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Description:
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Flow injection analysis (FIA ) is characterized by its ease of automation , high throughput , simple instrumental requirements , and wide applicability . These unique features make FIA a very useful analytical tool in industrial applications . In this dissertation , FIA systems , operating both in liquid and gas phase , were used to solve some challenging industrial analytical problems .
At first , multi -channel FIA systems with thermometric , conductivity , and photometric detectors were designed to simultaneously determine hydroxide , chloride , hypochlorite , and chlorate ions that exist in Chlor -Alkali cell effluents in concentrations ranging from sub -millimolar to several molar concentrations . A negative bleaching method and a positive absorbance iodiometric method were studied and optimized for this purpose . The methods are reliable , simple , fast , and capable of a throughput rate of -100 samples per hour .
A liquid phase FIA system was developed for automated measurement of hydroperoxides in oil , fat , and polyol samples . Lipid peroxidation has received much attention because of toxicities , bitter tastes , and off flavors produced during lipid oxidation . The method is based on the oxidation of Fe (II ) to Fe (III ) by peroxides in organic medium , followed by the colorimetric detection of the latter as the thiocyanate complex . The system exhibits a wide dynamic range and good linearity (e .g . , linear r^2 , 0 .9943 for 0 .1 -120 meq /kg cottonseed oil hydroperoxides ) with a good throughput rate (up to 60 samples /h ) .
Oxidative stability determination of various materials containing fats and oils is an important process in food , feed , and related industries . It is also a difficult parameter to measure . An attractive gas phase FIA method was developed for the stability evaluation . In the method , the rate of oxygen consumption of samples are measured at discrete temperatures . For all samples studied , log (oxygen consumption ) is linearly related to the reciprocal of the absolute temperature . This makes it possible to extrapolate the temperature -dependent data to predict the stability of the samples at other temperatures , e .g . , typical ambient storage temperatures , at which the direct determination of oxidative stability would be too slow for most samples . Compared with existing methods , not only is the developed method reliable , but also its sample throughput rate is an order of magnitude faster . |