Simulation Calculation of Selective Reflective Films based on Metamaterials and Prediction of Color in Light Filter with Machine Learning
Abstract
In this study, we have developed a novel three-layer cylindrical periodic structure utilizing metamaterials, combining a periodic cylindrical arrangement with a Metal-Insulator-Metal (MIM) three-layer configuration. The finite difference time domain method is used to calculate the reflection curve of the structure, and then the color coordinates of the structure under the D65 light source are calculated. We obtain the relationship between the color presented by the structure and the variation of structural size parameters. Then the random forest algorithm is used for machine learning, and a more accurate learning model is obtained. The coefficient of determination R2 is above 0.98. This result ensures that the random forest algorithm can be used in the calculation of superstructure. The article presents a novel light filter design with tunable color properties and machine learning framework for accurate color predictions based on structural parameters.