In this talk we propose a model for the simulation of retinal prostheses based on the use  of organic polymer nanoparticles (NP). The model consists of a nonlinearly coupled system of elliptic partial differential equations accounting for:

(1) light photoconversion into free charged carriers in the NP bulk;
(2) charge transport in the NP bulk due to drift and diffusion forces;
(3) net charge recombination in the NP bulk due to the balance between light
absorption and particle-particle recombination;
(4) electron-driven molecular oxygen reduction and capacitive coupling at the NP-solution interface;
(5) ion electrodiffusion in the solution bulk;
(6) capacitive and conductive coupling across the neuronal membrane.

Model dependent variables are represented by the electric potential, the number densities of photogenerated charge carriers in the NP bulk and the molar densities of moving ions in the aqueous solution surrounding the NP. The physical mechanisms (4) and (6) are mathematically expressed by nonlinear transmission conditions across interfaces which in turn give rise to the nonlinear coupling among the dependent variables throughout the whole computational domain. The proposed model is solved in stationary conditions and in one spatial dimension by resorting to a solution map which is a modification of the Gummel Decoupled algorithm conventionally used in inorganic semiconductor simulation. System discretization is conducted using the Finite Element Method, with stabilization terms to prevent spurious unphysical oscillations in the electric potential and ensure positivity of carrier and ion concentrations. Model predictions suggest that the combined effect of NP polarization and resistivity of the NP-neuron interface results in neuron depolarization and supports the efficacy of organic NPs in the design and development of retinal prostheses.

Zoom link: https://ncsu.zoom.us/j/8027642791?pwd=d1lNaWZyUW4zeUFvaTA5VmlsTWtjdz09