Harnessing Biobased Materials in Photosynaptic Transistors with Multibit Data Storage and Panchromatic Photoresponses Extended to Near-Infrared Band

24 February 2023
In this publication of R. Borsali and Y. Sakai-Otsuka and their collaborators, the authors develop a "Green" Photosynaptic device, including a biocomposite, which is an effective guide for applications in artificial visual perception, detection and memory in neuromorphic computers and intelligent systems. Click on the title for more information.

Abstract:

“Owing to ever-increasing environmental impact, nature-inspired biomimetic electronics are key to unlock the potential of developing environmentally friendly brain-like computing and biomimetic artificial-intelligence systems. Thus far, the development of photosynaptic devices via green processing using biobased materials has become a major challenge, owing to restrictions in complex architecture, material design, and stimulation wavelength. This article reports on the first bioinspired phototransistor using biocomposites comprising semiconducting block copolymers, poly(3-hexylthiophene)-block-maltoheptaose, and bacteriochlorophyll (BCHL), which extend the photoresponse from visible to UV to near-infrared light, to exhibit fundamental sensing, computing, and memory functions. The superior ultrafast (50 ms) and multilevel (>9 bits) photoresponses of a single cell of the synaptic devices are attributed to hydrogen-bonding interaction (i) between the block copolymers to facilitate the self-assembled microstructure, and (ii) within the block copolymer and BCHL to homogeneously disperse the natural chromophore. Notably, a two-terminal flexible synaptic device comprising biocomposites and a biobased poly(ethylene furanoate) substrate with high mechanical endurance is demonstrated to exhibit synaptic functionality and environmentally benign properties without using a gate impetus and hazardous ingredients. Collectively, the photosynaptic transistor comprising a biocomposite successfully provides an effective guide for applications in artificial visual perception, sensing, and memory in neuromorphic computing and intelligent systems.”

The publication is available on the editor’s website

Such collaboration is part of the Green Material Institute France Taiwan. More about this International Research Project: irp-gmi.cnrs.fr