Scalable, ultra-resistant structural colors based on network metamaterials

Structural colors have drawn wide attention for their potential as a future printing technology for various applications, ranging from biomimetic tissues to adaptive camouflage materials. However, an efficient approach to realize robust colors with a scalable fabrication technique is still lacking, hampering the realization of practical applications with this platform. Here, we develop a new approach based on large-scale network metamaterials that combine dealloyed subwavelength structures at the nanoscale with lossless, ultra-thin dielectric coatings. By using theory and experiments, we show how subwavelength dielectric coatings control a mechanism of resonant light coupling with epsilon-near-zero regions generated in the metallic network, generating the formation of saturated structural colors that cover a wide portion of the spectrum. Ellipsometry measurements support the efficient observation of these colors, even at angles of 70°. The network-like architecture of these nanomaterials allows for high mechanical resistance, which is quantified in a series of nano-scratch tests. With such remarkable properties, these metastructures represent a robust design technology for real-world, large-scale commercial applications.

Citation

Galinski H, Favraud G, Dong H, Gongora JST, Favaro G, et al. (2016) Scalable, ultra-resistant structural colors based on network metamaterials. Light: Science & Applications 6: e16233. Available: http://dx.doi.org/10.1038/lsa.2016.233.

Acknowledgements

For computing, we used the resources of the KAUST Supercomputing Laboratory and the Redragon cluster of the Primalight group. FC acknowledges the Air Force Office of Scientific Research (MURI: FA9550-14-1-0389) for financial support. Part of the nano-fabrication was performed at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Coordinated Infrastructure (NNCI), which is supported by the National Science Foundation under NSF award no. 1541959. CNS is part of Harvard University. AF thanks P Magistretti for fruitful discussions on brain functions. AF acknowledges financial support from KAUST (Award CRG-1-2012-FRA-005). HG acknowledges the financial support of the ‘Size matters’ project (TDA Capital Ltd, London, UK). HD acknowledges the financial support by the Master Thesis Grant of the Zeno Karl Schindler Foundation (Switzerland).