Cost-effectiveness of alternative powertrains for reduced energy use and CO2 emissions in passenger vehicles

This work analysed the cost-effectiveness of avoiding carbon dioxide (CO2) emissions using advanced internal combustion engines, hybrids, plug-in hybrids, fuel cell vehicles and electric vehicles across the nine UK passenger vehicles segments. Across all vehicle types and powertrain groups, minimum installed motive power was dependent most on the time to accelerate from zero to 96.6km/h (60mph). Hybridising the powertrain reduced the difference in energy use between vehicles with slow (t z - 60 > 8 s) and fast acceleration (t z - 60 < 8 s) times. The cost premium associated with advanced powertrains was dependent most on the powertrain chosen, rather than the performance required. Improving non-powertrain components reduced vehicle road load and allowed total motive capacity to decrease by 17%, energy use by 11%, manufacturing cost premiums by 13% and CO2 emissions abatement costs by 15%. All vehicles with advanced internal combustion engines, most hybrid and plug-in hybrid powertrains reduced net CO2 emissions and had lower lifetime operating costs than the respective segment reference vehicle. Most powertrains using fuel cells and all electric vehicles had positive CO2 emissions abatement costs. However, only vehicles using advanced internal combustion engines and parallel hybrid vehicles may be attractive to consumers by the fuel savings offsetting increases in vehicle cost within two years. This work demonstrates that fuel savings are possible relative to today's fleet, but indicates that the most cost-effective way of reducing fuel consumption and CO2 emissions is by advanced combustion technologies and hybridisation with a parallel topology. © 2014 Elsevier Ltd.

GaAs/AlGaAs MQW材料激子吸收谱的电场效应及pin结构自电光效应器件（SEED)的研究

Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z

SEED器件及智能象元研究

Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z

64×64 InGaAs/GaAs多量子阱SEED光子集成智能像素面阵研究

Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z

The influence of low-temperature Ge seed layer on growth of high-quality Ge epilayer on Si(100) by ultrahigh vacuum chemical vapor deposition

High-quality Ge epilayer on Si(1 0 0) substrate with an inserted low-temperature Ge seed layer and a thin Si0.77Ge0.23 layer was grown by ultrahigh vacuum chemical vapor deposition. The epitaxial Ge layer with surface root-mean-square roughness of 0.7 nm and threading dislocation density of 5 x 10(5) cm(-2) was obtained. The influence of low temperature Ge seed layer on the quality of Ge epilayer was investigated. We demonstrated that the relatively higher temperature (350 degrees C) for the growth of Ge seed layer significantly improved the crystal quality and the Hall hole mobility of the Ge epilayer. (C) 2008 Elsevier B.V. All rights reserved.

Effects of seed dot layer and thin GaAs spacer layer on the structure and optical properties of upper In(Ga)As quantum dots

The structure and optical properties of In(Ga)As with the introduction of InGaAlAs or InAlAs seed dot layers are investigated. The area density and size homogeneity of the upper InGaAs dots are efficiently improved by the introduction of a buried layer of high-density dots. Our explanation for the realization of high density and size homogeneity dots is presented. When the GaAs spacer layer is too thin to cover the seed dots, the upper dots exhibit some optical properties like those of a quantum well. By analyzing the growth dynamics, we refer to this kind of dot as an empty-core dot. (C) 2003 American Institute of Physics.

Structure and optical properties of upper In(Ga)As quantum dots on a different seed layer with a thin GaAs spacer layer

The structure and optical properties of In(Ga)As grown with the introduction of InGaAlAs or InAlAs seed dots layers are investigated. The area density and size homogeneity of the upper InGaAs dots are efficiently improved with the introduction of a layer of high-density buried dots. When the GaAs spacer layer is too thin to cover the seed dots, the upper dots exhibit the characterization of a quantum well. By analyzing the growth dynamics, we refer to it as an empty-core structure dot. (C) 2002 Elsevier Science B.V. All rights reserved.

Size and shape evolution of self-assembled coherent InAs/GaAs quantum dots influenced by seed layer

The size and shape Evolution of self-assembled InAs quantum dots (QDs) influenced by 2.0-ML InAs seed layer has been systematically investigated for 2.0, 2.5, and 2.9-ML deposition on GaAs(1 0 0) substrate. Based on comparisons with the evolution of InAs islands on single layer samples at late growth stage, the bimodal size distribution of InAs islands at 2.5-ML InAs coverage and the formation of larger InAs quantum dots at 2.9-ML deposition have been observed on the second InAs layer. The further cross-sectional transmission electron microscopy measurement indicates the larger InAs QDs: at 2.9-ML deposition on the second layer are free of dislocation. In addition, the interpretations for the size and shape evolution of InAs/GaAs QDs on the second layer will be presented. (C) 2001 Elsevier Science B.V. All lights reserved.

Effects of seed layer on the realization of larger self-assembled coherent InAs/GaAs quantum dots

The size and shape evolution of self-assembled InAs quantum dots (QDs) influenced by 2.0 ML InAs seed layer has been systematically investigated for 2.0, 2.5, and 2.9 ML deposition on GaAs(100) substrate. Based on comparisons with the formation of large incoherent InAs islands on single-layer samples at late growth stage, the larger coherent InAs quantum dots at 2.9 ML deposition has been observed on the second InAs layer. A simple model analysis accounting for the surface strain distribution influenced by buried islands gives a stronger increment of critical QD diameter for dislocation nucleation on the second layer in comparison with the single-layer samples. Additionally, the inhibition of dislocation nucleation in InGaAs/GaAs large islands can also be explained by our theoretical results. (C) 2000 American Institute of Physics. [S0021-8979(00)08922-2].

Flip-chip bonded hybrid CMOS/SEED optoelectronic smart pixels

Hybrid integration of GaAs/AlGaAs multiple quantum well self electro-optic effect device (SEED) arrays are demonstrated flip-chip bonded directly onto 1 mu m silicon CMOS circuits. The GaAs/AlGaAs MQW devices are designed for 850 nm operation. Some devices are used as input light detectors and others serve as output light modulators. The measurement results under applied biases show good optoelectronic characteristics of elements in SEED arrays. Nearly the same reflection spectrum is obtained for the different devices at an array and the contrast ratio is more than 1.2:1 after flip-chip bonding and packaging. The transimpedance receiver-transmitter circuit can be operated at a frequency of 300 MHz.

Quantifying the effectiveness of SiO2/Au light trapping nanoshells for thin film poly-Si solar cells

In order to enhance light absorption of thin film poly-crystalline silicon (TF poly-Si) solar cells over a broad spectral range, and quantify the effectiveness of nanoshell light trapping structure over the full solar spectrum in theory, the effective photon trapping flux (EPTF) and effective photon trapping efficiency (EPTE) were firstly proposed by considering both the external quantum efficiency of TF poly-Si solar cell and scattering properties of light trapping structures. The EPTF, EPTE and scattering spectrum exhibit different behaviors depending on the geometric size and density of nanoshells that form the light trapping layer. With an optimum size and density of SiO2/Au nanoshell light trapping layer, the EPTE could reach up to 40% due to the enhancement of light trapping over a broad spectral range, especially from 500 to 800 nm.

A New Discrimination Method of Maize Seed Varieties Based on Near-Infrared Spectroscopy

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12 000-4 000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by Psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91. 8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.