Coupling of photovoltaics with neurostimulation electrodes—optical to electrolytic transduction

The wireless transfer of power for driving implantable neural stimulation devices has garnered significant attention in the bioelectronics field. This study explores the potential of photovoltaic (PV) power transfer, utilizing tissue-penetrating deep-red light-a novel and promising approach that has received less attention compared to traditional induction or ultrasound techniques. Our objective is to critically assess key parameters for directly powering neurostimulation electrodes with PVs, converting light impulses into neurostimulation currents. We systematically investigate varying PV cell size, optional series configurations, and coupling with microelectrodes fabricated from a range of materials such as Pt, TiN, IrO , Ti, W, PtO , Au, or poly(3,4 ethylenedioxythiophene):poly(styrene sulfonate). Additionally, two types of PVs, ultrathin organic PVs and monocrystalline silicon PVs, are compared. These combinations are employed to drive pairs of electrodes with different sizes and impedances. The readout method involves measuring electrolytic current using a straightforward amplifier circuit. Optimal PV selection is crucial, necessitating sufficiently large PV cells to generate the desired photocurrent. Arranging PVs in series is essential to produce the appropriate voltage for driving current across electrode/electrolyte impedances. By carefully choosing the PV arrangement and electrode type, it becomes possible to emulate electrical stimulation protocols in terms of charge and frequency. An important consideration is whether the circuit is photovoltage-limited or photocurrent-limited. High charge-injection capacity electrodes made from pseudo-faradaic materials impose a photocurrent limit, while more capacitive materials like Pt are photovoltage-limited. Although organic PVs exhibit lower efficiency than silicon PVs, in many practical scenarios, stimulation current is primarily limited by the electrodes rather than the PV driver, leading to potential parity between the two types. This study provides a foundational guide for designing a PV-powered neurostimulation circuit. The insights gained are applicable to both and applications, offering a resource to the neural engineering community.