Fig. 1. Schematic diagram of the nanostructure characterization process and studied parameters. (a) Process flow of nanostructure characterization process; (b) periodic nanohole and nanopillar plasmonic nanostructure formed by nanoimprint lithography on glass substrate; (c) representative SEM images of the experimental samples of (b); (d) Au, Ag, and Al metal films evaporated on the structures; (e) dielectric coating covered on the structures to be identified for its refractive index.

Fig. 2. Results of DNN1. (a) The architecture of DNN1. The input layer has 201 neurons and the output layer has four neurons; there are five hidden layers. (b)–(d) The absolute error of the testing data set, where (b) is for diameter, (c) is for thickness, and (d) is for period. (e) Relative error of the testing data set; (f) example of two transmission spectra of the real structure and the predicted structure, with an MSE slightly higher than the mean value.

Fig. 3. Results of DNN3. (a) The architecture of DNN3. The input layer has 201 neurons and the output layer has six neurons; there are five hidden layers. (b)–(e) The absolute error of the testing data set, where (b) is for diameter, (c) is for thickness, (d) is for period, and (e) is for the dielectric coating refractive index. (f) Relative error of the testing data set; (g) example of two transmission spectra of the real structure and the predicted structure, with an MSE slightly higher than the mean value.

Fig. 4. Results of DNN4. (a) The architecture of DNN4. The input layer has 201 neurons and the output layer has seven neurons; there are five hidden layers. (b) SEM images of nanohole and nanopillar structures prepared by nanoimprint lithography; (c) comparison of the experimental and simulated spectra; the yellow line indicates that the dielectric layer material is SU8, while the blue one indicates the air. (d) The absolute error of the testing data set; the top is the experimental data group, and the bottom is the total mixed data. (e) The relative error of the testing data set; the top is the experimental data, and the bottom is the total mixed data. (f) Statistics of the number of predictions that successfully identify the data type (experimental or simulated), structure type (nanohole or nanopillar), metal type, metal film thickness, and refractive index of dielectric layer collected for experimental data.

Table 1. Statistics of Characterization Error Distribution of DNNs