PAME: plasmonic assay modeling environment

Abstract

Plasmonic assays are an important class of optical sensors that measure biomolecular interactions in real-time without the need for labeling agents, making them especially well-suited for clinical applications. Through the incorporation of nanoparticles and fiberoptics, these sensing systems have been successfully miniaturized and show great promise for in-situ probing and implantable devices, yet it remains challenging to derive meaningful, quantitative information from plasmonic responses. This is in part due to a lack of dedicated modeling tools, and therefore we introduce PAME, an open-source Python application for modeling plasmonic systems of bulk and nanoparticle-embedded metallic films. PAME combines aspects of thin-film solvers, nanomaterials and fiber-optics into an intuitive graphical interface. Some of PAME’s features include a simulation mode, a database of hundreds of materials, and an object-oriented framework for designing complex nanomaterials, such as a gold nanoparticles encased in a protein shell. An overview of PAME’s theory and design is presented, followed by example simulations of a fiberoptic refractometer, as well as protein binding to a multiplexed sensor composed of a mixed layer of gold and silver colloids. These results provide new insights into observed responses in reflectance biosensors.