The development of bio-inspired neural systems has emerged as a transformative approach to overcome the limitations of von Neumann architecture, replicating the remarkable energy efficiency and unified sensory-processing capabilities of biological neurons. In this work, we present a monolithic neuromorphic platform utilizing cascaded single-walled carbon nanotube thin-film transistors (SWCNT TFTs) that integrate Mini-light-emitting diodes (Mini-LEDs) with optoelectronic synaptic transistors, achieving synergistic optoelectronic integration. The SWCNT TFTs exhibit dual functionality: (1) as highly stable active-matrix drivers (>1000 operational cycles) enabling precise Mini-LED grayscale modulation, and (2) as efficient optoelectronic synaptic devices. Fabricated at wafer-scale with micrometer feature sizes, these devices demonstrate exceptional performance metrics, including low operating voltages (±1 V), high on/off ratios (10⁶), near-ideal subthreshold swing (78 mV·dec⁻¹), and precise Mini-LED current regulation (10⁻⁸ A–10⁻⁴ A) under 25 Hz pulsed gate operation. The optoelectronic synaptic devices based on organic-semiconductor heterojunction formed between poly (3,3’’’-didodecyl quaterthiophene) (PQT-12) and semiconducting SWCNTs enable broadband photoresponses (365 nm–710 nm) through efficient charge transport, driven by TFT-controlled Mini-LED pulses. The implemented bio-inspired visual system successfully emulates fundamental synaptic functionalities, exhibiting excitatory postsynaptic currents (EPSC), short-term potentiation (STP), and long-term potentiation (LTP). Notably, we demonstrate system-level functionality through a five-layer convolutional neural network, achieving 92.02% accuracy on MNIST classification, while the monolithic integration establishes a biomimetic closed-loop “electrical-optical-electrical” pathway that faithfully simulates complete biological synaptic operation. This pioneering cascade of electronic, photonic, and optoelectronic components represents a significant advancement toward high-density, energy-efficient neuromorphic computing.

The development of large-area high-performance flexible photoelectronic synaptic devices has become a hot topic in the field of neuromorphic computing and artificial vision systems. In this work, we have successfully prepared a large-area, ultra-flexible semiconducting single-walled carbon nanotubes (sc-SWCNTs) photoelectronic synaptic thin-film transistors (TFTs) array (33 × 34) using solution-processable AlO_x thin film as the dielectrics by roll-to-roll gravure printing. Our photoelectronic synaptic TFTs exhibit excellent electrical properties with high switching ratio (≥ 10⁵), low subthreshold swing (73 mV·dec⁻¹), excellent photoresponse properties over a wide wavelength range (from 270 to 650 nm), sustained photoconductivity effect (only 26.7% drop after removing light source for 36,000 s) and remarkable mechanical reliability and flexibility (maintaining excellent electrical properties after bending more than 15,000 cycles with a bending radius of 5 mm). In addition, concepts such as multimodal optoelectronic synaptic plasticity, optical writing speed perception simulation, and human eye self-recovery model have been successfully demonstrated using printed flexible sc-SWCNTs photoelectronic neuromorphic TFTs arrays. More importantly, we systematically investigated the response characteristics of these devices under deep ultraviolet light stimulation and, for the first time, successfully simulated bio-inspired visual perception self-recovery including the dynamic transition of the visual system from clarity to blurriness and their self-recovery over time. This work indicates that our photoelectronic neuromorphic TFT devices have great practical potential in human–computer interaction, environment perception, and visual simulation.

Artificial multisensory devices play a key role in human-computer interaction in the field of artificial intelligence (AI). In this work, we have designed and constructed a novel olfactory-visual bimodal neuromorphic carbon nanotube thin film transistor (TFT) arrays for artificial olfactory-visual multisensory synergy recognition with a very low power consumption of 25 aJ for a single pulse, employing semiconducting single-walled carbon nanotubes (sc-SWCNTs) as channel materials and gas sensitive materials, and poly[[4,8-bis[5-(2-ethylhexyl)-2-thienyl]benzo[1,2-b:4,5-b0]dithiophene-2,6-diyl]-2,5-thiophenediyl-[5,7-bis(2-ethylhexyl)-4,8-dioxo-4H,8H-benzo[1,2-c:4,5-c0]dithio-phene-1,3-diyl]] (PBDB-T) as the photosensitive material. It is noted that it is the first time to realize the simulation of olfactory and visual senses (from 280 nm to 650 nm) with the wide operating temperature range (0–150 °C) in a single SWCNT TFT device and successfully simulate the recovery of olfactory senses after COVID-19 by olfactory-visual synergy. Furthermore, our SWCNT neuromorphic TFT devices with a high I_On/I_Off ratio (up to 10⁶) at a low operating voltage (−2 to 0.5 V) canmimic not only the basic biological synaptic functions of olfaction and vision (such as paired-pulse facilitation, short-term plasticity, and long-term plasticity), but also optical wireless communication by Morse code. The proposed multisensory, broadband light-responsive, low-power synaptic devices provide great potential for developing AI robots to face complex external environments.