[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-126571-105":59,"doc-detail-126571-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","efficient-atomistic-simulations-of-radiation-damage-in-w-and-w-mo-using-machine-learning-potentials","Efficient atomistic simulations of radiation damage in W and W-Mo using machine-learning potentials","","Gaussian approximation potential (GAP) is an accurate machine-learning interatomic potential recently extended to model radiation effects. This study validates a faster variant, tabulated GAP (tabGAP), by simulating primary radiation damage in 50–50 W–Mo alloys and pure W with classical molecular dynamics. W–Mo shows a defect survival count comparable to pure W, with more efficient defect recombination during early cascade stages and, in some cases, complete recombination after cascades cool.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/efficient-atomistic-simulations-of-radiation-damage-in-w-and-w-mo-using-machine-learning-potentials/126571/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/efficient-atomistic-simulations-of-radiation-damage-in-w-and-w-mo-using-machine-learning-potentials/126571.png","ImageObject",300,407,{"name":92,"@type":93},"Himbo","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-20","2026-08-05",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main goal of the study?","Question",{"text":112,"@type":113},"To validate tabulated GAP (tabGAP), a faster machine-learning interatomic potential, for modeling primary radiation damage in W and W–Mo systems.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does W–Mo radiation damage compare with pure W in the simulations?",{"text":117,"@type":113},"W–Mo exhibits a similar number of surviving defects as pure W, despite differences in recombination behavior during and after cascades.",{"name":119,"@type":110,"acceptedAnswer":120},"What performance and damage-retention trade-off is observed for tabGAP versus GAP?",{"text":121,"@type":113},"tabGAP is about two orders of magnitude faster than GAP while producing comparable numbers of surviving defects and defect cluster sizes.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},126571,1785933393,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":129,"read_time":144},687207017582,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","[https://helda.helsinki.fi](https://helda.helsinki.fi)  \n\n| Efficient atomistic simulations of radiation damage in W and W-Mo using machine-learning potentials\u003Cbr>Koskenniemi, Mikko 2023-04-15 |\n| --- |\n| Koskenniemi , M , Byggmästar , J , Nordlund , K & Djurabekova , F 2023 , ' Efficient\u003Cbr>atomistic simulations of radiation damage in W and W-Mo using machine-learning potentials' , Journal of Nuclear Materials , vol. 577 , 154325 . [https://doi.org/10.1016/j.jnucmat.2023.154325](https://doi.org/10.1016/j.jnucmat.2023.154325) |\n| [http://hdl.handle.net/10138/356993](http://hdl.handle.net/10138/356993)\u003Cbr>[https://doi.org/10.1016/j.jnucmat.2023.154325](https://doi.org/10.1016/j.jnucmat.2023.154325) |\n| cc_by\u003Cbr>publishedVersion |\n\nDownloaded from Helda, University of Helsinki institutional repository. This is an electronic reprint of the original article.  \nThis reprint may differ from the original in pagination and typographic detail. Please cite the original version.  \nJournal of Nuclear Materials 577 (2023) 154325  \nContents lists available at ScienceDirect  \nJournal of Nuclear Materials  \njournal [homepage:](homepage: www.elsevier.com/locate/jnucmat)[ www.elsevier.com/locate/jnucmat](homepage: www.elsevier.com/locate/jnucmat)  \n| Efficient atomistic simulations of radiation damage in W and W–Mousing machine-learning potentials\u003Cbr>Mikko Koskenniemia,∗, Jesper Byggmästara, Kai Nordlunda, Flyura Djurabekovaa,ba Department of Physics, University of Helsinki, P.O. Box 43, FI-00014, Finland\u003Cbr>b Helsinki Institute of Physics, Helsinki, Finland |  |  |  |\n| --- | --- | --- | --- |\n| a r t i c l e i n f o |  | a b s t r a c t |  |\n| Article history:\u003Cbr>Received 1 August 2022\u003Cbr>Revised 6 February 2023\u003Cbr>Accepted 7 February 2023\u003Cbr>Available online 9 February 2023 |  | The Gaussian approximation potential (GAP) is an accurate machine-learning interatomic potential that was recently extended to include the description of radiation effects. In this study, we seek to validate a faster version of GAP, known as tabulated GAP (tabGAP), by modelling primary radiation damage in 50– 50 W–Mo alloys and pure W using classical molecular dynamics. We find that W–Mo exhibits a similar number of surviving defects as in pure W. We also observe W–Mo to possess both more efficient recombination of defects produced during the initial phase of the cascades, and in some cases, unlike pure W, recombination of all defects after the cascades cooled down. Furthermore, we observe that the tabGAP is two orders of magnitude faster than GAP, but produces a comparable number of surviving defects and cluster sizes. A small difference is noted in the fraction of interstitials that are bound into clusters.\u003Cbr>© 2023 The Author(s). Published by Elsevier B.V.\u003Cbr>This is an open access article under the CC BY license ([http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/)) |  |\n| Keywords:\u003Cbr>Machine-learning potentials\u003Cbr>Molecular dynamics\u003Cbr>Tungsten\u003Cbr>Binary alloys\u003Cbr>Radiation damage\u003Cbr>Collision cascades |  |  |  |\n\n1. Introduction  \nNuclear energy is an integral part of modern society; nuclear fuels are millions of times more energy-dense than chemical ones, such as oil. Moreover, they release no greenhouse gases. The materials in nuclear reactors are exposed to intense irradiation, and the understanding of the consequences of this process on the durability and reliability of the materials is vital not only for existing power plants but more so for future fusion and next-generation fission reactors [1]. This motivates the search for new radiationtolerant materials. Tungsten-based high-entropy alloys (HEA) are a class of materials that show promising resilience to radiation [2], making them particularly interesting in the field of nuclear energy applications.  \nMolecular dynamics [3](MD) is a widely used method to study how materials respond to radiation and gives insight into atomicscale phenomena and their underlying mechanisms t","cbCaigVbzpllCMNW","https://ap.wps.com/l/cbCaigVbzpllCMNW","pdf",3350324,13,"English","# Abstract\n# Introduction\n## Motivation: radiation effects in nuclear materials\n## Simulation approach: molecular dynamics\n## Interatomic potentials and machine-learning potentials\n## GAP and the need for faster tabGAP","[{\"question\":\"What is the main goal of the study?\",\"answer\":\"To validate tabulated GAP (tabGAP), a faster machine-learning interatomic potential, for modeling primary radiation damage in W and W–Mo systems.\"},{\"question\":\"How does W–Mo radiation damage compare with pure W in the simulations?\",\"answer\":\"W–Mo exhibits a similar number of surviving defects as pure W, despite differences in recombination behavior during and after cascades.\"},{\"question\":\"What performance and damage-retention trade-off is observed for tabGAP versus GAP?\",\"answer\":\"tabGAP is about two orders of magnitude faster than GAP while producing comparable numbers of surviving defects and defect cluster sizes.\"}]","Efficient atomistic simulations of radiation damage in W and W-Mo using machine-learning potentials | PDF",33]