Work

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

Year: 2026
Type: article
Abstract: 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 MAPbI 3 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 µm 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 × 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 × 10 inputs into 80 × 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.
Language: English
Open Access status: hybrid
Estimated APC paid: $5,790
Award: G206712281
OpenAlex ID: W7135016392
FWCI: 3.531
Cites: 48
Cited by: 2
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