自动化图书馆生成和随机量化使协调化学中的多样性发现成为可能
Daniel J Kowalski1, Catriona M MacGregor1, De-Liang Long1
1School of Chemistry, University of Glasgow, Glasgow G12 8QQ, United Kingdom.
Journal of the American Chemical Society
|January 17, 2023
概括
在化学领域,自动化图书馆生成加速了发现. 这项研究引入了使用贝叶斯优化和质谱学的新的工作流程来探索化学空间,使材料发现中的"工程偶然性"成为可能.
科学领域:
- 协调化学
- 自动化实验
- 化学图书馆生成
背景情况:
- 高质量的化学库对于发现新材料,新方法和新模型至关重要.
- 在化学研究中,有效和高效地创建这样的图书馆仍然是一个重大挑战.
研究的目的:
- 使用自动化硬件展示图书馆生成工作流程的自动化.
- 通过将贝叶斯优化与新量化结合起来,开发一个新的工作流程来预测图书馆的形成.
- 探索有针对性的合成和库的化学和工艺空间.
主要方法:
- 使用自动化硬件,包括Chemputer,用于图书馆生成实验.
- 采用以目标为导向的协调复合体来验证合成操作.
- 实现了贝叶斯优化与高斯过程替代模型的定向探索.
- 使用质谱数据来指导寻找新化学实体的量化新奇性.
主要成果:
- 在协调化学中成功自动化关键工作流程.
- 在定义的化学和工艺空间内生成专注的库.
- 开发和验证了一个新的工作流程,用于寻找图书馆的形成,展示了有针对性的探索.
- 观察到意想不到的化物复合物的形成, 展示了"工程偶然性".
结论:
- 开发的自动化工作流程有效地指导化学过程空间的探索.
- 这种方法通过在搜索过程中"工程偶然性"来促进新化合物的发现.
- 通过自动化和智能化图书馆生成, 该方法为加速材料发现提供了强大的工具.
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