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 ( 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.

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