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A label-free optical biosensor is described that employs a silicon-based high-contrast grating (HCG) resonator with a spectral linewidth of ~500 pm that is sensitive to ligand-induced changes in surface properties. The device is used to generate thermodynamic and kinetic data on surface-attached antibodies with their respective antigens. The device can detect serum cardiac troponin I, a biomarker of cardiac disease to 100 pg/ml within 4 mins, which is faster, and as sensitive as current enzyme-linked immuno-assays for cTnI.

We have developed a microelectromechanical system (MEMS) optical phased array incorporating a high-index-contrast subwavelength grating (HCG) for beamforming and beamsteering in a range of ± 1.26° × 1.26°. Our approach needs only a thin single-layer HCG made of silicon, considerably improving its speed thanks to the low mass, and is suitable for high optical power applications. The measured resonant frequency of HCG is 0.32 MHz.

We report a high speed 8x8 optical phased array using tunable 1550 nm all-pass filters with ultrathin high contrast gratings (HCGs) as the microelectromechanical-actuated top reflectors. The all-pass filter design enables a highly efficient phase tuning (1.7 π) with a small actuation voltage (10 V) and actuation displacement of the HCG (50 nm). The microelectromechanical HCG structure facilitates a high phase tuning speed >0.5 MHz. Beam steering is experimentally demonstrated with the optical phased array.

We report on microelectromechanical systems (MEMS)-actuated 32 × 32 optical phased arrays (OPAs) with high fill-factors and microsecond response time. To reduce the mirror weight and temperature-dependent curvature, we use high-contrast-grating (HCG) mirrors comprising a single layer of sub-wavelength polysilicon gratings with 400 nm thickness, 1250 nm pitch, and 570 nm grating bar width. The mirror has a broad reflection band and a peak reflectivity of 99.9% at 1550 nm wavelength. With 20 × 20 μm2 pixels and 2 μm, the OPA has a total aperture of 702 × 702 μm2 and a fill factor of 85%. The OPA is electrostatically controlled by voltage and has a total field of view of ± 2°, an instantaneous field of view (beam width) of 0.14°, and a response time of 3.8 μs. The latter agrees well with the mechanical resonance frequency of the HCG mirror (0.42 MHz).

Abstract:In this paper, a new color image encryption algorithm based on a fractional-order hyperchaotic system is proposed. Firstly, four chaotic sequences are generated by a fractional-order hyperchaotic system. The parameters of such a system, together with the initial value, are regarded as the secret keys and the plain image is encrypted by performing the XOR and shuffling operations simultaneously. The proposed encryption scheme is described in detail with security analyses, including correlation analysis, histogram analysis, differential attacks, and key sensitivity analysis. Experimental results show that the proposed encryption scheme has big key space, and high sensitivity to keys properties, and resists statistical analysis and differential attacks, so it has high security and is suitable for color image encryption.

We demonstrate efficient optical modulation of surface-normal reflection in a novel device structure integrating graphene on a high contrast grating (HCG) resonator. As high as 11 dB extinction ratio is achieved by varying the voltage applied to a single atomic layer of graphene on a HCG resonator. The device topology facilitates easy fabrication of large 2D arrays, and free-space operation. We also demonstrate a graphene-oxide-graphene structure which can potentially operate at MHz operation speed. The devices are fully fabricated by standard CMOS compatible processes indicating that the integrated structure of graphene-on-HCG shows great promise for display, imaging and interconnects applications with low-cost and large scalability.

This study proposes a novel super-resolution regularisation model based on adaptive sparse representation and selflearning frameworks. The fidelity term in the model ensures that the reconstructed image is consistent with the observation image. The adaptive sparsity regularisation term constrains the reconstructed image with an adaptive sparse representation, which successfully harmonises the sparse representation and the collaborative representation adaptively via producing suitable coefficients. To construct a more effective dictionary, the high-frequency features from the underlying image patches are extracted, and the dictionary learning and sparse representation are integrated. To this end, the alternating minimisation algorithm is used to divide this model into three subproblems, and the alternating direction method of multipliers and iterative back-projection method are used to solve the subproblems. To illustrate the effectiveness of the proposed method, additional experiments are conducted on some generic images. Compared with some state-of-the-art algorithms, the experimental results demonstrate that the proposed method achieves better results in terms of both visual quality and noise immunity.