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Cu2CdSn(S,Se)(4) is an important candidate material for thin film solar cell absorber layers. In this work, low-cost Cu2CdSnS4 nanocrytal thin film with a stannite structure has been successfully fabricated by a butyldithiocarbamate-based ethanol solution approach. The selenized Cu2CdSn(S,Se)(4) thin film shows large densely packed grains and has a suitable band gap value of 1.01 eV. The Cu2CdSn(S,Se)(4) thin film solar cell with a proof-of-concept power conversion efficiency of 3.1% was fabricated. (C) 2014 Elsevier B.V. All rights reserved.

SESAMe v3.0, a spatially explicit multimedia fate model with 50 × 50 km(2) resolution, has been developed for China to predict environmental concentrations of benzo[a]pyrene (BaP) using an atmospheric emission inventory for 2007. Model predictions are compared with environmental monitoring data obtained from an extensive review of the literature. The model performs well in predicting multimedia concentrations and distributions. Predicted concentrations are compared with guideline values; highest values with some exceedances occur mainly in the North China Plain, Mid Inner Mongolia, and parts of three northeast provinces, Xi'an, Shanghai, and south of Jiangsu province, East Sichuan Basin, middle of Guizhou and Guangzhou. Two potential future scenarios have been assessed using SESAMe v3.0 for 2030 as BaP emission is reduced by (1) technological improvement for coal consumption in energy production and industry sectors in Scenario 1 (Sc1) and (2) technological improvement and control of indoor biomass burning for cooking and indoor space heating and prohibition of open burning of biomass in 2030 in Scenario 2 (Sc2). Sc2 is more efficient in reducing the areas with exceedance of guideline values. Use of SESAMe v3.0 provides insights on future research needs and can inform decision making on options for source reduction.

In this paper, a three-rotor turboprop engine (with a fixed-speed free turbine) is set as the studied object. Under the certain flight conditions and the transient state control law, the main influencing factors affecting the position of low-pressure rotor transient state line are studied. They are the ratio of MIL (moment of inertia of low pressure rotor) to MIH (moment of inertia of high pressure rotor), the ratio of HPC (high pressure compressor) pressure ratio to LPC (low pressure compressor) pressure ratio and the ratio of design point HPR (high pressure rotor) speed to design point LPR (low pressure rotor) speed. The influence of these three factors on the position of low-pressure rotor transient state line is obtained and the mechanism is analyzed.

The rapid fabrication of starch gels with excellent mechanical properties still presents a challenge. This study aimed to develop a simple alcohol soaking method to fabricate strong starch gels in a short time. The mechanical properties, crystallization behaviors, and structural characteristics of starch gels were investigated by rheological testing, texture profile analysis, differential scanning calorimetry (DSC), X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and low-field nuclear magnetic resonance (LF-NMR). The mechanical strength of the starch gel increased from 170.21 g to 666.16 g. The gelation time of starch gel decreased from 12 h (traditional retrogradation) to 2 h. DSC indicated that the enthalpy of starch gel increased from 0.88 J/g to 2.90 J/g. XRD analysis showed that the crystallinity of starch gel increased from 3.8% to 8.9% after alcohol soaking. Alcohol dehydrated the starch gels system, so that amylopectins were arranged to form more crystals. This new simple approach, alcohol soaking to form strong starch gels, can expand the applications of starch in food, agriculture, and textiles.

Abstract Accurate estimation of the remaining useful life of lithium-ion batteries is critically important for electronic devices. In the existing literature, the widely applied model-based approaches for remaining useful battery life estimation are limited by the complexity of the electrochemical modeling required. In addition, data-driven approaches for remaining useful battery life estimation commonly define unreliable sliding window sizes empirically and the prediction accuracy of these approaches needs to be improved. To address the above issues, use of a hybrid neural network with the false nearest neighbors method is proposed in this paper. First, the false nearest neighbors method is used to calculate the sliding window size required for prediction. Second, a hybrid neural network that combines the advantages of a convolutional neural network with those of long short-term memory is designed for model training and prediction. Remaining useful life prediction experiments for batteries with various rated capacities are performed to verify the effectiveness of the proposed approach, and the results demonstrate that the proposed approach offers wide generality and reduced errors when compared with the other state-of-the-art methods.

Abstract In the present study, Loblolly pine biomass residue was converted to bio-oil in a two-step process, consisting of 1) fast pyrolysis in the presence of zeolite ZSM-5 as a catalyst to produce pyrolysis oil, 2) hydrogenation of pyrolysis oil using formic acid as the hydrogen source in presence of Ru/activated carbon catalyst. Pyrolysis oils were analyzed by 13C, 31P and HSQC-NMR and the results revealed that the zeolite-induced catalytic fast pyrolysis process led to effective demethoxylation, producing more catechol and p-hydroxy-phenyl hydroxyl groups in the bio-oils, resulting in a decrease in the methoxyl group content by about 85 % and rich aromatic structures in the pyrolysis oils. The properties of pyrolysis oil with and without zeolite were in the bio-oil range. Hydrogenated pyrolysis oil showed that 79 % of the aromatic protons are eliminated and 87 % of protons are aliphatic in nature, with no oxygen attached to the α-carbon.

Cattail-grass-derived porous carbon as high-capacity anode materials were prepared via high-temperature carbonization and activation with KOH. The samples exhibited different structures and morphologies with increasing treatment time. It was found that the cattail grass with activation treatment—1 (CGA-1) sample obtained at 800 °C for 1 h presented excellent electrochemical performance. As an anode material for lithium-ion batteries, CGA-1 showed a high charge–discharge capacity of 814.7 mAh g−1 at the current density of 0.1 A g−1 after 400 cycles, which suggests that it has a great potential for energy storage.