Determination of arsenic in petroleum refinery streams by electrothermal atomic absorption spectrometry after multivariate optimization based on Doehlert design

Direct determination of arsenic and antimony in naphtha by electrothermal atomic absorption spectrometry with microemulsion sample introduction and iridium permanent modifier

“…However, among these modification approaches, the permanent modifier Ir showed better performance than the others, presenting sensitivity around 1.3 times higher than Ir-W and 1.4 times higher than Pd modifier. This behavior was very similar to that previously observed in the determination of arsenic in industrial effluents [20]. On the other hand, the behavior of Sb in aqueous solution (Fig.…”

“…In this experiment, the emulsions were initially prepared as recommended by Meeravali and Kumar [15], for example, by mixing 2 mL of naphtha sample (straight distillation naphtha spiked with oil standard solution of the analytes) with 1 mL of a 3% Triton X-100 solution. In both cases, nitric acid (3% v/v) was also added to the surfactant solution, since in a previous work we observed that it is preponderant in the arsenic stabilization [20].…”

Optimization of an open-focused microwave oven digestion procedure for determination of metals in diesel oil by inductively coupled plasma optical emission spectrometry

“…For this purpose a multivariate experiment based on a Doehlert matrix [32][33][34][35][36][37] was planned by varying the mass of diesel oil between 1.5 and 3.5 g and the volume of H 2 O 2 between 10 and 20 ml. A summary of the experiment and the results obtained for RCC are shown in Table 4.…”

Multivariate optimization of the determination of zinc in diesel oil employing a novel extraction strategy based on emulsion breaking

“…The multivariate optimization is advantageous compared with univariate optimization because it allows the achievement of optimum conditions with a few experiments and permits the observation of the interactions between variables, which is not possible when univariate approaches are used. The Response Surface Methodology (RSM) based on the Doehlert designs [15] can be considered one of the most efficient strategies for the optimization of analytical procedures [16][17][18][19][20][21][22][23] and has been especially useful in the optimization of sample preparation procedures [24][25][26][27].…”