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Oxygen tolerant polymerizations including Photoinduced Electron/Energy Transfer-Reversible Addition–Fragmentation Chain-Transfer (PET-RAFT) polymerization allow for high-throughput synthesis of diverse polymer architectures on the benchtop in parallel. Recent developments have further increased throughput using liquid handling robotics to automate reagent handling and dispensing into well plates thus enabling the combinatorial synthesis of large polymer libraries. Although liquid handling robotics can enable automated polymer reagent dispensing in well plates, photoinitiation and reaction monitoring require automation to provide a platform that enables the reliable and robust synthesis of various polymer compositions in high-throughput where polymers with desired molecular weights and low dispersity are obtained. Here, we describe the development of a robotic platform to fully automate PET-RAFT polymerizations and provide individual control of reactions performed in well plates. On our platform, reagents are automatically dispensed in well plates, photoinitiated in individual wells with a custom-designed lightbox until the polymerizations are complete, and monitored online in real-time by tracking fluorescence intensities on a fluorescence plate reader, with well plate transfers between instruments occurring via a robotic arm. We found that this platform enabled robust parallel polymer synthesis of both acrylate and acrylamide homopolymers and copolymers, with high monomer conversions and low dispersity. The successful polymerizations obtained on this platform make it an efficient tool for combinatorial polymer chemistry. In addition, with the inclusion of machine learning protocols to help navigate the polymer space towards specific properties of interest, this robotic platform can ultimately become a self-driving lab that can dispense, synthesize, and monitor large polymer libraries.
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Typology Development for Synthetic Chemistry Sub-Tasks: Towards Human-Robot Collaboration Task Design in the Wet Lab
Chemical manufacturing is a growing field that contributes to many industries and employs tens of thousands of researchers in wet labs. Automation tools for synthetic chemistry are of interest not only for their potential impact on efficiency and productivity, but also on human resources and safety, since synthetic chemistry poses a number of occupational risks and is largely inaccessible to researchers with physical disabilities. Currently, most automation tools for synthetic chemistry are either designed to perform highly specialized tasks or they are designed as closed-loop systems with minimal interaction between human and machine during a synthesis procedure. We are pursuing an alternative, human-centered approach to robotic tools for synthetic chemistry, in which general-purpose collaborative robots (cobots) offer diverse forms of support to human researchers in the lab. In order to design frameworks for productive scientist-cobot collaborations, we need a deep understanding of the task space in synthetic chemistry labs and the impact of these various activities on the researchers. Based on observations and surveys from a group of experimental scientists, we have identified and analyzed 10 manual tasks commonly performed by researchers in the wet lab, each of which may be broken down into a sequence of sub-tasks. We conducted an in-depth analysis of the two most frequently performed sub-tasks: liquids dispensing and solids handling. Through subcoding, we identified 40 liquid dispensing typologies and 18 solid handling typologies, and evaluated the burden associated with each of these sub-tasks using the NASA TLX. These data will be of value for the design of human-centered automation tools that support, rather than displace, researchers performing manual tasks in the lab, in order to foster a safer and more accessible lab environment.
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- Award ID(s):
- 2222952
- PAR ID:
- 10615163
- Publisher / Repository:
- American Society of Mechanical Engineers
- Date Published:
- ISBN:
- 978-0-7918-8840-7
- Format(s):
- Medium: X
- Location:
- Washington, DC, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1115/DETC2024-142677
