A Bio‐Electronic Hybrid Solid–Liquid Pixelated Color Image Sensor Array as a Direct‐to‐Display Artificial Retina Emulator
Abstract Inspired by animal retina architectures, a proof‐of‐concept hybrid solid–liquid biocompatible image sensor array that integrates biological and artificial photodetection mechanisms is presented. The device comprises 16‐pixel sensors combining printed organic semiconductors, laser‐patterned transparent microelectrodes, and printed platinum reference electrodes within Ames’ medium—an electrically active, water‐based biological electrolyte widely used in retinal research. Twelve photosensors emulate rod‐like spectra, while a central 2 × 2 photodetector array reproduces the cone‐mediated dichromatic vision sensitivity of mice. Each pixel captures light and converts it into electrical signals through the electrolyte. Color images are generated on a display in real time by processing light‐evoked signals from the array, with rod‐like pixels contributing grayscale contrast proportional to irradiance. Each pixelated sensor unit, consisting of electrode/polymer/retinal‐water‐based‐medium, functions as a true biohybrid photoreceptor, merging biological/artificial and liquid/solid components. The device exhibits tens of millisecond‐scale temporal responses, typical of water‐ionic‐based biological retinas, and sensitivities comparable to solid‐state polymer semiconductor photodetectors. By replicating spectral and temporal responses of natural photoreceptors, along with their characteristic photogenerated electrical signatures, this scalable, biocompatible technology platform bridges living and electronic systems, opening new pathways for understanding the biophysics and engineering of phototransduction in biological liquid environments, artificial vision, adaptive biointerfaces, and neuromorphic sensory processing.
Authors
- Aldo Di Carlo (ORCID: https://orcid.org/0000-0001-6828-2380)
- Luigi Angelo Castriotta (ORCID: https://orcid.org/0000-0003-2525-8852)
- Ebin Joseph (ORCID: https://orcid.org/0000-0001-7924-1816)
- Thomas Meredith Brown (ORCID: https://orcid.org/0000-0003-2141-3587)
- Hiroki Asari (ORCID: https://orcid.org/0000-0003-3396-1935)
- P. G. Medaglia (ORCID: https://orcid.org/0000-0003-4392-293X)
- G.C. Cardarilli (ORCID: https://orcid.org/0000-0002-7444-876X)
- Maria Assunta Ucci
- Antonella Camaioni (ORCID: https://orcid.org/0000-0002-7059-2617)
- Claudio Leonardi (ORCID: https://orcid.org/0000-0002-6379-3410)
- Paolo Mariani (ORCID: https://orcid.org/0000-0003-4491-2127)
- Luca Di Nunzio (ORCID: https://orcid.org/0000-0002-4312-7939)
- Luigi Vesce (ORCID: https://orcid.org/0000-0003-3322-8688)
- Manuela Ciocca (ORCID: https://orcid.org/0000-0001-8014-9814)
- Suresh Kumar Podapangi (ORCID: https://orcid.org/0000-0003-0946-9895)
Institutions
- University of Rome Tor Vergata (IT)
- Free University of Bozen-Bolzano (IT)
- European Molecular Biology Laboratory (IT)
- National Research Council (RO)
- National Research Council (IT)
Publication Details
- Journal
- Advanced Materials Technologies
- Published
- 2025-11-25
- DOI
- https://doi.org/10.1002/admt.202501461
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00