Gate-Tunable Positive and Negative Photoconductance in Near-Infrared Organic Heterostructures for in-Sensor Computing.

The rapid growth of sensor data in the artificial intelligence often causes significant reductions in processing speed and power efficiency. Addressing this challenge, in-sensor computing has been introduced as an advanced sensor architecture that simultaneously senses, memorizes and processes images at the sensor level. However, this has rarely been reported for organic semiconductors that possess inherent flexibility and tunable bandgap. Herein, we introduce an organic heterostructure that exhibits a robust photoresponse to near-infrared (NIR) light, making it ideal for in-sensor computing applications. This heterostructure, consisting of partially overlapping p-type and n-type organic thin films, is compatible with conventional photolithography techniques, allowing for high integration density of up to 520 devices per square centimeter with a 5 µm channel length. Importantly, by modulating gate voltage, both positive and negative photoresponses to NIR light (1050 nm) are attained, which establishes a linear correlation between responsivity and gate voltage and consequently enables real-time matrix multiplication within the sensor. As a result, this organic heterostructure facilitates efficient and precise NIR in-sensor computing, including image processing and nondestructive reading and classification, achieving a recognition accuracy of 97.06%. Our work serves as a foundation for the development of reconfigurable and multifunctional NIR neuromorphic vision systems. This article is protected by copyright. All rights reserved.