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The degradation of Acid Blue 111 anthraquinone dye has been studied by the simple electro-assisted Fenton process and the obtained results were compared to the Fenton process. Ferrous sulphate and hydrogen peroxide were used and in the electro-assisted Fenton process IrOx electrode was used as the anode. The influence of hydrogen peroxide and ferrous ion concentration, as well as pH on the processes was investigated. A second-order kinetic was established and rate constants were determined. The degradation was followed by ultraviolet-visible spectroscopy, gas and liquid chromatography-mass spectrometry analysis. Mineralization of Acid Blue 111 was confirmed by total organic carbon analysis and ion chromatography analysis. Efficiency and energy consumption of the processes were calculated. Also, phytotoxicity was studied using the Mung bean seeds. According to the obtained results, the simple electro-assisted Fenton process was much efficient in the degradation of Acid Blue 111 dye than the Fenton process.

The degradation of Acid Blue 111 anthraquinone dye has been studied by the simple electro-assisted Fenton process and the obtained results were compared to the Fenton process. Ferrous sulphate and hydrogen peroxide were used and in the electro-assisted Fenton process IrOx electrode was used as the anode. The influence of hydrogen peroxide and ferrous ion concentration, as well as pH on the processes was investigated. A second-order kinetic was established and rate constants were determined. The degradation was followed by ultraviolet-visible spectroscopy, gas and liquid chromatography-mass spectrometry analysis. Mineralization of Acid Blue 111 was confirmed by total organic carbon analysis and ion chromatography analysis. Efficiency and energy consumption of the processes were calculated. Also, phytotoxicity was studied using the Mung bean seeds. According to the obtained results, the simple electro-assisted Fenton process was much efficient in the degradation of Acid Blue 111 dye than the Fenton process.

The presented study describes macroporous crosslinked poly(glycidyl methacrylateco-ethylene glycol dimethacrylate) [PGME] functionalized with diethylenetriamine [PGME-deta] as a potential recovery agent for Mo(VI) oxyanions from aqueous solutions. Sorption studies were carried out by varying experimental conditions (pH, time, concentration, temperature). Kinetics of Mo(VI) sorption was investigated in batch (static) experiments, in the temperature range 298-343 K. Sorption dynamics data were fitted to seven chemical-reaction and particle-diffusion models. The kinetics studies showed that Mo(VI) sorption adhered to the pseudo-second-order model under all investigated operating conditions. The sorption kinetics was determined to be governed by both the intraparticle diffusion and the external film diffusion to a lesser extent. The temperature rise promotes the molybdate species removal, with the maximum experimental uptake capacity of 4.02 mmol g(-1) at 298 K, at the selected pH which is consistent with the predominance range of hydrolized polynuclear Mo(VI) forms and optimum electrostatic attraction.

The presented study describes macroporous crosslinked poly(glycidyl methacrylateco-ethylene glycol dimethacrylate) [PGME] functionalized with diethylenetriamine [PGME-deta] as a potential recovery agent for Mo(VI) oxyanions from aqueous solutions. Sorption studies were carried out by varying experimental conditions (pH, time, concentration, temperature). Kinetics of Mo(VI) sorption was investigated in batch (static) experiments, in the temperature range 298-343 K. Sorption dynamics data were fitted to seven chemical-reaction and particle-diffusion models. The kinetics studies showed that Mo(VI) sorption adhered to the pseudo-second-order model under all investigated operating conditions. The sorption kinetics was determined to be governed by both the intraparticle diffusion and the external film diffusion to a lesser extent. The temperature rise promotes the molybdate species removal, with the maximum experimental uptake capacity of 4.02 mmol g(-1) at 298 K, at the selected pH which is consistent with the predominance range of hydrolized polynuclear Mo(VI) forms and optimum electrostatic attraction.

In this work, antimicrobial bioinspired films made from chitosan incorporated with triclosan were investigated. The tensile strenght of these films were in the range of 33 and 39 MPa, which presented satisfied mechanical stability comparable to the synthetic-based packages commonly used in industry. The addition of triclosan enhanced thermal stability and antimicrobial activity of chitosan films against Escherichia coli and Staphylococus aureus. Results obtained in this work demonstrated that chitosan/triclosan films could be potentially used as an eco-sustainable package in healthcare sector to prevent infections/contaminations.

In this work, antimicrobial bioinspired films made from chitosan incorporated with triclosan were investigated. The tensile strenght of these films were in the range of 33 and 39 MPa, which presented satisfied mechanical stability comparable to the synthetic-based packages commonly used in industry. The addition of triclosan enhanced thermal stability and antimicrobial activity of chitosan films against Escherichia coli and Staphylococus aureus. Results obtained in this work demonstrated that chitosan/triclosan films could be potentially used as an eco-sustainable package in healthcare sector to prevent infections/contaminations.

Natural minerals, such as quartz, clinoptilolite and calcite, are useful as sorbents for various applications, but their content of heavy metals ions is the most problematic obstacle to their application. Before their (re)use, the minerals must be purified. In this work, the subject was desorption of lead from a natural multi-component mineral sample consisting of a mixture of silicates (mainly quartz and clinoptilolite) and calcite formations. Besides deionized water, different extraction solutions were tested: NaCl, KCl, CaCl2, MgCl2, HCl, HNO3, EDTA, EDTA/HCl, EDTA/NaOAc-HOAc, HOAc, NaOAc and NaOAc-HOAc. Several parameters were varied in order to obtain the optimal conditions for the desorption process: the concentration of the extraction solution, the ratio of the mass of the sample and volume of the extractant, and the pH value of the suspension. The best purification effect in one desorption cycle was obtained when 0.1 M EDTA, at a pH value of 3.5 (0.2 M EDTA was mixed with 0.01 M acetic buffer, at pH value 3.0, in ratio 1:1) was applied. Sequential extraction (5 consecutive iterations) was performed to provide a more efficient purification process. The lead content (58.20 mg/kg) was decreased by: 20% (using HOAc), 21% (using EDTA) and by more than 50% (using EDTA/NaOAc-HOAc). The pH value and conductivity were measured at all critical points to clarify the mechanism of the desorption process. The formation of Pb-EDTA complex is the result of two parallel phenomena, complexing and ion-exchange. An enhanced adsorption capacity and an improved microelement profile for the purified samples were also attained. The mineralogical and radiochemical performances of the sample were determined by the X-ray diffraction and gamma spectrometry techniques. Microelement analyses of the native and purified samples were performed by inductively coupled plasma optical emission spectroscopy (ICP-OES).

Natural minerals, such as quartz, clinoptilolite and calcite, are useful as sorbents for various applications, but their content of heavy metals ions is the most problematic obstacle to their application. Before their (re)use, the minerals must be purified. In this work, the subject was desorption of lead from a natural multi-component mineral sample consisting of a mixture of silicates (mainly quartz and clinoptilolite) and calcite formations. Besides deionized water, different extraction solutions were tested: NaCl, KCl, CaCl2, MgCl2, HCl, HNO3, EDTA, EDTA/HCl, EDTA/NaOAc-HOAc, HOAc, NaOAc and NaOAc-HOAc. Several parameters were varied in order to obtain the optimal conditions for the desorption process: the concentration of the extraction solution, the ratio of the mass of the sample and volume of the extractant, and the pH value of the suspension. The best purification effect in one desorption cycle was obtained when 0.1 M EDTA, at a pH value of 3.5 (0.2 M EDTA was mixed with 0.01 M acetic buffer, at pH value 3.0, in ratio 1:1) was applied. Sequential extraction (5 consecutive iterations) was performed to provide a more efficient purification process. The lead content (58.20 mg/kg) was decreased by: 20% (using HOAc), 21% (using EDTA) and by more than 50% (using EDTA/NaOAc-HOAc). The pH value and conductivity were measured at all critical points to clarify the mechanism of the desorption process. The formation of Pb-EDTA complex is the result of two parallel phenomena, complexing and ion-exchange. An enhanced adsorption capacity and an improved microelement profile for the purified samples were also attained. The mineralogical and radiochemical performances of the sample were determined by the X-ray diffraction and gamma spectrometry techniques. Microelement analyses of the native and purified samples were performed by inductively coupled plasma optical emission spectroscopy (ICP-OES).

Asymmetric polyethersulfone membranes with submicron particles comprising crosslinked glycidyl methacrylate copolymer were prepared by a combination of a traditional immersion precipitation process for making membranes with photopolymerization and crosslinking of functional monomers included in the casting solution. As the concentration of polymerizable monomers increased the original macrovoid structure was replaced by a hybrid morphology with microglobules typical of macroporous methacrylate adsorbers embedded within microporous structure with no significant effects on water permeability. The epoxide groups present in glycidyl methacrylate copolymer were transformed into amine functionalities by ring opening under alkaline conditions. Permeation of Orange G solution at low transmembrane pressures was used to demonstrate suitability of these novel membranes for membrane adsorption.

A highly porous calcium carbonate (calcite; sorbent 1) was used as a support for modification with alpha-FeOOH (calcite/goethite; sorbent 2), alpha-MnO2 (calcite/alpha-MnO2; sorbent 3) and alpha-FeOOH/alpha-MnO2 (calcite/goethite/alpha-MnO2; sorbent 4) in order to obtain a cheap hybrid materials for simple and effective arsenate removal from aqueous solutions. The adsorption ability of synthesized adsorbents was studied as a function of functionalization methods, pH, contact time, temperature and ultrasonic treatment. Comparison of the adsorptive effectiveness of synthesized adsorbents for arsenate removal, under ultrasound treatment and classical stirring method, has shown better performance of the former one reaching maximum adsorption capacities of 1.73, 21.00, 10.36 and 41.94 mg g(-1), for sorbents 1-4, respectively. Visual MINTEQ equilibrium speciation modeling was used for prediction of pH and interfering ion influences on arsenate adsorption.

Asymmetric polyethersulfone membranes with submicron particles comprising crosslinked glycidyl methacrylate copolymer were prepared by a combination of a traditional immersion precipitation process for making membranes with photopolymerization and crosslinking of functional monomers included in the casting solution. As the concentration of polymerizable monomers increased the original macrovoid structure was replaced by a hybrid morphology with microglobules typical of macroporous methacrylate adsorbers embedded within microporous structure with no significant effects on water permeability. The epoxide groups present in glycidyl methacrylate copolymer were transformed into amine functionalities by ring opening under alkaline conditions. Permeation of Orange G solution at low transmembrane pressures was used to demonstrate suitability of these novel membranes for membrane adsorption.

A highly porous calcium carbonate (calcite; sorbent 1) was used as a support for modification with alpha-FeOOH (calcite/goethite; sorbent 2), alpha-MnO2 (calcite/alpha-MnO2; sorbent 3) and alpha-FeOOH/alpha-MnO2 (calcite/goethite/alpha-MnO2; sorbent 4) in order to obtain a cheap hybrid materials for simple and effective arsenate removal from aqueous solutions. The adsorption ability of synthesized adsorbents was studied as a function of functionalization methods, pH, contact time, temperature and ultrasonic treatment. Comparison of the adsorptive effectiveness of synthesized adsorbents for arsenate removal, under ultrasound treatment and classical stirring method, has shown better performance of the former one reaching maximum adsorption capacities of 1.73, 21.00, 10.36 and 41.94 mg g(-1), for sorbents 1-4, respectively. Visual MINTEQ equilibrium speciation modeling was used for prediction of pH and interfering ion influences on arsenate adsorption.

A highly porous calcium carbonate (calcite; sorbent 1) was used as a support for modification with alpha-FeOOH (calcite/goethite; sorbent 2), alpha-MnO2 (calcite/alpha-MnO2; sorbent 3) and alpha-FeOOH/alpha-MnO2 (calcite/goethite/alpha-MnO2; sorbent 4) in order to obtain a cheap hybrid materials for simple and effective arsenate removal from aqueous solutions. The adsorption ability of synthesized adsorbents was studied as a function of functionalization methods, pH, contact time, temperature and ultrasonic treatment. Comparison of the adsorptive effectiveness of synthesized adsorbents for arsenate removal, under ultrasound treatment and classical stirring method, has shown better performance of the former one reaching maximum adsorption capacities of 1.73, 21.00, 10.36 and 41.94 mg g(-1), for sorbents 1-4, respectively. Visual MINTEQ equilibrium speciation modeling was used for prediction of pH and interfering ion influences on arsenate adsorption.

Asymmetric polyethersulfone membranes with submicron particles comprising crosslinked glycidyl methacrylate copolymer were prepared by a combination of a traditional immersion precipitation process for making membranes with photopolymerization and crosslinking of functional monomers included in the casting solution. As the concentration of polymerizable monomers increased the original macrovoid structure was replaced by a hybrid morphology with microglobules typical of macroporous methacrylate adsorbers embedded within microporous structure with no significant effects on water permeability. The epoxide groups present in glycidyl methacrylate copolymer were transformed into amine functionalities by ring opening under alkaline conditions. Permeation of Orange G solution at low transmembrane pressures was used to demonstrate suitability of these novel membranes for membrane adsorption.

Two samples of macroporous crosslinked poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate), poly(GMA-co-EGDMA), with different porosity parameters were synthesized by suspension copolymerization and functionalized with ethylene diamine and diethylene triamine. The kinetics of Cr(VI) sorption by amino-functionalized poly(GMA-co-EGDMA) was investigated under non-competitive conditions. Competitive kinetics was studied from following multicomponent solutions: Cu(II) and Cr(VI); Cu(II), Co(II), Cd(II) and Ni(II): Cr(VI), Cu(II), Co(II) and Cd(II) solutions. Two kinetic models (the pseudo-first and pseudo-second-order) were used to determine the best-fit equation for the metals sorption by poly(GMA-co-EGDMA)-en and poly(GMA-co-EGDMA)-deta.

Recently. it has come to our attention, that a polemical note by Milonjic [S.K. Milonjic, Comments on "factors influencing the removal of divalent cations by hydroxyapatite", J. Hazard. Mater. 162 (2009) 1588-1589]. has been published raising several critical comments on some experimental procedures, as well as the presentation and interpretation of some data found in the cited paper by Smiciklas et al. [L. Smiciklas, A. Onjia. S. Raicevic, Dj. Janackovic, M. Mitric, Factors influencing the removal of divalent cations by hydroxyapatite, J. Hazard. Mater. 152 (2008) 876-884]. Since we have not received any prior copy of this discussion through the process involved in the acceptance of these comments, we now take the opportunity of responding. We have reviewed some scientific papers dealing with cation sorption, in order to demonstrate variety of experimental approaches used for batch sorption tests, regarding solution pH. Finally, we justified experimental methods and data interpretation methods we chose to perform in the mentioned manuscript.

Recently. it has come to our attention, that a polemical note by Milonjic [S.K. Milonjic, Comments on "factors influencing the removal of divalent cations by hydroxyapatite", J. Hazard. Mater. 162 (2009) 1588-1589]. has been published raising several critical comments on some experimental procedures, as well as the presentation and interpretation of some data found in the cited paper by Smiciklas et al. [L. Smiciklas, A. Onjia. S. Raicevic, Dj. Janackovic, M. Mitric, Factors influencing the removal of divalent cations by hydroxyapatite, J. Hazard. Mater. 152 (2008) 876-884]. Since we have not received any prior copy of this discussion through the process involved in the acceptance of these comments, we now take the opportunity of responding. We have reviewed some scientific papers dealing with cation sorption, in order to demonstrate variety of experimental approaches used for batch sorption tests, regarding solution pH. Finally, we justified experimental methods and data interpretation methods we chose to perform in the mentioned manuscript.

Two samples of macroporous crosslinked poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate), poly(GMA-co-EGDMA), with different porosity parameters were synthesized by suspension copolymerization and functionalized with ethylene diamine and diethylene triamine. The kinetics of Cr(VI) sorption by amino-functionalized poly(GMA-co-EGDMA) was investigated under non-competitive conditions. Competitive kinetics was studied from following multicomponent solutions: Cu(II) and Cr(VI); Cu(II), Co(II), Cd(II) and Ni(II): Cr(VI), Cu(II), Co(II) and Cd(II) solutions. Two kinetic models (the pseudo-first and pseudo-second-order) were used to determine the best-fit equation for the metals sorption by poly(GMA-co-EGDMA)-en and poly(GMA-co-EGDMA)-deta.

Inverse gas chromatography (IGC) is an attractive technique for polymer characterization due to possible simultaneous determination of various physicochemical properties of polymer systems merely from retention times of selected sorbates. The technique is especially advantageous to polymers that cannot be characterized by conventional methods. In this review, the utilization of the method for glass transition determination of homopolymers, copolymers and polymer blends is described. Advantages and drawbacks of the IGC method over traditionally used methods for glass transition temperature determination is discussed, along with the most important parameters that influence the precision and accuracy of the glass transition temperature (T-g) measurements.

An interpretative strategy (factorial design experimentation + total resolution analysis + chromatogram simulation) was employed to optimize the separation of 16 polycyclic aromatic hydrocarbons (PAHs) (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo(a)anthracene, benzo(k)fluoranthene, benzo(b)fluoranthene, benzo(a)pyrene, indeno(1,2,3-c,d)pyrene, dibenzo(a,h)anthracene, benzo(g,h,i)perylene) in temperature-programmed gas chromatography (GC). Also, the retention behavior of PAHs in the same GC system was studied by a feed-forward artificial neural network (ANN). GC separation was investigated as a function of one (linear temperature ramp) or two (linear temperature ramp+the final hold temperature) variables. The applied interpretative approach resulted in rather good agreement between the measured and the predicted retention times for PAHs in both one and two variable modeling. The ANN model, strongly affected by the number of input experiments, was shown to be less effective for one variable used, but quite successful when two input variables were used. All PAHs, including difficult to separate peak pairs (benzo(k)fluoranthene/benzo(b)fluoranthene and indeno(1,2,3-c,d)pyrene/dibenzo(a,h)anthracene), were separated in a standard (5% phenyl-95% climethylpolysiloxane) capillary column at an optimum temperature ramp of 8.0 degrees C/min and final hold temperature in the range of 260-320 degrees C.

The effect of pH, contact time, initial metal concentration and presence of common competing cations, on hydroxyapatite (HAP) sorption properties towards Ph2+, Cd2+, Zn2+, and Sr2+ ions was studied and compared using a batch technique. The results strongly indicated the difference between the sorption mechanism of Pb2+ and other investigated cations: the removal of Pb2+ was pH-independent and almost complete in the entire pH range (3-12), while the sorption of Cd2+, Zn2+ and Sr2+ generally increased with an increase of pH; the contact time required for attaining equilibrium was 30 mm for Pb 2+ versus 24h needed for other cations; maximum sorption capacity of HAP sample was found to be an order of magnitude higher for Pb2+ (3.263 mmol/g), than for Cd2+ (0.601 mmol/g), Zn (2+) (0.574 mmol/g) and Sr2+ (0.257 mmol/g); the selectivity of HAP was found to decrease in the order Ph2+ gt Cd2+ gt Zn2+ gt Sr2+ while a decrease of pHpzc, in respect to the value obtained in inert electrolyte, followed the order Cd2+ gt Zn2+ gt Ph2+ gt Sr2+; neither of investigated competing cations (Ca2+, Mg2+, Na+ and K+) influenced Pb2+ immobilization whereas the sorption of other cations was reduced in the presence of Ca2+, in the order Sr2+ gt Cd2+ gt Zn (2+). The pseudo-second order kinetic model and Langmuir isotherm have been proposed for modeling kinetic and equilibrium data, respectively. The sorption of all examined metals was followed by Ca2+ release from the HAP crystal lattice and pH decrease. The ion exchange and specific cation sorption mechanisms were anticipated for Cd2+, Zn2+ and Sr2+, while dissolution of HAP followed by precipitation of hydroxypyromorphite (Pb-10(PO4)(6)(OH)(2)) was found to be the main operating mechanism for Pb 2+ immobilization by HAP, with the contribution of specific cation sorption.

An interpretative strategy (factorial design experimentation + total resolution analysis + chromatogram simulation) was employed to optimize the separation of 16 polycyclic aromatic hydrocarbons (PAHs) (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo(a)anthracene, benzo(k)fluoranthene, benzo(b)fluoranthene, benzo(a)pyrene, indeno(1,2,3-c,d)pyrene, dibenzo(a,h)anthracene, benzo(g,h,i)perylene) in temperature-programmed gas chromatography (GC). Also, the retention behavior of PAHs in the same GC system was studied by a feed-forward artificial neural network (ANN). GC separation was investigated as a function of one (linear temperature ramp) or two (linear temperature ramp+the final hold temperature) variables. The applied interpretative approach resulted in rather good agreement between the measured and the predicted retention times for PAHs in both one and two variable modeling. The ANN model, strongly affected by the number of input experiments, was shown to be less effective for one variable used, but quite successful when two input variables were used. All PAHs, including difficult to separate peak pairs (benzo(k)fluoranthene/benzo(b)fluoranthene and indeno(1,2,3-c,d)pyrene/dibenzo(a,h)anthracene), were separated in a standard (5% phenyl-95% climethylpolysiloxane) capillary column at an optimum temperature ramp of 8.0 degrees C/min and final hold temperature in the range of 260-320 degrees C.

The effect of pH, contact time, initial metal concentration and presence of common competing cations, on hydroxyapatite (HAP) sorption properties towards Ph2+, Cd2+, Zn2+, and Sr2+ ions was studied and compared using a batch technique. The results strongly indicated the difference between the sorption mechanism of Pb2+ and other investigated cations: the removal of Pb2+ was pH-independent and almost complete in the entire pH range (3-12), while the sorption of Cd2+, Zn2+ and Sr2+ generally increased with an increase of pH; the contact time required for attaining equilibrium was 30 mm for Pb 2+ versus 24h needed for other cations; maximum sorption capacity of HAP sample was found to be an order of magnitude higher for Pb2+ (3.263 mmol/g), than for Cd2+ (0.601 mmol/g), Zn (2+) (0.574 mmol/g) and Sr2+ (0.257 mmol/g); the selectivity of HAP was found to decrease in the order Ph2+ gt Cd2+ gt Zn2+ gt Sr2+ while a decrease of pHpzc, in respect to the value obtained in inert electrolyte, followed the order Cd2+ gt Zn2+ gt Ph2+ gt Sr2+; neither of investigated competing cations (Ca2+, Mg2+, Na+ and K+) influenced Pb2+ immobilization whereas the sorption of other cations was reduced in the presence of Ca2+, in the order Sr2+ gt Cd2+ gt Zn (2+). The pseudo-second order kinetic model and Langmuir isotherm have been proposed for modeling kinetic and equilibrium data, respectively. The sorption of all examined metals was followed by Ca2+ release from the HAP crystal lattice and pH decrease. The ion exchange and specific cation sorption mechanisms were anticipated for Cd2+, Zn2+ and Sr2+, while dissolution of HAP followed by precipitation of hydroxypyromorphite (Pb-10(PO4)(6)(OH)(2)) was found to be the main operating mechanism for Pb 2+ immobilization by HAP, with the contribution of specific cation sorption.

Inverse gas chromatography (IGC) is an attractive technique for polymer characterization due to possible simultaneous determination of various physicochemical properties of polymer systems merely from retention times of selected sorbates. The technique is especially advantageous to polymers that cannot be characterized by conventional methods. In this review, the utilization of the method for glass transition determination of homopolymers, copolymers and polymer blends is described. Advantages and drawbacks of the IGC method over traditionally used methods for glass transition temperature determination is discussed, along with the most important parameters that influence the precision and accuracy of the glass transition temperature (T-g) measurements.

A three-layer feed-forward artificial neural network (ANN) with a back-propagation learning algorithm was used to predict the minimum detectable activity (AD) of radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) in environmental soil samples as a function of measurement time. The ANN parameters (learning rate, momentum, number of epochs, and the number of nodes in the hidden layer) were optimized simultaneously employing a variable-size simplex method. The optimized ANN model revealed satisfactory predictions, with correlation coefficients between experimental and predicted values 0.9517 for 232 Th (sample with U-238/Th-232 ratio of 1.14) to 0.9995 for K-40 (sample with U-238/Th-232 ratio of 0.43). Neither the differences between the measured and the predicted A(D) values nor the correlation coefficients were influenced by the absolute values of AD for the investigated radionuclides.

A quantitative structure retention relationship technique using an artificial neural network (ANN) has been used for the prediction of the Lee retention indices for PAHs on SE-52 and DB-5 stationary phases. The selected descriptors that appear in the ANN model are the boiling point, molecular weight, connectivity index and the Schabron molecular size descriptor. The network was trained and optimized using a training and validation data sets. For the evaluation of the predictive power of the ANN, the optimized network was used to predict the temperature-prograrnmed Lee retention indices of two unseen testing data sets. The results obtained showed that the mean of relative errors and the correlation coefficients between the calculated ANN and the experimental values of Lee retention indices for the validation and two testing sets are 1.42% and 0.9460 on SE-52; 1.32% and 0.9381; 1.43% and 0.8939 on DB-5 stationary phases, respectively. These values are in good agreement with the relative error obtained by experiment.

A three-layer feed-forward artificial neural network (ANN) with a back-propagation learning algorithm was used to predict the minimum detectable activity (AD) of radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) in environmental soil samples as a function of measurement time. The ANN parameters (learning rate, momentum, number of epochs, and the number of nodes in the hidden layer) were optimized simultaneously employing a variable-size simplex method. The optimized ANN model revealed satisfactory predictions, with correlation coefficients between experimental and predicted values 0.9517 for 232 Th (sample with U-238/Th-232 ratio of 1.14) to 0.9995 for K-40 (sample with U-238/Th-232 ratio of 0.43). Neither the differences between the measured and the predicted A(D) values nor the correlation coefficients were influenced by the absolute values of AD for the investigated radionuclides.

A quantitative structure retention relationship technique using an artificial neural network (ANN) has been used for the prediction of the Lee retention indices for PAHs on SE-52 and DB-5 stationary phases. The selected descriptors that appear in the ANN model are the boiling point, molecular weight, connectivity index and the Schabron molecular size descriptor. The network was trained and optimized using a training and validation data sets. For the evaluation of the predictive power of the ANN, the optimized network was used to predict the temperature-prograrnmed Lee retention indices of two unseen testing data sets. The results obtained showed that the mean of relative errors and the correlation coefficients between the calculated ANN and the experimental values of Lee retention indices for the validation and two testing sets are 1.42% and 0.9460 on SE-52; 1.32% and 0.9381; 1.43% and 0.8939 on DB-5 stationary phases, respectively. These values are in good agreement with the relative error obtained by experiment.

The concentrations of Cu, Zn, Mn, Fe, K, Ca, Mg, Al, Ba and B in 26 herbal drugs of special importance in phytopharmacywere studied. Flame atomic absorption and emission spectrometry (FAAS, FAES), as well as inductively coupled plasma atomic emission spectrometry (ICP-AES), were applied in this work. The whole procedure, from sample preparation, via dissolution, to measurements, was validated by using CRM (NIST 1573a-tomato leaves), and the obtained recovery values are in the range from 91 to 102%. Drug samples originated from medicinal plants cultivated in Serbia contained Cu (4.47-14.08 mg kg(-1)), Zn (8.4-54.5 mg kg(-1)), Mn (9-155 mg kg(-1)), Fe (47-546 mg kg(-1)), K (0.20-6.24%), Ca (0.18-1.84%), Mg (0.13-1.09%), Al (16-416 mg kg(-1)), Ba (11.70-84.83 mg kg(-1)) and B (5.1-118.7 mg kg(-1)). In order to get a better insight into the elemental patterns, a common chemometric approach to data evaluation was used. Four significant factors identified by principal component analysis (PCA) were attributed partly to the significant influential sources and high mobility of some elements thus referring to potential anthropogenic contamination as well.

The concentrations of Cu, Zn, Mn, Fe, K, Ca, Mg, Al, Ba and B in 26 herbal drugs of special importance in phytopharmacywere studied. Flame atomic absorption and emission spectrometry (FAAS, FAES), as well as inductively coupled plasma atomic emission spectrometry (ICP-AES), were applied in this work. The whole procedure, from sample preparation, via dissolution, to measurements, was validated by using CRM (NIST 1573a-tomato leaves), and the obtained recovery values are in the range from 91 to 102%. Drug samples originated from medicinal plants cultivated in Serbia contained Cu (4.47-14.08 mg kg(-1)), Zn (8.4-54.5 mg kg(-1)), Mn (9-155 mg kg(-1)), Fe (47-546 mg kg(-1)), K (0.20-6.24%), Ca (0.18-1.84%), Mg (0.13-1.09%), Al (16-416 mg kg(-1)), Ba (11.70-84.83 mg kg(-1)) and B (5.1-118.7 mg kg(-1)). In order to get a better insight into the elemental patterns, a common chemometric approach to data evaluation was used. Four significant factors identified by principal component analysis (PCA) were attributed partly to the significant influential sources and high mobility of some elements thus referring to potential anthropogenic contamination as well.

Physicochemical properties of hydroxyapatite (HAP) synthesized by neutralization method are heavily dependent on the process variables. A Plackett-Burman two-level experimental design was therefore, chosen to screen a large number of variables and to determine their effect on HAP characteristics. The sorption of cadmium ions on HAP was studied as well. Of six selected variables (temperature, mixing speed, reactant concentration, addition rate, presence of inert atmosphere and aging time), temperature has shown the strongest influence on HAP structural and sorption properties. Smaller crystallites, lower crystallinity and higher specific surface area lead to higher sorption of cadmium ions. Room temperature and no aging are preferable conditions for the synthesis of HAP with the highest sorption efficiency.

An artificial neural network (ANN) model for the prediction of measuring uncertainties in gamma-ray spectrometry was developed and optimized. A three-layer feed-forward ANN with back-propagation learning algorithm was used to model uncertainties of measurement of activity levels of eight radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) in soil samples as a function of measurement time. It was shown that the neural network provides useful data even from small experimental databases. The performance of the optimized neural network was found to be very good, with correlation coefficients (R-2) between measured and predicted uncertainties ranging from 0.9050 to 0.9915. The correlation coefficients did not significantly deteriorate when the network was tested on samples with greatly different uranium-to-thorium (U-238/Th-232) ratios. The differences between measured and predicted uncertainties were not influenced by the absolute values of uncertainties of measured radionuclide activities. Once the ANN is trained, it could be employed in analyzing soil samples regardless of the U-238/Th-232 ratio. It was concluded that a considerable saving in time could be obtained using the trained neural network model for predicting the measurement times needed to attain the desired statistical accuracy.

Physicochemical properties of hydroxyapatite (HAP) synthesized by neutralization method are heavily dependent on the process variables. A Plackett-Burman two-level experimental design was therefore, chosen to screen a large number of variables and to determine their effect on HAP characteristics. The sorption of cadmium ions on HAP was studied as well. Of six selected variables (temperature, mixing speed, reactant concentration, addition rate, presence of inert atmosphere and aging time), temperature has shown the strongest influence on HAP structural and sorption properties. Smaller crystallites, lower crystallinity and higher specific surface area lead to higher sorption of cadmium ions. Room temperature and no aging are preferable conditions for the synthesis of HAP with the highest sorption efficiency.

An artificial neural network (ANN) model for the prediction of measuring uncertainties in gamma-ray spectrometry was developed and optimized. A three-layer feed-forward ANN with back-propagation learning algorithm was used to model uncertainties of measurement of activity levels of eight radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) in soil samples as a function of measurement time. It was shown that the neural network provides useful data even from small experimental databases. The performance of the optimized neural network was found to be very good, with correlation coefficients (R-2) between measured and predicted uncertainties ranging from 0.9050 to 0.9915. The correlation coefficients did not significantly deteriorate when the network was tested on samples with greatly different uranium-to-thorium (U-238/Th-232) ratios. The differences between measured and predicted uncertainties were not influenced by the absolute values of uncertainties of measured radionuclide activities. Once the ANN is trained, it could be employed in analyzing soil samples regardless of the U-238/Th-232 ratio. It was concluded that a considerable saving in time could be obtained using the trained neural network model for predicting the measurement times needed to attain the desired statistical accuracy.

The concentrations of Cu, Zn, Mn, Fe, K, Ca, Mg, Al, Ba and B in 26 herbal drugs of special importance in phytopharmacywere studied. Flame atomic absorption and emission spectrometry (FAAS, FAES), as well as inductively coupled plasma atomic emission spectrometry (ICP-AES), were applied in this work. The whole procedure, from sample preparation, via dissolution, to measurements, was validated by using CRM (NIST 1573a-tomato leaves), and the obtained recovery values are in the range from 91 to 102%. Drug samples originated from medicinal plants cultivated in Serbia contained Cu (4.47-14.08 mg kg(-1)), Zn (8.4-54.5 mg kg(-1)), Mn (9-155 mg kg(-1)), Fe (47-546 mg kg(-1)), K (0.20-6.24%), Ca (0.18-1.84%), Mg (0.13-1.09%), Al (16-416 mg kg(-1)), Ba (11.70-84.83 mg kg(-1)) and B (5.1-118.7 mg kg(-1)). In order to get a better insight into the elemental patterns, a common chemometric approach to data evaluation was used. Four significant factors identified by principal component analysis (PCA) were attributed partly to the significant influential sources and high mobility of some elements thus referring to potential anthropogenic contamination as well.

An artificial neural network (ANN) model for the prediction of retention times in high-performance liquid chromatography (HPLC) was developed and optimized. A three-layer feed-forward ANN has been used to model retention behavior of nine phenols as a function of mobile phase composition (methanol-acetic acid mobile phase). The number of hidden layer nodes, number of iteration steps and the number of experimental data points used for training set were optimized. By using a relatively small amount of experimental data (25 experimental data points in the training set), a very accurate prediction of the retention (percentage normalized differences between the predicted and the experimental data less than 0.6%) was obtained. It was shown that the prediction ability of ANN model linearly decreased with the reduction of number of experiments for the training data set. The results obtained demonstrate that ANN offers a straightforward way for retention modeling in isocratic HPLC separation of a complex mixture of compounds widely different in pK(a) and log K-ow values.

An artificial neural network (ANN) model for the prediction of retention times in high-performance liquid chromatography (HPLC) was developed and optimized. A three-layer feed-forward ANN has been used to model retention behavior of nine phenols as a function of mobile phase composition (methanol-acetic acid mobile phase). The number of hidden layer nodes, number of iteration steps and the number of experimental data points used for training set were optimized. By using a relatively small amount of experimental data (25 experimental data points in the training set), a very accurate prediction of the retention (percentage normalized differences between the predicted and the experimental data less than 0.6%) was obtained. It was shown that the prediction ability of ANN model linearly decreased with the reduction of number of experiments for the training data set. The results obtained demonstrate that ANN offers a straightforward way for retention modeling in isocratic HPLC separation of a complex mixture of compounds widely different in pK(a) and log K-ow values.

Elemental composition of Echinacea purpurea (Asteracae), grown in Serbia under strongly controlled conditions, has been studied. To distinguish elemental patterns of different parts of the plant, the content of Zn, Fe, Cu, Mn, Ca, Mg, Sr, Ni, and Li in root versus upper plant parts were determined, by flame atomic absorption and flame atomic emission spectrometry. Analyses of the mentioned elements in soil and in an ethanolic extract of E. purpurea were made, too. The trace element data were evaluated by multivariate methods, i.e. principal component analysis and hierarchical cluster analysis. This revealed two groups of elements (I: Fe, Cu, Mn, Li; II: Ca, Mg, Zn, Ni), while trace element profiles of root. stem, leaves, and flowers of this plant differed significantly. However, no significant difference in the trace element patterns between the summer and the autumn harvest samples was found.

Elemental composition of Echinacea purpurea (Asteracae), grown in Serbia under strongly controlled conditions, has been studied. To distinguish elemental patterns of different parts of the plant, the content of Zn, Fe, Cu, Mn, Ca, Mg, Sr, Ni, and Li in root versus upper plant parts were determined, by flame atomic absorption and flame atomic emission spectrometry. Analyses of the mentioned elements in soil and in an ethanolic extract of E. purpurea were made, too. The trace element data were evaluated by multivariate methods, i.e. principal component analysis and hierarchical cluster analysis. This revealed two groups of elements (I: Fe, Cu, Mn, Li; II: Ca, Mg, Zn, Ni), while trace element profiles of root. stem, leaves, and flowers of this plant differed significantly. However, no significant difference in the trace element patterns between the summer and the autumn harvest samples was found.

Adsorption properties of two laboratory synthesized macroporous copolymers based on methyl and glycidyl methacrylate were investigated by inverse gas chromatography. Retentions of 12 organic compounds were measured in the temperature range from 65 to 80 degrees C. The gas/solid partition coefficients and the related thermodynamic function of adsorption at zero surface coverage were determined. The dispersive component of free surface energy of both copolymers, at investigated temperatures, was also calculated. The obtained experimental data were used to explain the polymer-adsorbate interaction.

Adsorption properties of two laboratory synthesized macroporous copolymers based on methyl and glycidyl methacrylate were investigated by inverse gas chromatography. Retentions of 12 organic compounds were measured in the temperature range from 65 to 80 degrees C. The gas/solid partition coefficients and the related thermodynamic function of adsorption at zero surface coverage were determined. The dispersive component of free surface energy of both copolymers, at investigated temperatures, was also calculated. The obtained experimental data were used to explain the polymer-adsorbate interaction.