Abstract

Our group designs and fabricates micropillar lasers with integrated saturable absorbers which can be modeled using the LIF neuron model and demonstrate important neuromimetic properties such as excitable behaviour, temporal summation, spike latency and refractory periods. Using these basic properties, we build computing primitives based on coupled laser systems.

Abstract

Foundry-manufactured, monolithically integrated multilayer silicon nitride-on-silicon photonic platforms are suitable for large-scale photonic circuits.  These photonic platforms contain several waveguide layers, and light is routed amongst the layers to create 3D photonic devices and circuits.  We have realized a suite of devices in these platforms, including ultra-low-loss waveguide crossings, multi-layer grating couplers, and efficient modulators.  These advancements, which were initially driven by telecommunications, are leading to neurophotonic implants for brain activity mapping.

"Next-generation organic electro-optic materials for hybrid device architectures"
Gerard Zytnicki, Lewis Johnson and Paul Nye
(Nonlinear Material Corporation, Seattle, Washington)

Abstract

Next-generation silicon-organic hybrid (SOH) and plasmonic-organic hybrid (POH) device architectures have led to renewed interest in organic electro-optic (OEO) materials for chip-scale photonic integration under a different set of design constraints than for bulk devices. State-of-the art hybrid devices are capable of 10x the electro-optic activity of LiNbO3 and far superior device footprints, power efficiency, and signal quality to competing device architectures. Fully realizing the multiple order of magnitude reduction in modulator size from advances in hybrid devices will require development of materials with exceptional electro-optic activity and refractive indices that have been optimized for these device architectures. Multiscale modeling, combining classical condensed-phase simulations and electronic structure theory, has provided many crucial observations that suggest how to design the next generation of OEO molecules. We apply a variety of computational techniques to identify bottlenecks to materials performance and develop routes for transformative improvement in electro-optic materials, in addition to leveraging insights in dendritic chromophore systems to improve thermal stability. Our calculations have already identified synthetically feasible materials predicted to yield > 2x performance improvements versus the state of the art and provide a pathway to order-of-magnitude improvement.

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