Wearable in-sensor reservoir computing using optoelectronic polymers with through-space charge-transport characteristics for multi-task learning

Abstract

Designing efficient photonic neuromorphic systems remains a challenge. Here, the authors develop an in-sensor Reservoir Computing system for multi-tasked pattern classification based on a light-responsive semiconducting polymer (p-NDI) with efficient exciton dissociations, charge trapping capability, and through-space charge-transport characteristics.