无校准反应产量量定量通过HPLC与灭绝系数的机器学习模型
Matthew A McDonald1, Brent A Koscher1, Richard B Canty1
1Department of Chemical Engineering, Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA kfjensen@mit.edu.
Chemical science
|July 5, 2024
概括
这项研究引入了一种新的,无校准的方法,用于使用HPLC量化反应产量. 它将机器学习与光谱数据相结合,消除了自动化化学合成中纯标准的需要.
科学领域:
- 分析化学 分析化学
- 有机合成 有机合成
- 计算化学的计算化学
背景情况:
- 精确的反应产量确定对于化学合成优化至关重要.
- 传统方法依赖于校准标准,这些标准很难为低产量或小规模反应做好准备.
- 自动化合成平台需要无校准的量化方法以提高效率.
研究的目的:
- 开发一种方法来通过HPLC量化反应产量,而不需要纯校准标准.
- 为了实现自动反应优化和表征.
主要方法:
- 开发了一种机器学习模型来估计摩尔灭绝系数.
- 紫外线吸收和质谱与ML模型相结合.
- 综合方法在各种药物和工艺化学反应上得到了验证.
主要成果:
- 开发的方法准确量化反应产量,没有产品隔离或纯标准.
- 在各种反应类型中成功应用,包括胺基合和交叉合.
- 与自动化合成平台相结合,已经证明了它的实用性.
结论:
- 这种无校准的HPLC方法显著简化了自动化工合成的产量确定.
- 它克服了传统的基于校准的方法的局限性,特别是对于具有挑战性的反应.
- 在合成化学中促进自主发现,表征和优化.
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