High performance of silicided silicon-sidewall source and drain (S4D) structure

A silicided silicon-sidewall source and drain (S⁴D) structure is proposed for sub-0.1-μm devices. The merit of the S⁴D structure is that the series resistance of the source and drain is significantly reduced since the silicide layer is attached very close to the gate electrode and the silicon sidewall can be doped very highly. Thus, very high drain current drive can be expected, Another advantage of this structure is that the source and drain extensions are produced by the solid-phase diffusion of boron from the highly doped silicon-sidewall. Thus, shallow extensions with very high doping can be realized. A 75-nm gate length pMOSFET fabricated with this structure is shown to exhibit excellent electrical characteristics     

Photo response analysis in CCD image sensors with a VOD structure

Photo response in CCD image sensors with Vertical-Overflow-Drain (VOD) was analyzed in an attempt to discover a way to lessen the photo response rise that accompanies increasing incident light intensity in the saturation region. A photo response analysis based on transistor I-V characteristics revealed that the extent of rise in the saturation region is uniquely determined by the non-ideality factor and temperature. Calculation of the non-ideality factor and its dependence on P-well impurity concentration and layer thickness further revealed that fabrication of P-wells with lower impurity concentrations and thicker layers would be effective in suppressing photo response rise     

Color restoration method based on spectral information using normalized cut

This paper proposes a novel method for color restoration that can effectively apply accurate color based on spectral information to a segmented image using the normalized cut technique. Using the proposed method, we can obtain a digital still camera image and spectral information in different environments. Also, it is not necessary to estimate reflectance spectra using a spectral database such as other methods. The synthesized images are accurate and high resolution. The proposed method effectively works in making digital archive contents. Some experimental results are demonstrated in this paper.     

Trend of permanent magnet synchronous machines

The performance of permanent magnet synchronous machines (PMSMs) has improved rapidly by the progress in elemental technologies such as electromagnetic material technology, computer‐aided design technology, control technique, and drive circuit technology, and thus PMSMs are attractive as high‐performance machines in various fields. This paper describes the recent technology and the trends in PMSMs. To begin with the PMSMs are classified by the ratio of magnet torque to the reluctance torque and their features described, then the trend of the motor design and the electromagnetic material for highly efficient PMSM is shown. The technologies that help to reduce the vibration and noise are also described, and the recently developed PMSMs for traction drive application are introduced. Copyright © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Effect of Support Materials on the Selective Methanation of CO over Ru Catalysts

Selective methanation of CO in the reformate gas (CO/CO₂/H₂/H₂O = 0.175/17.9/70.9/11.1) proceeded over Ru catalysts supported on metal oxides and zeolites. CO was selectively methanated at wide temperature ranges (200–275 °C) over Ru/γ-Al₂O₃, Ru/TiO₂ Ru/H-Y and Ru/H-beta catalysts. Higher Ru contents in Ru/γ-Al₂O₃ improved the selective CO methanation rate.     

热压/热变形Nd2Fe14B/α-Fe纳米双相永磁体的研究

为了制备各向异性块状Nd2Fe14B／α—Fe纳米双相永磁体，研究了热压／热变形工艺参数与样品微观组织结构、磁性能之间的关系。结果表明，饱和磁化强度Js随模压温度的升高而提高；而剩磁Jr、内禀矫顽力Hcj和最大磁能积(BH)max开始都随模压温度的升高而上升，但超过一定温度后反而降低；同时提高热压压力会使磁性能增加，而热变形温度对磁性能影响很小。热变形后样品垂直于压力方向的磁性能略高于平行于压力方向，呈现出轻微的各向异性。Nd2Fe14B／α—Fe纳米双相永磁材料在热压／热变形后没有产生晶粒的择优长大，在晶体学上仍然是各向同性的。     

Production of ethyltert-butyl ether fromtert-butyl alcohol and ethanol catalyzed byβ-zeolite in reactive distillation

The synthesis of ethyl tert-butyl ether (ETBE) from a liquid phase reaction between tert-butyl alcohol (TBA) and ethanol (EtOH) in reactive distillation has been studied.β-Zeolite catalysts with three compositions (Si/Al ratio=13, 36 and 55) were compared by testing the reaction in a semi-batch reactor. Although they showed almost the same performance, the one with Si/Al ratio of 55 was selected for the kinetic and reactive distillation studies because it is commercially available and present in a ready-to-use form. The kinetic parameters of the reaction determined by fitting parameters with the experimental results at temperature in the range of 343–363 K were used in an ASPEN PLUS simulator. Experimental results of the reactive distillation at a standard condition were used to validate a rigorous reactive distillation model of the ASPEN PLUS used in a simulation study. The effects of various operating parameters such as condenser temperature, feed molar flow rate, reflux ratio, heat duty and mole ratio of H₂O : EtOH on the reactive distillation performance were then investigated via simulation using the ASPEN PLUS program. The results were compared between two reactive distillation columns: one packed withβ-zeolite and the other with conventional Amberlyst-15. It was found that the effect of various operating parameters for both types of catalysts follows the same trend; however, the column packed withΒ-zeolite outperforms that with Amberlyst-15 catalyst due to the higher selectivity of the catalyst.     

Sparse least squares support vector training in the reduced empirical feature space

In this paper we discuss sparse least squares support vector machines (sparse LS SVMs) trained in the empirical feature space, which is spanned by the mapped training data. First, we show that the kernel associated with the empirical feature space gives the same value with that of the kernel associated with the feature space if one of the arguments of the kernels is mapped into the empirical feature space by the mapping function associated with the feature space. Using this fact, we show that training and testing of kernel-based methods can be done in the empirical feature space and that training of LS SVMs in the empirical feature space results in solving a set of linear equations. We then derive the sparse LS SVMs restricting the linearly independent training data in the empirical feature space by the Cholesky factorization. Support vectors correspond to the selected training data and they do not change even if the value of the margin parameter is changed. Thus for linear kernels, the number of support vectors is the number of input variables at most. By computer experiments we show that we can reduce the number of support vectors without deteriorating the generalization ability.

Nanoparticle formation in H2O/N2 and H2O/Ar mixtures under irradiation by 20 MeV protons and positive corona discharge

To investigate the contribution of ions to gas nucleation, we have performed experiments on the formation of water droplets in H₂O/N₂ and H₂O/Ar gas mixtures by irradiation with a 20 MeV proton beam and by positive corona discharge. The size of the formed nanoparticles was measured using a differential mobility analyzer equipped with a Faraday cup electrometer. Using the proton beam, droplets around 10 nm in diameter were observed for both positively and negatively charged particles, but none were found when the corona discharge was used. This implies the importance of the presence of both positive and negative ions for the formation of nanosize droplets, which attract each other by Coulomb interactions, enhancing the collision frequency and leading to the formation of the 10 nm droplets.     

Interannual variations in vegetation activities and climate variability caused by ENSO in tropical rainforests

Interannual variations in terrestrial carbon cycle over tropical rainforests affect the global carbon cycle. Terrestrial ecosystem models show the interannual relationship between climate changes due to El Niño‐Southern Oscillation (ENSO) and net primary production over tropical rainforests. However, we need an independent analysis using satellite‐based vegetation index and climate parameters. In the present study, we extracted the ENSO‐related interannual variations from time‐series in Normalized Difference Vegetation Index (NDVI) and climate data from 1981 to 2000, and analysed their relevance. We detected relationships among NDVI, ENSO, and climate parameters from long‐term data with negative NDVI–ENSO, NDVI–temperature, and positive NDVI–precipitation relations. These correlations suggest that interannual variability in vegetation activities over tropical rainforests could be extracted from NDVI time‐series despite noise components in NDVI data, and that interannual changes in precipitation and temperature caused by ENSO play a more important role in vegetation activities over tropical rainforests than in incoming surface solar radiation.