Ultrasound-Assisted Dispersive Liquid-Liquid Microextraction Based on Melting of the Donor Phase: a New Approach for the Determination of Trace Elements in Solid Samples

Determination of Ultra-Trace Amounts of Copper in Environmental Water Samples by Dispersive Liquid-Liquid Microextraction Combined with Graphite Furnace Atomic Absorption Spectrometry

A new method of dispersive liquid-liquid microextraction (DLLME) combined with graphite furnace atomic absorption spectrometry (GFAAS) was proposed for the determination of ultra-trace copper. It was based on the reaction of Cu(II) with the laboratory-prepared chelating agent 2-(5-bromo-2-pyridylazo)-5-dimethylaminoaniline (5-Br-PADMA) in a HAc-NaAc buffer solution at pH 5.0 to form stable hydrophobic chelates, which were separated and enriched by DLLME with chlorobenzene (C6H5Cl) and acetonitrile (CH3CN) as extraction and disperser solvents, respectively. The sedimented phase containing the chelates was then determined with GFAAS. Various operating variables that may be affected by the extraction process such as the pH of the solution, the concentration of the chelating agent 5-Br-PADMA, the types and volumes of extraction and disperser solvents, the extraction time, and the centrifugation time were investigated. Under optimum conditions, the calibration curve was linear in the range from 0.02 ng/mL to 0.16 ng/mL of copper with a correlation coefficient of r = 0.9961, and the detection limit was 0.01 ng/mL based on 3Sb. The relative standard deviation for six replicate measurements of 0.05 ng /mL of copper was 3.9%. An enrichment factor (EF) of 110 was obtained. The method has the advantages of low detection limit, high sensitivity, simple operation, less consumption of organic solvents, higher enrichment factor, and environmental friendliness and was applied to the determination of trace copper in environmental water samples with satisfactory results.

Automatic Control of Mobile Industrial Robot Based on Multiobjective Optimization Strategy

In order to solve the optimal cascade mobile path selection problem when mobile industrial robots repair network coverage holes, a cascade mobile path selection optimization method considering the number and energy of intermediate cascade nodes is proposed. By calculating the energy availability of intermediate cascade nodes, this method further obtains the energy availability and decisive energy of each path, selects the optimal cascade mobile path from the perspective of multiobjective optimization, effectively balances the energy consumption of each mobile industrial robot, makes full use of the energy of the whole network, and prolongs the survival time of the network. Simulation results show that the optimization method has higher network energy efficiency than the standard cascaded mobile method.

Multivariate optimization of a dispersive liquid-liquid microextraction method for determination of copper and manganese in coconut water by FAAS

In this study, multivariate methodologies were applied in the optimization of a dispersive liquid-liquid microextraction (DLLME) method, aiming at the determination of Cu and Mn in coconut water samples by flame atomic absorption spectrometry. Some extractors (chloroform and CCl₄), dispersants (ethanol, methanol and acetonitrile) and complexing agents (5-Br-PADAP and Dithzone) were previously tested in the extraction. A mixture design was used to optimize the component proportions formed by chloroform (10%), acetonitrile (76%), and 0.020% 5-Br-PADAP solution (14%). Doehlert design optimized the variables pH, NaCl, and buffer amounts for the extraction of both metals. The following analytical characteristics, respectively for Cu and Mn, were accessed: limit of quantification (4.83 and 3.32 µg L^-1), enrichment factors (11 and 8 fold), and precision (6.6 and 6.0% RSD, n = 10). Addition/recovery tests of the analytes allowed to find values in the range of 96.5-120% for Cu and 99-107% for Mn.