Olefins from biomass feedstocks: catalytic ester decarbonylation and tandem Heck-type coupling
作者:Alex John、Levi T. Hogan、Marc A. Hillmyer、William B. Tolman
DOI:10.1039/c4cc09003a
日期:——
anhydride additives, the catalyticdecarbonylation of p-nitrophenylesters of aliphatic carboxylic acids to their corresponding olefins, including commodity monomers like styrene and acrylates, has been developed. The reaction is catalyzed by palladiumcomplexes in the absence of added ligands and is promoted by alkali/alkaline-earth metal halides. Combination of catalyticdecarbonylation and Heck-type coupling
A palladium-catalyzed oxidative esterification of aldehydes with phenols is described, using air as the clean oxidant. This reaction tolerates many functional groups, providing esters with yields ranging from moderate to excellent. (C) 2011 Elsevier Ltd. All rights reserved.
Pd-Catalyzed Decarbonylative Olefination of Aryl Esters: Towards a Waste-Free Heck Reaction
A new algorithm for generalized optimal discriminant vectors
作者:Xiaojun Wu、Yang Jingyu、Shitong Wang、Guo Yuefei、Qiying Cao
DOI:10.1007/bf02947310
日期:2002.5
A study has been conducted on the algorithm of solving generalized optimal set of discriminant vectors in this paper. This paper proposes an analytical algorithm of solving generalized optimal set of discriminant vectors theoretically for the first time. A lot of computation time can be saved because all the generalized optimal sets of discriminant vectors can be obtained simultaneously with the proposed algorithm, while it needs no iterative operations. The proposed algorithm can yield a much higher recognition rate. Furthermore, the proposed algorithm overcomes the shortcomings of conventional human face recognition algorithms which were effective for small sample size problems only. These statements are supported by the numerical simulation experiments on facial database of ORL.
Singularity analysis of geometric constraint systems
作者:Xiaobo Peng、Liping Chen、Fanli Zhou、Ji Zhou
DOI:10.1007/bf02947309
日期:2002.5
Singularity analysis is an important subject of the geometric constraint satisfaction problem. In this paper, three kinds of singularities are described and corresponding identification methods are presented for both under-constrained systems and over-constrained systems. Another special but common singularity for under-constrained geometric systems, pseudo-singularity, is analyzed. Pseudo-singularity is caused by a variety of constraint matching of under-constrained systems and can be removed by improving constraint distribution. To avoid pseudo-singularity and decide redundant constraints adaptively, a differentiation algorithm is proposed in the paper. Its correctness and efficiency have been validated through its practical applications in a 2D/3D geometric constraint solver CBA.