{"id":52323,"date":"2024-08-29T21:11:48","date_gmt":"2024-08-29T13:11:48","guid":{"rendered":"https:\/\/swarma.org\/?p=52323"},"modified":"2024-08-29T21:11:48","modified_gmt":"2024-08-29T13:11:48","slug":"%e6%96%b0ai%e9%9d%a9%e6%96%b0%e7%a7%91%e5%ad%a6%e6%8e%a2%e7%b4%a2%ef%bc%9a%e6%9d%90%e6%96%99%e8%ae%be%e8%ae%a1%e4%b8%8e%e5%88%86%e5%ad%90%e5%8f%91%e7%8e%b0%e4%b8%a8%e5%87%a0%e4%bd%95%e6%b7%b1%e5%ba%a6","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=52323","title":{"rendered":"\u65b0AI\u9769\u65b0\u79d1\u5b66\u63a2\u7d22\uff1a\u6750\u6599\u8bbe\u8ba1\u4e0e\u5206\u5b50\u53d1\u73b0\u4e28\u51e0\u4f55\u6df1\u5ea6\u5b66\u4e60\u8bfb\u4e66\u4f1a\u00b7\u5468\u516d\u76f4\u64ad"},"content":{"rendered":"
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AI4Materials Design: From Simulation to Generation<\/span><\/section>\n

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Digital transformation is revolutionizing the field of materials science, with deep learning at the forefront of this paradigm shift. This presentation will unpack the latest advancements in large-scale machine learning tools and their transformative applications in the realm of materials design. We will spotlight the power of deep graph learning, [1] active learning[2], and generative models[3-4] in constructing advanced AI emulators capable of simulating, generating, and designing new materials. Active learning streamlines the learning process by prioritizing the most informative data, whereas graph learning exploits the complex relationships within material structures, and generative models push the envelope in predicting and creating unprecedented material structures. These state-of-the-art tools are not only enhancing our predictive capabilities but also accelerating the design of innovative materials with bespoke properties. We will explore how these AI-driven strategies are being applied to real-world material challenges, demonstrate their potential to catalyze breakthroughs across various sectors, and discuss the ongoing efforts and future directions for integrating deep learning into materials science to foster interdisciplinary collaborations and drive further advancements in this dynamic and critical field.<\/span><\/section>\n


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