Taoyuan Innovation Institute of Technology

About: Taoyuan Innovation Institute of Technology is a based out in . It is known for research contribution in the topics: Membrane & Pervaporation. The organization has 663 authors who have published 1100 publications receiving 24644 citations.

The preparation and characterization of silver-loading cellulose acetate hollow fiber membrane for water treatment

Abstract: Silver-loading asymmetric cellulose acetate (CA) hollow fiber membrane was spun via the dry jet-wet spinning technique. The spinning solution was prepared by dissolving AgNO3 and CA in N,N-dimethylformamide (DMF). The silver ions were reduced in the spinning dope into silver nano-particles. The morphology of the resulting hollow fibers was examined using a scanning electron microscope and the silver content in the fiber was measured using an inductively coupled plasma atomic emission spectrometer. The antibacterial activities were evaluated. These hollow fibers had a sponge-like structure and dense inner and outer surfaces. At a 50 k magnification, the pore on the skin layer was not observable, while the nodule size was smaller than 10 nm. The residual silver content of as-spun hollow fiber was about 60% of the original silver added in the polymer solution. After immersing in water bath for 180 days, the silver content in the bulk of the hollow fibers decreased to 60% and the silver content on the surface reduced to 10%, yet still showed antibacterial activity against Escherichia coli and Staphylococcus aureus. After permeating with water for 5 days, the silver content in the hollow fibers decreased, and did not show antibacterial activity against E. coli and S. aureus. Thus, silver content must be periodically replenished after permeation. The proper range of AgNO3 in the spinning solution for CA hollow fiber should be about 100–1000 ppm. Copyright © 2005 John Wiley & Sons, Ltd.

Determination of optimal cutting parameters in wire electrical discharge machining

Abstract: Owing to the complexity of wire electrical discharge machining (wire-EDM), it is very difficult to determine optimal cutting parameters for improving cutting performance. The paper utilizes a feedforward neural network to associate the cutting parameters with the cutting performance. A simulated annealing (SA) algorithm is then applied to the neural network for solving the optimal cutting parameters based on a performance index within the allowable working conditions. Experimental results have shown that the cutting performance of wire-EDM can be greatly enhanced using this new approach.