{"id":131687,"date":"2024-11-18T18:30:07","date_gmt":"2024-11-18T18:30:07","guid":{"rendered":"https:\/\/blogs.nvidia.com\/?p=75747"},"modified":"2024-11-18T18:30:07","modified_gmt":"2024-11-18T18:30:07","slug":"from-algorithms-to-atoms-nvidia-alchemi-nim-catalyzes-sustainable-materials-research-for-ev-batteries-solar-panels-and-more-2","status":"publish","type":"post","link":"http:\/\/webdomino.net\/index.php\/nvidia\/from-algorithms-to-atoms-nvidia-alchemi-nim-catalyzes-sustainable-materials-research-for-ev-batteries-solar-panels-and-more-2\/","title":{"rendered":"From Algorithms to Atoms: NVIDIA ALCHEMI NIM Catalyzes Sustainable Materials Research for EV Batteries, Solar Panels and More"},"content":{"rendered":"<div id=\"bsf_rt_marker\"><\/div><p>More than <a  href=\"https:\/\/www.ifc.org\/content\/dam\/ifc\/doc\/mgrt\/ifc-sectornote-outlookforchemicals-final.pdf\">96%<\/a> of all manufactured goods \u2014 ranging from everyday products, like laundry detergent and food packaging, to advanced industrial components, such as semiconductors, batteries and solar panels \u2014 rely on chemicals that cannot be replaced with alternative materials.<\/p>\n<p>With AI and the latest technological advancements, researchers and developers are studying ways to create novel materials that could address the world\u2019s toughest challenges, such as energy storage and environmental remediation.<\/p>\n<p>Announced today at the <a  href=\"https:\/\/www.nvidia.com\/en-us\/events\/supercomputing\/?srsltid=AfmBOoosUwbNk4vUO_xaXF7Cc57yrUx_XmQuBNV324iojdsIxD770XDU\">Supercomputing 2024<\/a> conference in Atlanta, the NVIDIA ALCHEMI <a  href=\"https:\/\/www.nvidia.com\/en-us\/ai\/\">NIM microservice<\/a> accelerates such research by optimizing AI inference for chemical simulations that could lead to more efficient and sustainable materials to support the renewable energy transition.<\/p>\n<p>It\u2019s one of the many ways NVIDIA is supporting researchers, developers and enterprises to boost energy and resource efficiency in their workflows, including to meet requirements aligned with the global <a  href=\"https:\/\/www.net-zero-initiative.com\/en\">Net Zero Initiative<\/a>.<\/p>\n<h2><b>NVIDIA ALCHEMI for Material and Chemical Simulations<\/b><\/h2>\n<p>Exploring the universe of potential materials, using the nearly infinite combinations of chemicals \u2014 each with unique characteristics \u2014 can be extremely complex and time consuming. Novel materials are typically discovered through laborious, trial-and-error synthesis and testing in a traditional lab.<\/p>\n<p>Many of today\u2019s plastics, for example, are still based on material discoveries made in the mid-1900s.<\/p>\n<p>More recently, AI has emerged as a promising accelerant for chemicals and materials innovation.<\/p>\n<p>With the new ALCHEMI NIM microservice, researchers can test chemical compounds and material stability in simulation, in a virtual AI lab, which reduces costs, energy consumption and time to discovery.<\/p>\n<p>For example, running <a  href=\"https:\/\/arxiv.org\/abs\/2401.00096\">MACE-MP-0<\/a>, a pretrained foundation model for materials chemistry, on an <a  href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/h100\/\">NVIDIA H100 Tensor Core GPU<\/a>, the new NIM microservice speeds evaluations of a potential composition\u2019s simulated long-term stability 100x. The below figure shows a 25x speedup from using the NVIDIA Warp Python framework for high-performance simulation, followed by a 4x speedup with in-flight batching. All in all, evaluating 16 million structures would have taken months \u2014 with the NIM microservice, it can be done in just hours.<\/p>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"aligncenter size-full wp-image-75750\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/11\/alchemi-nim-chart.jpg\" alt=\"\" width=\"1999\" height=\"791\" srcset=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/11\/alchemi-nim-chart.jpg 1999w, https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/11\/alchemi-nim-chart-960x380.jpg 960w, https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/11\/alchemi-nim-chart-1680x665.jpg 1680w, https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/11\/alchemi-nim-chart-1280x506.jpg 1280w, https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/11\/alchemi-nim-chart-1536x608.jpg 1536w\" sizes=\"(max-width: 1999px) 100vw, 1999px\" \/><\/p>\n<p>By letting scientists examine more structures in less time, the NIM microservice can boost research on materials for use with solar and electric batteries, for example, to bolster the renewable energy transition.<\/p>\n<p>NVIDIA also plans to release NIM microservices that can be used to simulate the manufacturability of novel materials \u2014 to determine how they might be brought from test tubes into the real world in the form of batteries, solar panels, fertilizers, pesticides and other essential products that can contribute to a healthier, greener planet.<\/p>\n<p><a  href=\"https:\/\/www.ses.ai\/\">SES AI<\/a>, a leading developer of lithium-metal batteries, is using the NVIDIA ALCHEMI NIM microservice with the <a  href=\"https:\/\/chemrxiv.org\/engage\/chemrxiv\/article-details\/6525b39e8bab5d2055123f75\">AIMNet2<\/a> model to accelerate the identification of electrolyte materials used for electric vehicles.<\/p>\n<p>\u201cSES AI is dedicated to advancing lithium battery technology through AI-accelerated material discovery, using our Molecular Universe Project to explore and identify promising candidates for lithium metal electrolyte discovery,\u201d said Qichao Hu, CEO of SES AI. \u201cUsing the ALCHEMI NIM microservice with AIMNet2 could drastically improve our ability to map molecular properties, reducing time and costs significantly and accelerating innovation.\u201d<\/p>\n<p>SES AI recently mapped 100,000 molecules in half a day, with the potential to achieve this in under an hour using ALCHEMI. This signals how the microservice is poised to have a transformative impact on material screening efficiency.<\/p>\n<p>Looking ahead, SES AI aims to map the properties of up to 10 billion molecules within the next couple of years, pushing the boundaries of AI-driven, high-throughput discovery.<\/p>\n<p>The new microservice will soon be available for researchers to test for free through the <a  href=\"https:\/\/catalog.ngc.nvidia.com\/\">NVIDIA NGC<\/a> catalog \u2014<a  href=\"https:\/\/www.nvidia.com\/en-us\/content\/g\/alchemi-nim\/\"> be notified<\/a> of ALCHEMI\u2019s launch. It will also be downloadable from <a  href=\"http:\/\/build.nvidia.com\/\">build.nvidia.com<\/a>, and the production-grade NIM microservice will be offered through the <a  href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/products\/ai-enterprise\/?srsltid=AfmBOooICojeCS4rx5Uh8gOlO518zYqHmdh6fYyt9dKDvzJxhTPZMFX2\">NVIDIA AI Enterprise<\/a> software platform.<\/p>\n<p><i>Learn more about the <\/i><a  href=\"https:\/\/nvidia.slack.com\/archives\/C080X05V63Z\/p1731947161451579\"><i>NVIDIA ALCHEMI NIM microservice<\/i><\/a><i>, <\/i><i>and hear the latest on how AI and supercomputing are supercharging researchers and developers\u2019 workflows by joining <\/i><a  href=\"https:\/\/www.nvidia.com\/en-us\/events\/supercomputing\/?srsltid=AfmBOoosUwbNk4vUO_xaXF7Cc57yrUx_XmQuBNV324iojdsIxD770XDU\"><i>NVIDIA at SC24<\/i><\/a><i>, running through Friday, Nov. 22.<\/i><\/p>\n<p><i>See<\/i> <a  href=\"https:\/\/www.nvidia.com\/en-us\/about-nvidia\/legal-info\/\"><i>notice<\/i><\/a><i> regarding software product information.<\/i><\/p>\n","protected":false},"excerpt":{"rendered":"<p>More than 96% of all manufactured goods \u2014 ranging from everyday products, like laundry detergent and food packaging, to advanced industrial components, such as semiconductors, batteries and solar panels \u2014 rely on chemicals that cannot be replaced with alternative materials. With AI and the latest technological advancements, researchers and developers are studying ways to create\t<a class=\"read-more\" href=\"https:\/\/blogs.nvidia.com\/blog\/alchemi-nim\/\"><br \/>\n\t\tRead Article\t\t<span data-icon=\"y\"><\/span><br \/>\n\t<\/a><\/p>\n","protected":false},"author":127,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[343],"tags":[4223,49,4247,41,351,12142,13654,13647,166,13543,2659,297,157],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>From Algorithms to Atoms: NVIDIA ALCHEMI NIM Catalyzes Sustainable Materials Research for EV Batteries, Solar Panels and More - WebDomino.NET<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/webdomino.net\/index.php\/nvidia\/from-algorithms-to-atoms-nvidia-alchemi-nim-catalyzes-sustainable-materials-research-for-ev-batteries-solar-panels-and-more-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"From Algorithms to Atoms: NVIDIA ALCHEMI NIM Catalyzes Sustainable Materials Research for EV Batteries, Solar Panels and More - WebDomino.NET\" \/>\n<meta property=\"og:description\" content=\"More than 96% of all manufactured goods \u2014 ranging from everyday products, like laundry detergent and food packaging, to advanced industrial components, such as semiconductors, batteries and solar panels \u2014 rely on chemicals that cannot be replaced with alternative materials. 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