Unveiling the Photoinduced Recovery Mystery in Conjugated Polymer-Based Transistor Memory

Nanographene-Based Heterojunctions for High-Performance Organic Phototransistor Memory Devices

Organic phototransistors can enable many important applications such as nonvolatile memory, artificial synapses, and photodetectors in next-generation optical communication and wearable electronics. However, it is still a challenge to achieve a big memory window (threshold voltage response ∆V_th ) for phototransistors. Here, a nanographene-based heterojunction phototransistor memory with large ∆V_th responses is reported. Exposure to low intensity light (25.7 µW cm^-2 ) for 1 s yields a memory window of 35 V, and the threshold voltage shift is found to be larger than 140 V under continuous light illumination. The device exhibits both good photosensitivity (3.6 × 10⁵ ) and memory properties including long retention time (>1.5 × 10⁵  s), large hysteresis (45.35 V), and high endurance for voltage-erasing and light-programming. These findings demonstrate the high application potential of nanographenes in the field of optoelectronics. In addition, the working principle of these hybrid nanographene-organic structured heterojunction phototransistor memory devices is described which provides new insight into the design of high-performance organic phototransistor devices.

Flexibly Photo-Regulated Brain-Inspired Functions in Flexible Neuromorphic Transistors

As an attractive prototype for neuromorphic computing, the difficultly attained three-terminal platforms have specific advantages in implementing the brain-inspired functions. Also, in these devices, the most utilized mechanisms are confined to the electrical gate-controlled ionic migrations, which are sensitive to the device defects and stoichiometric ratio. The resultant memristive responses have fluctuant characteristics, which have adverse influences on the neural emulations. Herein, we designed a specific transistor platform with light-regulated ambipolar memory characteristics. Also, based on its gentle processes of charge trapping, we obtain the impressive memristive performances featured by smooth responses and long-term endurable characteristics. The optoelectronic samples were also fabricated on flexible substrates successfully. Interestingly, based on the optoelectronic signals of the flexible devices, we endow the desirable optical processes with the brain-inspired emulations. We can flexibly emulate the light-inspired learning-memory functions in a synapse and further devise the advanced synapse array. More importantly, through this versatile platform, we investigate the mutual regulation of excitation and inhibition and implement their sensitive-mode transformations and the homeostasis property, which is conducive to ensuring the stability of overall neural activity. Furthermore, our flexible optoelectronic platform achieves high classification accuracy when implemented in artificial neural network simulations. This work demonstrates the advantages of the optoelectronic platform in implementing the significant brain-inspired functions and provides an insight into the future integration of visible sensing in flexible optoelectronic transistor platforms.