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English(EN) Agentic-MatriBO: Capability-Compiled Agentic Bayesian Optimization for Materials and Chemical Design

新的智能贝叶斯优化框架增强材料设计

研究人员开发了Agentic-MatriBO,一个用于贝叶斯优化的新框架,旨在改进材料和化学设计。该系统使用大型语言模型来调整和优化合成、表征或模拟过程。Agentic-MatriBO包含一个用于提出优化配方的语言策略,一个用于根据能力目录检查提议的编译器,以及一个用于验证的执行层。该框架在四个数据集上与八个基线进行了比较,在各项任务中均显示出优越的平均终点质量,并在COF数据集上提高了累积质量。 AI

影响 该框架可以通过优化实验设计来加速材料科学和化学领域的发现。

排序理由 详细介绍新计算框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

新的智能贝叶斯优化框架增强材料设计

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详细介绍新计算框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yu Zeng, Yuchuan Chen, Ziyue Zhang, Zijian Wei, Yanyi Su, Guojiang Zhao, Hongshuai Wang, Zhifeng Gao ·

    Agentic-MatriBO:用于材料和化学设计的、能力编译的 Agentic 贝叶斯优化

    arXiv:2610.17832v1 Announce Type: cross Abstract: Materials and chemical optimization must choose the next synthesis, characterization, or high-fidelity simulation from sequential observations under a limited budget. Large language models can use task knowledge to propose adjustm…