Polymerization-induced self-assembly (PISA) is a versatile method to prepare nanoparticles of various morphology. Traditionally, nanoparticles are prepared via self-assembly of pre-formed polymers in H2O. Rigorous optimization is often required in these systems, involving iterative cycles of polymer synthesis, self-assembly, and evaluation of the self-assembled morphologies. PISA offers an elegant solution to the tedious procedures of conventional self-assembly by forming the particles in situ as the polymerization progresses.
Automated executions of chemical synthesis and discovery has risen as a critical enabling technology. New tools combining advanced robotics with experiment planning by machine learning, known as self-driving labs, are now attainable. However, the optimal deployment of these technologies remains under development, requiring a recursive design-make-build cycle dedicated to tuning and evolving the robotic platform.
I will start by discussing the advantages of alkynes as high-energy carbon-rich precursors for extended polyaromatics, stereoelectronics of alkyne cyclizations, the two general patterns of oligoalkyne folding into an aromatic ribbon, and the use of supramolecular effects in the design of traceless directing groups for radical reactions.[1]
