Regioisomerically pure 1(3)-rac-monoacylglycerols are conveniently prepared in high yields (>75%) and in multigram quantities by enzymatic esterification
of glycerol in the presence of various lipases(Chromobacterium viscosum, Rhizopus delemar, Rhizomucor miehei) with a variety of different acyl donors, such as free fatty acids, fatty acid alkyl esters, vinyl esters and triacylglycerols,
as well as natural fats and oils. All reactions are carried out in aprotic organic solvents with low water content, namelyn-hexane, diethyl ether, tBuOMe or mixtures of these solvents. Essential for the success of these transformations were the
following two factors. First, the creation of an artificial interphase between the solvent-immiscible hydrophilic glycerol
and the hydrophobic reaction medium by its adsorption onto a solid support. Second, a facile system for the separation of
the desired monoacylglycerol from the reaction mixture, coupled with the continuous recycling of acyl donor and undesirable
by-products. 相似文献
Here, an experimental investigation on the effective drag force in a conventional fluidized bed is presented. Two beds of different particle size distribution belonging to group B and group B/D powders were fluidized in air in a diameter column. The drag force on a particle has been calculated based on the measurement of particle velocity and concentration during pulse gas tests, using twin-plane electrical capacitance tomography. The validity of the voidage function “correction function”, (1−εs)n, for the reliable estimation of the effective drag force has been investigated. The parameter n shows substantial dependence on the relative particle Reynolds number , and the spatial variation of the effective static and hydrodynamic forces. It is also illustrated that, a simple correlation for the effective drag coefficient as function of the particle Reynolds number (Rep), expressed implicitly in terms of the interstitial gas velocity, can serve in estimating the effective drag force in a real fluidization process. Analysis shows that, the calculated drag force is comparable to the particle weight, which enables a better understanding of the particle dynamics, and the degree of spatial segregation in a multi-sized particle bed mixture. The analogy presented in this paper could be extended to obtain a generalized correlation for the effective drag coefficient in a fluidized bed in terms of Rep and the particle physical properties. 相似文献
Halloysite template, a ceramic substrate, is of a hollow cylindric structure, on which the fine Pd nanoparticles are uniformly formed by the reduction of palldate chloride to initiate electroless deposition. The electroless deposition of Ni is catalyzed by the Pd particles, which results in a uniform layer of Ni-P alloy on halloysite. The alloy is of a nanocrystalline structure, of which the average diameter is about 6 nm. After being heat-treated at 400 ℃, it contains both Ni and Ni12P5 crystal, meanwhile, the Ni crystal gets larger with an average size of 51.9 nm.The content of phosphorous in the Ni layer has a great influence on crystal structure. The metallized halloysite has a higher inherent coercive force, and a much lower saturation magnetization in its as-plated state, while after heattreatment, the inherent coercive force decreases drastically. These magnetic properties have great relationship with the superparamagnetism of Ni nanocrystalline and the stress anisotropy in Ni layer. 相似文献
The useful life of a cutting tool and its operating conditions largely control the economics of the machining operations. Hence, it is imperative that the condition of the cutting tool, particularly some indication as to when it requires changing, to be monitored. The drilling operation is frequently used as a preliminary step for many operations like boring, reaming and tapping, however, the operation itself is complex and demanding.
Back propagation neural networks were used for detection of drill wear. The neural network consisted of three layers input, hidden and output. Drill size, feed, spindle speed, torque, machining time and thrust force are given as inputs to the ANN and the flank wear was estimated. Drilling experiments with 8 mm drill size were performed by changing the cutting speed and feed at two different levels. The number of neurons in the hidden layer were selected from 1, 2, 3, …, 20. The learning rate was selected as 0.01 and no smoothing factor was used. The estimated values of tool wear were obtained by statistical analysis and by various neural network structures. Comparative analysis has been done between statistical analysis, neural network structures and the actual values of tool wear obtained by experimentation. 相似文献