Dynamic flexible optical sensing based on liquid integrated circuits.

Vision supplies more than 80% of the information, and innovations in artificial vision can catalyze a foundational shift for technologies such as embodied intelligence. Dynamic flexible optical sensing (DFOS), where the sensor itself modulates curvature on demand, offers curvature-matched optical acquisition, focus switching without moving optics, and multiplane light-field acquisition, yet repetitive and reversible deformation is still challenging for recent electronic arrays. Here, we propose a DFOS system based on liquid integrated circuits (LICs), integrating photosensitive ionic liquid (PIL) and stretchable liquid metal electrodes to achieve active curvature modulation for geometry-adaptive optical sensing. The PIL exhibits selective color perception, reversible photo-thermo-electric responses, and robust stability. This all-liquid architecture allows for large-amplitude hydraulically controlled curvature modulation (>31.9°) with a strain rate of ∼1.62% per second and exceptional durability (600 reversible cycles) without mechanical fatigue. With the assistance of machine learning, the system demonstrates multimodal signal acquisition (concave, planar, and convex configurations) for color, pattern, and distance recognition with high accuracy through hydraulically controlled curvature modulation.