Related papers: On-chip rewritable phase-change metasurface for pr…
Molding the flow of light at the nanoscale has been a grand challenge of nanophotonics for decades. It is now widely recognized that metasurfaces represent a chip-scale nanophotonics array technology capable of comprehensively controlling…
Optical metasurfaces have been enabling reduced footprint and power consumption, as well as faster speeds, in the context of analog computing and image processing. While various image processing and optical computing functionalities have…
As dynamic random access memory (DRAM) and other current transistor-based memories approach their scalability limits, the search for alternative storage methods becomes increasingly urgent. Phase-change memory (PCM) emerges as a promising…
There exists a significant scale gap between photonic neural network integrated chips and neural networks, which hinders the deployment and application of photonic neural network. Here, we propose hardware-aware lightweight spiking neural…
An optical equivalent of the field-programmable gate array (FPGA) is of great interest to large-scale photonic integrated circuits. Previous programmable photonic devices relying on the weak, volatile thermo-optic or electro-optic effect…
Photonics integrated circuitry would benefit considerably from the ability to arbitrarily control waveguide cross-sections with high precision and low loss, in order to provide more degrees of freedom in manipulating propagating light.…
Additive manufacturing using 2-Photon Polymerization (2PP, aka direct laser writing DLW) enables the fabrication of almost arbitrary complex 3D structures from the meso to the submicron scale. However, deviations between the anticipated…
The ability to reversibly and site-selectively tune ambipolar doping in a single semiconductor is crucial for reconfigurable electronics beyond silicon, but remains highly challenging. Here, we present a rewritable architecture based on…
Structural colors generated due to light scattering from static all-dielectric metasurfaces have successfully enabled high-resolution, high-saturation, and wide-gamut color printing applications. Despite recent advances, most demonstrations…
As transistor-based memory technologies like dynamic random access memory (DRAM) approach their scalability limits, the need to explore alternative storage solutions becomes increasingly urgent. Phase-change memory (PCM) has gained…
Photonic neuromorphic computing promises revolutionary advances in parallel and high-speed processing, yet a key challenge persists: co-integrating nonlinearity, dense connectivity, and intrinsic memory monolithically to enable…
Metasurfaces can manipulate the amplitude and phase of electromagnetic waves, offering applications ranging from antenna design and cloaking to imaging and communication. Additionally, temporal, and non-linear metasurfaces have the…
Photonic computing chips have made significant progress in accelerating linear computations, but nonlinear computations are usually implemented in the digital domain, which introduces additional system latency and power consumption, and…
Achieving an electrically tunable phased array optical antenna surface has been a principal challenge in the field of metasurfaces. In this letter, we demonstrate a device platform for achieving reconfigurable control over the resonant…
Phase-change memory (PCM) is a scalable and low latency non-volatile memory (NVM) technology that has been proposed to serve as storage class memory (SCM), providing low access latency similar to DRAM and often approaching or exceeding the…
Dedicated hardware implementations of spiking neural networks that combine the advantages of mixed-signal neuromorphic circuits with those of emerging memory technologies have the potential of enabling ultra-low power pervasive sensory…
The optical properties of phase-change materials (PCM) can be tuned to multiple levels by controlling the transition between their amorphous and crystalline phases. In multi-material PCM structures, the number of discrete reflectance levels…
Photocatalysis in atomically thin semiconductors is often limited by rapid electron-hole recombination, making it difficult to translate favorable band structures into efficient chemical function. Here we propose symmetry-defined periodic…
All-optical and fully reconfigurable diffractive optical neural network (DONN) architectures are promising for high-throughput and energy-efficient machine learning (ML) hardware accelerators for broad applications. However, current device…
Optical wave-based computing has enabled the realization of real-time information processing in both space and time domains. In the past few years, analog computing has experienced rapid development but mostly for a single function.…