Computational analysis of efficient organic solar cell-based retinal prosthesis using plasmonic gold nanoparticles

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Abstract

Introduction: Photovoltaic restoration of vision, especially in conjunction with the use of silicon photodiodes, has gained attention for use in patients affected by blindness due to retinal layer disease. Although the use of silicon photodiodes offers miniaturization of the implant unit and increase in the stimulation channel, the implant unit may suffer from the fracture of these brittle photodiodes when mechanical pressure exerted. Methods: We present an organic solar cell (OSC)-based retinal prosthesis in which spherical gold nanoparticles (AuNPs) are embedded into the active layer to increase the efficiency of the bioelectric interface. Results: We demonstrate computationally that a modeled OSC incorporating spherical AuNPs has three times higher efficiency than that of a bare OSC presented before for retinal prostheses. Our AuNP based OSC was able to activate the neuron at the minimum light intensity of 0.26 mW/mm2, which is lower than that of the bare OSC. Discussion: The use of AuNPs in OSC allows device miniaturization or lowering of the light exposure required for neural activation using a photovoltaic retinal prosthesis, which can generally be applied in a broad range of neural prostheses.

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Rahmani, A., & Eom, K. (2023). Computational analysis of efficient organic solar cell-based retinal prosthesis using plasmonic gold nanoparticles. Frontiers in Cellular Neuroscience, 17. https://doi.org/10.3389/fncel.2023.1205048

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