{"id":374987,"date":"2026-08-12T15:06:03","date_gmt":"2026-08-12T15:06:03","guid":{"rendered":"https:\/\/wolfscientific.com\/?p=374987"},"modified":"2026-08-12T15:06:03","modified_gmt":"2026-08-12T15:06:03","slug":"employing-ai-and-experimental-techniques-to-tackle-practical-materials-issues","status":"publish","type":"post","link":"https:\/\/wolfscientific.com\/?p=374987","title":{"rendered":"Employing AI and Experimental Techniques to Tackle Practical Materials Issues"},"content":{"rendered":"<p>Located in Cambridge, UK, the computational chemistry firm <a href=\"https:\/\/cusp.ai\/\">CuspAI<\/a> has established <a href=\"https:\/\/www.businesswire.com\/news\/home\/20260716196996\/en\/CuspAI-Launches-AI-Materials-Foundry-a-Global-Network-to-Accelerate-Breakthrough-Discoveries\">a coalition of 45 entities<\/a> focused on the identification of novel functional materials through the use of artificial intelligence (AI). The AI Materials Foundry features major tech players such as Facebook&#8217;s parent company Meta and chip manufacturer Nvidia. Additionally, it includes notable firms from the automotive, chemical, solar energy, and semiconductor sectors, as well as scientific data suppliers. CuspAI intends to collaborate with these partners to generate and evaluate forecasts for groundbreaking new materials.<\/p>\n<div class=\"inline_image inline_image_center image_size_full quote_style_2 darktext\" data-attachment=\"550602\" data-sequence=\"1\" data-background=\"#F9F9F9\" data-text-colour=\"dark\">\n<div class=\"quote-wrapper\">\n<div class=\"quote-author-image\"> <span class=\"quote-icon\"><\/p>\n<p>\t\t\t\t&lt;path d=&quot;M0.000214011 6.14353C0.000213849 4.28754 0.640213 2.78354 1.92021 1.63154C3.13621 0.543534 4.67221 -0.000466931 6.52821 -0.000467093C8.89621 -0.0004673 10.7522 0.735533 12.0962 2.20753C13.4402 3.74353 14.1122 5.75953 14.1122 8.25553C14.1122 10.8155 13.7282 12.9915 12.9602 14.7835C12.1282 16.5755 11.1682 18.0475 10.0802 19.1995C8.92821 20.4155 7.74421 21.3435 6.52821 21.9835C5.31221 22.6875 4.25621 23.1995 3.36021 23.5195L0.288213 18.3355C1.56821 17.8235 2.65621 16.9915 3.55221 15.8395C4.44821 14.7515 4.96021 13.5675 5.08821 12.2875C3.80821 12.2875 2.65621 11.7115 1.63221 10.5595C0.544215 9.47153 0.000214174 7.99953 0.000214011 6.14353ZM16.6082 6.14353C16.6082 4.28753 17.2482 2.78353 18.5282 1.63153C19.7442 0.543532 21.2802 -0.000468382 23.1362 -0.000468545C25.5042 -0.000468752 27.3602 0.735531 28.7042 2.20753C30.0482 3.74353 30.7202 5.75953 30.7202 8.25553C30.7202 10.8155 30.3362 12.9915 29.5682 14.7835C28.7362 16.5755 27.7762 18.0475 26.6882 19.1995C25.5362 20.4155 24.3522 21.3435 23.1362 21.9835C21.9202 22.6875 20.8642 23.1995 19.9682 23.5195L16.8962 18.3355C18.1762 17.8235 19.2642 16.9915 20.1602 15.8395C21.0562 14.7515 21.5682 13.5675 21.6962 12.2875C20.4162 12.2875 19.2642 11.7115 18<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Located in Cambridge, UK, the computational chemistry firm CuspAI has established a coalition of 45 entities focused on the identification of novel functional materials through the use of artificial intelligence (AI). The AI Materials Foundry features major tech players such as Facebook&#8217;s parent company Meta and chip manufacturer Nvidia. Additionally, it includes notable firms from [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":374988,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"Default","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[174],"class_list":["post-374987","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-source-chemistryworld-com"],"_links":{"self":[{"href":"https:\/\/wolfscientific.com\/index.php?rest_route=\/wp\/v2\/posts\/374987","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wolfscientific.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wolfscientific.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wolfscientific.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/wolfscientific.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=374987"}],"version-history":[{"count":0,"href":"https:\/\/wolfscientific.com\/index.php?rest_route=\/wp\/v2\/posts\/374987\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wolfscientific.com\/index.php?rest_route=\/wp\/v2\/media\/374988"}],"wp:attachment":[{"href":"https:\/\/wolfscientific.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=374987"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wolfscientific.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=374987"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wolfscientific.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=374987"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}