{"id":1149427,"date":"2025-10-08T08:00:00","date_gmt":"2025-10-08T15:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&#038;p=1149427"},"modified":"2026-01-26T07:41:58","modified_gmt":"2026-01-26T15:41:58","slug":"materials","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/materials\/","title":{"rendered":"Materials"},"content":{"rendered":"<section class=\"mb-3 moray-highlight\">\n\t<div class=\"card-img-overlay mx-lg-0\">\n\t\t<div class=\"card-background  has-background- card-background--full-bleed\">\n\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1400\" height=\"788\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1.jpg\" class=\"attachment-full size-full\" alt=\"background pattern\" style=\"\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1.jpg 1400w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-300x169.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-1024x576.jpg 1024w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-768x432.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-1066x600.jpg 1066w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-655x368.jpg 655w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-240x135.jpg 240w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-640x360.jpg 640w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-960x540.jpg 960w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/01\/mattergen-1-1280x720.jpg 1280w\" sizes=\"auto, (max-width: 1400px) 100vw, 1400px\" \/>\t\t<\/div>\n\t\t<!-- Foreground -->\n\t\t<div class=\"card-foreground d-flex mt-md-n5 my-lg-5 px-g px-lg-0\">\n\t\t\t<!-- Container -->\n\t\t\t<div class=\"container d-flex mt-md-n5 my-lg-5 \">\n\t\t\t\t<!-- Card wrapper -->\n\t\t\t\t<div class=\"w-100 w-lg-col-5\">\n\t\t\t\t\t<!-- Card -->\n\t\t\t\t\t<div class=\"card material-md-card py-5 px-md-5\">\n\t\t\t\t\t\t<div class=\"card-body \">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/lab\/microsoft-research-ai-for-science\/\" class=\"icon-link icon-link--reverse mb-2\" data-bi-cN=\"MSR AI for Science\">\n\t\t\t\t\t\t\t\t\t<span class=\"c-glyph glyph-chevron-left\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t\t\tMSR AI for Science\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<h1 class=\"wp-block-heading\" id=\"materials\">Materials<\/h1>\n\n\n\n<p>Using AI to reshape how we design and innovate advanced materials<\/p>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\">\n<h2 class=\"wp-block-heading\" id=\"virchow\">MatterGen<\/h2>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66%\">\n<p>MatterGen is a diffusion model specifically designed for generating stable inorganic materials across the periodic table. Crucially, the model can be fine-tuned to steer the generation towards a broad range of property constraints, including desired chemistry, symmetry as well as mechanical, electronic and magnetic properties. MatterGen reaches state-of-the-art performance in the de-novo generation of novel materials, and outperforms traditional computational methods like screening for inverse design.<\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<figure class=\"wp-block-video\"><video height=\"1080\" style=\"aspect-ratio: 1920 \/ 1080;\" width=\"1920\" autoplay controls loop src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2022\/07\/2025-0-bandgap_v5.mp4\"><\/video><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<figure class=\"wp-block-video\"><video height=\"1080\" style=\"aspect-ratio: 1920 \/ 1080;\" width=\"1920\" autoplay controls loop muted src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/2025-1-bulk_v5.mp4\"><\/video><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<figure class=\"wp-block-video\"><video height=\"1080\" style=\"aspect-ratio: 1920 \/ 1080;\" width=\"1920\" autoplay controls loop muted src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/2025-3-joint_v5.mp4\"><\/video><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-pill\"><a data-bi-type=\"button\" class=\"wp-block-button__link has-white-color has-blue-background-color has-text-color has-background has-link-color wp-element-button\" href=\"https:\/\/ai.azure.com\/explore\/models\/MatterGen\/version\/1\/registry\/azureml-msr?tid=72f988bf-86f1-41af-91ab-2d7cd011db47\" target=\"_blank\" rel=\"noreferrer noopener\">MatterGen model on Azure AI Foundry<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">Nature publication<\/span>\n\t\t\t<a href=\"https:\/\/www.nature.com\/articles\/s41586-025-08628-5\" data-bi-cN=\"A generative model for inorganic materials design\" target=\"_blank\" rel=\"noopener noreferrer\" data-external-link=\"true\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>A generative model for inorganic materials design<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-open-in-new-tab\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n\n\n\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">Blog<\/span>\n\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/blog\/mattergen-a-new-paradigm-of-materials-design-with-generative-ai\/\" data-bi-cN=\"MatterGen: A new paradigm of materials design with generative AI\" data-external-link=\"false\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>MatterGen: A new paradigm of materials design with generative AI<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-chevron-right\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n\n\n\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">STORY<\/span>\n\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/story\/ai-meets-materials-discovery\/\" data-bi-cN=\"AI meets materials discovery: The vision behind MatterGen and MatterSim\" data-external-link=\"false\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>AI meets materials discovery: The vision behind MatterGen and MatterSim<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-chevron-right\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"mattersim\">MatterSim<\/h2>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66%\">\n<p>MatterSim is a deep-learning model for accurate and efficient materials simulation and property prediction over a broad range of elements, temperatures, and pressures to enable the&nbsp;<em>in silico<\/em>&nbsp;materials design. MatterSim employs deep learning to understand atomic interactions&nbsp;from the very fundamental principles of quantum mechanics, across a comprehensive spectrum of elements and conditions\u2014from 0 to 5,000 Kelvin (K), and from standard atmospheric pressure to 10,000,000 atmospheres. In our experiment, MatterSim efficiently handles simulations for a variety of materials, including metals, oxides, sulfides, halides, and their various states such as crystals, amorphous solids, and liquids. Additionally, it offers customization options for intricate prediction tasks by incorporating user-provided data.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-pill\"><a data-bi-type=\"button\" class=\"wp-block-button__link has-white-color has-blue-background-color has-text-color has-background has-link-color wp-element-button\" href=\"https:\/\/ai.azure.com\/explore\/models\/MatterSim\/version\/1\/registry\/azureml?tid=72f988bf-86f1-41af-91ab-2d7cd011db47\">MatterSim model on Azure AI Foundry<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">Blog<\/span>\n\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/blog\/mattersim-a-deep-learning-model-for-materials-under-real-world-conditions\/\" data-bi-cN=\"MatterSim: A deep-learning model for materials under real-world conditions\" data-external-link=\"false\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>MatterSim: A deep-learning model for materials under real-world conditions<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-chevron-right\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n\n\n\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">Publication<\/span>\n\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/mattersim-a-deep-learning-atomistic-model-across-elements-temperatures-and-pressures\/\" data-bi-cN=\"MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures\" data-external-link=\"false\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-chevron-right\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div style=\"padding-bottom:32px; padding-top:32px\" class=\"wp-block-msr-immersive-section alignfull row wp-block-msr-immersive-section\">\n\t\n\t<div class=\"container\">\n\t\t<div class=\"wp-block-msr-immersive-section__wrapper col-lg-11 col-xl-9 px-0 m-auto\">\n\t\t\t<h2 class=\"wp-block-heading has-text-align-center has-white-color has-text-color has-link-color wp-elements-9b29f3b10f16e11bfb68c7a30a83f686\" id=\"work-with-us-1\">Work with us<\/h2>\n\n\n\n<p class=\"has-text-align-center has-white-color has-text-color has-link-color wp-elements-88989855b724b88c8331ca9e108dbbf0\">Check out our open roles<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a data-bi-type=\"button\" class=\"wp-block-button__link has-text-align-left wp-element-button\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/materials\/opportunities\">See careers<\/a><\/div>\n<\/div>\t\t<\/div>\n\t<\/div>\n\n\t<img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"667\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2.jpg\" class=\"wp-block-msr-immersive-section__background-image\" alt=\"\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2.jpg 1000w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2-300x200.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2-768x512.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2-240x160.jpg 240w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/div>\n\n\n","protected":false},"excerpt":{"rendered":"<p>Using AI to reshape how we design and innovate advanced materials MatterGen is a diffusion model specifically designed for generating stable inorganic materials across the periodic table. Crucially, the model can be fine-tuned to steer the generation towards a broad range of property constraints, including desired chemistry, symmetry as well as mechanical, electronic and magnetic [&hellip;]<\/p>\n","protected":false},"featured_media":1123152,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-1149427","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[990378,1033005,1137375],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[990009,1031883,1117392,1120956],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Rosa De Rosa","user_id":44078,"people_section":"Section name 0","alias":"rosaderosa"},{"type":"user_nicename","display_name":"Andrew Fowler","user_id":41850,"people_section":"Section name 0","alias":"fowlerandrew"},{"type":"user_nicename","display_name":"Robert Pinsler","user_id":41725,"people_section":"Section name 0","alias":"rpinsler"},{"type":"user_nicename","display_name":"Shoko Ueda","user_id":41913,"people_section":"Section name 0","alias":"shokoueda"},{"type":"user_nicename","display_name":"Bas Veeling","user_id":41916,"people_section":"Section name 0","alias":"basveeling"},{"type":"user_nicename","display_name":"Han Yang","user_id":44006,"people_section":"Section name 0","alias":"hanyan"},{"type":"user_nicename","display_name":"Claudio Zeni","user_id":41817,"people_section":"Section name 0","alias":"claudiozeni"},{"type":"user_nicename","display_name":"Daniel Z\u00fcgner","user_id":42990,"people_section":"Section name 0","alias":"dzuegner"}],"msr_research_lab":[],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1149427","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":18,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1149427\/revisions"}],"predecessor-version":[{"id":1160833,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1149427\/revisions\/1160833"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/1123152"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1149427"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1149427"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1149427"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1149427"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=1149427"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}