Synthesis,characterization, magnetic measurements and liquefied petroleum gas sensing properties of nanostructured cobalt ferrite and ferric oxide

In the present paper, a series of nanostructured cobalt ferrite systems was synthesized in different compositions via chemical co-precipitation method. The X-ray diffraction analysis of cobalt ferrite systems confirmed the formation of its nanoparticles having minimum crystallite size 7 nm. The surface morphologies of the cobalt ferrite illustrate the distribution of partially agglomerated spherical nanoparticles having particle size ~12 nm. The magnetic behaviors of the synthesized materials were characterized by magnetic measurements. Liquefied petroleum gas sensing investigations of the fabricated pellets illustrate that the cobalt ferrite synthesized in 1:1 M ratio possesses an improved response in comparison to other compositions. The maximum sensitivity of cobalt ferrite film sensor was 2.0 MΩ/s. The response and recovery times were ~30 and 60 s, respectively. The sensor was 95% reproducible after three months of fabrication of the film, showing the stability of the fabricated sensor.     

Wavelet-based hybrid natural image modeling using generalized Gaussian and α-stable distributions

Natural image is characterized by its highly kurtotic and heavy-tailed distribution in wavelet domain. These typical non-Gaussian statistics are commonly described by generalized Gaussian density (GGD) or α-stable distribution. However, each of the two models has its own deficiency to capture the variety and complexity of real world scenes. Considering the statistical properties of GGD and α-stable distributions respectively, in this paper we propose a hybrid statistical model of natural image’s wavelet coefficients which is better in describing the leptokurtosis and heavy tails simultaneously. Based on a clever fusion of GGD and α-stable functions, we establish the optimal parametric hybrid model, and a close-formed Kullback–Leibler divergence of the hybrid model is derived for evaluating model accuracy. Experiment results and comparative studies demonstrate that the proposed hybrid model is closer to the true distribution of natural image’s wavelet coefficients than the single modeling using GGD or α-stable, while is beneficial for applications such as image comparison.     

High-voltage and low specific on-resistance power UMOSFET using P and N type columns

For the first time, we present the unique features exhibited by power 4H–SiC UMOSFET in which N and P type columns (NPC) in the drift region are incorporated to improve the breakdown voltage, the specific on-resistance, and the total lateral cell pitch. The P-type column creates a potential barrier in the drift region of the proposed structure for increasing the breakdown voltage and the N-type column reduces the specific on-resistance. Also, the JFET effects reduce and so the total lateral cell pitch will decrease. In the NPC-UMOSFET, the electric field crowding reduces due to the created potential barrier by the NPC regions and causes more uniform electric field distribution in the structure. Using two dimensional simulations, the breakdown voltage and the specific on-resistance of the proposed structure are investigated for the columns parameters in comparison with a conventional UMOSFET (C-UMOSFET) and an accumulation layer UMOSFET (AL-UMOSFET) structures. For the NPC-UMOSFET with 10 µm drift region length the maximum breakdown voltage of 1274 V is obtained, while at the same drift region length, the maximum breakdown voltages of the C-UMOSFET and the AL-UMOSFET structures are 534 and 703 V, respectively. Moreover, the proposed structure exhibits a superior specific on-resistance (R_on,sp) of 2 mΩ cm², which shows that the on-resistance of the optimized NPC-UMOSFET are decreased by 56% and 58% in comparison with the C-UMOSFET and the AL-UMOSFET, respectively.     

Efficient dye-sensitized solar cells based on CNTs and Zr-doped TiO2 nanoparticles

The light scattering, harvesting and adsorption effects in dye-sensitized solar cells (DSSCs) are studied by preparation of coated carbon nanotubes (CNTs) with TiO₂ and Zr-doped TiO₂ nanoparticles in the forms of mono- and double-layer cells. X-ray diffraction (XRD) analysis reveals that the phase composition of Zr-doped TiO₂ electrode is a mixture of anatase and rutile phases with major rutile content, whereas it is the same mixture with major anatase content for coated CNTs with TiO₂. Furthermore, the average crystallite size of Zr-doped TiO₂ electrode is slightly decreased with Zr introduction. Field emission scanning electron microscope (FE-SEM) images show that the porosity of Zr-doped TiO₂ electrodes is higher than that of undoped electrode, enhancing dye adsorption. UV–visible spectroscopy analysis reveals that the absorption onset of Zr-doped TiO₂ electrodes is slightly shifted to longer wavelength (the red-shift) in comparison with that of undoped TiO₂ electrode. Moreover, the band gap energy of TiO₂ nanoparticles is decreased by Zr introduction, enhancing light absorption. It is found that electron injection of monolayer TiO₂ electrode is improved by introduction of 0.025 mol% Zr, resulted in enhancement of its power conversion efficiency (PCE) up to 6.81% compared with 6.17% for pure TiO₂ electrode. Moreover, electron transport and light scattering are enhanced by incorporation of 0.025 wt% coated CNTs with TiO₂ in the over-layer of double layer electrode. Therefore, double layer solar cell composed of 0.025 mol% Zr-doped TiO₂ nanoparticles as the under-layer and mixtures of these nanoparticles and 0.025 wt% coated CNTs with TiO₂ as the over-layer shows the highest PCE of 8.19%.     

Multi-Level Fusion Net for hand pose estimation in hand-object interaction

This work is about solving a challenging problem of estimating the full 3D hand pose when a hand interacts with an unknown object. Compared to isolated single hand pose estimation, occlusion and interference induced by the manipulated object and the clutter background bring more difficulties for this task. Our proposed Multi-Level Fusion Net focuses on extracting more effective features to overcome these disadvantages by multi-level fusion design with a new end-to-end Convolutional Neural Network (CNN) framework. It takes cropped RGBD data from a single RGBD camera at free viewpoint as input without requiring additional hand–object pre-segmentation and object or hand pre-modeling. Through extensive evaluations on public hand–object interaction dataset, we demonstrate the state-of-the-art performance of our method.     

Boron implantation and epitaxial regrowth studies of 6H SiC

Implantation of B has been performed into an epitaxially grown layer of 6H SiC, at two different B concentrations, 2×10¹⁶ cm⁻³ and 2×10¹⁸ cm⁻³. Subsequently, an epitaxial layer was regrown on the B implanted layer. The samples were investigated by transmission electron microscopy (TEM) and secondary ion mass spectrometry (SIMS). In the highly B-doped layers plate-like defects were found, associated with large strain fields, and an increased B concentration. These defects were stable at the originally implanted region during regrowth and at anneal temperatures up to 1700°C. In the samples implanted with the lower B concentration, no crystal defects could be detected by TEM. No threading dislocations or other defects were observed in the regrown epitaxial layer, which shows the possibility to grow a layer with high crystalline quality on B implanted 6H SiC. By SIMS, it was found that B piles up at the interface to the regrown layer, which could be explained by enhanced diffusion from an increased concentration of point defects created by implantation damage in the region. B is also spread out into the original crystal and in the regrown layer at a concentration of below 2×10¹⁶ cm⁻³, with a diffusion constant estimated to 1.3×10⁻¹² cm²s⁻¹. This diffusion is most probably not driven by implantation damage, but by intrinsic defects in the grown crystal. Our investigation shows that the combination of implantation and subsequent regrowth techniques could be used in SiC for building advanced device structures, with the crystal quality in the regrown layer not being deteriorated by crystal defects in the implanted region. A device process using B implantation and subsequent regrowth could on the other hand be limited by the diffusion of B.     

硅中硼离子注入校准样品的研制

本文主要介绍了硅中硼离子注入校准样品的制备与研究。分别用三台SIMS仪器对样品进行了深度剖析与比对,并对用作校准目的的样品主要参数进行了定值。     

Power Evaluation of the Los Angeles Oxygen–Fed Ozone System

The Los Angeles Department of Water and Power (LADWP) operates a 600 mgd (2,270 ML/day) direct filtration water treatment plant which includes a 7,900 lb/day (149 kg/hr) ozonation system. Ozone is applied as a preoxidant for the purposes of disinfection and microflocculation. The ozonation system is unique in that high purity oxygen is generated on–site and is used as the feed–gas in a once–through system. The process was selected through competitive bids and evaluated for total present worth from 20–year life cycle costs which included capital plus energy expenses. Power consumption (and penalty) was valued at $6,500/kW. System power demand was measured at nine ozone production rates. A minimum specific energy of 6.5 kWh/lb (14.3 kWh/kg) of ozone was observed when generating ozone at a concentration between 5 and 6 % (wt) [65 and 80 g/m³; where the standard temperature and pressure are 70F (21.11 C) and 1 atm, respectively]. The test methodology and data assessment considerations were developed jointly by the owner and manufacturer, and produced results with practical significance beyond the performance testing objective.     

Fabrication of CuInS2/CNTs absorber layers by sol–gel method

In this work, CuInS₂/multiwalled carbon nanotube (MWCNT) layers are fabricated by the sol–gel spin-coating method. We introduce two forms of MWCNTs into a CIS₂ solution, washed functional multiwalled carbon nanotubes (W-FMWCNTs) and unwashed-functional multiwalled carbon nanotubes (UW-FMWCNTs), in order to investigate the effects of MWCNTs and an acidic environment on the physical properties of the CIS₂ absorber layers. The structure and morphology of the samples are investigated by X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM), respectively. The XRD study shows that all samples crystallize in a tetragonal structure. The results obtained from the optical, thermo-electric, and electrical measurements indicate that the two groups of CIS₂ layers prepared using W- and UW-FMWCNTs show the opposite behaviors. The Seebeck coefficient (SC) measurements indicate possible formation of a p–n junction.     

Visible–infrared person re-identification based on key-point feature extraction and optimization

Feature extraction for visible–infrared person re-identification (VI-ReID) is challenging because of the cross-modality discrepancy in the images taken by different spectral cameras. Most of the existing VI-ReID methods often ignore the potential relationship between features. In this paper, we intend to transform low-order person features into high-order graph features, and make full use of the hidden information between person features. Therefore, we propose a multi-hop attention graph convolution network (MAGC) to extract robust person joint feature information using residual attention mechanism while reducing the impact of environmental noise. The transfer of higher order graph features within MAGC enables the network to learn the hidden relationship between features. We also introduce the self-attention semantic perception layer (SSPL) which can adaptively select more discriminant features to further promote the transmission of useful information. The experiments on VI-ReID datasets demonstrate its effectiveness.