Abstract
Plastics are versatile and durable yet made for eventual disposal, creating an inevitable environmental issue with plastic waste. Polydiketoenamines (PDKs) offer a solution as novel plastics that are infinitely chemically recyclable through acid-catalyzed hydrolysis. However, experimentally designing new PDK chemistries that target specific properties yet are still chemically recyclable requires significant time and resources. Here, we identify design rules for recyclable PDK chemistries using an interpretable model. We constructed a dataset of molecular features and hydrolysis kinetics by performing high-throughput hybrid-DFT calculations, taking into account the effect of molecular conformation on reaction energetics. We employed a random forest model and symbolic regression to yield an interpretable model based on features from the molecule geometry and electronic structure. This model was validated with 5-fold cross validation, and a subset of data was validated with experimental findings. In collaboration with an experimental team, we validated our model by testing recycling rate of a PDK monomer based on the discovered design rules.
*This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Berkeley Lab Undergraduate Research (BLUR) program. This research used the Savio computational cluster resource provided by the Berkeley Research Computing program at the University of California, Berkeley (supported by the UC Berkeley Chancellor, Vice Chancellor for Research, and Chief Information Officer). This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231.
