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A high performance sinusoidal grating-based surface plasmon resonance (SPR) biosensor is proposed. The angular interrogation method has been used to study the performance of the sensor. The sensitivity as well as the width of the SPR curves and reflective amplitude is considered for designing the sensor. Compared with the gold(Au)-based SPR sensor, we find that the silver(Ag)-based sensor has the better performance. Numerical simulations show that the sensitivity of the Ag-based sensor is 193.9°/RIU.

An efficient surface enhanced Raman scattering (SERS) substrate has been developed based on highly ordered arrays of graphene–isolated Au nanoparticle (G/AuNP). By combining the electromagnetic enhancement activity of AuNP arrays and unique physical/chemical properties of graphene, the G/AuNP arrays shows high performance in terms of sensitivity, signal-to-noise ratio and reproducibility. The average enhancement factor obtained from the G/AuNP arrays for rhodamine 6G probe molecules is over 10 7 . The maximum deviations of SERS intensities from 20 positions of a same SERS substrate are in the range of 4.74% to 6.89% and from 20 different substrates in various batches are in the range of 5.67% to 8.37%, depending on different vibration modes. As a practical application of this SERS system, we detect the adenosine concentration in human serum. The detection results show a good linear correlation between SERS intensity and adenosine concentration within the range of 2 to 250 nM. This work may open up new opportunities in developing the applications of SERS in biomedical diagnostics, biological sensing and other biotechnology.

In adaptive filtering, several algorithms are developed in the quest for greater convergence speed, mostly relying on second order statistics. Here we modify the Recursive Least Square (RLS) equations by using as performance surface a weighted sum of even error power. As a result, the equations turn out to be simple, elegant, while yielding faster convergence and preserving the computational cost when compared with the existing RLS algorithm. HighlightsIn this study, we propose a new recursive algorithm that optimizes a sum of the even powers of the error.In adaptive filtering, several algorithms were developed to improve convergence speed, but they rely mostly on second order statistics.This algorithm seems to be faster than usual recursive algorithms presents in the literature.

Nanogaps or sharp protrusions has been proved useful for surface enhanced Raman scatting (SERS) in single-molecule sensing and a low cost method for fabricating SERS active substrate with these naonstructures is very important for practical applications of SERS in clinical or biological area. In this work, PMMA 3D nanostructures with sub-20nm ordered nanogap network and sharp tips are fabricated by high-fidelity replica molding. The morphology, water repellency property and Raman enhancement effect of the 3D nanostructures are characterized by SEM, water contact angle and SERS. The results show that the 3D nanostructure of rocket-like array has higher SERS enhancement factor (EF) than the 3D nanostructure of nano-lawn due to the ordered nanogaps, and both of them change the surface wettability of PMMA from hydrophilic to hydrophobic, especially for the 3D structure of nano-lawn.

Techniques available in the literature to enhance the robustness of generic model control (GMC) are reviewed. We show that none of these techniques utilize a rigorous analysis of the process-model mismatch. This paper presents GMC from the geometric perspective in order to analyze the effect of process uncertainties in the closed-loop response. The geometric approach defines a performance surface for the closed-loop response with no model error. When the model is not perfect, the system leaves the surface, making the response diffrent from the reference. A technique based on sliding mode control, called sliding generic model control, is developed here to take into account the process uncertainties and to keep the system close to the GMC performance surface.

In this poster paper, a novel grinding process for replacing conventional surface and creep feed grinding processes is presented. This grinding process allows high removal rates in hard machining with flexibility and a good surface finish at the same time. A peel grinding process is conducted with a high workpiece velocity and a high depth of cut, using a conventional surface grinding machine and an electroplated CBN wheel with a custom shape. To validate the efficiency of this process, the process forces and the surface roughness values have been carried out experimentally.