{"id":3182,"date":"2025-10-19T10:01:00","date_gmt":"2025-10-19T08:01:00","guid":{"rendered":"https:\/\/kraftscharling.dk\/?p=3182"},"modified":"2025-09-05T08:16:31","modified_gmt":"2025-09-05T06:16:31","slug":"ais-effect-on-materials-research-and-quantum-chemistry","status":"publish","type":"post","link":"https:\/\/kraftscharling.dk\/en\/ais-effekt-pa-materialeforskning-og-kvantekemi\/","title":{"rendered":"AI\u2019s effect on materials research and quantum chemistry"},"content":{"rendered":"<p class=\"wp-block-paragraph\"><em>AI\u2019s combination of pattern recognition and immense computational power offers major potential effect on materials research and quantum chemistry. The opportunities even carry geopolitical significance.<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">This blog post is the eighth in the series on AI\u2019s disruption of innovation<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">This blog entry is the eighth in a series about the disruptive impact of a technology based on a new form of intelligence that is self-learning, universally enabling, and allows for deep customization:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/kraftscharling.dk\/en\/where-does-ai-impact-today\/\">Where does AI impact today?<\/a><\/li>\n\n\n\n<li>What is new and disruptive about AI?<\/li>\n\n\n\n<li>AI\u2019s effect on robotics and experimental automation<\/li>\n\n\n\n<li>AI\u2019s effect on climate and meteorological research<\/li>\n\n\n\n<li>AIs impact on social sciences<\/li>\n\n\n\n<li>AIs impact on education and mental health<\/li>\n\n\n\n<li>AI\u2019s impact on biotechnology and pharmaceuticals<\/li>\n\n\n\n<li><strong>AI\u2019s effect on materials research and quantum chemistry<\/strong><\/li>\n\n\n\n<li>AI\u2019s effect on theoretical physics and mathematics<\/li>\n\n\n\n<li>What should investment strategies in AI take into account?<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">AI is expected to accelerate materials development significantly<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">AI accelerates the development of new materials with greater durability, higher tolerances, and lower environmental impact. The current push comes from the need to reduce geopolitical risks in supply chains. As a result, development times are simultaneously shrinking to a fraction of today\u2019s.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Historically, new materials have mostly been discovered through trial and error. For instance, Thomas Edison tested around 6,000 different materials for his lightbulb. Going forward, generative AI makes \u201cinverse design\u201d possible, where the desired properties of a material are specified up front. Likewise, predictive AI can sift through vast databases to identify candidate replacements for existing materials.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">There is a need for new materials ...<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The commercial perspectives are large and growing due to geopolitical uncertainties, increasing tolerance requirements, and environmental concerns.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Geopolitically,<\/strong> global supply chains are fragmenting. <a href=\"http:\/\/Geopolitisk fragmenterer verdens forsyningsk\u00e6der. Afbrud af Neodymium forsyninger er allerede i dag en reel og kritisk risiko for alle virksomheder, der anvender elektronik (inds\u00e6t link til https:\/\/www.washingtonpost.com\/business\/2025\/06\/22\/us-rare-earth-neodymium-magnets-china\/?utm_source=chatgpt.com).\">Disruptions in neodymium supply, for instance, are already today a real and critical risk for all companies that use electronics.<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Tolerance requirements<\/strong> are also rising. This applies to next-generation chips (beyond silicon or gallium arsenide), batteries (anode, cathode, and electrolyte alike), solar cells, climate-resilient construction materials, and more.&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>To circumvent the effects of U.S. sanctions on advanced computer chips, China has been particularly active in developing 2D wafers of indium selenide <a href=\"https:\/\/www.science.org\/doi\/10.1126\/science.adu3803\">, which can be layered and folded.<\/a>AI technologies made this rapid progress possible. Although indium selenide lacks immediate commercial advantages, it has theoretically eliminated China\u2019s vulnerability to chip supply chain disruptions.<\/li>\n\n\n\n<li>Similarly, ASML and IMEC in Belgium are focusing on photonics-based interposers and CFETs, which will eventually phase out silicon, and with it dependency on the U.S. (Spruce Pine Mine), though only in the longer term.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">It has also become increasingly necessary to develop recyclable or biodegradable materials to reduce <strong>environmental and climate impacts<\/strong>. Most extraction and refining processes for raw materials remain highly polluting to local environments, often with radioactive contamination.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AI models have, for example, <a href=\"https:\/\/www.frontiersin.org\/journals\/energy-research\/articles\/10.3389\/fenrg.2025.1569716\/abstract?utm_source=chatgpt.com\">proven useful in integrating vast amounts of geological data for companies like BHP and Rio Tinto<\/a>.\u00a0<\/li>\n\n\n\n<li>They have also significantly <a href=\"https:\/\/kraftscharling.dk\/en\/geothermal-energy-breakthrough\/\">increased the efficiency and potential of geothermal systems<\/a>.\u00a0<\/li>\n\n\n\n<li>Finally, <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0012825224002691?utm_source=chatgpt.com\">research in Finland and Canada has applied AI to develop bacterial consortia<\/a>capable of isolating copper and rare earth elements.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">\u2026 which AI is precisely needed to develop<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Inverse design and predictive screening have become possible thanks to AI\u2019s massive computational power, morphogenetic capabilities, and self-learning. This allows for a faster path from ideas to candidate materials. In 2023, for instance, Google DeepMind\u2019s GNoME identified over 2.2 million new crystal structures, 380,000 of which are considered stable enough for practical use. IBM and MIT have likewise been highly active in this field. The same methods have been applied to <a href=\"https:\/\/pubs.acs.org\/doi\/10.1021\/acs.est.4c08298?utm_source=chatgpt.com\">machine intelligence, guided design of polymer membranes<\/a> and, for example, <a href=\"https:\/\/arxiv.org\/abs\/2108.12019?utm_source=chatgpt.com\">high-temperature alloys<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AI can simulate material tolerances and behavior under extreme conditions, drastically reducing development timelines. In the 1980s, lithium-ion technology took 10\u201315 years to mature. By contrast, at the end of 2023, Berkeley Lab simulated over 100,000 potential electrolytes. The TRL 1\u20134 stage took only a few weeks, from which a few hundred candidate materials were selected for TRL 5\u20138 development. Similarly, in early 2024, Microsoft and PNNL developed a solid-state battery up to TRL 5. The entire process took just 80 hours, completed over a single weekend.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nanomaterials are another key focus area. In spring, for example, Caltech and the University of Toronto developed a simulated lattice material five times stronger than titanium but lighter in weight. NVidia is also heavily active here, as nanophotonics are central to next-generation chips.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">This is also relevant for Energy Production and Climate Transition ...<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">New materials are also being designed for carbon capture. AI has identified synthetic rock-dust compounds that can be spread on farmland to sequester CO\u2082 while enriching soil with essential minerals.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Similarly, the efficiency of solar cells is expected to multiply thanks to <a href=\"https:\/\/gizmodo.com\/researchers-harness-black-metal-for-solar-power-boost-2000642794\">new \u201cblack\u201d metal composites, which AI has shown to be practically viable<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">... and for Quantum Chemistry and Quantum Computers<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Quantum chemical calculations are highly precise and therefore extremely time- and resource-intensive on traditional supercomputers. Quantum computers are closely tied to materials research, where progress depends on advances in superconductors and nanotechnology (see below). Microsoft, Amazon, and Google have each launched new qubit technologies (Majorana, Ozelot, Willow), with their own distinctive features, strengths, and weaknesses.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But software development is especially lagging behind. AI\u2019s unique capabilities are critical for developing software to run simulations of quantum-physical systems. These were previously computationally unrealistic but are essential to accelerating the development of quantum chips and their software layers. <a href=\"https:\/\/www.adlittle.com\/en\/insights\/viewpoints\/quantum-summer-or-winter\">Today, 3 out of 4 experts estimate that quantum computers will reach commercial scale (TRL 8\u20139) by 2032 at the latest<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The field is therefore of both strategic and geopolitical significance ...<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The geopolitical uncertainties of recent years have highlighted the world\u2019s supply dependencies. In many cases, these risks are critical. As a result, ambitions have risen to replace natural materials that are only available, mined, or refined in a handful of countries. This affects, for instance, the design of new materials for superconductors, lightweight composites, battery materials, and magnetic applications.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Over the past 4\u20136 years, the U.S. Department of Defense has conducted intensive research into alternative compounds to rare earths. This includes substitutes for super-magnetic neodymium, a cornerstone in all electrical products (see above). This dependency is one reason why one of the first investments of the U.S.\u2019s new Sovereign Wealth Fund was in MP Materials. The company owns a California mine that was the world\u2019s largest rare earth producer until the 1990s, when China took over the role.<\/li>\n\n\n\n<li>Meanwhile, companies like Hitachi Metals, Niron Magnetics, Denso, Toshiba, and several Indian firms are developing alternatives to rare earths\u2014especially neodymium. <a href=\"https:\/\/www.reuters.com\/sustainability\/climate-energy\/siemens-gamesa-chinese-magnet-suppliers-discuss-european-production-coo-says-2025-06-26\/?utm_source=chatgpt.com\">The EU is also active with PASSENGER projects under the EU Critical Raw Materials Act.<\/a>.<\/li>\n\n\n\n<li>Tesla and CATL, for their part, use AI technologies to identify substitutes for cobalt and nickel, most of which are currently extracted in the DR Congo, Russia, and Indonesia.<\/li>\n\n\n\n<li>AI models also help optimize the design of thin-film materials (such as perovskites, i.e. organic solar cells), which can be manufactured without rare earths and produced on nearly every continent.<\/li>\n\n\n\n<li>AI models likewise support the design of next-generation chips, free of silicon (dominated by the U.S.) or gallium\/arsenide (dominated by China).<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">... and thus many are very active, including Big Tech<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Big Tech is highly engaged in this field. Google\u2019s DeepMind has developed GNoME and AlphaFold. Microsoft is focused on quantum chemistry (Azure Quantum) and collaborates with PNNL. IBM works on designing crystals, polymers, and catalysts, as well as new materials for quantum computers. NVidia is concentrating on hardware and software platforms, with partnerships particularly in Big Pharma.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Among industrial companies, BASF, Dow, DuPont, and 3M are generally far ahead. Among academic institutions, Lawrence Berkeley National Lab is especially active in developing new materials. In nanomaterials, quantum chemistry, and fusion energy, leading players include MIT, Caltech, the University of Toronto, and Carnegie Mellon University. In Europe, the University of Oulu in Finland, Pforzheim University, and Cambridge are particularly noteworthy.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"741\" height=\"1024\" src=\"https:\/\/kraftscharling.dk\/wp-content\/uploads\/Materialeforskning-superleder-kvantecomputer-741x1024.png\" alt=\"\" class=\"wp-image-3187\" srcset=\"\" sizes=\"(max-width: 741px) 100vw, 741px\" data-srcset=\"\" \/><\/figure>","protected":false},"excerpt":{"rendered":"<p>AIs kombination af m\u00f8nstergenkendelse og enorm regnekraft giver stor mulig effekt p\u00e5 materialeforskning og kvantekemi. Potentialerne har endda geopolitisk v\u00e6rdi. Dette blog indl\u00e6g er nummer otte i r\u00e6kken om AIs disruption p\u00e5 innovation Dette blog indl\u00e6g er nummer otte i r\u00e6kken om den disruptive effekt af en teknologi, der bygger p\u00e5 en ny form for [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":3183,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[24,35],"tags":[],"class_list":["post-3182","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-topledelse"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AIs effekt p\u00e5 materialeforskning og kvantekemi - Kraft Scharling<\/title>\n<meta name=\"description\" content=\"AIs kombination af m\u00f8nstergenkendelse og enorm regnekraft giver stor mulig effekt p\u00e5 materialeforskning og kvantekemi\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/kraftscharling.dk\/en\/ais-effect-on-materials-research-and-quantum-chemistry\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AIs effekt p\u00e5 materialeforskning og kvantekemi - 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