Publications

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We theoretically analyze the second harmonic generation capacity of two-dimensional periodic metamaterials comprising sub-wavelength resonators strongly coupled to intersubband transitions in quantum wells (QWs) at mid-infrared frequencies. The metamaterial is designed to support a fundamental resonance at ∼30THz and an orthogonally polarized resonance at the second harmonic frequency (∼60THz), while the asymmetric quantum well structure is designed to provide a large second order susceptibility. Upon continuous wave illumination at the fundamental frequency we observe second harmonic signals in both the forward and backward directions, with the forward efficiency being larger. We calculate the overall second harmonic conversion efficiency of the forward wave to be ∼1.3×10-2 W/W2 - a remarkably large value, given the deep sub-wavelength dimensions of the QW structure (about 1/15th of the free space wavelength of 10μm). The results shown in this Letter provide a strategy for designing easily fabricated sources across the entire infrared spectrum through proper choice of QW and resonator designs. © 2014 AIP Publishing LLC.

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Microalgae have been identified as a promising renewable feedstock for production of lipids for feeds and fuels. Current methods for identifying algae strains and growth conditions that support high lipid production require a variety of fluorescent chemical indicators, such as Nile Red and more recently, Bodipy. Despite notable successes using these approaches, chemical indicators exhibit several drawbacks, including non-uniform staining, low lipid specificity, cellular toxicity, and variable permeability based on cell-type, limiting their applicability for high-throughput bioprospecting. In this work, we used in vivo hyperspectral confocal fluorescence microscopy of a variety of potential microalgae production strains (Nannochloropsis sp., Dunaliella salina, Neochloris oleoabundans, and Chlamydomonas reinhardtii) to identify a label-free method for localizing lipid bodies and quantifying the lipid yield on a single-cell basis. By analyzing endogenous fluorescence from chlorophyll and resonance Raman emission from lipid-solubilized carotenoids we deconvolved pure component emission spectra and generated diffraction limited projections of the lipid bodies and chloroplast organelles, respectively. Applying this imaging method to nutrient depletion time-courses from lab-scale and outdoor cultivation systems revealed an additional autofluorescence spectral component that became more prominent over time, and varied inversely with the chlorophyll intensity, indicative of physiological compromise of the algal cell. This signal could result in false-positives for conventional measurements of lipid accumulation (via spectral overlap with Nile Red), however, the additional spectral feature was found to be useful for classification of lipid enrichment and culture crash conditions in the outdoor cultivation system. Under nutrient deprivation, increases in the lipid fraction of the cellular volume of ~. 500% were observed, as well as a correlated decrease in the chloroplast fraction of the total cellular volume. The results suggest that a membrane recycling mechanism dominates for nutrient deprivation-based lipid accumulation in the microalgae tested.

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We demonstrate a new type of electrically tunable strong coupling between a planar metamaterial layer and an ultra-thin epsilon-near-zero layer made of a doped semiconductor. This can find novel applications in chip-scale infrared optoelectronic devices. © OSA 2013.

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Tellurium dielectric resonator metamaterials were fabricated using a newly developed multi-cycle deposition-etch process. Deposition and etching of Tellurium were studied in detail. All the samples showed two transmission minima corresponding to magnetic and electric dipole resonances. © 2013 The Optical Society.

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Multivariate curve resolution (MCR) is a useful and important analysis tool for extracting quantitative information from hyperspectral image data. However, in the case of hyperspectral fluorescence microscope images acquired with CCD-type technologies, cosmic spikes and the presence of detector artifacts in the spectral data can make the extraction of the pure-component spectra and their relative concentrations challenging when applying MCR to the images. In this paper, we present new generalized and automated approaches for preprocessing spectral image data to improve the robustness of the MCR analysis of spectral images. These novel preprocessing steps remove cosmic spikes, correct for the presence of detector offsets and structured noise as well as select spectral and spatial regions to reduce the detrimental effects of detector noise. These preprocessing and MCR analysis techniques incorporate the use of an optical filter to prevent light from impinging on a small number of spectral pixels in the CCD detector. This dark spectral region can be incorporated into any spectral imaging system to enhance modeling of detector offset and structured noise components as well as the automated selection of spatial regions to restrict the analysis to only those regions containing viable spectral information. The success of these automated preprocessing methods combined with new MCR modeling approaches are demonstrated with realistically simulated data derived from spectral images of macrophage cells with green fluorescence protein (GFP). Further, we demonstrate using spectral images from the green alga, Chlorella, approaches for the analyses when fluorescent species with widely different relative spectral intensities are present in the image. We believe that the preprocessing and MCR approaches introduced in this paper can be generalized to several other hyperspectral image technologies and can improve the success of automated MCR analyses with little or no a priori information required about the spectral components present in the samples. © 2012 Elsevier B.V.

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