Optical and photoelectric modeling of thick film bacteriorhodopsin sensors

Abstract

This dissertation addresses the structural characterization and optimization of thick-film bacteriorhodopsin (BR) sensors, aiming to advance their applicability in optoelectronics and imaging. BR, with its robust light-driven proton pump offers a promising material for organic photodetectors when immobilized in polymer film between transparent electrodes, due to its stability and well-defined photoresponse. The research proposes a comprehensive simulation model for these sensors, combining optical modeling, molecular population dynamics, and photoelectric response (PER) analysis.

The optical properties of BR sensors were characterized using the transfer matrix method (TMM), complemented by Kramers–Kronig analysis to reconstruct the complex refractive index of BR in polyvinyl alcohol films from molar absorption coefficient data. Spectrophotometer measurements were used both for model verification a nd f or calibrating layer thicknesses, refractive indices, and BR concentrations. Sensitivity analysis confirmed that gold electrode thickness, BR concentration, and film thickness are the dominant design parameters for such sensors.

The photocycle dynamics of BR were modeled with rate equations linking molecular state populations to intrinsic photovoltage generation in BR. These kinetics were combined with an equivalent-circuit model to account for loading effects from measurement instrumentation. The resulting model provided a realistic description of observed PER and clarified the relation between molecular properties and measurement instrumentation.

Finally, a stacked three-layer sensor architecture inspired by trichromatic color channels commonly used in conventional imaging sensors is proposed. Simulations show that, under realistic illumination and exposure conditions, each BR layer can generate a measurable photoelectric signal within a practical dynamic range, supporting the feasibility of stacked color-sensitive BR-based imaging sensor.

The main contribution of this thesis is a validated modeling methodology for thick BR sensors. The work bridges optical, molecular, and electrical domains, enabling parameter estimation, structural characterization and optimization, and feasibility analysis of single and stacked BR sensors. The modeling methodology provides a foundation for future development of organic photodetector devices.