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Hydroxide ion conducting block copolymers have the potential to possess the multiple properties required for anion exchange membranes to enable long-lasting alkaline fuel cell performance, and therefore can accelerate the advancement of the alkaline fuel cell, a low-cost alternative to the well-adopted commercial proton exchange membrane fuel cell. In this paper, an overview of hydroxide ion transport (a property that is proportional to fuel cell performance) in block copolymers will be presented and the subsequent impact of block copolymer morphology on ion transport (conductivity), where the careful design of block copolymer chemistry and chain architecture can accelerate hydroxide ion transport. 

Reversible addition–fragmentation chain–transfer (RAFT) polymerization of methyl methacrylate (MMA) is modeled and monitored using a multi-rate multi-delay observer in this work. First, to fit the RAFT reaction rate coefficients and the initiator efficiency in the model, in situ 1 H nuclear magnetic resonance (NMR) experimental data from small-scale (<2 mL) NMR tube reactions is obtained and a least squares optimization is performed. 1 H NMR and size exclusion chromatography (SEC) experimental data from large-scale (>400 mL) reflux reactions is then used to validate the fitted model. The fitted model accurately predicts the polymer properties of the large-scale reactions with slight discordance at late reaction times. Based on the fitted model, a multi-rate multi-delay observer coupled with an inter-sample predictor and dead time compensator is designed, to account for the asynchronous multi-rate measurements with non-constant delays. The multi-rate multi-delay observer shows perfect convergence after a few sampling times when tested against the fitted model, and is in fair agreement with the real data at late reaction times when implemented based on the experimental measurements.