A green and simplified approach for the quantitative and sensitive analysis of heavy metal ions in sea and stream waters

Elimination of the matrix effect is a major challenge in developing a method for the quantification of heavy metals (HMs) in water samples. In this regard, the current research describes the simultaneous analyses of Cu(II), Cd(II), and Ni(II) ions in water matrices through flame atomic absorption spectrophotometry (FAAS) after preconcentration with carrier element-free co-precipitation (CEFC) technique by the help of an organic co-precipitant, 3-{[5-(4-Chlorobenzyl)-3-(4-chlorophenyl)-1H-1,2,4-triazol-1-yl]-methyl}-4-[2,4-(dichlorobenzylidene)amino]-1H-1,2,4-triazole-5(4H)-thione (CCMBATT). Based on our literature research, CCMBATT was employed for the first time in this study as an organic co-precipitant for the preconcentration of HMs. Factors such as solution pH, concentration of co-precipitant, sample volume, standing time, centrifugation rate, and time were thoroughly examined and optimized to achieve the highest efficiency in terms of HM recovery. The limits of detection (LODs) (with 10 number of tests) of 0.54, 0.34, and 1.95 μg L-1 and the relative standard deviations (RSD %) of 2.1, 3.3, and 3.0 were determined for Cu(II), Cd(II) and Ni(II) ions, respectively. Recovery results of HMs for the spiked samples were in the range of 92.8-101.0%, demonstrating the trueness of the method and its applicability to the water samples matrix.

Enhancement of adsorptive removal efficiency of an anionic dye from aqueous solutions using carboxylic acid-modified mulberry leaves: Artificial neural network modeling, isotherm, and kinetics evaluation

Natural mulberry leaves and carboxylic acid-modified mulberry (Morus alba L.) leaves were used for the first time to scrutinize the effects of modification on the retention efficiency of an anionic dye (Remazol Brilliant Blue R (RBBR)) from aqueous solutions to suggest an economical and promising adsorbent for the treatment of dye-contaminated water. The characterization of the adsorbents was accomplished through common techniques including SEM, FTIR, and pH_pzc determination. Several parameters studied in batch experiments pointed out that the initial pH of 2.0 and the contact time of 240 min were optimum conditions for all the developed RBBR uptake processes. An artificial neural network (ANN) model was applied to formulate a forecast model for the uptake efficiency of RBBR. The experimental data were assessed by different kinetic and isotherm models to explain the mechanism of the developed processes in more detail. Maximum monolayer adsorption capacities of natural mulberry leaves and acetic acid-, citric acid-, and oxalic acid-modified mulberry leaves were determined as 64.5, 95.2, 84.8, and 91.7 mg g^-1, respectively, by the Langmuir isotherm model. These results demonstrated that the modification with carboxylic acids significantly increases the anionic dye adsorption capacity of the mulberry leaves.