.png){kind=icon}
返回
Precise Polymer Synthesis by Autonomous Self-Optimizing Flow Reactors
.png){kind=icon}
PRE
AI
DOI：10.1002/anie.201810384.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A novel continuous flow system for automated high-throughput screening, autonomous optimization, and enhanced process control of polymerizations was developed. The computer-controlled platform comprises a flow reactor coupled to size exclusion chromatography (SEC). Molecular weight distributions are measured online and used by a machine-learning algorithm to self-optimize reactions towards a programmed molecular weight by dynamically varying reaction parameters (i.e. residence time, monomer concentration, and control agent/initiator concentration). The autonomous platform allows targeting of molecular weights in a reproducible manner with unprecedented accuracy (<2.5 % deviation from pre-selected goal) for both thermal and light-induced reactions. For the first time, polymers with predefined molecular weights can be custom made under optimal reaction conditions in an automated, high-throughput flow synthesis approach with outstanding reproducibility.
Keyword:
flow reactors
machine learning
monomers
polymers
synthetic methods
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
16.9
论文数:
5.7W
被引数:
53.0W
机构
引用论文
Photoinduced Organocatalyzed Atom Transfer Radical Polymerization Using Continuous Flow.png)
MACROMOLECULES
OAAI
MACROMOLECULESIF5.2
OAAI分享收藏分享收藏分享收藏
查看更多内容