Application of the fractional Fourier transform to the design of LCOS based optical interconnects and fiber switches

It is shown that reflective liquid crystal on silicon (LCOS) spatial light modulator (SLM) based interconnects or fiber switches that use defocus to reduce crosstalk can be evaluated and optimized using a fractional Fourier transform if certain optical symmetry conditions are met. Theoretically the maximum allowable linear hologram phase error compared to a Fourier switch is increased by a factor of six before the target crosstalk for telecom applications of -40 dB is exceeded. A Gerchberg-Saxton algorithm incorporating a fractional Fourier transform modified for use with a reflective LCOS SLM is used to optimize multi-casting holograms in a prototype telecom switch. Experiments are in close agreement to predicted performance. © 2012 Optical Society of America.

Comparison between granular pillared, organo- and inorgano-organo-bentonites for hydrocarbon and metal ion adsorption

Granular reactive materials have higher permeability and are therefore desirable for in situ groundwater pollution control. Three granular bentonites were prepared: an Al-pillared bentonite (PBg), an organo-bentonite (OBg) using a quaternary ammonium cation (QAC), and an inorgano-organo-bentonite (IOBg), using both the pillaring agent and the QAC. Powdered IOB (IOBp) was also prepared to test the effect of particle size. The modified bentonites were characterised with X-ray diffraction (XRD), Fourier transform infrared spectrometry (FT-IR), thermal gravimetric analysis (TGA) and uniaxial compression tests. The d-spacing increased only with QAC intercalation. The Young's modulus of IOBg was twice as high as OBg. Batch adsorption tests were performed with aqueous multimetal solutions of Pb2+, Cu2+, Cd2+, Zn2+ and Ni2+ ions, with liquid dodecane and with aqueous dodecane solutions. Metal adsorption fit the Langmuir isotherm. Adsorption occurred within 30min for PBg, while the granular organo-bentonite needed at least 12h to reach equilibrium. IOBp had the maximum adsorption capacity at higher metal concentration and lower adsorbent content (Cu2+: 2.2, Ni2+: 1.7, Zn2+: 1.4, Cd2+: 0.9 and Pb2+: 0.7 all in mmolg-1). The dual pillaring of the QAC and Al hydroxide increased the adsorption. The adsorption of liquid dodecane was in the order IOBg>OBg>PBg (3.2>2.7>1.7mmolg-1). Therefore IOBg has potential for the removal of toxic compounds found in soil, groundwater, storm water and wastewater. © 2012 Elsevier B.V.

Three-dimensional distribution of Al in high-k metal gate: Impact on transistor voltage threshold

The three-dimensional spatial distribution of Al in the high-k metal gates of metal-oxide-semiconductor field-effect-transistors is measured by atom probe tomography. Chemical distribution is correlated with the transistor voltage threshold (VTH) shift generated by the introduction of a metallic Al layer in the metal gate. After a 1050 °C annealing, it is shown that a 2-Å thick Al layer completely diffuses into oxide layers, while a positive VTH shift is measured. On the contrary, for thicker Al layers, Al precipitation in the metal gate stack is observed and the VTH shift becomes negative. © 2012 American Institute of Physics.

The effect of cationic, non-ionic and amphiphilic surfactants on the intercalation of bentonite

Surfactant-clay interactions are key for the development of new clay applications and inorganic-organic nanocomposites. Bentonite, with montmorillonite as the principal clay mineral constituent, was modified with varying concentrations of hexadecethyltrimethylammonium chloride (HDTMA), as a reference cationic surfactant, polypropylene glycol (PPG) 1200 and 2000, as non-ionic surfactants, and lecithin and Topcithin®, as amphiphilic phospholipid surfactants, according to the cation exchange capacity (CEC). The modified bentonites were characterised by X-ray diffraction, thermogravimetric analysis (TGA), Fourier transform infrared (FTIR) spectrometry, specific surface area and pore volume. Three intercalation regions have been identified depending on the surfactant. The non-ionic surfactant caused only a crystalline expansion of bentonite interlayers, while the cationic surfactant induced an osmotic intercalation. The amphiphilic lecithin derivatives intercalated more extensively with the bentonite matrix. The TGA and the FTIR spectra showed that, at lower concentrations, the PPGs and HDTMA adopted a disordered conformation that required more energy to degrade, while at higher concentrations, the surfactants were ordered in the interlayer space of the bentonite. The lecithin derivative surfactant had a greater thermal and conformation stability. The specific surface area reduced with increasing surfactant concentrations. This study highlights the effect of surfactant type on the interlayer space of montmorillonite in the perspective of developing novel clay functions. © 2013.

Properties and microstructure of GGBS-magnesia pastes

Reactive magnesia (MgO) was used as an alkali activator for ground granulated blast-furnace slag (GGBS) and its activating efficiency was investigated compared with hydrated lime. GGBS-MgO and GGBS-hydrated lime paste samples with different compositions and different water to solid ratios were prepared and cured for different periods. A range of tests was conducted to investigate the properties and microstructure of the pastes, including compressive strength, X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, energy dispersive X-ray and thermogravimetric analysis. The results showed that the reactive MgO acts as an effective alkali activator of GGBS, achieving higher 28-day compressive strength than that of the corresponding GGBS-hydrated lime system. The extensive microstructural investigation indicated that the main hydration product of reactive MgO-activated GGBS and hydrated lime-activated GGBS systems was hydrated calcium silicate, but there was much more hydrotalcite present in the former, which contributed to its superior 28-day compressive strength.

Semantic transform: Weakly supervised semantic inference for relating visual attributes

Relative (comparative) attributes are promising for thematic ranking of visual entities, which also aids in recognition tasks. However, attribute rank learning often requires a substantial amount of relational supervision, which is highly tedious, and apparently impractical for real-world applications. In this paper, we introduce the Semantic Transform, which under minimal supervision, adaptively finds a semantic feature space along with a class ordering that is related in the best possible way. Such a semantic space is found for every attribute category. To relate the classes under weak supervision, the class ordering needs to be refined according to a cost function in an iterative procedure. This problem is ideally NP-hard, and we thus propose a constrained search tree formulation for the same. Driven by the adaptive semantic feature space representation, our model achieves the best results to date for all of the tasks of relative, absolute and zero-shot classification on two popular datasets. © 2013 IEEE.