Stanford engineers debuted a new framework introducing computational tools and self-reflective AI assistants, potentially advancing fields like optical computing and astronomy.

Artificial intelligence speeds metasurface design from unit cells to full optical systems, enabling compact imaging, AR and VR displays and advanced LiDAR. (Nanowerk News) Optical metasurfaces, with ...

A new review article published in iOptics reveals how artificial intelligence (AI) is providing solutions for metasurface technology to transition from unit optimization to system-level integration.

Optical metasurfaces, with their ultra-thin and lightweight properties, are driving the miniaturization and planarization of optical systems. However, their development from unit-cell design to system ...

Metasurfaces are two-dimensional (2D), nanoengineered surfaces that interact strongly with electromagnetic waves and can control light with remarkable precision. These ultra-thin layers can be used to ...

Abstract: This article presents a physics-informed deep learning framework using deep neural networks (DNNs) for metasurface (MS) design. By integrating equivalent circuit parameters as physically ...

Abstract: Training a deep learning (DL) model with data collected from full-wave simulations to accurately estimate electromagnetic responses has become a prevalent approach for metasurface ...

Computational optics represents a shift in approach where optical hardware and computational algorithms are designed to work together, enabling imaging capabilities that surpass those of traditional ...

From Cape Town to Tehran to Lima to Phoenix, dozens of cities across the globe have recently experienced water shortages. In the next five years the world’s demand for fresh water could significantly ...