Results 191 to 200 of about 7,053 (306)

Spatially Encoded Polaritonic Ultra‐Strong Coupling in Gradient Metasurfaces with Epsilon‐Near‐Zero Modes

Advanced Materials, Volume 38, Issue 1, 2 January 2026.
Dielectric dual gradient metasurfaces supporting quasi‐bound‐states‐in‐the‐continuum are leveraged to spatially encode both the spectral and coupling parameter space and demonstrate ultra‐strong coupling to an epsilon‐near‐zero mode in an ultra‐thin SiO2 layer.The platform achieves exceptional mode overlap, reaching a normalized coupling strength of η =
Enrico Baù, Andreas Aigner, Jonas Biechteler, Connor Heimig, Thomas Weber, Thorsten Gölz, Stefan A. Maier, Andreas Tittl   +7 more
wiley   +1 more source

Plasmonic Su-Schrieffer-Heeger chains with strong coupling amplitudes. [PDF]

Sci Adv
Schurr B, Hensen M, Brenneis L, Kessler P, Qin J, Lisinetskii V, Thomale R, Brixner T, Hecht B.   +8 more
europepmc   +1 more source

Plasmonic Structures for Subwavelength Guiding and Enhanced Light-Matter Interactions

, 2018
Amirreza Mahigir, Amirreza Mahigir
openalex   +2 more sources

E‐Textiles in Biomedicine: Real Time Sensing, Energy Storage, and Therapeutic Applications

Advanced Materials Interfaces, Volume 13, Issue 1, 7 January 2026.
E‐textiles merge electronics with fabrics to create intelligent, wearable systems for health, sports, and fashion. By embedding sensors, actuators, and conductive components, these textiles provide real‐time physiological monitoring. Complemented by flexible power sources including embedded batteries and energy‐harvesting technologies, e‐textiles ...
Shiva Sharma, Sudheesh K. Shukla, Atheesha Singh, Krishna K. Govender, Penny P. Govender   +4 more
wiley   +1 more source

Breakdown of the effective medium theory: a perspective from Goos-Hänchen shift. [PDF]

Nanophotonics
Gong W, Shi Y, Liu Z, Zhang C, Cui Z, Chen Y, Zhou X.   +6 more
europepmc   +1 more source

Next Generation of Thermal Barrier Coatings with High Temperature Metal‐Silicide Metamaterials

Advanced Optical Materials, Volume 14, Issue 2, 14 January 2026.
Thermal metamaterials have emerged as a powerful platform in the engineering of radiative heat transfer across a broad range of applications, including thermal imaging, passive cooling, and thermo‐photovoltaics. Here, a novel application is presented for metamaterials: thermal dual barrier coatings (TDBCs).
Ali Jishi, Avra S Bandyopadhyay, Xueji Wang, Tyler J Sentz, Aashish Poudel, Daien He, Wenbo Sun, Ashwin K Boddeti, Indra Subedi, Prabin Dulal, Bailey Frye, Nikolas Podraza, Chinmay Khandekar, Fanglin Bao, Thomas Thundat, Zubin Jacob   +15 more
wiley   +1 more source

High-efficiency broadband active metasurfaces via reversible metal electrodeposition. [PDF]

Light Sci Appl
Li Q, Kulkarni SP, Sui C, Chen TH, Yan G, Wu R, Chen W, Hung PJ, Wu X, Emersic T, Aydin K, Hsu PC.   +11 more
europepmc   +1 more source

Advanced Emissivity Tuning Via Femtosecond Laser Surface Engineering

Advanced Optical Materials, Volume 14, Issue 1, 9 January 2026.
Femtosecond laser surface processing (FLSP) is employed to fabricate titanium‐based metamaterials with engineered micro/nano‐scale features that exhibit spectrally selective and omnidirectional thermal emissivity. By integrating advanced ellipsometry, electromagnetic modeling, and compositional analysis, the work reveals resonance‐driven emissivity ...
Zahra Kamali Khanghah, Andrew Butler, Andrew Reicks, Juveriya Parmar, Eva Schubert, Craig Zuhlke, Mathias Schubert, Ufuk Kilic, Mohammad Ghashami   +8 more
wiley   +1 more source

Subwavelength imaging using orbital angular momentum waves generated by metasurfaces. [PDF]

Sci Rep
Ashrafian M, Yousefi L.
europepmc   +1 more source

Inverse Design in Nanophotonics via Representation Learning

Advanced Optical Materials, Volume 14, Issue 1, 9 January 2026.
This review frames machine learning (ML) in nanophotonics through a classification based on where ML is applied. We categorize methods as either output‐side, which create differentiable surrogates for solving Maxwell's partial differential equations (PDEs), or input‐side, which learn compact representations of device geometry.
Reza Marzban, Ali Adibi, Raphaël Pestourie   +2 more
wiley   +1 more source