{"id":4971,"date":"2025-07-07T10:35:39","date_gmt":"2025-07-07T10:35:39","guid":{"rendered":"https:\/\/scientificworld.org\/?p=4971"},"modified":"2025-07-07T10:35:43","modified_gmt":"2025-07-07T10:35:43","slug":"machine-learning-unveils-ph-dependent-secrets-of-tin-catalysts-for-co%e2%82%82-conversion","status":"publish","type":"post","link":"https:\/\/scientificworld.org\/?p=4971","title":{"rendered":"Machine Learning Unveils pH-Dependent Secrets of Tin Catalysts for CO\u2082 Conversion"},"content":{"rendered":"\n<p>Researchers at Tohoku University\u2019s Advanced Institute for Materials Research (WPI-AIMR) have harnessed machine learning to decode the performance of tin (Sn) catalysts in converting CO\u2082 into sustainable fuels. Published in&nbsp;<a href=\"http:\/\/dx.doi.org\/10.1002\/adfm.202506314\"><em>Advanced Functional Materials<\/em>&nbsp;<\/a>on June 26, 2025, this breakthrough could accelerate the design of efficient catalysts, advancing efforts toward carbon neutrality.<\/p>\n\n\n\n<p>The study addressed a critical gap in understanding how Sn catalysts function under varying pH conditions. By employing machine learning potential, the team analyzed data from over 1,000 experimental sources to simulate SnO\u2082\/SnS\u2082 configurations. These simulations, which aligned closely with real-world experiments, revealed how pH levels influence the CO\u2082 reduction reaction\u2014a key step in producing carbon-based fuels.<\/p>\n\n\n\n<p><em>&#8220;This approach saves years of lab work by pinpointing which experiments matter most,&#8221;<\/em>&nbsp;said lead researcher Hao Li. The model\u2019s accuracy in predicting catalyst behavior under different conditions marks a significant leap over previous methods, which often overlooked pH-dependent effects.<\/p>\n\n\n\n<p>The findings pave the way for optimizing Sn-based catalysts, bringing affordable green fuel production closer to reality. Next, the team aims to refine the machine learning framework to further bridge theory and practice.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at Tohoku University\u2019s Advanced Institute for Materials Research (WPI-AIMR) have harnessed machine learning to decode the performance of tin (Sn) catalysts in converting CO\u2082 into sustainable fuels. Published in&nbsp;Advanced Functional Materials&nbsp;on June 26, 2025, this breakthrough could accelerate the design of efficient catalysts, advancing efforts toward carbon neutrality. The study addressed a critical gap [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1143],"tags":[1423,1212,2355,2354],"class_list":["post-4971","post","type-post","status-publish","format-standard","hentry","category-materials-science","tag-co","tag-materials-science","tag-sn-based-catalysts","tag-sno"],"_links":{"self":[{"href":"https:\/\/scientificworld.org\/index.php?rest_route=\/wp\/v2\/posts\/4971","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scientificworld.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/scientificworld.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/scientificworld.org\/index.php?rest_route=\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/scientificworld.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4971"}],"version-history":[{"count":1,"href":"https:\/\/scientificworld.org\/index.php?rest_route=\/wp\/v2\/posts\/4971\/revisions"}],"predecessor-version":[{"id":4972,"href":"https:\/\/scientificworld.org\/index.php?rest_route=\/wp\/v2\/posts\/4971\/revisions\/4972"}],"wp:attachment":[{"href":"https:\/\/scientificworld.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4971"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/scientificworld.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4971"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/scientificworld.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4971"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}