Meniscus Pixel Printing for Contact-Lens Vision Sensing and Robotic Control

Abstract

Contact lenses are emerging as strong candidates for next-generation extended reality (XR) interfaces due to their lightweight and ergonomic form factor. However, integrating photodetector arrays onto the limited area of a lens remains challenging with conventional micropatterning approaches, which rely on masks, multistep processes, and specialized equipment that inherently limit throughput and scalability. To address these constraints, we introduce a Meniscus Pixel Printing (MPP) strategy that enables rapid, mask-free patterning of MAPbI3 perovskite photodetectors without costly or complex fabrication tools. MPP uses a self-confined meniscus at a pipette tip to deterministically transfer perovskite ink, enabling 200 & micro;m pixels to be printed within 1 s per pixel. In addition to planar substrates, MPP demonstrates stable pixel patterning on curved surfaces, highlighting its geometric adaptability and process versatility. Using this approach, we fabricate a 10 & times; 10 perovskite photodetector array and demonstrate stable photoresponse, retaining 92% of its initial performance after two months of storage. To overcome limited pixel density, a deep-learning-based super-resolution (SR) model reconstructs 10 & times; 10 inputs into 80 & times; 80 optical information with 97.2% accuracy and 0.03 s latency. Additionally, an AI-based eye-tracking system recognizes nine eye gestures with 99.3% accuracy, enabling smooth hands-free robotic arm control.