Automation of Controlled/Living Radical Polymerization

• Main Authors: Matthew Tamasi, Shashank Kosuri, Jason DiStefano, Robert Chapman, Adam J. Gormley
• Format: Article
• Language: English
• Published: Wiley 2020-02-01
• Series: Advanced Intelligent Systems
• Subjects: automation; high throughput; oxygen tolerant; polymers; reversible addition–fragmentation chain transfer
• Online Access: https://doi.org/10.1002/aisy.201900126

Controlled/living radical polymerization (CLRP) techniques are widely utilized to synthesize advanced and controlled synthetic polymers for chemical and biological applications. While automation has long stood as a high‐throughput (HTP) research tool to increase productivity as well as synthetic/analytical reliability and precision, oxygen intolerance of CLRP has limited the widespread adoption of these systems. Recently, however, oxygen‐tolerant CLRP techniques, such as oxygen‐tolerant photoinduced electron/energy transfer–reversible addition–fragmentation chain transfer (PET–RAFT), enzyme degassing of RAFT (Enz‐RAFT), and atom‐transfer radical polymerization (ATRP), have emerged. Herein, the use of a Hamilton MLSTARlet liquid handling robot for automating CLRP reactions is demonstrated. Synthesis processes are developed using Python and used to automate reagent handling, dispensing sequences, and synthesis steps required to create homopolymers, random heteropolymers, and block copolymers in 96‐well plates, as well as postpolymerization modifications. Using this approach, the synergy between highly customizable liquid handling robotics and oxygen‐tolerant CLRP to automate advanced polymer synthesis for HTP and combinatorial polymer research is demonstrated.