AI_Biosensor_Data

This dataset contains the results of 5000 Finite-Difference Time-Domain (FDTD) simulations of a grating-based optical biosensor. The simulations were performed using Lumerical Solutions 2019 and controlled by a custom Python script. The dataset includes 11 parameters, such as analyte layer thickness, refractive index, peak wavelength, full width at half maximum (FWHM), and peak reflectance. This data was used to train and evaluate a Multi-Layer Perceptron (MLP) model for predicting peak wavelength and FWHM. The dataset enables advanced visualization and analysis of the sensor's performance, revealing significant sensitivity enhancement for specific conditions and complex variations in sensitivity. This comprehensive dataset is a valuable resource for researchers interested in optical biosensors, AI/ML applications in biosensing, and data-driven sensor optimization.