One-step synthesis of agarose coated magnetic nanoparticles and their application in the solid phase extraction of Pd(II) using a new magnetic field agitation device

A magnetic solid phase extraction method based on agarose coated magnetic nanoparticles)ACMNPs(coupled to a new magnetic field agitation (MFA) device was developed and investigated for the separation, preconcentration and determination of Pd(II) in aqueous solutions. For the first time, the formation of the nanoparticles and their encapsulation in agarose micro-flakes was conducted in a single step. For this purpose, preparation of the magnetic iron oxide nanoparticles was performed in an alkaline agarose solution. The sizes of Fe₃O₄ nanoparticles and agarose micro-flakes were 10–14 nm and 90–130 μm, respectively. The nanomagnetic agarose particles were functionalized by iminodiacetic acid and subjected to magnetic field agitation in the MFA device. The influence of different analytical parameters such as pH, ionic strength, type and volume of desorption solvent and amount of the adsorbent on the preconcentration of Pd(II) were investigated. Eight replicated analysis at the optimized conditions, resulted in a recovery of 94.1% with an RSD of 5.2% for Pd(II). The detection limit of the method (3σ) was 47 ng L⁻¹ for the analyte. The method was successfully applied to the determination of Pd(II) in natural water samples.     

Intermittency of energy in rapid granular shear flows

Hard-disk simulations are used for two-dimensional rapid granular shear flows of circular disks between two rotating cylinders. The intermittency effects associated with the rate of the energy dissipation of collisions are studied. The statistics of intermittent signals of energy dissipation reveals that a power law governs the dynamics of rapid shear granular flows. A dynamical system approach based on the Gledzer-Ohkitani-Yamada shell model of turbulence is employed to reproduce signals for energy dissipation that are statistically consistent with those from simulations. The results suggest that rapid granular flows can be analyzed by appropriate turbulent models.     

On hydraulic permeability of random packs of monodisperse spheres: Direct flow simulations versus correlations

Hydraulic permeability is studied in porous media consisting of randomly distributed monodisperse spheres by means of computational fluid dynamics (CFD) simulations. The packing of spheres is generated by inserting a certain number of nonoverlapping spherical particles inside a cubic box at both low and high packing fractions using proper algorithms. Fluid flow simulations are performed within the interparticulate porous space by solving Navier-Stokes equations in a low-Reynolds laminar flow regime. The hydraulic permeability is calculated from the Darcy equation once the mean values of velocity and pressure gradient are calculated across the particle packing. The simulation results for the pressure drop across the packing are verified by the Ergun equation for the lower range of porosities (<0.75), and the Stokes equation for higher porosities (∼1). Using the results of simulations, the effects of porosity and particle diameters on the hydraulic permeability are investigated. Simulations precisely specified the range of applicability of empirical or semi-empirical correlations for hydraulic permeability, namely the Carman-Kozeny, Rumpf-Gupte, and Howells-Hinch formulas. The number of spheres in the model is gradually decreased from 2000 to 20 to discover the finite-size effect of pores on the hydraulic permeability of spherical packing, which has not been clearly addressed in the literature. In addition, the scale dependence of hydraulic permeability is studied via simulations of the packing of spheres shrunk to lower scales. The results of this work not only reveal the validity range of the aforementioned correlations, but also show the finite-size effect of pores and the scale-independence of direct CFD simulations for hydraulic permeability.     

Reversed-phase dispersive liquid-liquid microextraction with central composite design optimization for preconcentration and HPLC determination of oleuropein

A reversed-phase dispersive liquid-liquid microextraction (RP-DLLME) method was developed for the preconcentration and direct HPLC determination of oleuropein in olive's processing wastewater (OPW) and olive leaves extracts. In conventional DLLME, the sedimented phase is a micro-drop of a chlorinated organic solvent that is not compatible with RP-HPLC. Therefore, solvent evaporation and reconstitution with an appropriate solvent is often required. In RP-DLLME, this problem was overcome by overturning the solvent polarity in the ordinary DLLME and replacing the organic solvent with water. A central composite chemometrics design was used for multivariate optimization of the effects of five different parameters influencing the extraction efficiency of the method. In the optimized conditions, a mixture of 1.4 mL of an ethyl acetate extract of sample and 40 μL water (pH 5.0) was rapidly injected into 5.3 mL of cyclohexane. After centrifugation of the formed cloudy mixture, a micro-drop of the aqueous phase was sedimented at the conical bottom of the centrifuge tube. This phase, that contained the preconcentrated and partially purified analyte, was directly injected into an RP-HPLC column for analysis. A mean extraction recovery of 102.5 (±4.5) % with enrichment factors exceeding 38, was obtained for five replicated analysis. The detection limit of the method (3σ) for OE was 0.02 μg L⁻¹ for OPW and 2 × 10⁻³ mg kg⁻¹ for olive leaves samples. The results showed that, RP-DLLME is a promising technique which is quick, easily operated and can be directly coupled to HPLC.     

Surface effect on the coalescence of Pt clusters: A molecular dynamics study

We have performed molecular dynamics simulations for Pt_N + Pt_N → Pt_2N (N = 147, 324, 500,792), to investigate the effect of size and substrate on coalescence temperature. Our simulations show that platinum nanoclusters coalesce at the temperatures lower than the cluster melting point. The difference between coalescence and melting temperatures decreases with the increase in cluster size and presence of substrate. These thermal behaviors affect catalytical properties of nanoclusters and the substrate, as an environment, has major effect on activity of metal nanoclusters.     

Ultrafine agarose-coated superparamagnetic iron oxide nanoparticles (AC-SPIONs): a promising sorbent for drug delivery applications

A method for one-step synthesis of ultrafine agarose-coated superparamagnetic iron oxide nanoparticles (AC-SPIONs) was developed. The method is facile and fast and requires no organic solvent or surfactant. The average particle size of the prepared AC-SPIONs was only 20–40 nm with a narrow size distribution and with large saturation magnetization at room temperature. The obtained ultrafine nanogel particles were characterized by scanning electron microscopy, energy-dispersive X-ray analysis, Fourier transform infrared spectroscopy, transmission electron microscopy and vibrating sample magnetometer techniques. The AC-SPIONs were epoxy-activated by epichlorohydrin and aminated by ammonium hydroxide. The amination of the particles was investigated by the Kaiser test. The adsorption of two model compounds (gallic acid and ellagic acid) on the functionalized nanoparticles and their releases from them were investigated spectrophotometrically in three different pH values under biological conditions. The functionalized AC-SPIONs displayed good adsorption and in vitro drug release in a phosphate-buffered saline (pH 7.4). The ultrafine AC-SPIONs can be potentially used in magnetic solid-phase extraction, drug delivery, protein purification and enzyme immobilization methods.     

Dispersive Liquid‐Liquid Microextraction of Cu(II) Using a Novel Dioxime for Its Highly Sensitive Determination by Graphite Furnace Atomic Absorption Spectrometry

A dispersive liquid‐liquid microextraction (DLLME) technique was proposed for the enrichment and graphite furnace atomic absorption spectrometric (GFAAS) determination of Cu²⁺ in water samples. In this method a mixture of 480 μL acetone (disperser solvent) containing 26 μg S,S‐bis(2‐aminobenzyl)‐dithioglyoxime (BAT) ligand and 20 μL carbon tetrachloride (extraction solvent) was rapidly injected by a syringe into 5 mL aqueous sample containing copper ions (analyte). Thereby, a cloudy solution formed. After centrifugation, the fine droplets containing the extracted copper complex were sedimented at the bottom of the conical test tube. This phase was collected by a microsyring and after dilution by methanol, 20 μL of it was injected into the graphite tube of the instrument for analysis. Effects of some parameters on the extraction, such as extraction and disperser solvent type and volume, extraction time, salt concentration, pH and concentration of the chelating agent were optimized. The response surface method was used for optimization of the effective parameters on the extraction recovery. Under these conditions, an enrichment factor of 312 was obtained. The calibration graph was linear in the rage of 2–50 μ L⁻¹ Cu²⁺ with a detection limit of 0.03 μg L⁻¹ and a relative standard deviation (RSD) for five replicate measurements of 3.4% at 20 μg L⁻¹ Cu²⁺. The method was successfully applied to the determination of Cu²⁺ in some spring water samples.     

A new algorithm for the determination of protolytic constants from spectrophotometric data in multiwavelength mode: Calculations of acidity constants of 4-(2-pyridylazo)resorcinol (PAR) in mixed nonaqueous-water solvents

A new efficient, simple and versatile algorithm is presented for determination of the protolytic constants from spectrophotmetric data in multiwavelength mode based on the combining of hard and soft modeling. The algorithm was checked by determining the acidity constants of a triprotic acid from theoretical and real absorption-pH data. The real spectral data are obtained from photometric titration of different solutions of 4-(2-pyridylazo)resorcinol (PAR) by a standard base solution under an inert atmosphere. The algorithm starts the minimization process using an user supplied number of components and initial guesses of the unknown parameters and refined in a least squares manner. New algorithm is implemented in the new version of DATAN package (version 3.1). The validity of the obtained results was checked by some well known programs such as DATAN 2.1, SPECFIT/32, SQUAD, a modified version of difference spectra and a A-pH curve method. The comparison of the outputs of the DATAN 3.1 with the other programs reveals that there is a very good agreement between the obtained results and mentioned programs.