Gallium is a well-suited material for fabricating flexible photonic devices due to its fluidic and metallic properties. Localized Plasmonic resonance relies on fabricating metallic structures at the nanoscale with an extremely small gap between them, thus employing lithography or self-assembly techniques involving multiple reagents and process steps. In this work, we demonstrate a single-step and scalable fabrication of non-coalescent Ga Nanospheres on a biocompatible elastomeric substrate, Polydimethylsiloxane (PDMS), by exploiting the capillary interactions between liquid Ga and the uncured oligomers of PDMS. This approach enables the fabrication of multiple structural colors and mechanochromic sensors in a single deposition, owing to the active role played by PDMS in determining Ga nanostructures.
We describe an LSTM-based autoencoder for inversely designing an achromatic metalens comprised of cylindrical unit cells. The training data for our model has phase and transmission values corresponding to the heights and radii of each meta-unit. We use multiple data sequences (phase and transmission) to train the model and a multi-output model framework. The autoencoder is trained for 2500 iterations using the Adam optimizer with a learning rate of 0.001 and is subsequently used for inversely predicting the meta-unit dimensions at each radial position of the lens. Our model is validated via simulations as well as experiments.
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