摘要
The method based on solvent parameters(mass,cycle of acidification, and autodeposition time), combined with response surface methodology(RSM) modeling and optimization, has been developed for maximizing ^(210)Po activity in tea samples, as observed by an alpha spectrometer. RSM based on 3-factor and 5-level composite center design was used to obtain the optimal combination of solvent conditions. As solvent parameters for ^(210)Po activity, different masses(0.5, 0.75, 1, 1.5, and 2 g), different cycles of acidification(2, 3, 4, 5, and 6 times), and different autodeposition times(2, 3, 4, 5, and 6 h) were studied. The 3D response surface plot and the contour plot derived from the mathematical models were used to determine the optimal conditions. According to the obtained results, the experimental value of ^(210)Po activity was in good agreement(R^2=0.96) with the value predicted by the model. We found a favorable effect of mass on the ^(210)Po activity(p\0.05).
The method based on solvent parameters(mass,cycle of acidification, and autodeposition time), combined with response surface methodology(RSM) modeling and optimization, has been developed for maximizing ^(210)Po activity in tea samples, as observed by an alpha spectrometer. RSM based on 3-factor and 5-level composite center design was used to obtain the optimal combination of solvent conditions. As solvent parameters for ^(210)Po activity, different masses(0.5, 0.75, 1, 1.5, and 2 g), different cycles of acidification(2, 3, 4, 5, and 6 times), and different autodeposition times(2, 3, 4, 5, and 6 h) were studied. The 3D response surface plot and the contour plot derived from the mathematical models were used to determine the optimal conditions. According to the obtained results, the experimental value of ^(210)Po activity was in good agreement(R^2=0.96) with the value predicted by the model. We found a favorable effect of mass on the ^(210)Po activity(p\0.05).
