The synthesis of nanostructured W2C on ultrahigh surface area carbon materials via carbothermal hydrogen reduction

Nanostructured tungsten carbides were synthesized, for the first time, with a size distribution of 5-12 nm on ultrahigh surface area carbon material, by carbothermal hydrogen reduction (CHR) at 850degreesC and metal Ni promoted CHR at 650 degreesC.

A Mossbauer study of In-Fe2O3/HZSM-5 catalysts for the selective catalytic reduction of NO by methane

The selective catalytic reduction of NO by CH4 was compared over In-Fe2O3/HZSM-5 catalysts prepared by impregnation and co-impregnation methods. It was found that the catalyst preparation method greatly affected the catalyst activity. The impregnated catalyst was very active, but the co-impregnated one showed poor activity. The In Fe2O3/HZSM-5 catalysts were investigated by Mossbauer spectroscopy. The results showed that indium cations entered into the iron oxide lattice in the co-impregnated catalyst, while the impregnated catalyst exhibited a more stable structure, when both of the catalysts were treated severely in the reaction atmosphere. Characterization by means of combined in situ temperature programmed reduction (TPR)- Mossbauer spectroscopy further revealed that the performances of the two catalysts were different in the TPR processes.

Water reduction and oxidation on Pt-Ru/Y2Ta2O5N2 catalyst under visible light irradiation

Y2Ta2O5N2 is presented as a novel photocatalyst with high activity for water splitting under visible-light irradiation in the presence of appropriate sacrificial reagents; the activity for reduction to H-2 is increased by the incorporation of Pt or Ru as a co-catalyst, with a significant increase in production efficiency when both Pt and Ru are present.

Potential CO2 Emission Reduction by Development of Non-Grain-Based Bioethanol in China

Assessment of the potential CO2 emission reduction by development of non-grain-based ethanol in China is valuable for both setting up countermeasures against climate change and formulating bioethanol policies. Based on the land occupation property, feedstock classification and selection are conducted, identifying sweet sorghum, cassava, and sweet potato as plantation feedstocks cultivated from low-quality arable marginal land resources and molasses and agricultural straws as nonplantation feedstocks derived from agricultural by-products. The feedstock utilization degree, CO2 reduction coefficient of bioethanol, and assessment model of CO2 emission reduction potential of bioethanol are proposed and established to assess the potential CO2 emission reduction by development of non-grain-based bioethanol. The results show that China can obtain emission reduction potentials of 10.947 and 49.027 Mt CO2 with non-grain-based bioethanol in 2015 and 2030, which are much higher than the present capacity, calculated as 1.95 Mt. It is found that nonplantation feedstock can produce more bioethanol so as to obtain a higher potential than plantation feedstock in both 2015 and 2030. Another finding is that developing non-grain-based bioethanol can make only a limited contribution to China's greenhouse gas emission reduction. Moreover, this study reveals that the regions with low and very low potentials for emission reduction will dominate the spatial distribution in 2015, and regions with high and very high potentials will be the majority in 2030.

Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression

Semisupervised dimensionality reduction has been attracting much attention as it not only utilizes both labeled and unlabeled data simultaneously, but also works well in the situation of out-of-sample. This paper proposes an effective approach of semisupervised dimensionality reduction through label propagation and label regression. Different from previous efforts, the new approach propagates the label information from labeled to unlabeled data with a well-designed mechanism of random walks, in which outliers are effectively detected and the obtained virtual labels of unlabeled data can be well encoded in a weighted regression model. These virtual labels are thereafter regressed with a linear model to calculate the projection matrix for dimensionality reduction. By this means, when the manifold or the clustering assumption of data is satisfied, the labels of labeled data can be correctly propagated to the unlabeled data; and thus, the proposed approach utilizes the labeled and the unlabeled data more effectively than previous work. Experimental results are carried out upon several databases, and the advantage of the new approach is well demonstrated.

Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction

The Gaussian process latent variable model (GP-LVM) has been identified to be an effective probabilistic approach for dimensionality reduction because it can obtain a low-dimensional manifold of a data set in an unsupervised fashion. Consequently, the GP-LVM is insufficient for supervised learning tasks (e. g., classification and regression) because it ignores the class label information for dimensionality reduction. In this paper, a supervised GP-LVM is developed for supervised learning tasks, and the maximum a posteriori algorithm is introduced to estimate positions of all samples in the latent variable space. We present experimental evidences suggesting that the supervised GP-LVM is able to use the class label information effectively, and thus, it outperforms the GP-LVM and the discriminative extension of the GP-LVM consistently. The comparison with some supervised classification methods, such as Gaussian process classification and support vector machines, is also given to illustrate the advantage of the proposed method.

Carbon nanotubes decorated with Pt nanocubes by a noncovalent functionalization method and their role in oxygen reduction

Combined with polymer wrapping and layer-by-layer techniques, a noncovalent functionalization method is developed to disperse Pt nanocubes (NCs) onto carbon nanotubes (CNTs). By adjusting the relative ratio of Pt NCs to CNTs, nanotubes with different Pt NC loadings are produced. The composites exhibit excellent electrocatalytic activity towards oxygen reduction.

Carbon-supported Pd nanocatalyst modified by non-metal phosphorus for the oxygen reduction reaction

A carbon-supported palladium catalyst modified by non-metal phosphorus(PdP/C) has been developed as an oxygen reduction catalyst for direct methanol fuel cells.The PdP/C catalyst was prepared by the sodium hypophosphite reduction method. The as-prepared Pd nanoparticles have a narrow size distribution with an average diameter of 2 nm. Energy dispersive X-ray analysis (EDX), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD) results indicate that P enters into the crystal lattice of Pd and forms an alloy.

The synthesis of ionic-liquid-functionalized multiwalled carbon nanotubes decorated with highly dispersed Au nanoparticles and their use in oxygen reduction by electrocatalysis

Multiwalled carbon nanotube (MWCNT)/ionic liquid/gold nanoparticle hybrid materials have been prepared by a chemical route that involves functionalization of MWCNT with amine-terminated ionic liquids followed by deposition of Au. Transmission electron microscopy revealed well-distributed Au with a narrow size distribution centered around 3.3 nm. The identity of the hybrid material was confirmed through Raman and X-ray photoelectron spectroscopy.

Green synthesis of 1-2 nm gold nanoparticles stabilized by amine-terminated ionic liquid and their electrocatalytic activity in oxygen reduction

Stable gold nanoparticles with average size 1.7 nm synthesized by an amine-terminated ionic liquid showed enhanced electrocatalytic activity and high stability.

Pd nanoparticles supported on WO3/C hybrid material as catalyst for oxygen reduction reaction

Pd nanoparticles supported on WO3/C hybrid material have been developed as the catalyst for the oxygen reduction reaction (ORR) in direct methanol fuel cells. The resultant Pd-WO3/C catalyst has an ORR activity comparable to the commercial Pt/C catalyst and a higher activity than the Pd/C catalyst prepared with the same method. Based on the physical and electrochemical characterizations, the improvement in the catalytic performance may be attributed to the small particle sizes and uniform dispersion of Pd on the WO3/C, the strong interaction between Pd and WO3 and the formation of hydrogen tungsten bronze which effectively promote the direct 4-electron pathway of the ORR at Pd.

Determination of Cd2+ and Pb2+ on glassy carbon electrode modified by electrochemical reduction of aromatic diazonium salts

Carbon modified by the reduction of aromatic diazonium derivatives was first used as electrode for the electrochemical stripping analysis of heavy metals. As a model, the glassy carbon electrode was modified with benzoic acid by electrochemical reduction of diazobenzoic acid, and the resulting modified electrodes were used for determination of Cd2+ and Pb2+. The anodic peak currents of cadmium and lead at the benzoic acid-modified glassy carbon electrode are 7.2 and 6 times of that at the bare glassy carbon electrode. A linear response was observed for Pb2+ and Cd2+ in the range of 0.5-50 mu g/l.