Persistent radicals in organic photonic synaptic transistors for pattern recognition of electrical and multicolor...

Organic photonic synaptic transistors (OPSTs) integrate light detection and signal processing, memory, and computation capabilities due to their intrinsic multifunctionality. Despite the many strategies reported in the literature, OPSTs mainly rely on nanomaterial engineering, while a true molecular design approach to the intrinsic properties of the materials, enabling a finer control of neuromorphic functions, is still lacking. This study presents a solution-processed multilayer OPST, integrating in a single device the functions of multi-modal synapsis and dendritic-like neuromorphic computing. The device combines a bulk heterojunction photoactive layer based on a persistent organic radical and a relaxor-like ferroelectric polymer as a dielectric layer. Multilevel atomistic simulations illustrate how the peculiar electronic structure of the persistent organic radical in the photoactive layer enables the activation of different photophysical pathways occurring under different (multicolor) optical stimulations, which can correlate with different synaptic outputs (current facilitation) in the device. Then, we first show experimentally that synaptic functions such as short-term and long-term plasticity (STP and LTP, respectively) are enabled in the OPST by the synergic combination of optical and electrical stimulations: STP under blue-light stimulation and LTP under near-infrared light-stimulation or under sequential blue-light and electrical stimulation. Then, we demonstrate that the multi-mode operation of the OPST allows modulating a neuromorphic behavior which simulates dendritic parallel learning and signal integration under different patterns of the incoming stimuli. Specifically, different patterns from eight combinations of optical and electrical stimuli are recognized and classified. Overall, the proposed material-design based approach lays the foundation for a new class of organic photonic synaptic devices, including OPSTs, that can perform complex dendritic computations, paving the way for more efficient and powerful artificial photonic neural systems.