Artificial neural network to estimate the refractive index of a liquid infiltrating a chiral sculptured thin film in a sensor chip

摘要

We experimentally expanded the capabilities of optical sensing based on surface plasmon resonance in a prism-coupled configuration by incorporating artificial neural networks (ANNs). We fabricated a sensor chip comprisinga metal thin film and a porous chiral sculptured thin film (CSTF) deposited successively on a glass substratethat can be affixed to the base of a triangular prism. When a uid is brought in contact with the exposed faceof the CSTF, the latter is infiltrated. As a result of infiltration, the traversal of light entering one slanted faceof the prism and exiting the other slanted face of the prism is affected. We trained an ANN using measuredreectance data and found that the presence of the CSTF does not inhibit sensing performance. Thisfindingclears the way for further research on using a single sensor chip for simultaneous multi-analyte sensing.