Photonics Research, Volume. 9, Issue 5, B236(2021)
Accurate inverse design of Fabry–Perot-cavity-based color filters far beyond sRGB via a bidirectional artificial neural network
Fig. 1. (a) Schematic illustration of a transmissive F-P-cavity-based color filter with an MIM structure. (b) The training and validation dataset generated by the F-P cavity plotted in a CIE 1931-
Fig. 2. Forward neural network for predicting F-P cavity structural colors. (a) The relationships of different parameters in the dataset. The single arrow means the transformation is unidirectional, the double arrow means the transformation is reversible. (b) The architecture of the forward neural network with input layer of geometric parameter
Fig. 3. Forward neural network training for predicting F-P cavity structural colors. The histogram of the probability and average values of
Fig. 4. Inverse neural network for predicting F-P cavity structural colors. (a) The bidirectional architecture with input layer of Lab values and output layer of geometric parameter
Fig. 5. Actual application of the INN-based structural color design. (a) The origin and (b) the reproduction via INN of the painting “Haystacks, end of Summer” by Claude Monet. Reproduction of “Haystacks, end of Summer” is permitted by the Musée d’Orsay, Paris (RF 1975 3).
Fig. 6. Transmissive spectra and corresponding CIE 1931-RGB tristimulus values for the designed colors. The transmissive spectra (black line) and the contribution from the three stimuli (shades underneath the line) for the (i, ii, iii) blue, (iv, v, vi) green, and (vii, viii, ix) red color designed by the INN in this work. Within each figure, the middle row figure presents the original design, while the top and bottom figures represent the spectra from a 10 nm thinner layer and a 10 nm thicker dielectric layer. (b) The CIE 1931-RGB tristimulus values as a function of dielectric layer thickness for the blue, green, and red colors, respectively. The CIE 1931-RGB tristimulus values of the targeted colors are also included (dotted lines) for comparison.
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Peng Dai, Yasi Wang, Yueqiang Hu, C. H. de Groot, Otto Muskens, Huigao Duan, Ruomeng Huang. Accurate inverse design of Fabry–Perot-cavity-based color filters far beyond sRGB via a bidirectional artificial neural network[J]. Photonics Research, 2021, 9(5): B236
Special Issue: DEEP LEARNING IN PHOTONICS
Received: Nov. 26, 2020
Accepted: Mar. 1, 2021
Published Online: May. 7, 2021
The Author Email: Huigao Duan (duanhg@hnu.edu.cn), Ruomeng Huang (r.huang@soton.ac.uk)