Data Driven Discovery of Conjugated Polyelectrolytes for Neuromorphic Computing
In this project, we have constructed a database on conjugated polyelectrolytes (CPEs) based on high-throughput first-principles calculations and machine learning modeling. The database (https://www.cpegenome.com/) contains the properties of over 10,000 CPEs that are relevant to neuromorphic and optoelectronic applications. These properties include optimized molecular structure, ionization potential, electron affinity, energy gap, reorganization energy for electron and hole, and cohesive energy, etc. Additional material properties are being included. The CPE database is freely available to the public. Using the database, we have recently performed a comprehensive study on polaron properties in CPEs, including the stability, structural deformation, electronic structure, and optical absorption of both positive and negative polarons and bi-polarons. We have explored how these properties depend on the electrostatic interaction between the polarons and ionic functionalities, including alkyl chains, ionic groups, and counterions. We further examined how bandgap, polaron binding energy, and optoelectronic structure of CPEs can be tuned by various combinations of the donor and acceptor units in their backbones. Finally, the electrochemical stability of CPEs is studied to shed on the absence of negative polarons in CPEs. The strategy to improve the electrochemical stability of n-doped CPEs is also discussed.