Calibration-Free Quantification and Automated Data Analysis for High-Throughput Reaction Screening

The accelerated generation of reaction data through high-throughput experimentation and automation has the potential to boost organic synthesis. However, efforts to generate diverse reaction datasets or identify generally applicable reaction con-ditions are still hampered by limitations in reaction yield quantification. In this work, we present a semi-automated screening workflow that facilitates the analysis of reaction arrays with distinct products without relying on the isolation of reference material for external calibrations. The workflow is enabled by a flexible liquid handler and parallel GC-MS and GC-PA-FID analysis while we introduce pyGecko, an open-source Python library for processing GC raw data. pyGecko offers compre-hensive analysis tools allowing for the determination of reaction outcomes of a 96-reaction array in under a minute. Our workflow’s utility is illustrated for the scope evaluation of a site-selective thiolation of halogenated heteroarenes and the comparison of four cross-coupling protocols for challenging C–N bond formations.