\/bes\/pdf\/reports\/2024\/BES-Nuclear-Roundtable-Report-for-posting.pdf\">Foundational Science to Accelerate Nuclear Energy Innovation<\/a>&#8221; roundtable hosted by the U.S. Department of Energy\u2019s Office of Basic Energy Sciences in July 2022. A report summarizing the roundtable discussions and their implications was published in December 2024.\u00a0<\/p>\n\n\n\n<p>The report identifies five Priority Research Opportunities (PROs) that address key scientific challenges surrounding the development of next-generation fission and fusion energy systems. These opportunities span materials science, advanced coolants, interfacial chemistry, AI-driven material discovery, and multiscale experimental and computational techniques\u2014all essential for making nuclear energy more sustainable and competitive in the global energy mix.&nbsp;<\/p>\n\n\n\n<p>Couet led the panel on harnessing artificial intelligence (AI) and machine learning (ML) to accelerate the discovery of materials that can withstand extreme nuclear environments. Nuclear reactor designs are advancing to operate at higher temperatures, with novel coolants, and under extreme radiation conditions. To withstand these conditions without relying on expensive and time-consuming component monitoring and replacement campaigns, materials must be designed to be inherently resilient.&nbsp;<\/p>\n\n\n\n<p>\u201cTraditional material discovery approaches are often slow and costly,\u201d says Couet. \u201cAI and ML techniques provide an unprecedented opportunity to discover new materials faster, reduce experimental costs, and improve predictive modeling.\u201d<\/p>\n\n\n\n<p>AI-enhanced frameworks aim to elevate, not replace, traditional research approaches.&nbsp;<\/p>\n\n\n\n<p>\u201cWhile AI tools provide powerful predictive capabilities, they must be carefully grounded in fundamental physics and chemistry to be effective,\u201d says Couet. \u201cThe challenge is not just generating data faster, but combining AI-driven predictions with experimental validation to ensure the discovery of materials that are both theoretically promising and practically viable.\u201d<\/p>\n\n\n\n<p>Each research area discussed in the roundtable presents pivotal opportunities to innovate nuclear technologies, making them more efficient and sustainable.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Professor Adrien Couet served as a panel lead in the &#8220;Foundational Science to Accelerate Nuclear Energy Innovation&#8221; roundtable hosted by the U.S. Department of Energy&#8217;s Office of Basic Energy Sciences.<\/p>\n","protected":false},"author":118,"featured_media":84963,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_tec_requires_first_save":true,"_mbp_gutenberg_autopost":false,"_EventAllDay":false,"_EventTimezone":"","_EventStartDate":"","_EventEndDate":"","_EventStartDateUTC":"","_EventEndDateUTC":"","_EventShowMap":false,"_EventShowMapLink":false,"_EventURL":"","_EventCost":"","_EventCostDescription":"","_EventCurrencySymbol":"","_EventCurrencyCode":"","_EventCurrencyPosition":"","_EventDateTimeSeparator":"","_EventTimeRangeSeparator":"","_EventOrganizerID":[],"_EventVenueID":[],"_OrganizerEmail":"","_OrganizerPhone":"","_OrganizerWebsite":"","_VenueAddress":"","_VenueCity":"","_VenueCountry":"","_VenueProvince":"","_VenueState":"","_VenueZip":"","_VenuePhone":"","_VenueURL":"","_VenueStateProvince":"","_VenueLat":"","_VenueLng":"","_VenueShowMap":false,"_VenueShowMapLink":false,"_tribe_blocks_recurrence_rules":"","_tribe_blocks_recurrence_description":"","_tribe_blocks_recurrence_exclusions":"","footnotes":""},"categories":[2499,2500],"tags":[],"department":[2389],"class_list":["post-105844","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-faculty","category-research","department-nuclear-engineering-engineering-physics"],"acf":[],"_links":{"self":[{"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/posts\/105844","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/users\/118"}],"replies":[{"embeddable":true,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/comments?post=105844"}],"version-history":[{"count":5,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/posts\/105844\/revisions"}],"predecessor-version":[{"id":105861,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/posts\/105844\/revisions\/105861"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/media\/84963"}],"wp:attachment":[{"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/media?parent=105844"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/categories?post=105844"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/tags?post=105844"},{"taxonomy":"department","embeddable":true,"href":"https:\/\/engineering.wisc.edu\/wp-json\/wp\/v2\/department?post=105844"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}