Previously, we disclosed the development of a software platform to connect and coordinate various disparate laboratory devices (e.g., pumps, tanks, pipes, sensors, and analytical equipment). This platform allows the user to construct small-scale “chemical plants” and coordinate experiments to generate datasets that will be employed in machine learning research. Furthermore, the software can employ complex control schemes such as PID controllers with feedforward or deadtime characteristics. The software platform was initially employed in the synthesis of over 400 polylactide homopolymers with a urea-based catalyst system in 5 hours. We are currently using this software platform to model and control a laboratory scale manufacturing plant for carbonate monomers. This talk will cover both the software and hardware design of the automated multi-step synthesis and purification of carbonate monomers. Attention will also be given to the development of novel laboratory liquid-liquid extraction columns- a “continuous” analog to the ubiquitous “batch” separatory funnel. Finally, we will discuss plans for the development of machine learning methods that are being built on top of the software platform.

Development and use of a software platform applied towards the automated synthesis of carbonate monomers and machine learning applications

ACS Spring 2022

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