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Photonic Random-Access Memories (P-RAM) are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data links. Emerging Phase Change Materials (PCMs) have been showed…

Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved…

Reconfigurable photonic devices are rapidly emerging as a cornerstone of next generation optical technologies, with wide ranging applications in quantum simulation, neuromorphic computing, and large-scale photonic processors. A central…

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…

We propose an infrared power switch based on an asymmetric high-Q microcavity incorporating a metallic nanolayer in close proximity to a layer made of a phase-change material (PCM). The microcavity is designed so that when the PCM layer is…

Phase change materials (PCMs) hold considerable promise for thermal energy storage applications. However, designing a PCM system to meet specific performance presents a formidable challenge, given the intricate influence of multiple factors…

Scalable programmable photonic integrated circuits (PICs) can potentially transform the current state of classical and quantum optical information processing. However, traditional means of programming, including thermo-optic, free carrier…

Traditional DRAM-based main memory systems face several challenges with memory refresh overhead, high latency, and low throughput as the industry moves towards smaller DRAM cells. These issues have been exacerbated by the emergence of…

Chalcogenide phase-change materials (PCMs) are regarded as the leading candidate for storage-class non-volatile memory and neuro-inspired computing. Recently, using the $TiTe_2$/$Sb_2Te_3$ material combination, a new framework -…

Progress in integrated nanophotonics has enabled large-scale programmable photonic integrated circuits (PICs) for general-purpose electronic-photonic systems on a chip. Relying on the weak, volatile thermo-optic or electro-optic effects,…

Programmable photonic integrated circuits are expected to play an increasingly important role to enable high-bandwidth optical interconnects, and large-scale in-memory computing as needed to support the rise of artificial intelligence and…

Programmable photonic integrated circuits (PICs) offer a unique opportunity to create a flexible platform, akin to electronic field programmable gate array (FPGA). These photonic PGAs can implement versatile functionalities for applications…

Optical phase-change materials are highly promising for emerging applications such as tunable metasurfaces, reconfigurable photonic circuits, and non-von Neumann computing. However, these materials typically require both high melting…

The thermal properties of amorphous and crystalline phases in chalcogenide phase change materials (PCM) play a key role in device performance for non-volatile random-access memory. Here, we report the nanothermal morphology of amorphous and…

Leveraging the latent heat of phase change materials (PCMs) can reduce the peak temperatures and transient variations in temperature in electronic devices. But as the power levels increase, the thermal conduction pathway from the heat…

The combination of metasurfaces with chalcogenide phase-change materials is a highly promising route towards the development of multifunctional and reconfigurable nanophotonic devices. However, their transition into real-world devices is…

The incorporation of high-performance optoelectronic devices into photonic neuromorphic processors can substantially accelerate computationally intensive operations in machine learning (ML) algorithms. However, the conventional device…

In the search for phase change materials (PCM) that may rival traditional random access memory, a complete understanding of the amorphous to crystalline phase transition is required. For the well-known Ge2Sb2Te5 (GST) and GeTe (GT)…

Spiking Neural Networks (SNNs) offer an event-driven and more biologically realistic alternative to standard Artificial Neural Networks based on analog information processing. This can potentially enable energy-efficient hardware…

The prevalent high intrinsic absorption in the crystalline state of phase-change materials (PCMs), typically leads to a decline in modulation efficiency for phase-change metasurfaces, underutilizing their potential for quasi-continuous…