Automated High-Throughput and Dynamic Combinatorial Screening of Self-Sorted Molecular Organic Assemblies

A robotic lab assistant called the OT-2 Opentrons now runs 48 chemical reactions in parallel, searching for new porous organic cages—molecular structures with hollow interiors that can trap gases. The problem is that designing these cages has been painfully slow. Small tweaks to existing recipes rarely work, and each failed attempt wastes weeks of manual labour. The team automated the trial-and-error process, but that created a new bottleneck: analysing the flood of data from 48 simultaneous experiments took too long by hand. This research is fundamental science—it explores how to build and discover new molecular architectures efficiently. The immediate payoff is a faster, more systematic way to find porous organic cages. If the approach proves general, it could accelerate the discovery of materials for gas storage (capturing hydrogen or carbon dioxide), gas separation (purifying industrial feedstocks), or catalysis (speeding up chemical reactions). These are industrial processes that quietly underpin everything from fertiliser production to energy storage. No direct consumer product emerges from this work, but the chemical industry’s ability to make better sieves and sponges at the molecular level depends on exactly this kind of automated screening.