pyGecko

This illustration was made for an article that presents a novel approach to streamline the process of analyzing chemical reactions through a semi-automated workflow designed for high-throughput experimentation in organic chemistry. The authors developed a system that allows for the rapid quantification of reaction outcomes without needing to isolate reference materials, which is a common limitation in traditional methods. This workflow utilizes a flexible liquid handling system combined with advanced gas chromatography techniques for analyzing multiple reactions simultaneously.

A key feature of this work is the introduction of an open-source Python library named pyGecko, which facilitates the automated processing of raw data from gas chromatography mass spectrometry (GC-MS) and flame ionization detection (GC-FID). With pyGecko, researchers can efficiently analyze the results of up to 96 reactions in under a minute, making it significantly faster than previous methods.
The article demonstrates the effectiveness of this workflow by applying it to specific chemical reactions, such as site-selective thiolation of halogenated heteroarenes and various cross-coupling protocols. The results show that the system not only enhances the speed of data collection and analysis but also maintains high accuracy in quantifying reaction yields.

This work represents a significant advancement in the field of organic synthesis, enabling researchers to explore a broader range of chemical reactions with greater efficiency.