A Scalable Perovskite Platform With Multi-State Photoresponsivity for In-Sensor Saliency Detection.

Abstract

Artificial vision systems are increasingly central to edge intelligence, yet they often suffer from high data latency and energy consumption due to sensor-processor separation. In-sensor computing (ISC) provides a promising solution by integrating sensing and computation. However, current ISC devices remain constrained by scalability, uniformity, and processability. Here, we address these limitations via a reconfigurable perovskite-photovoltaic platform that can be facilely processed from solutions. This architecture allows precise, reconfigurable photoresponsivity tuning with ultra-low variability and supports fabrication on both rigid and flexible substrates. The device exhibits up to ±1120 mA W^- ¹ photoresponsivity and 1000 programmable states, with excellent air stability (30 days) and thermal reliability (80°C). The scalability of these devices is demonstrated via a proof of concept 32 × 32 array. The excellent uniformity and programmability of the array are utilized in energy-efficient face detection applications (achieving 95.2% sensitivity and 4.51 × speedup for subsequent computation) in addition to image feature extraction and MNIST digit recognition tasks (96.97% accuracy). Compared to previous ISC implementations, our system offers enhanced tunability, fabrication scalability, and functional stability. These results establish a practical perovskite-based ISC platform, offering new avenues for intelligent computing systems in robotics, wearable electronics, and neuromorphic vision.