Artificial neural networks for simultaneous spectrophotometric differential kinetic determination of Co(II) and V(IV)

A method for simultaneous analysis of V(IV) and Co(II) has been developed by using artificial neural network (ANN). This method is based on the difference of the chemical reaction rate of V(IV) and Co(II) with Fe(III) in the presence of chromogenic reagent, 1,10-phenanthroline. The reduced product of the reaction, Fe(II), can form a colored complex with 1,10-phenanthroline and make a visible spectrophotometric signal for indirect monitoring of the V(IV) and Co(II) concentrations. Feed forward neural networks have been trained to quantify considered metal ions in mixtures under optimum conditions. The networks were shown to be capable of correlating reduced spectral kinetic data using principal component analysis (PCA) of mixtures with individual metal ion. In this way an ANN containing three layers of nodes was trained. Sigmoidal and linear transfer functions were used in the hidden and output layers, respectively, to facilitate nonlinear calibration. Both V(IV) and Co(II) were analyzed in the concentration range of 0.1-4.0 μg ml⁻¹. The proposed method was also applied satisfactorily to the determination of considered metal ions in several synthetic and water samples.     

Application of artificial neural networks as a technique for interference removal: kinetic-spectrophotometric determination of trace amounts of Se(IV) in the presence of Te(IV)

Artificial neural networks (ANNs) are among the most popular techniques for nonlinear multivariate calibration in complicated mixtures using spectrophotometric data. In this study we propose a computer-based method for removing Te(IV) interference in the determination of Se(IV) using artificial neural networks. In this way, an artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. The resulting RMSE of prediction for selenium was obtained as 0.108.     

Cork biomass as biosorbent for Cu(II), Zn(II) and Ni(II)

The removal of Cu(II), Zn(II) and Ni(II) from solutions using biosorption in cork powder is described. The adsorption isotherms were determined, along with the effect of different variables, such as the solid–liquid ratio, temperature and pH on the removal efficiency of the metals. The potentiometric titration curve of the cork biomass was determined and some zeta-potential studies were carried out. The effect of the pre-treatment by Fisher esterification on the biosorption properties of cork is also presented. It was concluded that the adsorption of the heavy metals was favoured by an increase in pH. The degree of heavy metal removal is directly related to the concentration of cork biomass, and the maximum sorption capacity of cork biomass for Cu(II), Zn(II) and Ni(II) was 0.63, 0.76 and 0.34 meq./g, respectively. It is shown that ion exchange plays a more important role in the sorption of Cu(II) and Ni(II) on cork biomass than in the sorption of Zn(II). The pre-treatment by Fisher esterification confirmed the important role of the carboxylic groups in binding of Cu(II) and Ni(II) and showed that they are the only binding sites for Zn(II).     

Complexes of Co(II), Ni(II) and Cu(II) with lapachol

Complexes of naturally occurring hydroxynaphtho-quinone, lapachol (2-hydroxy-3(3-methyl-2-buthenyl)-1,4-naphthoquinone = HL) with Co(II), Ni(II) and Cu(II) have been prepared by reaction of the corresponding acetates with the ligand (HL) in ethanol. The molecular and crystal structures were determined for [CoL₂(EtOH)₂] (1), [NiL₂(EtOH)₂] (2), and [CuL₂(py)₂] (3). In all cases the deprotonated lapachol behaves as chelating bidentate ligand. The complexes were also characterized by elemental analyses, cyclic voltammetry, and FAB-MS.     

Spectrophotometric determination of Cu(II) with sequential injection analysis

A sequential injection system, based on the reaction of Cu(II) with diethyldithiocarbamate (DDTC), was developed for the determination of Cu(II) in plant food and water samples. The extraction procedure, generally used to extract the Cu(II)–DDTC complex for subsequent analysis was eliminated in this procedure. The complex was detected spectrophotometrically in aqueous solutions at 460 nm. The physical and chemical parameters depicting the system were studied to obtain optimum conditions for sample analysis. The system developed is fully computerized and able to monitor Cu(II) in samples at seven samples per hour with a relative standard deviation of <4.50%. The calibration curve is linear from 0.5–5.0 mg/l with a detection limit of 0.2 mg/l. Interferences were reduced by introducing multiple flow reversals, to increase mixing between the reagent and sample zones, and subsequently enhance working of the masking agents (EDTA/citrate).     

Artificial neural networks in foodstuff analyses: Trends and perspectives A review

Artificial neural networks are a family of non-linear computational methods, loosely inspired by the human brain, that have found application in an increasing number of fields of analytical chemistry and specifically of food control. In this review, the main neural network architectures are described and examples of their application to solve food analytical problems are presented, together with some considerations about their uses and misuses.     

Artificial neural networks in chemometrics: History, examples and perspectives

Artificial neural networks (ANNs) are non-linear computational tools suitable to a great host of practical application due to their flexibility and adaptability. However, their application to the resolution of chemometric problems is relatively recent (early 1990s).In this communication, different artificial neural networks architectures are presented and their application to different kinds of chemometric problems (mainly classification and regression) is discussed by means of examples taken from the authors' experience, stressing the pros and cons of ANNs with respect to traditional chemometric techniques.     

Simultaneous determination of Co, Ni, Cu and Zn ions in foodstuffs and vegetables with a new Schiff base using artificial neural networks

New complexes of Co²⁺, Ni²⁺, Cu²⁺ and Zn²⁺ with a recently synthesized Schiff base derived from 3,6-bis((aminoethyl)thio)pyridazine were applied for their simultaneous determination with artificial neural networks. The analytical data show the ratio of metal to ligand in all metal complexes is 1:1. The absorption spectra were evaluated with respect to Schiff base concentration, pH and time of the color formation reactions. It was found that at pH 10.0 and 60 min after mixing, the complexation reactions are completed and the colored complexes exhibited absorption bands in the wavelength range 300-500 nm. Spectral data was reduced using principal component analysis and subjected to artificial neural networks. The data obtained from synthetic mixtures of four metal ions were processed by principal component-feed forward neural networks (PCFFNNs) and principal component-radial basis function networks (PCRBFNs). Performances of the proposed methods were tested with regard to root mean square errors of prediction (RMSEP%), using synthetic solutions. Under the working conditions, the proposed methods were successfully applied to simultaneous determination of Co²⁺, Ni²⁺, Cu²⁺ and Zn²⁺ in different vegetable, foodstuff and pharmaceutical product samples.     

Application of generalized artificial neural networks coupled with an orthogonal design to optimization of a system for the kinetic spectrophotometric determination of Hg(II)

A simple and sensitive kinetic method for the determination of traces of mercury (70-760 ng ml⁻¹) based on its inhibitory effect on the addition reaction between methyl green and sulfite ion is proposed. The reaction was monitored spectrophotometrically by measuring the decrease in absorbance of methyl green at 596 nm between 2 and 4 min using a fixed time method. Artificial neural networks with back propagation algorithm coupled with an orthogonal array design were applied to the modeling of the proposed kinetic system and optimization of experimental conditions. An orthogonal design was utilized to design the experimental protocol, in which pH, concentration of sulfite, temperature, and concentration of methyl green were varied simultaneously. Optimum experimental conditions in term of sensitivity were generated by using ANNs. The rate of decrease in absorbance is inversely proportional to the concentration of Hg(II) over entire concentration range tested (100-550 ng ml⁻¹) with a detection limit of 45 ng ml⁻¹ and a relative standard deviation at 200-400 ng ml⁻¹ Hg(II) of 3.2% (n=5). A simple preconcentration step improved the limit of detection and linear dynamic range of the method to about 8 and 12-760 ng ml⁻¹, respectively, by about 10 times enrichment of mercury between 12 and 75 ng ml⁻¹. The method was based on enrichment of Hg(II) from dilute samples on an anionic ion exchanger fixed on a plastic strip and was applied to the determination of Hg(II) in environmental samples with satisfactory results.     

Polynuclear Cu(II), Ni(II) and Cd(II) coordination compounds with bis(pyrimidin-2-yl)amine and dicyanamide

In this study the synthesis, crystal structure and characterization of three new transition metal polynuclear compounds with formula [Cu(dipm)(μ-dca)₂]_n(H₂O) (1), [Ni(dipm)(μ-dca)₂]_n(C₂H₆O)_1/2 (2) and [Cd(dipm)(μ-dca)₂]_n (3) (in which dipm = bis(pyrimidin-2-yl)amine and dca = dicyanamide) are reported. The isostructural compounds 1 and 2 contain a double-bridging end-to-end dca unit connecting two metal ions and a single bridging end-to-end dca unit between subsequent metals. Compound 3 exhibits only single bridging end-to-end dca units, oriented in three directions, giving rise to a 3D framework.     

Madaline网络用于分光光度法同时测定铜钴镍的研究

采用4－（2－吡啶偶氮）－间苯二酚（PAR）－Cu,Co,Ni显色体系，应用Madline神经网络原理，对于吸收光谱严重重叠的三组分金属配合物体系同时进行含量测定，Cu^2 ,Co^2 ,Ni^2 的平均回收率分别为94％，101％，102％，实验表明，该法具有训练速度快，预测结果准确度良好等特点，有望成为多组分分析的有效方法之一。     

Reversed flow injection and sandwich sequential injection methods for the spectrophotometric determination of copper(II) with cuprizone

Two new flow methods, flow injection analysis (FIA) and sequential injection analysis (SIA), for the spectrophotometric determination of Cu(II) in water at trace levels have been developed and optimised. Both methods are based on the reaction with oxalic acid bis(cyclohexylidene hydrazide) (cuprizone) in alkaline media. The two procedures have been developed for the final aim to compare their performances and to offer new rapid heavy metals analysis tools, avoiding the use of extraction steps. A detailed study of the physico-chemical parameters affecting the systems performances has been carried out. The reversed FIA and sandwich SIA approaches offered the best sensitivity. In both cases, an extremely good linearity has been obtained within the range 0.06-4 μg ml⁻¹ (correlation coefficient r=0.9999), whereas the observed detection limits were 0.013 and 0.004 μg ml⁻¹, for FIA and SIA, respectively. Furthermore, due to the great similarity of the diffusion zones in the reaction slugs, our approach offers the opportunity to compare the two methods in analogous conditions. This SIA method, besides keeping its typical reagent saving features, offered analytical performances equivalent to those of FIA. To obtain these results, an original “stop-flow like” method was successfully employed in the SIA approach. Both methods were validated by analysis of real water samples, after copper addition, and certified reference samples of fortified and waste waters.     

Synthesis,characterization and the thermodynamic studies of some unsymmetrical tetradentate Schiff-base ligands and their Ni(II) and Cu(II) complexes

Some new unsymmetrical tetradentate Schiff-base ligands, (N-salicylidene-N′-pyrrolidene)-1,2-ethylenediamine(H₂salpyren) (H₂L¹), (H₂Mesalpyren) (H₂L²), (H₂phsalpyren) (H₂L³), (N-salicylidene-N′-pyrrolidene)-1,3-propylenediamine (H₂salpyrpd) (H₂L⁴), (H₂Mesalpyrpd) (H₂L⁵), (H₂phsalpyrpd) (H₂L⁶) and their Ni(II) and Cu(II) complexes were synthesized and characterized by elemental analyses, IR, UV-Vis, ¹H NMR and mass spectra and magnetic moments. Possible structures of these complexes have been proposed. The thermodynamic formation constants of the complexes were determined spectrophotometrically at constant ionic strength 0.1?M (NaClO₄), at 25°C in methanol.     

Artificial neural networks in analysis of indinavir and its degradation products retention

Artificial neural networks (ANN) are biologically inspired computer programs designed to simulate the way in which the human brain processes the information. In the past few years, coupling of experimental design (ED) and ANN became useful tool in the method optimization. This paper presents the application of ED-ANN in analysis of chromatographic behavior of indinavir and its degradation products. According to preliminary study, full factorial design 2⁴ was chosen to set input variables for network training. Experimental data (inputs) and results for retention factors from experiments (outputs) were used to train the ANN with aim to define correlation among variables. For networks training multi-layer perceptron (MLP) with back propagation (BP) algorithm was used. Network with the lowest root mean square (RMS) had 4-8-3 topology. Predicted data were in good agreement with experimental data (correlation was higher than 0.9713 for training set). Regression statistics confirmed good ability of trained network to predict compounds retention.     

Ligation properties of 2-acetyl-2-thiazoline semicarbazone (ATsc): Isolation, spectroscopic and X-ray study of ATsc and its Cu(II) and Ni(II) complexes

A new ligand, 2-acetyl-2-thiazoline semicarbazone (ATsc), has been prepared and characterized by a variety of physico-chemical techniques. Likewise, the metal complexes [CuCl₂(ATsc)] and [Ni(ATsc)₂](NO₃)₂ · H₂O have been isolated and characterized through elemental analysis, IR, UV–Vis–NIR diffuse reflectance and magnetic susceptibility, as well as, in the case of the copper complex, by means of EPR. Moreover, the structures have been determined by X-ray diffraction. In both complexes the Schiff base acts as a tridentate ligand through N(1), N(2) and O atoms, making two five-membered chelate rings. The copper complex consists of monomeric molecules in which the copper atom is five coordinated in a distorted square-pyramidal geometry, with one ATsc and two chlorine ligands. The complex cation of nickel possesses approximately a non-crystallographic C₂ symmetry. The environment around the nickel atom may be described as a distorted octahedral geometry with the metallic atom coordinated to two ATsc ligands.     

EPR, IR and electronic spectral studies on Ni(II) and Cu(II) complexes with N-donor tetradentate [N4] macrocyclic ligand

Nickel(II) and copper(II) complexes are synthesized with a novel tetradentate macrocyclic ligand, i.e. 2,6,12,16,21,22-hexaaza;3,5,13,15-tetraphenyltricyclo[15,3,1,1(7-11)] docosa;1(21),2,5,7,9,11(22),12,15,17,19-decaene (L) and characterized by the elemental analysis, magnetic susceptibility measurements, mass, (1)H NMR, IR, electronic and EPR spectral studies. All the complexes are non-electrolytic in nature. Thus, these may be formulated as [M(L)X(2)] [M=Ni(II), Cu(II) and X=Cl(-), NO(3)(-) and (1/2)SO(4)(2-)]. Ni(II) and Cu(II) complexes show magnetic moments corresponding to two and one unpaired electron, respectively. On the basis of IR, electronic and EPR spectral studies an octahedral geometry has been assigned for Ni(II) and tetragonal geometry for Cu(II) complexes.     

Ligand assembly and metal ion complexation: syntheses and X-ray structures of Ni(II) and Cu(II) benzoate and 4-tert-butylbenzoate complexes of cyclam

The syntheses and X-ray structures of trans-[Ni(O-benzoato)₂(cyclam)], trans-[Cu(H₂O)₂(cyclam)]-(benzoate)₂·2H₂O and trans-[Cu(H₂O)₂(cyclam)](4-t-butyl-benzoate)₂ (where cyclam is 1,4,8,11-tetraazacyclotetradecane) are described. The nickel complex has a tetragonally distorted octahedral coordination geometry with cyclam occupying the equatorial plane in a stable trans-III arrangement, with benzoate ligands filling the axial positions. The structure closely resembles the arrangement in the previously described hydrogen-bonded (metal-free) ligand assembly [(cyclamH₂)·(4-t-butyl benzoate)₂]·2(benzoic acid) if the latter benzoic acid moieties, which do not interact directly with the cyclam moiety, are ignored. The 2?:?1 fragment thus may be viewed as a ligand assembly “preorganized” for nickel ion complexation. In contrast to the nickel structure, the two trans-axial sites in both copper structures are occupied by aqua rather than O-carboxylate ligands. Although they do not form part of the inner coordination sphere in either complex, the two carboxylate anions remain hydrogen bound to the (coordinated) cyclam ligand, with the mode of packing being generally similar in each complex.     

Simultaneous spectrophotometric determination of four preservatives in foodstuffs by multivariate calibration and artificial neural networks

Benzoic acid(BA),methylparaben(MP),propylparaben(PP)and sorbic acid(SA)are food preservatives,and they have well defined UV spectra.However,their spectra overlap seriously,and it is difficult to determine them individually from their mixtures without preseparation.In this paper,seven different chemometric approaches were applied to resolve the overlapping spectra and to determine these compounds simultaneously.With respect to the criteria of%relative prediction error(RPE)and%recovery, principal component...     

Application of the spectral correction method and "neural networks" for simultaneous determination of V(V) and Al(III)

Simultaneous determination of V(V) and Al(III) was performed by application of neural networks when the calibration matrix was performed using β-correction spectra. Two reactions between V(V) and Al(III) and Alizarin Red S (ARS) as a ligand have been investigated and applied for the simultaneous spectrophotometric determination of these metal ions. The parameters controlling behavior of the system were investigated and optimum conditions selected. Feed-forward neural networks have been trained to quantify considered metal ions in mixtures under optimum conditions. Sigmoidal functions were used in the hidden and output layers. Determinations were made over the concentration range 0.10-7.80 μg ml⁻¹ of V(V) and 0.11-4.20 μg ml⁻¹ of Al(III). Applying this method satisfactorily to simultaneous determination of these metal ions in several synthetic solutions with total relative standard error less than 4.02% validated the proposed method.     

Normal spectrophotometric and stopped-flow spectrofluorimetric sequential injection methods for the determination of alendronic acid, an anti-osteoporosis amino-bisphosphonate drug, in pharmaceuticals

A normal spectrophotometric and a stopped-flow (SF) spectrofluorimetric method have been developed and optimized for the determination of alendronic acid (ALD) in its pharmaceutical formulations. Both methods are automated using the sequential injection analysis (SIA) principle. The spectrophotometric assay is based on the reaction of the analyte with Cu(II) ions in acidic medium to form an UV-absorbing derivative (λ_max = 240 nm). The SF spectrofluorimetric method is based on the reaction of ALD with o-phthalaldehyde (OPA) in the presence of 2-mercaptoethanol at basic medium (λ_ex = 340 nm/λ_em = 455 nm). Linear calibration curves were obtained in the range 1.0-60.0 mg l⁻¹ ALD for the UV method, and in the range 0.13-10.0 mg l⁻¹ ALD for the SF spectrofluorimetric one. The sampling rates were 60 and 30 h⁻¹, respectively. The developed assays are critically compared and their advantages are discussed. Both methods were applied to the analysis of an ALD containing pharmaceutical formulation with satisfactory accuracy and precision.