Browsing by Subject "metamaterial"
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Item Effects of size and frequency dispersion in plasmonic cloaking(2008-10) Alu, Andrea; Engheta, Nader; Alu, Andrea; Engheta, NaderThe plasmonic venue to realize invisibility and cloaking [A. Alu and N. Engheta, Phys. Rev. E 72, 016623 (2005)] is analyzed here in terms of its limitations and its frequency dispersion relative to the cloak size. Intrinsic limits due to causality and comparison with transformation-based cloaking techniques are discussed and analyzed. An interestingly simple low-dispersion cloak is also suggested for background materials with larger refractive index. These results may shed light on this scattering cancellation phenomenon, suggesting potential applications in scattering reduction and noninvasive probing.Item Machine Learning Assisted Mechanical Metamaterial Design for Additive Manufacturing(University of Texas at Austin, 2023) Wang, Jier; Panesar, AjitMetamaterials, widely studied for its counterintuitive property such as negative Poisson’s ratio, negative refraction, negative thermal expansion, and employed in various fields, are recognised to provide foundation for superior multiscale structural designs. However, current mechanical metamaterial design methods usually relay on performing sizing optimisations on predefined topology or implementing time-consuming inverse homogenisation methods. Machine Learning (ML), as a powerful self-learning tool, is considered to have the potential of discovering metamaterial topology and extending its property bounds. This work considers the use of Neural Networks (NNs), (De-Convolutional Neural Networks) DCNNs and Generative Adversarial Networks (GANs) to speed up the generation of new topologies for metamaterials. NNs and DCNNs are trained to inversely generate metamaterial designs based on the input target effective macroscale properties, whilst the generator in GANs is expected to output diverse metamaterial microstructures with random noise inputs. This work highlights the potential of data-driven approaches in Design for Additive Manufacturing (DfAM) as an alternative to the time-consuming, conventional methods.Item Plasmonic cloaking for irregular objects with anisotropic scattering properties(2010-02) Tricarico, S.; Bilotti, F.; Alu, A.; Vegni, L.; Alu, A.Here we extend the plasmonic cloaking technique to irregularly shaped objects with anisotropic scattering response. The scattering-cancellation approach to cloaking [A. Alugrave and N. Engheta, Phys. Rev. E 72, 016623 (2005)] has been extensively applied in the past to symmetrical geometries and canonical shapes. However, recent papers have raised some doubts concerning the fact that its use may not be as effective when dealing with strongly anisotropic and noncanonical geometries. Our goal here is to extend the plasmonic cloaking technique to irregular obstacles and to show that proper cloak design may provide a significant and uniform scattering reduction, independent of angle of incidence, position, and polarization of the illumination. We investigate how the volumetric effect of scattering cancellation provided by plasmonic media may drastically suppress the scattering for these irregular geometries independent of the illumination angle, and we shed some light on the physical mechanisms and the design rules at the basis of this cloaking technique when applied to objects whose scattering properties are dependent upon polarization and angle of incidence.