LABS: Laboratory Automation and Batch Scheduling - A Modular Open Source Python Program for the Control of Automated...

Area of Science:

• Chemical Engineering
• Laboratory Automation
• Software Development

Background:

• Automated laboratory synthesis requires flexible and customizable software solutions.
• Existing platforms often lack broad applicability or ease of customization.
• Integrating diverse lab devices into a unified system is challenging.

Purpose of the Study:

• To introduce LABS, an open-source Python-based software for orchestrating automated synthesis.
• To provide a user-friendly and highly customizable automation tool for experimental setups.
• To demonstrate the utility of LABS in optimizing flow electrolysis parameters.

Main Methods:

• Development of a Python-based software (LABS) with a user-friendly interface and flexible backend architecture.
• Integration of multiple laboratory devices for automated synthesis.
• Application of LABS to optimize flow electrolysis for oxidative coupling using design of experiments.

Main Results:

• LABS enables seamless data input, system monitoring, and device integration.
• The software facilitates easy modification of experimental parameters and routines.
• Successful optimization of electrolysis parameters for 2,4-dimethyl-phenol oxidative coupling was achieved.

Conclusions:

• LABS offers a widely applicable and customizable solution for laboratory automation.
• The software streamlines the process of setting up and controlling automated experiments.
• LABS proves effective in optimizing chemical synthesis processes, such as flow electrolysis.