About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
2026 Technical Division Student Poster Contest
|
| Presentation Title |
SPU-43: Optimizing Conjugated Polymer Synthesis Through Automation |
| Author(s) |
Avery Smith, Martin Seifrid, Kohen Goble, Kyle Hollars |
| On-Site Speaker (Planned) |
Avery Smith |
| Abstract Scope |
Conjugated polymers are used in biosensing, energy storage, and optoelectronics, but reliable synthesis is difficult due to side reactions and broad chain-length distributions that increase dispersity. Common methods include Suzuki and Stille polymerizations; however, Stille reactions rely on toxic organotin reagents and often produce lower molecular weights with higher dispersities. This work investigates a modified Suzuki polymerization using TMSOK under anhydrous conditions to improve control, reduce dispersity, and increase molecular weight. The project also aims to automate polymer synthesis to improve reproducibility and performance using a self-driving lab approach. Automated reactions carried out on the MEDUSA modular synthesis platform will be directly compared to conventional syntheses. Baseline polymer targets have been selected and initial conventional experiments completed. Next steps include running polymerizations on MEDUSA and applying Bayesian optimization to further improve conjugated polymer synthesis. |
| Proceedings Inclusion? |
Undecided |
| Keywords |
Machine Learning, Polymers, |