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English(EN) Adaptive catalyst discovery emerges from composable scientific intelligence

AI框架通过可重用知识加速催化剂发现

研究人员开发了可组合催化智能(CatAI),这是一个旨在加速催化剂发现的模块化AI框架。该系统从海量的结构-性质关系数据集中学习,并将它们组织成可用于特定任务的可重用物理化学编码器。与现有模型相比,CatAI在预测误差方面有了显著降低,并得到了实验验证,从而发现了一种用于聚合物合成的新型催化剂,其活性显著提高;以及另一种用于C-O偶联反应的催化剂,其性能优于传统体系。 AI

影响 通过支持可重用的AI组件来解决复杂问题,从而加速科学发现。

排序理由 该条目是一篇学术论文,详细介绍了一个用于科学发现的新AI框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI框架通过可重用知识加速催化剂发现

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该条目是一篇学术论文,详细介绍了一个用于科学发现的新AI框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Wentao Li, Qilong Cai, Qi Lei, Jinxing Chen, Ruixuan Chen, Jiangjie Qiu, Botian Wang, Kai Zhao, Honghao Chen, Leyi Zhao, Zemeng Wang, Yijun Li, Jun Yin, Fangfang Li, Hongxuan Liu, Yingdong Lu, Yawen Ouyang, Manu Suvarna, Wei-Ying Ma, Ya-Qin Zhang, Kostya… ·

    可组合科学智能催生自适应催化剂发现

    arXiv:2611.13536v1 Announce Type: new Abstract: Catalysis underpins chemical manufacturing, yet knowledge for catalyst design remains dispersed across experimental observations, computational data and catalysis subdisciplines. To overcome this challenge, we present Composable Cat…