Artificial Visual Systems With Tunable Photoconductivity Based on Organic Molecule‐Nanowire Heterojunctions

The visual system, one of the most crucial units of the human perception system, combines the functions of multi‐wavelength signal detection and data processing. Herein, the large‐scale artificial synaptic device arrays based on the organic molecule‐nanowire heterojunctions with tunable photoconductivity are proposed and demonstrated. The organic thin films of p‐type 2,7‐dioctyl[1]benzothieno[3,2‐b][1] benzothiophene (C8‐BTBT) or n‐type phenyl‐C61‐butyric acid methyl ester (PC61BM) are used to wrap the InGaAs nanowire parallel arrays to configure two different type‐I heterojunctions, respectively. Due to the difference in carrier injection, persistent negative photoconductivity (NPC) or positive photoconductivity (PPC) are achieved in these heterojunctions. The irradiation with different wavelengths (solar‐blind to visible ranges) can stimulate the heterojunction devices, effectively mimicking the synaptic behaviors with two different photoconductivities. The long‐term and multi‐state light memory are also realized through synergistic photoelectric modulation. Notably, the arrays with different photoconductivities are adopted to build the hardware kernel for the visual system. Due to the tunable photoconductivity and response to multiple wavelengths, the recognition rate of neural networks can reach 100% with lower complexity and power consumption. Evidently, these photosynaptic devices are illustrated with retina‐like behaviors and capabilities for large‐area integration, which reveals their promising potential for artificial visual systems. The two different organic‐inorganic type‐I heterojunctions are fabricated with the InGaAs nanowire parallel arrays to realize the tunable persistent negative photoconductivity (NPC) or positive photoconductivity (PPC). The device arrays with multi‐wavelength NPC and PPC phenomena are adopted to build the hardware kernel for the visual system, which reaches a 100% recognition rate with lower complexity and power consumption.