Nanocrystalline zirconia as catalyst support in methanol synthosis

Nanocrystalline zirconia was synthesized and used as catalyst support for methanol synthesis. The nanocrystallite particles have new physical and textural properties which are critical in determining the catalytic performance. Nanocrystalline zirconia changes the electronic structure and affects the metal and support interactions on the catalyst. leading to facile reduction. intimate interaction between copper and zirconia, more corner defects and oxygen vacancies on the surface of the catalyst. All these changes are beneficial to the reaction of methanol synthesis from hydrogenation of CO2. As a result. higher conversion of CO2 and selectivity of methanol are achieved compared to the catalysts prepared by conventional co-precipitation method. (C) 2004 Elsevier B.V. All rights reserved.

Synthesis and characterization of turbostratic carbons prepared by catalytic chemical vapour decomposition of acetylene

The turbostratic mesoporous carbon blacks were prepared by catalytic chemical vapour decomposition (CCVD) of acetylene using Ni/MgO catalysts prepared by co-precipitation. The relationship between deposition conditions and the nanostructures of resultant carbon black materials was investigated. It was found that the turbostratic and textural structures of carbon blacks are dependent on the deposition temperature and nickel catalyst loading. Higher deposition temperature increases the carbon crystallite unit volume V-nano and reduces the surface area of carbon samples. Moreover, a smaller V-nano is produced by a higher Ni loading at the same deposition temperature. In addition of the pore structure and the active metal surface area of the catalyst, the graphitic degree or electronic conductivity of the carbon support is also a key issue to the activity of the supported catalyst. V-nano is a very useful parameter to describe the effect of the crystalline structure of carbon blacks on the reactivity of carbon blacks in oxygen-carbon reaction and the catalytic activity of carbon-supported catalyst in ammonia decomposition semi-quantitatively. (C) 2006 Elsevier B.V. All rights reserved.

3D protein structure matching by patch signatures

For determining functionality dependencies between two proteins, both represented as 3D structures, it is an essential condition that they have one or more matching structural regions called patches. As 3D structures for proteins are large, complex and constantly evolving, it is computationally expensive and very time-consuming to identify possible locations and sizes of patches for a given protein against a large protein database. In this paper, we address a vector space based representation for protein structures, where a patch is formed by the vectors within the region. Based on our previews work, a compact representation of the patch named patch signature is applied here. A similarity measure of two patches is then derived based on their signatures. To achieve fast patch matching in large protein databases, a match-and-expand strategy is proposed. Given a query patch, a set of small k-sized matching patches, called candidate patches, is generated in match stage. The candidate patches are further filtered by enlarging k in expand stage. Our extensive experimental results demonstrate encouraging performances with respect to this biologically critical but previously computationally prohibitive problem.