All-dielectric metasurfaces comprising arrays of nanostructured high-refractive-index materials are re-imagining what is achievable in terms of the manipulation of light. However, the functionality of conventional dielectric-based metasurfaces is fixed by design; thus, their optical response is locked in at the fabrication stage. A far wider range of applications could be addressed if dynamic and reconfigurable control were possible. We demonstrate this here via the novel concept of hybrid metasurfaces, in which reconfigurability is achieved by embedding sub-wavelength inclusions of chalcogenide phase-change materials within the body of silicon nanoresonators. By strategic placement of an ultra-thin G e 2 S b 2 T e 5 layer and reversible switching of its phase-state, we show individual, multilevel, and dynamic control of metasurface resonances. We showcase our concept via the design, fabrication, and characterization of metadevices capable of dynamically filtering and modulating light in the near infrared (O and C telecom bands), with modulation depths as high as 70% and multilevel tunability. Finally, we show numerically how the same approach can be re-scaled to shorter wavelengths via appropriate material selection, paving the way to additional applications, such as high-efficiency vivid structural color generators in the visible spectrum. We believe that the concept of hybrid all-dielectric/phase-change metasurfaces presented in this work could pave the way for a wide range of design possibilities in terms of multilevel, reconfigurable, and high-efficiency light manipulation.

Metasurfaces and nanoantennas are redefining what can be achieved in terms of optical beam manipulation, as they provide a versatile design platform towards moulding the flow of light at will. Yet, once a conventional metasurface is designed and realised, its effect on optical beams is repeatable and stationary, thus its performance is 'locked-in' at the fabrication stage. A much wider range of applications, such as dynamic beam steering, reconfigurable and dynamic lensing, optical modulation and reconfigurable spectral filtering, could be achieved if real-time tuning of metasurface optical properties were possible. Chalcogenide phase-change materials, because of their rather unique ability to undergo abrupt, repeatable and non-volatile changes in optical properties when switched between their amorphous and crystalline phases, have in recent years been combined with metasurface architectures to provide a promising platform for the achievement of dynamic tunability. In this paper, the concept of dynamically tunable phase-change metasurfaces is introduced, and recent results spanning the electromagnetic spectrum from the visible right through to the THz regime are presented and discussed. The progress, potential applications, and possible future perspectives of phase-change metasurface technology are highlighted, and requirements for the successful implementation of real-world applications are discussed.

Advances in artificial intelligence have greatly increased demand for data-intensive computing. Integrated photonics is a promising approach to meet this demand in big-data processing due to its potential for wide bandwidth, high speed, low latency, and low-energy computing. Photonic computing using phase-change materials combines the benefits of integrated photonics and co-located data storage, which of late has evolved rapidly as an emerging area of interest. In spite of rapid advances of demonstrations in this field on both silicon and silicon nitride platforms, a clear pathway towards choosing between the two has been lacking. In this paper, we systematically evaluate and compare computation performance of phase-change photonics on a silicon platform and a silicon nitride platform. Our experimental results show that while silicon platforms are superior to silicon nitride in terms of potential for integration, modulation speed, and device footprint, they require trade-offs in terms of energy efficiency. We then successfully demonstrate single-pulse modulation using phase-change optical memory on silicon photonic waveguides and demonstrate efficient programming, memory retention, and readout of > 4 bits of data per cell. Our approach paves the way for in-memory computing on the silicon photonic platform. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

The operation of a single class of optical materials in both a volatile and nonvolatile manner is becoming increasingly important in many applications. This is particularly true in the newly emerging field of photonic neuromorphic computing, where it is desirable to have both volatile (short-term transient) and nonvolatile (long-term static) memory operation, for instance, to mimic the behavior of biological neurons and synapses. The search for such materials thus far have focused on phase change materials where typically two different types are required for the two different operational regimes. In this paper, a tunable volatile/nonvolatile response is demonstrated in a photonic phase-change memory cell based on the commonly employed nonvolatile material Ge 2 Sb 2 Te 5 (GST). A time-dependent, multiphysics simulation framework is developed to corroborate the experimental results, allowing us to spatially resolve the recrystallization dynamics within the memory cell. It is then demonstrated that this unique approach to photonic memory enables both data storage with tunable volatility and detection of coincident events between two pulse trains on an integrated chip. Finally, improved efficiency and all-optical routing with controlled volatility are demonstrated in a ring resonator. These crucial results show that volatility is intrinsically tunable in normally nonvolatile GST which can be used in both regimes interchangeably.

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