Calix[4]arene-based Mannich and Schiff bases as versatile receptors for dichromate anion extraction: synthesis and comparative studies

A series of novel calix[4]arene-based Mannich (5 and 6) and Schiff base (9–11) receptors have been synthesized and characterized by various analytical techniques. Competitive two-phase extraction experiments of these novel calix[4]arene amine- and imine-containing derivatives revealed a strong affinity for dichromate anions $\left({\text{Cr}}_2{\text{O}}_7^{2?}/{\text{HCr}}_2{\text{O}}_7^{?}\right)$. The protonated alkylinium form of 5, 6 and 9–11 proved to be effective extractants for transferring the dichromate anions from an aqueous into an organic phase. Moreover, the extraction of dichromate anions by 5 and 9 in the presence of competitive anions such as F^?, Cl^?, Br^?, ${\text{NO}}_3^{?}$, ${\text{NO}}_2^{?}$, ${\text{PO}}_4^{3?}$ and ${\text{SO}}_4^{2?}$ showed that 5 and 9 could be selective anion receptors for dichromate anions in the presence of those anions.     

Decision making with imprecise parameters

We analyze the impact of imprecise parameters on performance of an uncertainty-modeling tool presented in this paper. In particular, we present a reliable and efficient uncertainty-modeling tool, which enables dynamic capturing of interval-valued clusters representations sets and functions using well-known pattern recognition and machine learning algorithms. We mainly deal with imprecise learning parameters in identifying uncertainty intervals of membership value distributions and imprecise functions. In the experiments, we use the proposed system as a decision support tool for a production line process. Simulation results indicate that in comparison to benchmark methods such as well-known type-1 and type-2 system modeling tools, and statistical machine-learning algorithms, proposed interval-valued imprecise system modeling tool is more robust with less error.     

Nonlinear optical properties, synthesis, structures and spectroscopic studies of N-(4-nitrobenzylidene)-o-fluoroamine and N-(3-nitrobenzylidene)-p-fluoroamine

N-(4-nitrobenzylidene)-o-fluoroamine (1) and N-(3-nitrobenzylidene)-p-fluoroamine (2) have been synthesized. The crystal structures of both compounds have been defined by X-ray diffraction analysis, and characterized by FT-IR and UV-visible instrumental methods. The recorded spectrum by UV-visible spectroscopy for the investigated compounds show good transparency in the visible region, and have solvatochromic behavior in the UV region, implying nonzero microscopic first hyperpolarizability. We also report ab initio quantum chemical calculations of the electric dipole moments (mu) and the first hyperpolarizabilities (beta) of the studied compounds. Our results suggest that the investigated ligands might have microscopic nonlinear optical (NLO) behavior with nonzero values.     

The miniaturised process for lead removal from water samples using novel bioconjugated sorbents

ABSTRACT

In the present study, novel bioconjugated sorbents (peptide and oligo-nucleotide on the cobalt aluminate nanomaterials) were used to remove lead through miniaturised process and the concentration of lead was measured by inductively coupled plasma mass spectrometry. For this aim, lead was collected on sorbent in mini tube, and the influences of experimental conditions (e.g. pH of sample, amount of sorbent, concentration of eluent, foreign ions) and retention parameters on the recovery of the lead element were examined. After the optimisation of experimental parameters, a successful separation was obtained at pH 7.5 with high (>95%) quantitative recovery and high precision (<10% relative standard deviation). Using the proposed bioconjugated sorbents, the lead in sea water and tap water samples could be practically and easily removed with 95% confidence level. The detection limits of this method for lead using oligonucleotide and peptide on the cobalt aluminate nanomaterials were 0.14 and 0.12 µg/L (3σ, N = 10) with sample-matched blanks. This method can be widely used as promising and cost-effective nanomaterials to remove lead from water systems.