590 research outputs found

    Collective resonances in plasmonic crystals: Size matters

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    Periodic arrays of metallic nanoparticles may sustain Surface Lattice Resonances (SLRs), which are collective resonances associated with the diffractive coupling of Localized Surface Plasmon Resonances (LSPRs). By investigating a series of arrays with varying number of particles, we traced the evolution of SLRs to its origins. Polarization resolved extinction spectra of arrays formed by a few nanoparticles were measured, and found to be in very good agreement with calculations based on a coupled dipole model. Finite size effects on the optical properties of the arrays are observed, and our results provide insight into the characteristic length scales for collective plasmonic effects: for arrays smaller than 5 x 5 particles, the Q-factors of SLRs are lower than those of LSPRs; for arrays larger than 20 x 20 particles, the Q-factors of SLRs saturate at a much larger value than those of LSPRs; in between, the Q-factors of SLRs are an increasing function of the number of particles in the array.Comment: 4 figure

    Thermalization and Cooling of Plasmon-Exciton Polaritons: Towards Quantum Condensation

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    We present indications of thermalization and cooling of quasi-particles, a precursor for quantum condensation, in a plasmonic nanoparticle array. We investigate a periodic array of metallic nanorods covered by a polymer layer doped with an organic dye at room temperature. Surface lattice resonances of the array---hybridized plasmonic/photonic modes---couple strongly to excitons in the dye, and bosonic quasi-particles which we call plasmon-exciton-polaritons (PEPs) are formed. By increasing the PEP density through optical pumping, we observe thermalization and cooling of the strongly coupled PEP band in the light emission dispersion diagram. For increased pumping, we observe saturation of the strong coupling and emission in a new weakly coupled band, which again shows signatures of thermalization and cooling.Comment: 8 pages, 5 figures including supplemental material. The newest version includes new measurements and corrections to the interpretation of the result

    Rapid hydration and weakening of anhydrite under stress: implications for natural hydration in the Earth's crust and mantle

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    Mineral hydration is an important geological process that influences the rheology and geochemistry of rocks and the fluid budget of the Earth's crust and mantle. Constant-stress differential compaction (CSDC) tests, dry and "wet"tests under confining pressure, and axial-stress tests were conducted for the first time to investigate the influence of triaxial stress on hydration in anhydrite-gypsum aggregates. Characterization of the samples before and after triaxial experiments was performed with optical and scanning electron microscopy, including energy-dispersive spectroscopy and electron backscatter diffraction mapping. Stress-strain data reveal that samples that underwent constant-stress differential compaction in the presence of fluids are g1/4g14g% to g1/4g41g% weaker than samples deformed under wet conditions. The microstructural analysis shows that there is a strong temporal and spatial connection between the geometry, distribution, and evolution of fractures and hydration products. The increasing reaction surface area in combination with pre-existing gypsum in a gypsum-bearing anhydrite rock led to rapid gypsification. The crystallographic orientations of newly formed vein gypsum have a systematic preferred orientation for long distances along veins, beyond the grain boundaries of wall-rock anhydrite. Gypsum crystallographic orientations in {100} and {010} are systematically and preferentially aligned parallel to the direction of maximum shear stress (45g to σ1). Gypsum is also not always topotactically linked to the wall-rock anhydrite in the immediate vicinity. This study proposes that the selective inheritance of crystal orientations from favourably oriented wall-rock anhydrite grains for the minimization of free energy for nucleation under stress leads to the systematic preferred orientation of large, new gypsum grains. A sequence is suggested for hydration under stress that requires the development of fractures accompanied by localized hydration. Hydration along fractures with a range of apertures up to 120gμm occurred in under 6gh. Once formed, gypsum-filled veins represent weak surfaces and are the locations of further shear fracturing, brecciation, and eventual brittle failure. These findings imply that non-hydrostatic stress has a significant influence on hydration rates and subsequent mechanical strength of rocks. This phenomenon is applicable across a wide range of geological environments in the Earth's crust and upper mantle

    From weak to strong coupling of localized surface plasmons to guided modes in a luminescent slab

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    We investigate a periodic array of aluminum nanoantennas embedded in a light-emitting slab waveguide. By varying the waveguide thickness we demonstrate the transition from weak to strong coupling between localized surface plasmons in the nanoantennas and refractive index guided modes in the waveguide. We experimentally observe a non-trivial relationship between extinction and emission dispersion diagrams across the weak to strong coupling transition. These results have implications for a broad class of photonic structures where sources are embedded within coupled resonators. For nanoantenna arrays, strong vs. weak coupling leads to drastic modifications of radiation patterns without modifying the nanoantennas themselves, thereby representing an unprecedented design strategy for nanoscale light sources

    Exploring the Vision Processing Unit as Co-Processor for Inference

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    The success of the exascale supercomputer is largely debated to remain dependent on novel breakthroughs in technology that effectively reduce the power consumption and thermal dissipation requirements. In this work, we consider the integration of co-processors in high-performance computing (HPC) to enable low-power, seamless computation offloading of certain operations. In particular, we explore the so-called Vision Processing Unit (VPU), a highly-parallel vector processor with a power envelope of less than 1W. We evaluate this chip during inference using a pre-trained GoogLeNet convolutional network model and a large image dataset from the ImageNet ILSVRC challenge. Preliminary results indicate that a multi-VPU configuration provides similar performance compared to reference CPU and GPU implementations, while reducing the thermal-design power (TDP) up to 8x in comparison.The experimental results were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC Centre for High-Performance Com- puting (PDC-HPC). The work was funded by the European Commission through the SAGE project (Grant agreement no. 671500 / http://www.sagestorage.eu).Postprint (author's final draft
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